2020 forces converging - crossing creative disruptions - ed maguire

2020 forces converging Crossing creative disruptions

Special report

March 2015

Innovation

2 [email protected] 3 March 2015

Contents

Executive summary ............................................................................ 3

Waves, cross currents and undertow ................................................. 4

Cash builds amid decline in startups ................................................ 25

Charting the course for innovation ................................................... 37

20 themes for 2020 .......................................................................... 46

All prices quoted herein are as at close of business 27 February 2015, unless otherwise stated

Deep dive into innovation

We provide an update to our 2020 draws nearer and 2020 innovation report series.

Ed Maguire [email protected] +1 212 549 8200

Clarence Chan +1 212 549 8201

Find CLSA research on Bloomberg, Thomson Reuters, FactSet and CapitalIQ - and profit from our evalu@tor proprietary database at clsa.com

Produced by CLSA Americas LLC. For important disclosures please refer to page 145.

http://www.clsa.com/

https://www.clsa.com/member/report/487625560







Executive summary Innovation

3 March 2015 [email protected] 3

2020 forces converging We revisit our work on innovation as 2020 approaches and find that compute

power, global connectivity and powerful analytics drive an inflection in

progress. Technology magnifies and accelerates the divide between winners

and losers for startups, public companies and workers as we navigate

creatively disruptive shifts in industries and the economy. Software is the core

force shaping changes in technology, business and the economy. We explore

20 key themes influencing growth opportunities for investors, industry and

society at large. Akamai, Informatica, Red Hat, Salesforce and Splunk are our

top software BUYs.

In the year since we published 2020 draws nearer (Closer to the Turing point),

US stock indexes have reached all-time highs with robust capital markets and

M&A activity while the official unemployment rate has trended below 6%. The

confluence of technology enablers, a healthy venture-capital (VC) ecosystem

and a risk-taking culture gives rise to unique American advantages. However,

powerful automation and artificial intelligence eliminate a growing spectrum

of jobs, erode established industries, exert deflationary pressure on wages

and potentially dampen long-term GDP growth. Investors often underestimate

the zero-sum dynamics of this tech-led industrial revolution.

Robust gains in VC funding and investment complement healthy capital

markets and mergers & acquisition (M&A) activity. However, the pace of new

business formation continues to decline. Structural dynamics favor larger firms

as headwinds include slippage in science, technology, engineering and

mathematics (STEM) education, broken immigration policies, costly patent

litigation and over-regulation.

We update our technology “meta-themes” - transparent IT, intelligent systems

and convergence - to highlight the importance of platforms for innovation.

Software remains at the top of the tech value chain as the driving force in

innovation, gaining strategic importance for non-technology companies as well.

A new generation of high-growth businesses is built on connectivity, massive

data-processing power, near-ubiquitous reach and powerful analytics. We

explore 20 themes with disruptive potential for industries and incumbent

businesses that offer promise for investors and firms. We group these

innovations into five categories: building blocks, connectors, human

technology, intelligent machines and new horizons.

CLSA recommended innovation stocks

Name Ticker Rating Target price Last close Currency

Akamai AKAM US BUY 83.0 69.51 USD

Amazon AMZN US O-PF 365.0 380.16 USD

Apple AAPL US BUY 148.0 128.46 USD

Facebook FB US BUY 107.0 78.97 USD

Google GOOGL US BUY 650.0 558.40 USD

IBM IBM US O-PF 175.0 161.94 USD

Informatica INFA US BUY 52.0 42.95 USD

Red Hat RHT US BUY 72.0 69.12 USD

Salesforce.com CRM US BUY 77.0 69.38 USD

Samsung Electronics1 005930 KS O-PF 1,650,000.0 1,357,000.00 KRW

Splunk SPLK US BUY 87.0 67.25 USD

Tesla TSLA US O-PF 275.0 203.34 USD 1 Covered by CLSA; all others by CLSA Americas. Source: CLSA

Cash builds amid decline in startups

20 innovation themes for 2020

Crossing creative

disruptions at the midpoint of the decade

Waves, cross currents and undertow

Charting the course for innovation

Akamai, Informatica,

Red Hat, Salesforce and

Splunk are our top software BUYs



Section 1: Waves, cross currents and undertow Innovation


Waves, cross currents and undertow Since we published our report 2020 draws nearer (Closer to the Turing point)

in February 2014, US stock indexes have reached all-time highs with robust

capital markets and M&A activity while the official unemployment rate has

trended below 6%. The confluence of technology enablers, a healthy venture-

capital ecosystem and a risk-taking culture gives rise to unique American

advantages. However, powerful automation and artificial intelligence eliminate

a growing spectrum of jobs, erode established industries, exert deflationary

pressure on wages and potentially dampen long-term GDP growth. Investors

often underestimate the zero-sum dynamics of this tech-led industrial

revolution.

Our subtitle for this report, “Crossing creative disruptions”, refers to three

ideas: Crossing the chasm, author Geoffrey Moore’s classic analysis of high-

tech strategy; creative destruction, the term associated with economist

Joseph Schumpeter; and the principles of disruptive innovation, advanced by

professor Clayton Christensen. New technologies (and companies) must

“cross the chasm” between early adopters and the mainstream, and most will

fail. Creative destruction describes the ‘process of industrial mutation that

incessantly revolutionizes the economic structure from within, incessantly

destroying the old one, incessantly creating a new one’, according to

Schumpeter. Disruptive innovations enable an upstart to displace incumbent

leaders and can come from below, above or as a sudden “big bang”. All of

these dynamics are concurrently at play.

Innovation is the major growth driver for free markets. R&D-intensive “advanced

industries” account for 9% of employment but 17% of GDP. Global connectivity

allows businesses to scale more rapidly than ever, while accelerating the impact

from business-model vulnerabilities and disruptive competition. The year 2014

saw robust increases in venture-capital fundraising and investment, but

paradoxically, the rate of new business creation has been declining. It’s not clear

whether funding can drive a turnaround, but businesses face several secular

headwinds, including shortcomings in science, technology, engineering and

mathematics (STEM) education, broken immigration policies, costly patent

litigations and over-regulation. We discuss this topic in more detail in Section 3.

We are still optimistic about the potential for value creation and societal

transformation. Sustained progress in computing, storage and connectivity

powers increasingly sophisticated ideation, design, prototyping, research,

product development and business creation. However, the accelerating pace of

change amplifies risks, both from fundamentals and overly optimistic

expectations. There is growing evidence that technology amplifies inequality -

in wages as well as prospects for new businesses. “Category kings” that

dominate over 70% of the market cap in their sectors are reaching scale more

quickly than ever, relegating also-rans to fight over diminishing share of value.

Software is truly ‘eating the world’, in the words of venture capitalist Marc

Andreesen. The twin forces of digitization and dematerialization absorb the

functions of a wealth of products and services, expressed in powerful, connected

“apps”. In addition to tech hardware and services companies, non-tech consumer

and industrial firms are investing in and acquiring software to transform their

businesses. Value consistently migrates upward to platforms, analytics and

applications. Our favorite software category kings - Akamai, Informatica, Red

Hat, Salesforce.com and Splunk - remain our top BUY ideas.

A new generation of

startups creatively shapes the US economy

Innovation-intensive

“advanced industries”

generate disproportionate growth in GDP

Akamai, Informatica, Red

Hat, Salesforce.com and Splunk are top BUY ideas

There’s growing evidence

that technology amplifies

inequalities - for wages and startups

Investors often

underestimate zero-sum

dynamics of this tech-led industrial revolution




Wayfaring the cross currents of a new industrial revolution In early 2015, employment and a range of industries are navigating widespread disruption of an industrial revolution driven by information and communications technologies (ICT). It’s not exactly “bloodless”. Leaders have been dethroned, the status quo is fluid, massive wealth is being created with unprecedented velocity and there is bubbling discontent in the broader US economy as machines displace jobs and a disproportionate share of income accrues to an elite few.

For investors, there have never been more attractive opportunities and potential minefields as the pace of innovations accelerates. Innovation (which has become inseparable from technology) holds the key to value creation. With Moore’s Law and its corollaries as a backdrop, software becomes the defining vector that creates winners and losers, category kings and also-rans. In this report, we characterize 2015 in a big-picture context, pulse-check the current state of funding and entrepreneurship, examine drivers and developments within frameworks and explore 20 critical innovative themes.

Why is innovation so important? Innovation is critical to value creation in an economy increasingly shaped by advanced technology. The most innovative industries typically contribute outsized gains to GDP, create businesses that generate attractive returns for investors, and in the case of information technologies, enable productivity gains across a continuum of industries. Brookings Institute’s recent study, America’s Advanced Industries, defines advanced industries as having the top 20% of R&D spending per worker, with a proportion of personnel with STEM knowledge greater than the national average. The 50 industries include pharmaceuticals, motor vehicles, aerospace, oil and gas extraction, software design and telecommunications, among others. These advanced industries employ just 9% of the active workforce, but generate 17% of total US GDP.

Advanced industries employ 80% of the country’s engineers, generate roughly 85% of US patents and account for 60% of US exports. The segment has seen enormous gains in productivity: output increased 30% faster than the economy as a whole from 1980-2013. Since the end of the recession in 2010, advanced services have created 65% of the new jobs in the economy, with the most coming from computer-systems design, which generated 250,000 new jobs.

Technology accelerates time to market cap (TTMC) Technology is having a marked impact on the pace of value creation for new companies, expressed through fundraising, M&A and IPOs. Put simply, the rate at which startups create value is accelerating. Time to Market Cap: The New Metric that Matters is a recent study by Play Bigger Advisors LLC that analyzes VC-backed US technology companies founded since 2000. Authors Al Ramadan, Christopher Lochhead, Dave Peterson and Kevin Maney analyzed data from over 500k private companies, 18k private investors, 50k M&A deals and 50k VC funding rounds, dividing them into three four-year eras based on when they were founded.

The study found large and growing distinctions between winners and losers. Category kings are winners (Facebook, Twitter and Uber, for example) that dominate their markets and command over 70% of the total market value in their category, leaving everyone else to share the remaining 30%. This dynamic is far from new - author Geoffrey Moore explored this phenomenon in The Gorilla Game, a seminal book on high-technology business strategy.

Software becomes the defining vector that

creates winners and losers

The beginning of 2015 finds widespread

disruption from the tech industrial revolution

Advanced industries employ just 9% of the

workforce, but generate 17% of US GDP

Advanced industries have outsized impact on

economic growth

Category kings command over 70% of the total market value in their

category

The rate at which startups create value is

accelerating




Figure 1

Category kings take all the economics

Period Market cap of category kings

(US$bn)

Market cap of everyone else

(US$bn)

Total market cap (US$bn)

Category king (%)

Era 1 (2000-03) 70.5 28.9 99.4 71 Era 2 (2004-08) 303.9 82.8 386.7 79 Era 3 (2009-13) 65.2 25.8 91.0 72 All eras 439.6 137.5 577.1 76 Source: Play Bigger Advisors LLC, http://playbigger.com/time-to-market-cap

What’s different now is that winners are winning faster than ever. Companies headed for a US$1bn valuation will do so in a third of the time; it took 2.9 years on average for companies founded in 2009-13 versus 8.5 years for those founded in 2000-03. Not surprisingly, time to market cap is accelerating faster for consumer than enterprise companies.

Figure 2

Time to market cap in years

Market cap milestone

Era 1 (2000-03)

Era 2 (2004-08)

Era 3 (2009-13)

Era 3 to Era 1 speed ratio

US$500m 4.5 2.3 1.6 2.8 US$1bn 8.5 3.5 2.9 3.0 US$3bn 24.6 8.3 7.9 3.1 US$5bn na 13.1 13.0 3.1 Source: Play Bigger Advisors LLC, http://playbigger.com/time-to-market-cap

While the ramifications are obvious for the winners, this dynamic also has implications for losers. The study found that a six-year-old startup that has not become a category king has almost no chance of becoming one.

Investing in category kings for enterprise technology We like to bring our innovation work back to the software sector and highlight our bullish stance on five category kings from our coverage universe. They all share common characteristics: they dominate their respective markets in terms of market cap, share and technology; early advantages have been reinforced over time; technologies enable an ecosystem of applications and partners; and all continue to invest aggressively in innovation.

Akamai (AKAM): Media delivery, application performance and security services benefit from the adoption of mobile devices, e-commerce, Software as a Service (SaaS), social media and gaming, driving hard ROI-enabling business over the internet.

Informatica (INFA): Core business value centers on enabling analytics and data governance, untangling “hairballs” against increasing complexity.

Red Hat (RHT): More than a software company, it is a curator of streams of innovation through the open-source model. As leading-edge cloud technologies shift from proprietary to open source, Red Hat dominates the strategic high ground.

Salesforce.com (CRM): The 800-pound gorilla of SaaS is evolving into an innovation platform, with culture, strategy and momentum propelling sustainable growth.

Splunk (SPLK): A true technology platform, the ecosystem of developers and users creates value machine data in the white spaces between infrastructure management, analytics and security.

The 800-pound gorillas consistently dominate

their markets

What’s different now is that winners are winning

faster than ever

Startups destined for US$1bn market cap

achieve this milestone ever more rapidly

We highlight five category kings from our coverage

universe

A six-year-old startup that has not become a

category king has almost no chance




Other enterprise companies that fit the category king definition, according to Play Bigger, include Workday (WDAY), ServiceNow (NOW), Palo Alto Networks (PANW), Box (BOX), Tableau Software (DATA), Veeva (VEEV) and others. We’d highlight companies like Microsoft (MSFT), Oracle (ORCL), Autodesk (ADSK), VMware (VMW), EMC (EMC), Cisco (CSCO) and Intel (INTC) as category kings from earlier eras. Private enterprise companies with values over US$2bn (based on disclosed fundraising rounds) include Dropbox, Palantir Technologies, Nutanix, Pure Storage, Cloudera and Square.

Consumer category kings that are publicly traded include Facebook (FB), Google (GOOG), Amazon (AMZN), Apple (AAPL), Twitter (TWTR), LinkedIn (LNKD), Yelp (YELP) and GoPro (GPRO), among others. Private consumer-based category kings with values over US$2bn (based on disclosed fundraising rounds) include Uber, AirBnB, SnapChat, Pinterest, GrubHub, HomeAway and Houzz. We’ve seen large deals evidence rapid time to market cap: Facebook’s US$19bn deal for WhatsApp, Google’s US$3.2bn deal for Nest Labs and Facebook’s US$2bn deal for Oculus VR.

Watching new-generation technologies disrupt incumbents Successfully predicting which trends will pay off is a matter of timing as well as trial and error. Looking beyond “barbell” dynamics of new-generation category kings, there’s ongoing disruption within tech itself. Cloud computing, the trend towards “Everything as a Service” and embrace of open source for infrastructure have disrupted traditional on-premise tech companies (which are all undertaking broad efforts to effect business transitions to the cloud).

Figure 3

SaaS versus big tech stock performance

SaaS index components include Salesforce.com (CRM), Workday (WDAY), ServiceNow (NOW), NetSuite (N), Concur (CNQR), Ultimate Software (ULTI). Big tech index components include Microsoft (MSFT), IBM (IBM), Oracle (ORCL), SAP (SAP), Cisco (CSCO), Hewlett-Packard (HPQ). Source: Thomson Reuters, CLSA

Software as a Service and IT security have rewarded investors over the past five years. Software stocks have seen pronounced and sustained contrast between the high-growth SaaS and cloud names and on-premise incumbents. SaaS consistently outperformed the S&P500 over the past five years while big (on-premise) tech has underperformed since 2013.

50

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Feb 10 Aug 10 Feb 11 Aug 11 Feb 12 Aug 12 Feb 13 Aug 13 Feb 14 Aug 14 Feb 15

S&P500Top big tech companiesTop SaaS stocks by market cap

+22.7%

+92.0%

+298.0%

Enterprise category kings grow more slowly, but have more sustainable

businesses

Consumer category kings have generated stunning

valuations

The performance contrast between SaaS and on-premise tech becomes

more extreme

Traditional big tech and SaaS software

performance bifurcated in 2013




Playing secular trends can pay off, but watch the hype We’ve been highlighting the 3D printing sector as a key innovation trend since 2011, and since that time the sector has captured popular imagination and investor attention. Interest in and awareness of the potential for 3D printing, a technology that incorporates a range of techniques including additive manufacturing, reached fever pitch in 2014, and investors aggressively sought out the limited vehicles to gain exposure to the trend. This pushed valuations to a peak, followed by a crash and protracted period of underperformance.

Figure 4

3D printing stock performance

Index components include 3D Systems (DDD), Stratasys (SSYS), ExOne (XONE), Proto Labs (PRLB), VoxelJet (VJET). Source: Thomson Reuters, CLSA

However, there are secular themes that provide a bit more consistency. The IT security industry benefits from the need for constant innovation to protect data, systems and reputations from myriad evolving threats. Despite some froth during early 2014, the sector has modestly outperformed the market over the past three years.

Figure 5

IT security has been a good sector for investors

IT Security index components: AVG (AVG), Check Point Software (CHKP), Barracuda Networks (CUDA), Cyber-Ark (CYBR), FireEye (FEYE), Fortinet (FTNT), Imperva (IMPV), Guidance Software (GUID), NICE Systems (NQ), Palo Alto Networks (PANW), Proofpoint (PFPT), Symantec (SYMC), Qualys (QLYS), Varonis (VRNS), Qihoo360 (QIHU), Finjan Software (FNJN). Source: Thomson Reuters, CLSA

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Nasdaq Composite3D printing stocks

+189.7%

+120.6%

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Feb 13 May 13 Aug 13 Nov 13 Feb 14 May 14 Aug 14 Nov 14 Feb 15

Nasdaq CompositeSecurity names

+71.7%

+50.7%

3D printing stocks peaked in early 2014 and have

struggled since

IT security benefits from the need for constant

innovation

The dynamic nature of IT security offers continual

business opportunities in the sector




Of course, innovation does not insulate investors from the risks of globalization and competition. Despite being one of the most disruptive technologies longer term, solar stocks have been an ongoing disappointment to investors over the past five years.

Figure 6

Solar technology an idea well ahead of its time

Source: Thomson Reuters, CLSA

If one assesses stocks according to the Gartner “Hype Cycle”, the 3D sector may be nearing the “Trough of Disillusionment” before reaching the “Plateau of Productivity”, while solar remains mired in the trough for some time.

A brief survey of the rich landscape of innovation We explore 20 key innovations worthy of investors’ attention in Section 4. Not all are public entities, but all have consequential implications whether disruptive or in catalyzing the creation of new value. We classify these innovations into five broad categories, which we summarize on the following pages (see Section 4 for further details and the prominent players in each segment):

Building blocks: The foundational technologies for next-generation innovation.

Connectors: The forces that tie together (and push apart) the strands of technological innovation, business evolution and societal change.

Human technologies: The new ways that technology interacts with and extends human capabilities.

Intelligent machines: Cars, aircraft, robots and industrial equipment are becoming connected, smarter and increasingly autonomous.

New horizons: The new waves of innovation with the most potential to impact the world we live in.

A key thread across each category is the essential role that software and notably analytics play in enabling innovation. In our view, these are longer-term themes that could profoundly reshape markets, the economy and society at large. As is typical of long-term technology evolution, early stage activities are small, but with exponential progress, inflection points are likely to surprise.

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Nasdaq CompositeGuggenheim Invest Solar ETF

+119.7%

-56.0%

We detail 20 key innovations worthy of

investors’ attention

A key thread across each category is the essential

role of software and analytics

Apple’s US$834m investment in First Solar

marks a high-profile clean tech commitment




Building blocks We profile key innovations that are foundational in nature. Nanotech provides the avenue for a broad range of new materials with particular significance for semiconductors. As limits of Moore’s Law approach, graphene, organic transistors, 3D stacking, neurosynaptic chips and quantum computing promise new paths for computing. 3D printing is increasingly mainstream and consumer hype is frothy, though industrial uses are well established. Open-source development models are pervading software, hardware and new business models.

Advances in nanotechnology underpin an enormous range of innovations in materials that promise new solutions in medicine and healthcare, electronics, industrial design and the military. While much of the discussion has been futuristic, there has been very real progress towards engineering nanoscale machines. Large corporations including GE, HP and Lockheed Martin are leading research and development in nanorobotics.

Figure 7

Building blocks

Innovation What it means Who could benefit Potentially at risk Related companies

Nanotechnology New materials could transform aerospace, medicine, military and manufacturing. Research in semiconductors seeks to break through the limits of Moore’s Law. Any machines at molecular scale can be engineered to perform specific functions. Potential uses are nanomedicine biochips, nucleic acidbots, bacterias, bioprinting

Consumers, businesses, aerospace, military, healthcare, semiconductors, biotech firms, pharmaceutical companies, medical patients

Prevailing technologies

IBM (IBM), Advanced Nanotech (AVNA), American Superconductor (AMSC), Altair Nanomaterials (ALTI), Arrowhead Research (ARWR), FEI Company (FEIC), GE (GE), Hewlett-Packard (HPQ), Northrop Grumman (NOC), American Pharmaceutical Partners (APPX), Harris & Harris Group (TINY), Nanogen (NGEN), LSI Logic (LSI), Lumera Corp (LMRA), Nanometrics (NANO), Nanophase Technologies (NANX), NVE (NVEC), Ultratech (UTEK), Veeco Instruments (VECO)

Beyond Moore's Law

As the computing industry approaches the physical limits of performance improvement in silicon chips, there are ongoing efforts to extend the exponential trend through new technologies

Consumers, businesses, aerospace, military, semiconductors, computing hardware and software, scientific research

na Intel (INTC), AMD (AMD), IBM (IBM), Google (GOOG), Lockheed Martin (LMT), D-Wave Systems (Private)

3D printing Custom fabrication, prototyping, spare parts

Consumers, designers, industrial designers, manufacturers, service providers, materials producers

Spare parts, machine tooling, mass manufacturing

3D Systems (DDD), Stratasys (SSYS), ExOne (EXONE), Proto Labs (PRLB), VoxelJet (VJET), Arcam (Sweden), envisionTEC, EOS (Germany), Renishaw (UK), Organovo (ONVO), Autodesk (ADSK), Staples (SPLS), Adobe (ADBE), Microsoft (MSFT)

Open-source everything

The open-source model is transforming software development, crowdsourcing, prototyping, datacenters and the replacement of proprietary systems

Entrepreneurs, operators of cloud datacenters, corporations and service providers, SaaS independent software vendors (ISVs), consumers, industrial designers, military, consultants

Traditional proprietary hardware and software vendors including HP, Dell, Oracle, IBM, Microsoft, VMware, Cisco, EMC, Juniper, etc

Facebook (FB), Google (GOOG), Intel (INTC), AMD (AMD), Red Hat (RHT), Hortonworks (HDP), Microsoft (MSFT)

Source: CLSA

In 2014, the interest and hype around 3D printing finally peaked, and stocks gave back much of their gains from 2013. While hype around consumer 3D printing is frothy, industrial additive manufacturing is well established for prototyping with less than 1% of firms using it for production.

We profile innovations that are foundational

in nature

We profile innovations that are foundational

in nature

Small things with big impact: nanotech,

nanomaterials and nanobots

3D printing - At the peak of hype, but real

technology




Open-source principles inherently enable innovation, not just in software, hardware and services, but through the derivative benefits to technology users in any endeavor. The open-source model has transformed software development and is increasingly being applied in hardware, networking, crowdsourcing, media and new business models.

Connectors In an environment of accelerating change, certain technologies play the role of connectors, acting as enabling catalysts that harness new innovations and pave the way for entrepreneurs.

The combination of advanced mathematics, access to massive computing power through peer-sharing, the open-source ethos and powerful new software gives rise to technology-based currency alternatives. Typically created with cryptographic algorithms with security inherent in the designs, there are nearly 100 alternative currencies in various stages of evolution with Bitcoin as the dominant one. In the aftermath of the crash of a speculative bubble, there is increasing interest and investment in the underlying technological principles.

Artificial intelligence (AI) governs everything from speech recognition to search, airplane navigation and auto-pilot systems, motion-detection systems like Microsoft’s Kinect for Xbox and intelligent assistants for smartphones. A new generation of self-learning computing promises to instrument the physical world, and integration with advanced robotics will power a new generation of autonomous and semi-autonomous machines.

Figure 8

Connectors


Bitcoin, cryptocurrencies and blockchain

Open-source currencies provide alternative payment systems not tied to governments

Startup businesses, low-income workers, citizens in unstable countries, investors

Banks, credit card and money transfer firms

Private companies for now: CoinDesk, Coinbase, BitPay, many others

Deep learning and the next phase of AI

Artificial intelligence governs everything from speech recognition to search, airplane navigation and auto-pilot systems, motion-detection systems and intelligent assistants for smartphones

Advertisers, businesses, consumers, government, society at large

Jobs across a wide range of capacities from blue-collar drivers, security guards and others to knowledge workers like translators, paralegals, medical professionals, investment analysts

Google (GOOG), Microsoft (MSFT), IBM (IBM), Baidu (BIDU), Facebook (FB), Amazon (AMZN), LinkedIn (LNKD), many startups

Security Trust is paramount in a connected world. Rising levels of increasingly complex IT security threats compel increasingly innovative defenses

Consumers, businesses, government, society at large

Everyone and everything connected to the internet, including consumers, businesses, utilities, governments

AVG (AVG), Barracuda Networks (CUDA), Check Point (CHKP), CyberArk (CYBR), FireEye (FEYE), Fortinet (FTNT), Imperva (IMPV), Imprivata (IMPR), MobileIron (MOBL), NQ Mobile (NQ), Palo Alto Networks (PANW), Qihoo360 (QIHU), Symantec (SYMC), Qualys (QLYS), Proofpoint (PFPT), Cisco (CSCO), IBM (IBM), CA (CA), EMC (EMC) and many others

The sharing economy

Everything becomes a service as people create new communities for sharing

Consumers, advertisers, startups

Retailers, hotels, asset vendors

Netflix (NFLX), Avis/Zipcar (CAR), Ebay (EBAY), Amazon (AMZN), Groupon (GRPN), Chegg (CHGG), BMW, Yelp (YELP); startups like Uber, AirBnB, TaskRabbit, Lyft, others

Source: CLSA


Connectors act as enabling catalysts

There are nearly 100 alternative currencies in

various stages of evolution

Artificial intelligence is seeing another

resurgence - this time as foundational technology




Trust provides the basis for essential functions of commerce and society. With the explosion of connections, applications, communications, information and systems, there’s increasing need for trust to facilitate e-commerce, electronic money transfers and modern conveniences such as ATMs. Threats continue to become more pervasive, driven by technological advances and the growing involvement of organized crime and governments. The IT security market is dynamic, conducive to startups offering fertile ground for innovators and investors.

Much of the value in the trade of traditional goods and services is the friction involved with connecting the asset with demand at the time and place of need. With a world of users connected to the internet, this gives rise to services that intermediate and provide a trusted framework. We believe companies like Netflix, Uber and AirBnB offer a blueprint for what the next generation of high-growth businesses will look like.

Human technology Advances in natural user interfaces make controlling compute increasingly seamless, as translation services bridge language barriers close to real time; natural language understanding makes interactions more human; and motion-sensing advances control computing from the human body.

Over the past three years, augmented-reality and virtual-reality technologies have captured public imagination and we are seeing viable products on the cusp of mass markets. Facebook’s Oculus VR, Google Glass and Microsoft HoloLens reflect a range of approaches to the user experience that will lead to a new generation of applications and entertainment.

Figure 9

Human technology


Next-generation user interface

Speech, touch, gesture, language translation, brain computer interfaces (BCI), natural language understanding

Anyone that wishes to interact with computing: consumers, business, transportation, healthcare, education, telecommunications, manufacturing, military, etc

Service jobs, especially call centers, legacy hardware providers

Microsoft (MSFT), Nuance (NUAN), Google (GOOG), Apple (AAPL), IBM (IBM)

Virtual reality Gaming, entertainment, commerce, travel

Consumers, game developers, content creators

na Facebook (FB), Microsoft (MSFT), Samsung, Sony (SNY), Google (GOOG)

Wearables Healthcare, retail, customer service, finance

Healthcare patients, consumers, medical personnel, investors

Administrative, customer-service jobs

Apple (AAPL), Google (GOOG), Samsung, Sony (SNY), Nike (NKE), Intel (INTC), Qualcomm (QCOM), Microsoft (MSFT), GoPro

Body 2.0 Mobility, strength augmentation

Disabled and/or handicapped, military, construction workers, etc

na Raytheon (RTN); private companies including Berkeley Bionics, Ekso Bionics, Rex Bionics, Cyberdyne

Computational genomics

Gene sequencing, genetic analysis

Individuals, health patients, pharmaceutical companies

na Agilent Technologies (A), Bio-Rad Laboratories (BIO), Danaher (DHR), Illumina (ILMN), Life Technologies (LIFE), PerkinElmer (PKI), Safeguard Scientifics (SFE), Sigma Aldrich (SIAL), Techne (TECH), Thermo Fisher (TMO), Waters (WAT)

Source: CLSA

Security is an ongoing “arms race” between bad

actors and security professionals

Assets are rented not owned in the

“sharing economy”

Natural user interfaces make controlling compute

increasingly seamless

Augmented reality and virtual reality have

captured public imagination




2014 was the year that hype around wearable computing reached fever pitch, and a flood of new market entrants has resulted in a highly fragmented market with no breakout successes. Fitness bands, smartwatches, glasses, connected clothing and a myriad of other devices battle for market share and mindshare as the industry awaits the Apple Watch. Advances in bionics, prosthetics and exoskeletons are empowering the physically disabled as well as giving industrial workers and soldiers superhuman strength.

Mobile healthcare technology is seeing robust innovation among consumers and professionals, though adoption is concentrated at the ends of the spectrum among the very healthy and very sick. Complementing the surge of entrants in wearable activity trackers (Jawbone, Fitbit, Nike+) are similar advances in FDA-approved apps for diagnostics and treatment. Despite robust VC investment and high-profile media coverage, the market remains nascent and highly fragmented. We expect Apple, Google, IBM, Microsoft and Qualcomm to foster a robust ecosystem of startups and partnerships.

The declining cost of computing, more powerful systems and the capacity to store and process massive quantities of data create conditions conducive to accelerating innovation in the life sciences. With Illumina’s latest machines lowering the cost of a sequenced human genome below US$1,000, genomics is actively decoding elusive mysteries of DNA, the “source code” for the human body, with promise of proactive avoidance and better treatment for cancer, Alzheimer’s, multiple sclerosis and other chronic diseases.

Intelligent machines There has been a dramatic increase in awareness around consumer and commercial drones, technically known as unmanned aerial vehicles (UAVs), as growing availability of cheaper and more powerful systems makes the technology ever more accessible. While UAVs are a substantial market for military aerospace suppliers, it’s the consumer and commercial markets that give rise to new investment opportunities.

The fundamental nature of transportation is changing as autonomous vehicles prove technological viability and sensor-based vehicle communications systems promise to ease traffic jams and improve safety. The bigger challenges lie ahead with laws, lawmakers and insurance companies.

Advances in robotics are having a transformative effect on manufacturing and industry as a new wave of personal and collaborative robotics comes to market. A key thread across each category is the essential role that software and notably analytics play in enabling innovation.

2014 was the year that the Internet of Things as a term became widely adopted in the mainstream media, and our report Deep Field: Discovering the Internet of Things focused on the growing relevance and opportunities across consumers and businesses in a full spectrum of industries. The 2015 Consumer Electronics Show hosted over 900 companies exhibiting Internet-of-Things solutions, primarily in the smart home, automotive and wearable categories. While the major inflection point is not expected until 2017-20, seeds for immense transformations are already sowed.

Connected health poised for steady adoption

Computational genomics are decoding the software

of nature

2014 was the year that hype around wearable

computing reached fever pitch

Autonomous vehicles and robotics will remake

transportation and manufacturing

Consumer and commercial drone

markets give rise to new investment opportunities

A world connected - the Internet of Everything




Figure 10

Intelligent machines


Drones Drone aircraft, delivery services, consumer hobbyists, precision agriculture, public safety

Merchants, military, residents of remote areas, farmers, transportation companies, public safety

na Google (GOOG), Amazon (AMZN), Lockheed Martin (LMT), AeroVironment (AVAV), Northrop Grumman (NOC), Boeing, Textron (TXT), General Dynamics (GD), SAIC (SAIC), GoPro (GPRO), Ambarella (AMBA), IXYS Corp, (IXYS), InvenSense (INVS) and others

Smarter cars and autonomous vehicles

Self-driving cars, trucks, buses, industrial vehicles

Consumers, businesses, automobile manufacturers, auto supply chain, military

Spare auto parts, the auto industry itself

Google (GOOG), Toyota Motor (TM), Ford Motor (F), General Motors (GM), Raytheon (RTN), AeroVironment (AVAV), Boeing (BA), Northrop Grumman (NOC), Textron (TXT), BAE Systems (BAESY), Adept Technology (ADEP), Bosch, STMicro, InvenSense, Skyworks Solutions, Nvidia, Qualcomm, Broadcom, Infineon, Texas Instruments

Robotics Automated manufacturing, surgical robots, trainable robotic assistants, domestic robots

Manufacturers, healthcare, consumers, military

Labor, especially employees doing repetitive tasks in manufacturing, service, etc

Amazon (AMZN), iRobot (IRBT), Google (GOOG), Raytheon (RTN), Moog (MOG), Intuitive Surgical (ISRG), Cognex (CGNX), Accuray (ARAY), AeroVironment (AVAV), Northrop Grumman (NOC), Rockwell Automation (ROK), General Dynamics (GD), Boeing (BA), Teledyne (TDY), Textron (TXT)

The Internet of Things

Myriad implications for both industrial and consumer

Consumers, businesses, manufacturers, logistics, military, public safety, wireless sensor network providers, analytic software vendors

na IBM (IBM), CA Technologies (CA), Cisco (CSCO), EMC (EMC), GE (GE), National Instruments (NATI), Google (GOOG), Intel (INTC), AMD (AMD), Siemens (SIE), Teradata (TDC), SAP (SAP), Splunk (SPLK), Informatica (INFA), Broadcom (BRCM), Qualcomm (QCOM); wireless network, sensor and analytic software vendors

Source: CLSA

New horizons With aggregate student debt in the USA having surpassed US$1tn, there’s increasing interest in online alternatives. Khan Academy has seen good success offering online instruction for K-12. College-level massive online open courses (MOOCs) have seen significant momentum and VC investment. Challenges are high dropout rates and accreditation, but the joint Georgia Tech/Udacity Master in Computer Science program points in an encouraging direction.

Figure 11

New horizons


MOOCs College-level online courses

Students, education startups

Traditional universities, colleges

DeVry (DV), Strayer Education (STRA), Capella (CPLA), 2U (TWOU), Apollo Education Group (APOL), Rosetta Stone (RST); private companies including Coursera, Udacity, edX

The clean web

Energy conservation, smart grid, energy usage analytics

Consumers, businesses, the environment

Utilities ABB Systems (ABB), Badger Meter (BMI), IBM (IBM), CA Technologies (CA), Cisco (CSCO), GE (GE), EMC (EMC), Emerson Electric (EMR), Google (GOOG), Intel (INTC), AMD (AMD), Itron (ITRI), EnerNoc (ENOC), SilverSpring (SSNI), Opower (OPWR); private firms including Gridpoint, Tendril, many others

The new space race

Cargo, exploration, space mining

Aerospace firms, suppliers, scientific research

na Boeing (BA), Northrop Grumman (NOC), Lockheed Martin (LMT), Raytheon (RTN); private companies Virgin Galactic, Planetary Resources, SpaceX

Source: CLSA

There is a surge of interest in measuring and optimizing energy usage among individuals, businesses and especially operators of power-hungry datacenters. Despite concerns over a “cleantech bubble”, progress is real, with growing mainstream acceptance of “green” alternatives such as Tesla’s electric cars. Leading tech companies are committing to and investing in clean power, with Apple’s US$845m investment in solar power in California the most prominent.

MOOCs don’t fail me now

Powering the future with “the clean web”




We highlight key areas with innovation momentum: energy analytics for homes and businesses; technology for energy companies (smart grid); and energy-efficient technologies for the “green datacenter”.

A new wave of privately funded companies is pursuing a range of ventures including commercial space-cargo flights, low-Earth-orbit space tourism, asteroid exploration for resource extraction and longer-term plans for manned space ventures to the Moon and Mars. Major aerospace firms Boeing, Lockheed Martin and Northrop Grumman are actively engaged, alongside leading private companies SpaceX, Virgin Galactic and Planetary Resources.

Software - Value is migrating upward as it “eats the world” We’ve long expounded the view that value migrates upward in the technology “stack” from hardware to infrastructure software to software applications. There is an ongoing tech-sector business model transition from products to products plus services to services. Declining cost of compute and storage allows system architecture to evolve from optimized, tightly coupled systems (mainframe) to computationally “wasteful”, loosely coupled cloud-computing services. As we discuss in more detail in Section 3, hardware and services vendors are increasingly moving into software for technology and business reasons. This does not preclude disruption, but mitigates the impact for a while.

Manufacturers and retailers increasingly attach software and cloud services to their physical products. Non-technology companies are compelled to invest in applications and services to differentiate their products in a global market. It’s no longer tech and internet companies vying for the most promising startups in Silicon Valley; companies in other sectors are seeking out investment and acquisition opportunities. General Motors recently terminated a US$3bn outsourcing agreement with HP to do more in-house development, in the process increasing the number of programmers from 1,500 to 8,000.

Companies in retail, agriculture, industrial equipment, automotive, consumer-packaged goods, energy, utilities, telecommunications, media and nearly every sector must adapt and evolve or face disruption, or worse. There are numerous recent examples of non-technology companies making investments or acquisitions in software:

GE created a separate business division - GE Software - to advance its vision for “software-defined machines”.

Under Armour bought fitness tracking app developer MyFitnessPal for US$475m.

Monsanto acquired the Big Data weather analytics company Climate Corporation for US$930m.

Companies like Coca-Cola, General Motors, Castrol and many others seek to replicate the Silicon Valley innovation model by establishing their own startup incubators and venture funds. If software is in fact transforming every industry, investors need to evaluate non-tech companies based on their command and embrace of these new technologies.

Signs pointing to an improving backdrop, but doubts remain There are several contrasting views regarding prospects for growth and innovation at the beginning of 2015. With the S&P500 and Dow Jones Industrial Average hitting new highs, there’s clearly a bullish stance driving public market investment.

There’s a transition from an economy of products

to an economy of products plus services

To die on Mars? The new space race

Non-tech corporations are investing to compete in a

digitized, connected world

Non-tech companies are establishing startup

incubators and venture funds

There’s clearly a more bullish tone driving public

market investment

Non-technology companies feel compelled

to invest in applications and services




Figure 12

Dow Jones Industrial Average versus US unemployment rate

Source: Research.stlouisfed.org, Thomson Reuters

Sentiment is steadily improving, judging by the influx of VC funding and concurrent increase of investments. GDP in the USA has been steadily inching up and the official unemployment rate has dipped below 6% as a sluggish post-recession recovery begins to pick up the pace. However, there’s ongoing debate regarding the future of US growth between the techno-optimists and those that view technology as ultimately contributing to slowing GDP growth.

Techno-optimists cite the Law of Accelerating Returns There’s an optimistic school of thought that the convergence of information technologies, clean energy and connectivity bringing billions of new minds online will catalyze enormous gains in wealth, health and quality of life. The most passionate advocates like Ray Kurzweil and Peter Diamandis of Singularity University see the current technological disruptions to industry and employment as temporary, paralleling the dislocations seen in prior industrial revolutions. People have dealt with change in the past, ergo this time it’s just another cycle set to play out along historical lines.

Technologists and investors tend to project the future in stepwise terms. Human beings naturally have linear intuitions about the future because linear thinking progresses logically from experience. However, innovations and paradigm shifts occur at an accelerating, often exponential pace. This creates a disconnect. The difference between linear and exponential growth is tremendous: 30 linear steps equals 30, while 30 exponential steps equals one billion. This is the nature of information technology, and it has powerful implications for the pace of innovation more broadly in society. This phenomenon is known as the Law of Accelerating Returns.

The way the exponential progress in technology accelerates change can be illustrated by comparing mass adoption of inventions over the past 150 years. One only has to look at the rapid growth of Facebook and the explosive growth in tablet computing that the iPad catalyzed to appreciate accelerating paradigms.

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Tapping into accelerating change

As US indexes hit new highs, unemployment finally dips below 6%

Techno-optimists see current disruptions to

industry and employment as temporary




Figure 13

Adoption paradigms are accelerating

Source: Ray Kurzweil, KurzweilAI.net

In The Age of Spiritual Machines, author Ray Kurzweil coined the phrase ‘the second half of the chessboard’ in reference to the point where an exponentially growing factor begins to have a significant economic impact on an organization's overall business strategy. While the numbers on the first half of the chessboard are large if each square doubles the number of grains of rice (from the story of the clever inventor’s idea when a king asked him to name his own reward), the amount on the second half is over 4bn times larger. Today’s computer chips pack over 4bn times more computing power per dollar than was available in the mid 1960s, packing more power in a pocket smartphone than NASA used to send astronauts to the Moon.

Innovation fuels an optimistic view of the future We share an optimistic view, though tempered somewhat. Cloud computing, the mobile internet, non-traditional user interfaces, advances in programming science and artificial intelligence, and falling costs of compute and bandwidth place unprecedented power in the hands of everyone, from a child with a cellphone to entrepreneurs to researchers seeking to solve the challenges of medicine. For investors, it’s critical to time investments in disruptive technologies appropriately, as there are risks being too early or too late.

Mired in the trough of a tech “supercycle” but with an upturn ahead There’s also a longer-term view that the economy is undergoing a protracted realignment as it emerges from the trough of a multidecade technology supercycle. Economist Carlota Perez defines the “turning point” as the current phase of the grand ICT supercycle that commenced with the crash of the internet bubble in the early 2000s and persists today. Perez’ view is that this turning-point period may last a few more years, with structural changes to the economy working themselves out until we emerge into a new economic “golden age” in the decades ahead.

Perez has framed current conditions as part of a cycle that has played out with prior secular technology shifts. Her work draws from economists Nikolay Kondratieff and Joseph Schumpeter in framing multidecade waves of technological change that occur in surges about once every 50 years. These

Telephone Radio Televison

PC

Mobile Phone

The Web

Facebook

?

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(Years)

Technological change has reached ‘the second half

of the chessboard’

Carlota Perez frames current problems as a

consistent pattern seen in prior technology shifts

The turning-point period may last a few more years

The challenge always remains a combination of

timing and careful selection

The rate at which new inventions reach

widespread adoption is accelerating




technology waves come in two major stages, installation and deployment, punctuated by a turning point (invariably a bubble, crash and recession). The current ICT revolution is the fifth upheaval experienced by the capitalist system since the first industrial revolution in the late 18th Century. Since we first encountered this thesis in 2011, we have become more convinced of its applicability to our current conditions.

Figure 14

The historical record: Bubble prosperities, recessions and golden ages

Source: Carlota Perez

The installation period typically begins within a mature economy, where there are battles between new and old, with a great deal of experimentation in the free markets. What follows is a frenzy of investing, inflated asset prices and speculation. This aptly describes both the dot.com bubble as well as the real-estate asset bubbles. We are experiencing a painful transition likely to last a few more years as the economy readjusts and the ICT revolution propagates broadly across society and the economy. The current economic dislocation is unsettling, but innovations highlighted within this report lay the groundwork for the next golden age.

During the deployment period, there is expansion of both new and rejuvenated sectors, as this phase allows the potential of new technologies to come to fruition. This is a period of creative construction, where the benefits of wealth are spread more broadly, and capital and finance decisions are directed towards production rather than speculation. There’s a fair case to be made that the modest improvements in the economy, emergence of new types of business models such as sharing-economy apps, increased VC funding and an improving employment backdrop point to the emerging character of the new economy. However, the disruptive impact does not appear to have played out fully at this point.

Maturity

1771The IndustrialRevolutionBritain

1829Age of Steamand RailwaysBritain

1875Age of Steel andheavy EngineeringBritain/USA/Germany

1908Age of Oil, Autosand Mass ProductionUSA

1971The ICTRevolutionUSA

INSTALLATION PERIOD Bubble collapse DEPLOYMENT PERIODNo., date, revolution, core country

TURNINGBubble prosperity POINT Golden age prosperity

1st Canal mania Great British leap

2nd Railway mania The Victorian Boom

Internet mania, Telecoms, emerging markets,

Financial casino & housing

Sustainable global "golden age"?5th

London funded global market infrastructure build-

up (Argentina, Australia, USA)

Belle Epoque (Europe) "Progressive Era" (USA)3rd

The Roaring Twenties Autos, housing radio, aviation electricity

Post-war Golden Age4th

1793-97

1848-50

1890-95

Europe1929-33

USA1929-43

2007/08-????

Every major technology development surge has seen the same

pattern play out

The installation phase is a period where new firms are formed and

older firms fail




The new normal is here and it’s not growing There’s also a growing school of thought that views the technology-led productivity gains of the 1990s and early 2000s as temporary - that the real impact of the ICT revolution will be a lower sustained pace of economic growth. Robert Gordon, professor of economics at Northwestern University, created a stir with his paper “Is US Economic Growth Over” in 2012 and several subsequent updates. He predicts that for the next 25-40 years, real per-capita disposable income of the bottom 99% of the US income distribution would grow at an average annual rate of 0.2%, a tenth the pace of the 2% per year for the century before 2007.

Gordon makes the argument by comparing the ICT revolution to the first two industrial revolutions, with the view that the first two revolutions spurred growth that lasted 100 years as innovations were absorbed into the economy. His view is that after an initial boost in productivity and growth from 1994-2004, the potential impact from further technology innovations will be minimal while multiple headwinds will limit US economic growth.

Gordon makes the case that the impact of the second industrial revolution beginning around 1870 was exceptional because the major inventions of the era coincided within a short time and powered a massive transformation of society and the economy. These inventions included electricity, the internal combustion engine, running water, indoor heating and plumbing, rearranging molecules with petroleum, chemicals, plastics and pharmaceuticals, and the evolution of communications and entertainment devices including the telephone, phonograph, radio and motion pictures. These innovations saw adoption from zero to near 100% in developed countries, creating massive new industries as a result.

From productivity gains to entertainment devices In contrast, the third industrial revolution (which he characterizes as computers and the internet) provided an initial boost to productivity by automating away rote tasks and repetitive work. There was a boost to economic growth at the advent of the “new economy” in the late 1990s, but after 2004 most of the impact of innovations has been around devices and entertainment and the economic benefit faded. In his view, the biggest gains from computers and the internet have already been well absorbed by the economy and society and the changes ahead are far less consequential. This line of thought aligns with economist Tyler Cowen’s book The Great Stagnation.

Gordon segments the average growth rates of US labor productivity into several intervals to illustrate his case: from 1891-1972, labor productivity growth averaged 2.33% per year; from 1972-1996, it was 1.38%; from 1996-2004, it was 2.46%; and from 2004-2012, it was just 1.33%. In his view, the era of computers replacing human labor is over, replaced by a succession of consumer entertainment and communications devices that have little to no effect on productivity. In our view, the declining cost of compute, storage and connectivity is just now (2015) enabling a whole range of new uses of the technology in different industries - with the impact from “sharing economy” and Internet-of-Things applications yet to come.

Technology has deflationary impact on corporate wages There’s increasing evidence that adoption of technology drives value creation by automating tasks, but this has deflationary impact on wages. Andrew McAfee of MIT compared labor’s share of corporate expenses versus corporate profits as a share of GDP. 2015 data show ever-widening divergence since the

There are growing views that the ICT revolution

will lower the sustained pace of economic growth

The first two industrial revolutions spurred growth that lasted

100 years

The impact of the second industrial revolution

beginning around 1870 was exceptional

After 2004, most of the impact of innovations has been around devices and

entertainment

Is the era of computers replacing human

labor over?

Increasing evidence that technology drives value

creation but is deflationary to wages




last recession. Corporate profits, meanwhile, have never been higher in absolute terms or as a percentage of GDP. This analysis highlights that the two lines typically move in the opposite direction: when more money is paid out to workers, there’s less left over for profits. The labor component includes realized compensation and fringe benefits as well as benefits like healthcare coverage for retirees.

Figure 15

Corporate profits gain as a share of GDP, while labor’s share of business declines

Source: Research.stlouisfed.org, Andrew McAfee (MIT)

It’s our view that technological advances are also a key factor behind the growing divergence between rising corporate profits and labor’s declining fortunes. When technologies arise that reduce the need for human workers at lower costs, the cost of technologies also tends to decline over time. This allows productivity gains without impacting corporate profits, while reducing labor’s share of the pie.

We’d note that there is also a “productivity paradox”, which refers to the transformative technologies - that there is typically a delay between the installation of the new systems and realization of productivity benefits. MIT professor Erik Brynjolffson found that there can be a five- to seven-year lag between deployment of an enterprise-resource-planning (ERP) system and subsequent benefits. A contrarian view to Robert Gordon’s argument is that he may not anticipate the delayed impact of technologies on a broad societal scale. The explosive proliferation of smartphones and social computing is just taking hold, which would suggest that broader gains in productivity lie ahead and their impact may surprise us in magnitude and apparent suddenness.

Digital disruptions can catch the best informed by surprise Technology revolutions can be painfully disruptive. Forecasting the future is difficult, and even those with the deepest expertise can fail to anticipate adoption of disruptive technologies - by orders of magnitude. In the mid-1980s, AT&T asked McKinsey to forecast the number of cellphones in the USA in 2000 - the forecast was 900,000 - the actual number turned out to be 109m. In 2000, Kodak had US$14bn in revenue and US$2.2bn in profit, and filed for bankruptcy in 2012. Often it’s the industry experts that dismiss disruptive technologies.

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Technologies get cheaper over time, so productivity

gains don’t impact corporate profits

Automation enhances profits by reducing

wages

The productivity paradox could play out on

a larger scale

Even those with the deepest expertise can fail to anticipate adoption of disruptive technologies




Tech disruptions come from below, from above and as a “big bang” Stanford professor and author of Clean Disruption Tony Seba characterizes three types of technology disruption:

Disruption from below, which refers to the classic disruptive innovation articulated by Clayton Christensen in his book The Innovator’s Dilemma, where new entrants have lower cost and functionality and ultimately displace incumbents who are focused on taking care of their customers. Change can come rapidly. The print newspaper industry increased from US$20bn in 1950 to US$60bn in 2000, then dropped in half by 2010 because of web advertising.

Disruption from above, which differs in that the disrupting products start at the high end of the market, eventually disrupting incumbents as prices decline over time. Tesla is an example of a superior product and service that works its way down market as costs decline.

Big bang disruption, which starts with better performance, lower price and more customization. The impact of Google Maps on hardware GPS units is an example.

Technology adoption exacerbates imbalances Despite the promises of innovation, Robert Gordon and other others are quantifying painful economic imbalances that are becoming more pronounced. The modern digital revolution has yet to deliver on the promise of better jobs and higher productivity. Instead, the new economy is creating immense wealth with far fewer workers, with income growth stagnating for the vast majority of employed. The stratification of income growth over the past decade has concentrated the majority of income gains in the top percentile while the median income in 2011 is 8% lower than in 2007, having peaked in 1998. These figures show earnings from labor are declining as a share of total economic output, but the share gains from highly skilled sectors have been growing.

Figure 16

Median income and employment have diverged from GDP growth

Source: Research.stlouisfed.org, Andrew McAfee (MIT)

Cutting a broad swath through unskilled jobs The phenomenon of technology replacing jobs is not at all new. What’s different now is that it’s software and artificial intelligence replacing tasks and jobs at a dramatic pace. The downside for employment is that fewer people

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Despite the promises of innovation, there are

increasingly painful imbalances

Software and artificial intelligence are replacing

tasks and jobs at a dramatic pace

Disruptions come from below, from above and as

a “big bang”

The “Great Decoupling” of income and employment

from GDP growth accelerated in the 1980s




are required in many industries (eg, airlines, manufacturing and the supply chain). As service-sector tasks are increasingly automated, this reduces the need for cashiers, toll takers and potentially taxi drivers as we’ve previously seen technology replace stenographers, typists or bookkeeping people. Economist Tyler Cowen highlights the growing phenomenon of the technology-aided high performer. He notes that we are seeing what's called labor-market polarization, a concept identified with MIT labor economist David Autor. Increasingly, workers are falling into two camps: those that do very well and those that do not do well at all.

Digitization and dematerialization: Everything becomes software The forces of digitization (of information and media) and dematerialization (reducing goods and services to software) have profound implications for the economy and for society on a global basis. Rendering physical goods into digital bits and bytes has profound implications across the value chain, impacting manufacturers, the supply chain, distribution, retailers and end users.

Digitization turns services into software An example of the impact of digitization is tax-preparation software. Intuit created packaged software that replaces many of the functions previously performed by a certified public accountant (CPA) or other tax-preparation professionals. Typically for less than US$100, the consumer gains access to the same (or more up-to-date) level of expertise that not only formerly costs hundreds of dollars but also employed many middle-class professionals. Over the next decade, we expect to see further disruption and transition as physical goods and services are increasingly attached to and replaced by software.

Dematerialization turns gadgets into bits An example of dematerialization is the transformation of consumer electronics into software applications. Historian Steve Cichon looked at a 1991 ad by Radio Shack. He calculated that 15 items, including pocket calculators, cameras, mobile telephone, video camera, clock radio, portable CD player, video cassette player and other items, were worth US$3,054 at the time (equivalent to US$5,100 in 2012 dollars). He found that the functions of all of these items were included in a US$600 iPhone, a 10:1 compression of value.

“The second economy” connections largely hidden from view Digitization has transformative and disruptive implications. Dematerialization (of personal electronics, recorded music, books, video, etc) alters the economics of many businesses based on physical goods. As more computers become connected, a fundamental shift occurs as business processes that were previously handled by human beings are now being executed electronically. Because these processes usually involve computers talking to one another, they are unseen.

W Brian Arthur, professor at the Santa Fe Institute, raised the idea of a “second economy” in a 2011 article for the McKinsey Global Institute. He argued that information technology is creating a digital second economy. Processes in the physical economy are being entered in the digital economy, where conversations occur between servers and nodes, checking steps and updating data before reconnecting with humans. Processes that used to be handled by humans, such as booking an airline ticket and checking in for a flight, are now handled almost entirely by electronic means.

Rendering physical goods into digital bits and bytes has profound implications

across the value chain

Software programs can replace expert

professional services

A fundamental shift as human business

processes become digital communications

Information technology is creating a hidden, digital

“second economy”

Consumer electronics are being reduced to software

applications




Arthur describes the second economy as ‘vast, silent, connected, unseen and autonomous (meaning that human beings may design it but are not directly involved in running it). It is remotely executing and global, always on and endlessly configurable. It is concurrent - a great computer expression - which means that everything happens in parallel. It is self-configuring, meaning it constantly reconfigures itself on the fly, and increasingly it is also self-organizing, self-architecting and self-healing.’

Despite disruption, traditional GDP measures may not capture change One of the great challenges with the advent of digitization is that measuring digital goods and services as a proportion of GDP is difficult, if not impossible. Eric Brynjolfsson and Andrew McAfee, authors of The Second Machine Age, estimated the total value of digitized goods to the US economy at roughly US$300bn per year that does not get measured as traditional output.

Much economic value is not captured by traditional means While the music industry saw revenue decline from US$16bn in 1998 to around US$6bn in 2008, listeners have been able to access music through YouTube, Spotify, Pandora, iTunes and other sources that are difficult to measure. Similar economics apply to magazines, newspapers and other print media that have seen readers migrate online. Hours spent on the internet continue to climb (doubling from 2001 to 2011) and consumers access ever more free goods in the form of Facebook postings, blogs, online videos, games and other pursuits. As the volume of digital goods increases, this renders the traditional GDP measure less useful.

Challenges to US long-term growth are broad-based In his January 2014 paper, “Is US Economic Growth Over? Faltering Innovation Confronts the Six Headwinds,” Robert Gordon cites the following challenges to growth: the end of the “demographic dividend”; rising inequality; factor price equalization stemming from the interplay between globalization and the internet; the twin educational problems of cost inflation in higher education and poor secondary student performance; the consequences of environmental regulations and taxes that will make growth harder to achieve than a century ago; and the overhang of consumer and government debt.

More funding, but fewer startups 2014 saw a turnaround as 254 US venture funds, up 23% YoY, raised a total of US$29.8bn, up 68% YoY, surpassing 2008 levels. According to the MoneyTree Report by PriceWaterhouseCoopers (PwC) and the National Venture Capital Association (NVCA), startup investments in 2014 were US$48.3bn, up 61% from 2013. University of Maryland economist John Haltiwanger’s team used Census Bureau data to calculate annual startup rates by dividing the number of new firms by the total number of firms for each year. In the late 1980s, the startup rate was 12.0%. This declined to 10.6% before the 2007 Great Recession, then fell sharply below 8% in 2009. The percentage of all firms that were five years or younger was 47% in the late 1980s and declined to 39% in the mid 2000s. According to US Census Bureau data, all net new job creation in the USA between 1980 and 2005 came from young businesses less than five years old.

The skills gap remains an issue with many unfilled jobs Despite growing cannibalization of many types of jobs, there is also a growing unfilled need for more highly trained employees. A report from Georgetown University's Center on Education and the Workforce, authors Anthony

The second economy is ‘vast, silent, connected,

unseen and autonomous’

An estimated US$300bn in digital goods are not

measured in annual US GDP

The music industry saw revenue decline from

US$16bn in 1998 to around US$6bn in 2008

All net new job creation in the USA between 1980

and 2005 came from young businesses

There are multiple headwinds challenging long-term US economic

growth




Carnevale, Nicole Smith and Jeff Strohl predict a shortage of 3m workers with post-secondary degrees by 2018, increasing to 5m by 2020. The lack of skills in science, technology, engineering and mathematics is pronounced. This points to shortcomings in K-12 education, while disproportionate cost increases in higher education are an obstacle and burden to students.

R&D investment lags, while regulation creates new burdens The USA is now in 10th place among the Organization for Economic Co-operation and Development (OECD) nations in R&D investment as a percentage of GDP, a decline from 2nd place in 1992. Between 2009-11, the Obama administration issued 106 new regulations that are each expected to have an economic impact of at least US$100m a year. Sarbanes-Oxley costs roughly US$1m, on average, a year for public companies, a significant burden for smaller public firms.

What the new economy will look like There’s always risk in trying to predict what the future economy will look like, but there are threads that will characterize the coming decade. Many of the changes will be generational, as the digitally native millennials increasingly exert impact on commerce, culture and innovation. Other shifts result from what Gartner refers to as the “Nexus of Forces”, IDC defines as the “3rd Platform” and BCG describes as a “software-driven digital metasystem” - a mobile-first environment of near-infinite compute power and connectivity with the capacity to scale massively sophisticated analytics in real time.

Products become experiences. This also touches on a potentially more profound shift away from a consumerist culture based on ownership of physical products. Sharing-economy businesses like Uber, AirBnB and Lyft address needs through a shared-asset model. Connected health-fitness trackers include gamified cloud applications. In “How Smart, Connected Products Are Transforming Competition,” a November 2014 Harvard Business Review cover story, co-authors Michael Porter of Harvard Business School and Jim Heppelman, CEO of PTC, outline how an emerging generation of cloud-service-enhanced products will create new partner ecosystems and fundamentally new value chains in the economy.

Design drives differentiation. Companies like Apple, Chrysler, Oxo and others have embraced the premise that smartly designed computers, cars and kitchen tools can stand out in established categories. While engineering remains critically important, creative design is paramount for developed-market firms to prosper in an environment where production is global, choices are myriad and competition is omnidirectional.

More value from fewer resources. Businesses are finding ways to produce more with less energy and materials. Additive manufacturing (3D printing) reduces manufacturing waste; smart grids and intelligent thermostats like Nest optimize energy consumption; and cloud computing allows startups and enterprises to innovate faster with lower costs and overhead. The ability for startups like Pinterest and WhatsApp to scale to hundreds of millions of users with only a few dozen employees is a harbinger of hyper-efficient organizations.

The skills gap is forecast to create a shortage of

5m workers by 2020

There will be growing emphasis on the total

experience rather than discrete products

Creative design is paramount for developed-

market firms to prosper

Businesses are finding ways to produce more

with less energy and materials

There are threads that will characterize the

coming decade


Section 2: Cash builds amid decline in startups Innovation


Cash builds amid decline in startups Robust gains in VC funding and investment complement healthy capital markets

and M&A activity. However, the pace of new business formation continues to

decline. Structural dynamics favor larger firms as headwinds include slippage in

science, technology, engineering and mathematics (STEM) education, broken

immigration policies, costly patent litigations and over-regulation.

Availability of financing options is crucial to innovation activity and

competitiveness, and 2014 saw robust activity in IPOs, M&A, venture-capital

funding and investment. As the bar to the capital markets grew higher in the

wake of Sarbanes-Oxley legislation, the ability to secure returns through

initial public offerings has been difficult since the number of annual offerings

peaked at 650 in 1996. For venture-backed firms, the past decade has been

challenging, as the number of offerings dropped from 92 in 2007 to just

seven in 2008. However, this has rebounded to 81 in 2013 and 115 in 2014.

Research firm CB Insights identified 590 US tech companies backed by

venture capital or private equity with valuations over US$100m in the IPO

pipeline in 2014. Of these, 43% raised additional financing or exited via IPO

or M&A, with the remaining 57% still active. We see 2015 shaping up to be

another strong year, with 588 US tech companies in the IPO pipeline backed

by venture capital or private equity with valuations over US$100m.

Figure 17

Annual US venture-capital exit activity

Year Total M&A

deals

(No.)

M&A deals with

disclosed values

(No.)

Total disclosed

M&A value

(US$m)

Average M&A

deal size

(US$m)

No. of

IPOs

Total offer

amount

(US$m)

Average IPO

offer amount

(US$m)

2007 488 200 30,745.5 153.7 92 12,365.5 134.4

2008 423 134 16,236.9 121.2 7 765.0 109.3

2009 361 109 12,364.9 113.4 13 1,979.8 152.3

2010 545 151 17,713.5 117.3 66 7,409.5 112.3

2011 500 169 24,093.2 142.6 50 10,441.1 208.8

2012 490 132 22,694.2 171.9 49 21,459.9 438.0

2013 393 95 16,909.8 178 81 11,068.2 136.6

2014 455 132 46,024.1 348.7 115 15,299.1 133.0

Source: Thomson Reuters, National Venture Capital Association

In 2014, venture-backed IPOs raised US$15.3bn from 115 listings, reflecting

the strongest full-year total for the number of venture-backed IPOs since 2000.

Figure 18

US venture-backed company M&A deal activity

Source: Thomson Reuters, National Venture Capital Association

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For startups, access to

venture capital and angel

investors is particularly important

Venture-backed M&A

exits increased in

2014 from 2013

With 588 US tech firms in

the IPO pipeline, 2015 is

shaping up to be another strong year

Robust gains in VC

funding and investment,

but pace of new business formation declining




The pace of M&A exits grew significantly as acquisitions of venture-backed companies were valued at US$46.0bn in 2014 from 132 deals with disclosed values out of a total of 455 deals. This marks the strongest year for venture-backed M&A since 2012. The average M&A deal size grew to US$348.7m in 2014 from US$178.0m in 2013, representing a YoY increase of 96%. Excluding Facebook’s record-breaking acquisition of WhatsApp for US$19.5bn, total disclosed M&A value would be US$26.5bn or US$202.5m in the average M&A deal size, still representing a YoY growth of 14%.

Venture fundraising recovers Funding had also been challenging for the past five years, particularly for smaller firms, but 2014 saw a turnaround as 254 US venture funds, up 23% YoY, raised a total of US$29.8bn, up 68% YoY in dollar terms and surpassing 2008 levels.

Figure 19

Annual US venture-capital fundraising activity

Year Number of funds Venture capital (US$m) 2008 213 25,050.4 2009 161 16,088.7 2010 175 13,272.0 2011 191 19,060.5 2012 218 19,838.2 2013 207 17,694.1 2014 254 29,826.4 Source: Thomson Reuters, National Venture Capital Association

The Center for Venture Research found that US angel investors funded 70,730 entrepreneurial ventures worth some US$24.8bn in 2013, up 8.3% from US$22.9bn in 2012. The number of active investors increased 11.4% from 2012 to 299k, but data showed that investors who did invest in 2013 have decreased individual investments slightly from US$85k in 2012 to US$83k in 2013, representing a 2.8% YoY decline. Angels invested in a variety of sectors, with software leading at 23%, followed by media (16%), healthcare (14%), biotech (11%) and retail (7%).

According to the MoneyTree Report by PwC and the NVCA, startup investments in 2014 were US$48.3bn, up 61% from 2013. The number of deals at 4,356 grew 4% from a year ago. Internet-specific companies captured a total of US$11.9bn in 2014, the highest level since 2000, while the software industry also grew to the highest level since 2000, with a total of US$19.8bn investments from 1,799 deals in 2014, representing a 77% YoY increase in dollar terms and a 10% YoY increase in deal volume.

However, entrepreneurial activity has declined Despite the robust capital market and VC rebound, entrepreneurial activity has been declining. The formation of new firms has seen a continued dip since reaching its most recent peak in 2010, returning to the pre-recessionary levels of 2006. The Kauffman Index of Entrepreneurial Activity tracks the pace of formation of new businesses in the USA. It’s not particularly clear what the drivers are, but the trend has been underway for some time.

Last year was also strong for venture-backed M&A

Funding grew dramatically (68% YoY)

for VC firms in 2014

US venture funds raised US$29.8bn in 2014

VC investments increased 61% YoY in 2014

It’s not immediately clear why startup activity

has declined




University of Maryland economist John Haltiwanger’s team used Census Bureau data to calculate annual startup rates by dividing the number of new firms by the total number of firms for each year. In the late 1980s, the startup rate was 12.0%. This declined to 10.6% before the 2007 Great Recession, then fell sharply below 8% in 2009. The percentage of all firms five years or younger was 47% in the late 1980s and declined to 39% in the mid 2000s.

Figure 20

Kauffman Index of Entrepreneurial Activity

Source: Kauffman Foundation

The increasing capital efficiency of software and internet firms (with the proliferation of open-source software and public cloud computing) reduces initial capital needs for many startups. This, in turn, lowers barriers to entry for startups, while altering the value equation. Because the amount of capital needed is less, a VC investment in itself is no longer a de facto competitive advantage for startups competing for the same markets to the extent that capital access itself is strategic. The value that venture investors provide is management insight, access to executives and customers, mentoring and other intangibles.

R&D spending modestly improving, but lagging other nations Battelle/R&D Magazine forecasts 3.2% growth to US$465bn in US R&D expenditures in 2014. With an Office of Management and Budget (OMB) estimated 2.2% inflation rate in 2014, this effectively represents an increase of 1.0% in real terms. In 2013, the US federal government spent US$121bn on R&D funding, representing a drop to 27% of the overall US total from the prior year due mainly to the impact from sequestration. The most active investors in innovation are in the computer/electronics industry, which accounted for 26% of R&D spending in 2014. Healthcare is the second-largest R&D spender, accounting for 21% of the total, followed by autos at 16% and industrials at 11%.

According to Booz & Company’s annual study of the 1,000 largest publicly traded firms based on R&D investment, R&D spending grew at 1.4% to US$647bn in 2014, the second year in a row of slower-than-average growth after the strong gains in 2011 and 2012. The three top industries by R&D spending were computing & electronics, healthcare and auto.

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(%)

Lightweight innovation has reduced capital needs

for software and internet startups

Many well-known technologies have their

roots in government R&D

Downward trend of entrepreneurial activity

continued in 2013

Chinese firms grew R&D investment in 2014 at an

impressive 45.9% YoY




Figure 21

Global innovation spending by industry

Source: Booz & Company

A recent study by the Brookings Institution noted that the US share of global patenting and R&D is falling much faster than its share of global GDP and population - meaning it’s not simply the result of demography or macroeconomic convergence. From 1981 to 2011, the US share of world GDP fell 7% versus a 1% decline in share of world population. While this reflects gains from smaller countries, the USA lost 12% share of global patenting and R&D spending, while US R&D imports saw an 18% Cagr from 2000 to 2012, twice as fast as R&D export growth.

Federal support for basic research as a percentage of GDP has declined 13% over the past decade. In 1992, the USA had the second-highest R&D investments as a percentage of GDP among OECD nations. It has now fallen to 10th place. While the USA is losing some of its competitive edge, emerging nations are increasing their research investments in order to stimulate economic growth. China is projected to outspend the USA in R&D within the next 10 years.

Innovation benefits from technology enablers We identify several accelerators of innovation from a technological perspective. The convergence of enabling factors and technologies leading to declining cost of innovation - open source, cloud computing, mobility and commoditization of hardware/software and bandwidth - provides the catalyst to create value and accelerate innovation, all facilitated by software. Key enabling trends include:

Exponential declines in the cost of computing, bandwidth and storage, which lower barriers to adoption and enable unparalleled scale for new ventures.

Cloud computing, which enables users to procure IT resources and content on an as-needed basis.

Open-source software, which empowers users with flexibility and increasingly robust functionality at little or no cost.

The mobile internet, which connects users with information and applications regardless of device, connection or location.

Computing and electronics

26%

Healthcare21%

Auto16%

Industrials11%Software and

internet9%

Chemicals and energy

7%

Aerospace and defense

3%

Consumer3%

Telecom2%

Other2%

The most innovative companies are in the

computer/electronics industry

Over the next decade, computing will become increasingly embedded

in daily life

The USA lost more share of global patents and R&D

spending than GDP or population

The rank of R&D investment as a share of

GDP has dropped as well




Growing penetration of internet users and social networking, which results in near-ubiquitous reach of services.

Computing is becoming more intuitive and pervasive with the evolution of more powerful software, rapid growth of endpoint devices, availability of instant-on connectivity and declining costs of hardware, bandwidth and storage. We see the continuous elevation of simplicity of experience to the user as logic controls the underlying systems, processes and infrastructure with increasing power. These concurrent trends have a transformative impact, accelerating innovation across the broader economy in traditionally non-tech as well as technology industries.

Commoditization of computing, bandwidth and storage The commoditization of computing, bandwidth and storage has proven to be a continuous dynamic. The principle of Moore’s Law, which holds that processor performance can double every 18 months, has held fast since the 1970s, while price performance of Dram continues to improve along a similar dynamic.

Figure 22

Moore’s Law

Source: Wikipedia (Wgsimon)

In fact, the dynamic of exponential cost and performance improvement is occurring across a broad range of technologies. While improvement occurs at different rates, the consistent historical trend remains a common dynamic across different hardware technologies. Butters’ Law (named for Gerald Butters, former head of Lucent's Optical Networking Group at Bell Labs) posits that the amount of data coming out of an optical fiber doubles every nine months, essentially cutting the cost of data transmission in half over that period.

Technology has a transformative impact, accelerating innovation

across the economy

Cost of computing, bandwidth and storage

continues to decline

Moore’s Law has held fast since the 1970s




Figure 23

Time to double (or half)

Dynamic Ram memory “half pitch” feature size 5.4 years

Dynamic Ram memory (bits per dollar) 1.5 years

Average transistor price 1.6 years

Microprocessor cost per transistor cycle 1.1 years

Total bits shipped 1.1 years

Processor performance in MIPS 1.8 years

Transistors in Intel microprocessors 2.0 years

Microprocessor clock speed 2.7 years MIPS = Millions of instructions per second, a measure of processing capacity. Source: Ray Kurzweil, KurzweilAI.net

Cloud computing accelerates incubation of new ideas Cloud computing has lowered barriers for technology adoption, reduced time to market and placed unprecedented computing power in the hands of startups, departmental IT staff and others heretofore lacking access to scalable systems.

Importantly, the availability of cloud-based resources is lowering barriers for startups and fuels accelerating innovation. The capital efficiency that can be applied to developing, introducing and then iterating on these new applications is declining. The capital efficiency for a venture firm trying to launch new companies is becoming much better. The Law of Accelerating Returns on these technologies is at play.

Cloud computing facilitates a range of new use cases around social computing, mobile services and high-performance analytics, all of which have the potential to create new economic value. Cloud computing reflects the industrialization of information technology. While this has disruptive effects on certain providers of infrastructure components and services, there are many beneficiaries of broad-based adoption of cloud computing.

Businesses benefit from lower costs for technology, IT staff and overhead, while gaining benefits of agility. Lowering the marginal cost of failure accelerates innovation and allows for rapid value creation. The extensible aspects of cloud computing allow businesses to scale online operations far more quickly than possible on their own, for less capital, with less risk.

Consumers benefit directly and indirectly from the availability of cloud-enabled applications. Cloud-enabled search, entertainment, information services, location-based services and applications democratize access to culture, knowledge and commerce. Dematerialization of physical goods (for instance, the digitization of books, music and video) into cloud-delivered services reduces friction around information flow.

It’s our view that cloud computing and related technologies such as open-source software and higher-level programming languages are a parallel to James Watt’s steam engine in the first industrial revolution, with compute power substituting for coal. As such, disruption within the IT infrastructure market is likely to continue along a path of creative destruction as proprietary infrastructure hardware and software providers see their ability to charge premium “rents” and enjoy attractive profit margins steadily erode.

A wholesale economic model disrupts a bespoke industry. We point to the 2006 introduction of Amazon’s EC2 as the turning point where scalable compute and storage became available on a self-serve, pay-per-use model.

Availability of cloud-based resources is

lowering barriers for startups

Exponential cost and performance

improvement occurs across technologies

Cloud computing enables social computing, mobile

services and high-performance analytics

Open-source software and higher-level programming languages parallel James

Watt’s steam engine




Native cloud architecture commoditizes infrastructure hardware and software. A mature Platform-as-a-Service (PaaS) layer decouples the application logic from the underlying infrastructure and makes infrastructure components increasingly interchangeable and subject to the forces of commoditization.

Open source - Freeing innovation and enabling cloud computing Open-source principles inherently enable innovation, not just in software, hardware and services, but through the derivative benefits to technology users in any endeavor. There are over one billion lines of freely available open-source code that developers and business users can access to create applications and new businesses. Free open-source software reduces costs for startups as well as new projects within IT organizations. Even with paid technical expertise and support, the ROI tends to be overwhelmingly favorable for open source.

Open-source alternatives to proprietary technologies gain ground The shift to cloud computing accelerates as open source is increasingly viable for the enterprise. There are increasingly viable open-source alternatives to proprietary software, all the way up the stack from OS (Linux, Android) to database (MySQL, MongoDB, Cassandra), Big Data/data-warehousing management (Hadoop, Talend), content management (Drupal), application server (JBoss), analytic tools (R language, Pentaho, Jaspersoft), customer relationship management (CRM) (SugarCRM) and many more. It is not unusual for startups, particularly in the internet or e-commerce arena, to avoid use of proprietary software entirely.

The mobile internet - “Any device, always on, anywhere” The explosive adoption of internet-enabled smartphones and the growing availability of wireless internet are key innovation vectors for new services and applications, including micropayments, content streaming, multiplayer gaming, location-based services and a plethora of targeted applications. In the coming decade, the deployment of high-speed mobile networks will help realize the vision of always-on high-speed internet connections and adoption of data-based applications.

Figure 24

Global IPv6-capable devices will reach 6.2bn by 2019

Note: Internet Protocol version 6 (IPv6). Source: Cisco 2015

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2014 2015 2016 2017 2018 2019

Number of devices (bn)

Open source has been critical to enable

innovation, not just in software

Adoption of smartphones and the wireless internet helps realize the vision of

pervasive computing

The leading cloud platforms, including

Google and Amazon EC2, are built on open source

Smartphone penetration will connect billions to the internet for the first time




Advanced mobile networks support a new generation of innovative applications, including content, shopping, HDTV, collaboration, social networking, video conferencing, robust gaming, additional personalized offerings and Internet-of-Things applications. This in turn expands the innovation of connected devices beyond tablets, smartphones and laptops. Increasingly, there will be wireless-connected audio, video, sensors, industrial equipment, automobiles and appliances. The availability of greater bandwidth will facilitate adoption of advanced applications, which should drive further growth of data traffic.

The proliferation of mobile applications is representative of the variety of innovations enabled by smartphones and the mobile internet, and this will be reflected both in consumer and enterprise adoption. New types of mobile applications expected to see healthy growth include money transfer by short message service (SMS), mobile search and browsing, location-based services, mobile music and video services, near-field communications services, mobile health monitoring and many others.

Mobile explosion a hotbed for innovation The world is increasingly mobile, with over 6.9bn estimated subscribers in 2014, representing approximately 96% of the world’s population, according to the International Telecommunication Union. The penetration rate for fixed-line telephone service in 2014 was estimated to be less than 16% of the world’s population. IDC estimates the worldwide mobile-phone market will grow at 5.4% YoY in 2014 to over 1.93bn mobile-phone shipments, with smartphones accounting for 67% or nearly 1.3bn units.

Figure 25 Figure 26

Mobile broadband connections, excluding M2M Global average mobile network connection speeds

Note: Machine to machine (M2M). Source: GSMA Intelligence Source: Cisco VNI Mobile 2015

Not only are the number of connections growing, bandwidth is as well. The GSM Association estimates mobile broadband connections at a 15% Cagr from 2013-20, while average global mobile network connection speed is forecast to increase by a 9% Cagr from 2014 to 2019.

In the USA, mobile penetration is heading towards ubiquity, with 41% of households “wireless only” in 2013 as estimated by the National Center for Health Statistics. For carriers, mobile revenue continues to benefit from subscriber adoption, growing 2.2 times in wireless data usage in 2013 over 2012, driven by the proliferation of smartphones, tablets, netbooks and other mobile devices.

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Innovations and connectivity enable a new

class of mobile applications to emerge

Total global mobile subscribers approximate

96% of the world’s population

More devices, faster connections: more bits

More advanced mobile networks will support a new range of innovative

applications




Figure 27

US mobility statistics

Dec 97 Dec 98 Dec 02 Dec 03 Dec 07 Dec 08 Dec 11 Dec 12 Dec 13

Wireless subscribers (m) 55.3 69.2 140.8 158.7 255.4 270.3 316.0 326.4 335.7

Wireless penetration % of total US population 19.8 24.6 48.0 53.6 83.1 87.2 99.7 102.2 104.3

Wireless-only households % of US households na na na 4.2 15.8 20.2 34.0 38.2 41

Annualized total wireless revenue (US$bn) 27.4 33.1 76.5 87.6 138.9 148.1 169.8 185.0 189.2

Annual voice minutes of use (bn) 62.9 89.0 619.8 829.9 2,120.0 2,200.0 2,296.0 2,300.0 2,620.0

Annual wireless data usage (MB) na na na na na na 866.7 1,468.0 3,230.0

Source: CTIA

Cisco’s Visual Networking Index (VNI) estimates that global mobile data traffic will increase nearly 10-fold between 2014 and 2019 to 24.3 exabytes per month (a 57% Cagr), with mobile video increasing 13-fold to 72% of the global mobile data traffic in 2019.

Smartphone apps are the nexus of innovation The broad adoption of smartphones paves the way for rapid innovation of new internet-based applications and services. Apple’s AppStore has more than 1.3m applications with over 85bn downloads reported. The evolving ecosystem around smartphone platforms has given rise to many successful new businesses - not just games, but thousands of applications for productivity, news, lifestyle and other uses. Statista predicts annual mobile application downloads to reach 269bn in 2017.

Figure 28

Free versus paid mobile app downloads worldwide

Source: Statista, CLSA

Internet adoption grows potential end markets for innovators According to Cisco’s estimates, the total number of internet users worldwide exceeded 2.5bn in 2013, about 35% of the worldwide population of 7.2bn. Cisco expects growth to continue, with an estimated 4bn global internet users in 2018, representing more than 51% of the world’s population. Thirty-three percent of internet traffic in 2013 originated from non-PC devices (including tablets, smartphones and televisions); this number is likely to grow to 57% by 2018.

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App downloads (bn)

Free downloads Paid-for downloads

Adoption of smartphones paves the way for rapid

innovation of new applications and services

Cisco estimates 4bn internet users

worldwide by 2018

Statista forecasts an increasing ratio of free

application downloads for every paid app download




Figure 29

Global internet users by country, 2012

Source: International Telecommunications Union (ITU)

The ITU estimates that over 40% of the global population was connected to the internet in 2014, with the most dramatic growth occurring in Africa, the Arab States and the former (Russian) Commonwealth of Independent States.

Figure 30

Worldwide internet usage

Region 2005 2014 Cagr 2005-14 (%)

Penetration % of total population, 2014

Africa 17 172 29.6 19.0 Arab States 26 152 21.6 40.6 Asia & Pacific 344 1,310 16.0 32.4 Commonwealth of Independent States1

29 158 20.9 55.9

Europe 277 467 6.0 74.8 The Americas 316 639 8.1 65.5 World total 1,009 2,898 12.4 40.2 1 Also known as the Russian Commonwealth. Source: ITU World Telecommunication/ICT Indicators database

Never a straight line - The headwinds to innovation The USA is struggling to sustain its competitive edge, which has slipped over the past decade. The Information Technology and Innovation Foundation ranked the USA fourth out of 44 nations in innovation-based competitiveness in a 2011 report, with the USA ranking second to last in the rate of change in its competitive position between 1999 and 2011. There are multiple factors behind this slippage, and much can be attributed to regulatory obstacles, shortcomings of the educational system and the increasingly litigious environment around intellectual property. The Global Innovation Index, sponsored by the World Intellectual Property Organization, INSEAD and Cornell’s Johnson School, showed the USA was down one place from 2013 to 6th in 2014. However, there are signs of improvement. In 2014, the country was placed third in the World Economic Forum’s (WEF) annual Global Competitiveness ranking.

Concerns over the higher-education bubble One of the greatest challenges for students - and the economy as a whole - is the untenable state of student debt, which now exceeds US$1.2tn in the aggregate in the USA. Debt service limits borrowing capacity for buying a car,

Number of internet users worldwide exceeded

2.5bn in 2013, ~35% of worldwide population

America’s competitive edge has been slipping

Penetration in Africa, the Middle East and Asia has

a long way to go

One of the greatest challenges is the

untenable state of student debt




home and starting a family, and ultimately could cause real-estate-asset deflation for retiring baby boomers who fail to find buyers for trade-up homes. In our view, higher education is the next bubble to deflate. There are already signs of price declines at lower-tier colleges and declining grad-school enrollment in certain fields. Later in this report, we address the rising phenomenon of MOOCs as a partial means to address these issues.

An educated workforce is critical for innovation A highly educated workforce with significant participation in science and technology is key to drive innovative effectiveness. The USA is one of the world’s most educated countries, ranking fifth among OECD countries in terms of tertiary level educational attainment for those aged 25-64, with 42% holding a degree from an institution of higher learning.

According to the OECD, the USA was ranked one of the best educated in the world, with the percentage of 25-34 year olds with higher-education attainment at 43% in 2011. This places the USA at No.12 of 37 OECD and G20 countries. Higher-education attainment in the USA is growing slower than other OECD and G20 countries; US attainment levels increased an average of 1.3% between 2000 and 2010, versus 3.7% for OECD counterparts.

However, graduates are not choosing the right majors. The USA severely lags in science, technology, engineering and math (STEM) achievement, which is critical for an R&D-intensive workforce. The USA ranks 23rd among developed nations in terms of annual STEM graduates per person aged 20-34. It ranks 32nd in the percentage of its graduates majoring in STEM fields - just 13% of graduates majored in science, computer science, or engineering (compared to 27% in South Korea and Germany)

Immigration restrictions challenge entrepreneurs Immigration and innovation are inextricably linked, as many of the most creative entrepreneurs, scientists and investors have been attracted to the US environment and culture. Today, the USA places onerous restrictions on entry into the country, no matter what the reason. Annual caps and large fees on visas for highly skilled potential employees (H-1B) limit the number of jobs available to foreign graduates of America’s university system.

According to the Institute of International Education, a record high of 886,052 international students were enrolled in US institutions in 2013/2014, up 8.1% YoY compared to 4.2% for total US higher-education enrollment during the same period. Over 37% of international students were pursuing graduate degrees, with 46% enrolled in a science and engineering program. According to the National Science Foundation, foreign students at US universities earned 36% of science and engineering doctoral degrees in 2012.

Immigrants play a vital role in driving American innovativeness and growth. Immigrant inventors contribute to more than a quarter of US global patent applications. Meanwhile, 42% of the Fortune 500 companies were founded by an immigrant or their children. These 211 companies employ more than 10m people worldwide and generated US$5tn in revenue for the US economy in 2013, according to Innovate for America. As many companies are dissuaded by the process of sponsoring a highly skilled foreign employee (which can be timely, costly and aggravating), many engineers, scientists and entrepreneurs are choosing to pack up and return home - often India or China - to work for competitors to US firms or to start businesses that create jobs abroad.

Since 9/11, the USA places onerous

restrictions on entry into the country

About 40% of international students in

the USA are pursuing graduate degrees

Immigrant inventors contribute to more than a

quarter of US global patent applications

The rate of increase in education attainment lags

OECD counterparts

The USA severely lags in STEM achievement

The USA ranks No.5 in advanced degrees




Patently difficult According to The Economist, America’s patent system squelches competition, slows innovation and enables egregious predation through the legal system. “Patent trolls” are also known as patent assertion entities (PAEs) and often come in the form of non-practicing entities (NPEs), which are commonly shell companies with no operations, just a portfolio of patents used as the basis for litigation. In 2007, PAEs filed 24% of patent infringement suits in the USA, and this increased to 56% in 2012, according to a 2013 study by Robin Feldman, professor of law at the University of California, Hastings College of Law. The Department of Justice has an even higher calculation, estimating that PAEs filed 2,921 of 4,701 suits, representing 62% of all patent suits in 2012. According to RPX Corp, over 3,600 companies and names defendants were sued by PAEs in 2007, more than triple the number in 2007.

A May 2014 study by Catherine Tucker, professor of marketing at MIT Sloan School of Business, finds that VC investment would have likely been nearly US$22bn higher but for litigation brought by frequent litigators (defined as companies that file 20 or more patent lawsuits). The study covered the period from 1995 to 2012 and estimated with a 95% confidence interval that the amount of investment was between US$8.1-41.8bn relative to a baseline of roughly US$131bn of investment that actually occurred during that period. A 2012 study by James Bessen and Michael J Meurer of Boston University estimated the annual cost of NPE patent assertions at around US$29bn for defendants’ direct costs as a result of litigation as of 2011, up to US$80bn if indirect costs are included.

As of 2010, tech companies were far and away the top targets of litigation initiated by NPEs, with HP, Apple, AT&T, Sony and Microsoft topping the list. However, the big firms are not the only ones hit. Companies with less than US$10m in revenue comprise 55% of unique defendants to PAE suits. Of the sectors with the most litigated patents, PatentFreedom placed the semiconductor industry first, followed by software applications, financial services, communications equipment and system-infrastructure software.

As of 2015, there are active efforts underway by Representative Bob Goodlatte (R-VA) and John Cornyn (R-TX) to pass bipartisan legislation to force patent trolls to pay defendants’ legal fees if they lose a frivolous lawsuit, limit scope of discovery so targets are not overwhelmed with costly requests; and require infringement charges to be more specific.

Non-practicing entities - “Patent trolls” file more

than half of US patent lawsuits

Companies with less than US$10m in revenue

comprise 55% of unique defendants

The annual direct cost of NPE patent assertions is

estimated at around US$29bn

Bipartisan legislation underway to limit the

damage of patent trolls


Section 3: Charting the course for innovation Innovation


Charting the course for innovation We update our technology “meta-themes” - transparent IT, intelligent

systems and convergence - to highlight the importance of platforms for

innovation. “Transparent IT” describes how technology becomes increasingly

ambient, interactions more natural and tools more intuitive and powerful. The

combination of ubiquitous connectivity and Big Data analytics linking the

physical world with information technologies enables powerful, interactive

“intelligent systems”. Integration and coupling erase categorical distinctions

between hardware, software, services and content in a process we refer to as

“convergence”. Software remains at the top of the tech value chain as the

driving force in innovation, gaining strategic importance for non-technology

companies as well.

Transparent IT. Complexity gives way to simplicity. Powerful capabilities

become accessible and pervasive, while advanced technologies become

subsumed into systems and the environment.

Intelligent systems. Software and technology systems increasingly drive

intelligent automation, decision enhancement, process optimization and

risk management in self-directed, recursive systems. Advancements in

analytics and artificial intelligence create leverage from the exponential

growth of data from users, devices, sensors, applications and systems.

Convergence. Software, hardware, services, content and business

processes straddle previously discrete definitional and categorical barriers.

We expect vertical and horizontal integration, cross-disciplinary

development and M&A, and organic evolution.

Transparent IT Innovation over the next decade will be characterized by the trend towards

transparent IT, technology that appears so simple that the underlying

complexity becomes invisible to the user. The early Internet-of-Things vision

advanced the idea of “ambient computing,” which in many respects is

synonymous with transparent IT.

Computing is increasingly embedded in the daily lives of consumers, businesses

and other organizations. It will become more intuitive and pervasive with

adoption of natural user interfaces, more powerful software, proliferation of

devices, ubiquity of instant-on connectivity and declining costs of hardware,

bandwidth and storage. We expect the continuous elevation of simplicity of

experience to the user as logic controls the underlying systems, processes and

infrastructure with increasing power.

We identify four vectors that drive accelerating innovation towards

transparent IT: cloud computing, mobile internet connectivity, natural user

interfaces and more powerful development tools.

User interfaces - “See me, feel me, touch me - think me?” Natural

interfaces expand the experience of computing beyond the traditional

keyboard/mouse, touch and speech recognition currently available. Touch

and haptic interfaces enable new types of applications: gaming,

empowering the disabled, medical procedures, industrial processes,

training, simulation and therapy. Haptic interfaces have applications in

virtual reality (by enabling real touch to operate in artificial environments)

and through teleoperation (using real touch to operate in real

environments via computer). Motion detection has gone mainstream in

gaming, with adoption in retail, healthcare and other scenarios. Brain

Simplicity wins

Things get smarter

Solutions are neatly wrapped and delivered

Complexity gets pushed

down, logic moves

to higher levels

Technology is dissolving into the walls

Updating our technology “meta-themes”




computer interfaces (BCIs) are also making strides, notably to assist the physically disabled. When coupled with self-learning capabilities and advances in natural language understanding, users will increasingly see computing as a natural extension of personal intent. A new generation of augmented reality (AR), virtual reality (VR) and “holographic” computing technologies will lead to more immersive experiences. We cover this topic in more depth in Section 4 of this report.

Cloud computing - A paradigm shift in computing. Cloud computing represents the transition of information technology to a utility model - the “industrialization of computing”. The emerging cloud software architecture causes a shift away from the enterprise IT economic model built around tightly coupled systems, proprietary software & hardware and extensive IT implementation, development, monitoring and support services towards a more open model built for massive scale. It emphasizes commodity hardware, open-source software and more automated processes.

The mobile internet - “Any device, always on, anywhere”. The rapid adoption of smartphones and the growing availability of wireless internet are key vectors for realizing the vision of pervasive computing and a wealth of related applications, including micropayments, content streaming, multiplayer gaming, location-based services, enterprise applications and Internet-of-Things use cases. The introduction of high-speed 4G mobile networks encourages adoption of data-based applications. We expect the move to 5G wireless to make significant progress towards always-on high-speed internet connection. Additionally the trajectory of cost declines in bandwidth follows a corollary of Moore’s Law known as Butters’ Law, with potentially even more profound ramifications for adoption.

Development tools & standards - Simpler, more powerful. Higher-level software programming languages bring development closer to the business process and put increasing power in the hands of business users. There are over a billion lines of open-source code freely available that developers and business users apply to create applications and new businesses. Standards such as HTML 5 enable a new class of rich, interactive mobile applications. Broad adoption of representational state transfer (REST) APIs enables web services to be combined into Web 2.0-style mashups, giving rise to new business models in “The API economy”.

Intelligent systems Analytics and self-learning are increasingly embedded into systems. Their power accrues from the growing predictive strength of software, standards-enabled integration, always-on connectivity and the proliferation of sensors and remote-controlled devices. The concepts behind intelligent systems have been around for decades, but constraints around limitations of connectivity, throughput and computational power are falling away. The emergence of Big Data technologies like Hadoop enables a vastly expanded scope of unstructured data analytics.

The surge of data generated by applications offers unprecedented visibility into operations and businesses. Smaller and more powerful sensors generate huge amounts of data, which can be used to improve energy efficiency and optimize broad functional aspects of the supply chain. Data warehousing, business intelligence and predictive analytics have matured and are easier and faster than ever to deploy. Systems will leverage the power of predictive analytics and advanced techniques to optimize business processes, improve collaboration, target information flow and reduce risk. New types of devices

Adoption of smartphones and the wireless internet help realize the vision of

pervasive computing

Standards such as HTML 5 promise to enable a new class of rich, interactive and mobile applications

Moving towards a more open model built for

massive scale

Real-time intelligence is increasingly embedded

into systems

More data are available and analytic technologies

have matured




that generate data for analysis and receive instructions remotely give rise to new solutions. The adoption of IPv6 will allow for billions more devices to be connected to the internet, each with a unique IP address. The Internet of Things will enable far more pervasive analytics.

Prediction and optimization embedded in the walls Predictive analytics grow in value and effectiveness with increases in computational power. If business intelligence looks to understand the past, predictive analytics looks to the future, to calibrate marketing and operational efficiencies and reduce risk of all types. Predictive analytics are relevant in many situations including:

Online search and advertising, to improve query results and better target ads and recommendations. Much of the leading intellectual horsepower in the analytics community has been focused on web-based analytics. Google, Facebook, Amazon, Microsoft and other firms are leaders in this regard.

All types of marketing, to improve effectiveness and revenue “lift” from campaigns. Teradata, IBM, Oracle, Salesforce.com and many other firms are focused on analytic marketing.

Manufacturing and operations, to anticipate potential safety, maintenance and quality-assurance issues. GE, Rockwell, Siemens and other industrial conglomerates leverage new sensor technologies as data inputs to drive improvements.

Financial-risk management, to help mitigate portfolio or credit risk (a prominent example is credit scores). IBM, Verisk, FICO and many other firms address a multitude of different aspects of risk management.

We highlight several manifestations of intelligent systems:

Marketing optimization. The use of analytics is a long-standing part of marketing and campaign management, where vendors, such as SAS and IBM, have provided the analytic horsepower to fuel effective campaigns. Vendors such as Salesforce, Oracle, Teradata and IBM continue to drive incremental value through the use of scoring and predictive analysis.

Risk management, churn analysis and fraud prevention. For financial-services firms, solving the risk-management problem requires pulling together multiple sources of data and applying risk analytics to detect potentially consequential changes. Vendors such as RiskMetrics, Verisk, NICE, IBM, SAS and many others are focused on evolving challenges associated with detecting electronic fraud.

Smart grid, smart buildings, smart datacenters. The “smart grid” employs two-way technologies to control appliances and heating, ventilation and air conditioning (HVAC) systems at a home or building, allowing customers and utilities to keep costs under control. Companies focused on this problem include iTron, EnerNoc, Silver Spring Networks and privately held GridPoint, among others.

Convergence - Products become solutions Users and consumers of IT are concerned foremost with the experience and utility, not technology for its own sake. Increasingly, vendors combine hardware, software, services, connectivity and content into packaged solutions. Advantages include accelerated time to deployment, reduced integration and implementation service costs and increased efficacy of the overall solution. This also blurs the lines of product categories.

Risk management continues to gain

importance in financial markets

Smart-grid technologies employ predictive

techniques to conserve energy

The value of predictive analytics continues to

grow with increases in computational power

Software offerings increasingly combine hardware, software,

connectivity and content




Apps are top of the tech food chain As first discussed in our February 2010 Compubiquity report, it’s our consistent view that applications are where ultimate value in IT resides. Automating business processes, facilitating communications and collaboration, entertaining and informing users and enabling business models - the value to the users is defined by their utility. It’s a broad generalization, but the higher the vendor operates up the stack, the better cushioned from forces of commoditization. Applications can be deployed both as SaaS and on-premise offerings, and broadly include enterprise and consumer applications as well as the proprietary code powering e-commerce and internet sites. Latency and data gravity considerations inform the choice to deploy on premise or in the cloud.

Along these lines, the distinction between discrete software, hardware, services and content blends into solutions. Vendors are at once more diversified and vertically integrated. Business models blur categories as value creation accrues in different points in the delivery chain. Apple, Microsoft, Amazon and Google all offer a combination of hardware, software, services and content. We expect increasing convergence over the next decade across technology and media sectors as software, hardware and content providers seek to improve customer stickiness, drive incremental revenue and erect higher competitive barriers.

Figure 31

Value moves up in stacks

Source: Jonathan Murray, Warner Music Group

The “SMAC” stack + “things” = new innovations There is increasing focus on the characteristics of the next generation of applications. In fact, a new acronym has emerged to describe the new generation of apps: SMAC, which refers to social, mobile, analytics and cloud.

Social - Socially enabled applications need global scale, ability to perform multiple real-time operations, relatively low latency and a distributed architecture.

Mobile - With mobile applications, more of the application logic resides in centralized datacenters, delivered as a service to mobile endpoint devices. There’s increasing importance of location-based services. Mobile smartphones turn people into sensors, extending the edge of the network to individuals.

Analytics - With the immense proliferation of data, the opportunities to deliver context-aware, real-time analytics demand scalable data-management systems with intelligent filtering capabilities. There are many different types of analytics - “in-flight” including operational analytics (trends, statistical variations and calculated metrics), operational insights, predictive analytics and anomaly detection.

Business models will evolve as value creation

accrues in different points in the delivery chain

Next-generation applications embrace

social, mobile, analytics and cloud

Value migrates from infrastructure to platform

to application





Cloud - Public and private cloud services increasingly draw from mega datacenters that provide massive scalability. The flexible architecture accelerates the forces that commoditize underlying infrastructure components. A key consequence of adoption of the new cloud computing architectures is that we will see more organizations elevate the importance of the software development function. We are seeing large investments pour into the development platforms for next-generation architecture. GE, for example, has invested US$100m in the EMC/VMware Pivotal spinout.

Adding the “T” to SMAC - When social, mobile, analytics and cloud technologies connect to physical “things”, devices become smarter. This is where the magic happens. Combining location-based services with social technologies along with mobility and analytics creates new opportunities for products. We believe there’s enormous potential for smart, context-aware objects and devices enabled by apps built on the SMAC stack.

Figure 32

The SMAC stack will enable new applications that connect to “things”

Source: Cognizant Technologies

Convergence will reshape landscapes of industry and technology We expect convergence to play out along several vectors over the next decade:

Everything as a Service. Acceptance of Software as a Service (SaaS) paves the way for services to reach lower down the stack. Platform as a Service (PaaS) and Infrastructure as a Service (IaaS) hide the underlying complexity of computing and storage infrastructure and allow users, service providers and application developers to access resources in a holistic fashion. This is a profound shift (and challenge) for incumbent technology providers, financially, organizationally and culturally.

Commoditization of IT infrastructure. A corollary to the trend towards Everything as a Service and transparent IT is the continual commoditization of compute, memory, bandwidth and storage. The next generation of cloud architecture is heavily based on open-source software - and with the rise of open-source hardware and software defined networking, this trend extends into networking and datacenters.

Expect the continual commoditization of compute, memory,

bandwidth and storage

For those that consume these services, the

experience is what counts

More organizations elevate the importance of the software development

function

When SMAC technologies connect to physical

“things”, devices become smarter

The SMAC stack represents a new wave

of application architecture




Content integrates into the IT ecosystem. This is a longer-term trend, as proprietary content and information services become increasingly integrated into solutions. It’s possible proprietary or exclusive content could be used as leverage for the “platform” players, though content providers are likely to prefer to retain a certain amount of leverage.

Physical and logical control systems converge. Rising interest in the Industrial Internet of Things shifts focus on the need for integration between physical and IT systems. A notable area has been energy management in the datacenter around IT power management. Internet-of-Things uses are extending this to public infrastructure, automotive and industrial uses.

The directions of convergence We summarize the broad directional convergence trends as follows:

Software vendors move into hardware and content.

Hardware vendors move into software and services.

Services vendors move into software and content.

Content vendors move into hardware and software.

Figure 33

Converging IT ecosystem

Source: CLSA

Software vendors move into hardware and content Technology vendors increasingly deliver hardware and software bundled with services, both at the consumer and enterprise. Apple is a prime example of vertically integrated solutions for the consumer. Google offers Nexus phones and tablets, Microsoft offers Lumia phones, the Surface tablet and laptop hybrids and Amazon offers the Kindle reader, Fire phone and TV. Enterprise-software vendors (particularly in infrastructure, security and networking) deliver integrated appliances. Oracle’s Exa-systems, IBM’s Pure Systems and Check Point’s security appliances reflect increasingly sophisticated hardware/software systems. There are divergent trends, however. Microsoft’s acquisition of Nokia’s phone business is contrasted by Google’s divestiture of Motorola Mobility and IBM’s divestiture of its x86 server business, both to Lenovo.

Software Content

Hardware

Connectivity

Solutions

Physical facilities and logical systems controls

are converging

We expect application appliances to become

more common along with hybrid cloud offerings

Software, hardware, connectivity and content

will converge into holistic solutions




Software vendors also seek to diversify their revenue streams from products to product and service models. Microsoft is making the transition with Xbox Live, Office365 and Azure. Oracle is increasingly offering its portfolio with on-premise and cloud options that incorporate its engineered systems. Many if not most of the enterprise software perpetual license vendors are moving towards additional subscription-based businesses and/or hardware via acquisitions and partnerships to reinforce the value of an integrated portfolio and reduce reliance on a single-business model.

Hardware vendors move into software and services For hardware vendors, the appeal of software’s margins and recurring revenue streams is compelling. We expect continuing development and M&A. This trend has been so consistent we would expect hardware vendors to continue to drive consolidation in the software sector. The past decade has seen a growing number of software companies acquired by firms for which hardware had been a predominant focus.

IBM: SoftLayer, Trusteer, Kenexa, Cognos, SPSS

HP: Tipping Point, Autonomy, Vertica, ArcSight, Voltage, EDS (services)

Cisco: Sourcefire, Composite Software, JouleX, Meraki, WebEx

Dell: Quest Software, SecureWorks, Boomi, Perot Systems (services)

EMC: VMware, Pivotal Labs, Greenplum, RSA (software)

Intel: Mashery (SaaS), McAfee, Wind River (software)

Services vendors move into software and content IT services vendors such as Accenture, CSC, Cognizant and others specialize in customized solutions that incorporate proprietary IP, packaged software and hardware. With adoption of cloud computing and SaaS, the diminished need for technology-implementation services pressures many traditional types of engagements. As a result, we are seeing value-add resellers (VARs) and consulting firms move into managed services. Over time, the large business process outsourcing (BPO) and IT outsourcing vendors need to provide increasingly differentiated, higher-value solutions, with Cognizant’s acquisition of TriZetto Group a harbinger of more to come, in our view. We expect more IT services vendors to move into SaaS and other offerings.

Content vendors move into hardware and software Content companies are increasingly looking for new ways to monetize their assets, in particular publishers and entertainment companies whose models have been undermined by digitization of books, periodicals and music. The two most common approaches currently include writing custom apps for smartphones (all of the major media companies have done this) or alternatively opening up access to content through web-service application programming interfaces (APIs). Content retailers, including Amazon and Barnes & Noble, use devices (Kindle and Nook) to promote proprietary ecosystems enhanced with digital delivery services. Apple’s iPad has boosted magazines and other periodicals in digital form. Even the DVD kiosk rental service RedBox has moved into online video streaming offerings that compete with Netflix.

Expect vendors to blend software, hardware, content and services

Pressures from cloud computing and SaaS force

IT service providers towards higher value

Watch more content companies build business

models from web APIs




Publishers of textbooks and scholarly journals are under significant pressures from digitization and easy availability of used books. Providers of proprietary data, such as Bloomberg, Acxiom, Dun & Bradstreet, Experian and others, already sell raw data, provide benchmarking services and offer analysis for structured data. Increasingly, these providers of proprietary content are using APIs to turn their content into services that can be delivered over the internet.

Value grows as businesses evolve from products to platforms We’ve discussed in the past how the convergence of enabling forces gives rise to a new type of economy, and convergence is occurring because vendors seek to become platforms rather than components. Marshall van Alstyne of the MIT Center for Digital Business has produced a body of insightful work focused on how and why platforms are so valuable. It’s our view that the trend towards connecting “things” or products to services provides promising opportunities for existing businesses to evolve.

Figure 34

Platform strategies create additional value by leveraging third parties

Source: Marshall van Alstyne, MIT Center for Digital Business

A platform can be defined as a system that must provide a useful function or service and allow third-party access, according to van Alstyne, Geoffrey Parker and Sangeet Paul Choudary in their book Platform Strategy. Examples of platforms include Apple’s iTunes (which allows users to put music, movies and apps onto an iPod, iPhone or iPad), Microsoft (which allows companies to develop and run applications), Facebook (which enables users to connect to family, friends and acquaintances and play games), and Google’s Android platform (smartphone and tablet OS enables 3rd-party applications). Venture capitalist Marc Andreessen says, ‘A platform is a system that can be . . . adapted to countless needs and niches that the platform’s original developers could not possibly have contemplated . . . ”

Brand consultancy Interbrand highlights the top global brands in an annual survey. In 2013, three of the top five brands (Apple, Google and Microsoft) were platforms. According to van Alstyne’s analysis, platform companies’ share of market cap out of the top 20 firms has increased from 10% in 2001 to over 25% in 2013.

From publishers to information brokers

The Internet of Things creates opportunity for

more businesses to pursue platform strategy

A platform is a system that must provide a useful

function or service and allow third-party access

In 2013, three of the top five brands (Apple,

Google and Microsoft) were platforms

Connecting products to services provides

promising opportunities for existing businesses




Figure 35

Twelve of Interbrand’s 30 brands are platforms

Source: Geoffrey Parker, Marshall van Alstyne and Sanjeet Paul Choudary

Platforms are the principle behind convergence The advantage of platforms is that they can harness innovation from ecosystems of partners, creating aggregate value far greater than could be developed by a single company itself. Apple’s success against Nokia, Sony and Microsoft in phones and music players can be attributed to the breadth of reach. Instead of a linear value chain where users purchase a product in a “razors and razor blades” model through a single provider, Apple’s support of music, video, books and applications created a virtuous cycle where the more devices it sold, the more developers were attracted to write apps for the platform, attracting more consumer demand.

Platforms can harness innovation from

ecosystems of partners

The top platform brands all have active strategies for the Internet of Things


Section 4: 20 themes for 2020 Innovation


20 themes for 2020 We profile 20 innovation themes with potential to create new value, disruption

and investment opportunities. A key thread across each category is the

essential role that software and notably analytics plays in enabling innovation.

These are longer-term themes that could profoundly reshape markets, the

economy and society at large. As is typical of long-term technology evolution,

activities in the early stages of markets represent little revenue, but with

exponential progress, inflection points are likely to surprise.

Building blocks We profile key innovations that are foundational in nature. Nanotech provides

the avenue for a broad range of new materials with particular significance for

semiconductors. As limits of Moore’s Law approach, graphene, organic

transistors, 3D stacking, neurosynaptic chips and quantum computing

promise new paths for computing. 3D printing came of age in 2014 and the

consumer hype has faded a bit, though industrial uses are well established.

Open-source development models are pervading software, hardware and new

business models.

Figure 36

Building blocks


Nanotechnology New materials could transform aerospace, medicine, military and manufacturing. Research in semiconductors seeks to break through the limits of Moore’s Law. Any machines at molecular scale can be engineered to perform specific functions. Potential uses are nanomedicine biochips, nucleic acidbots, bacterias, bioprinting

Consumers, businesses, aerospace, military, healthcare, semiconductors, biotech firms, pharmaceutical companies,

medical patients

Prevailing technologies

IBM (IBM), Advanced Nanotech (AVNA), American Superconductor (AMSC), Altair Nanomaterials (ALTI), Arrowhead Research (ARWR), FEI Company (FEIC), GE (GE), Hewlett-Packard (HPQ), Northrop Grumman (NOC), American Pharmaceutical Partners (APPX), Harris & Harris Group (TINY), Nanogen (NGEN), LSI Logic (LSI), Lumera Corp (LMRA), Nanometrics (NANO), Nanophase Technologies (NANX), NVE (NVEC), Ultratech (UTEK), Veeco Instruments

(VECO)

Beyond Moore's Law

As the computing industry approaches the physical limits of performance improvement in silicon chips, there are ongoing efforts to extend the exponential trend

through new technologies

Consumers, businesses, aerospace, military, semiconductors, computing hardware and software, scientific research

na Intel (INTC), AMD (AMD), IBM (IBM), Google (GOOG), Lockheed Martin

(LMT), D-Wave Systems (Private)

3D printing Custom fabrication,

prototyping, spare parts

Consumers, designers, industrial designers, manufacturers, service providers, materials

producers

Spare parts, machine tooling, mass manufacturing

3D Systems (DDD), Stratasys (SSYS), ExOne (EXONE), Proto Labs (PRLB), VoxelJet (VJET), Arcam (Sweden), envisionTEC, EOS (Germany), Renishaw (UK), Organovo (ONVO),

Autodesk (ADSK), Staples (SPLS),

Adobe (ADBE), Microsoft (MSFT)


The open-source model is transforming software development, crowdsourcing, prototyping, datacenters and the replacement of proprietary systems

Entrepreneurs, operators of cloud datacenters, corporations and service providers, SaaS independent software vendors (ISVs), consumers, industrial designers,

military, consultants

Traditional proprietary hardware and software vendors including HP, Dell, Oracle, IBM, Microsoft, VMware, Cisco, EMC, Juniper,

etc

Facebook (FB), Google (GOOG), Intel (INTC), AMD (AMD), Red Hat (RHT),

Hortonworks (HDP), Microsoft (MSFT)

Source: CLSA

A key thread across each

category is the essential

role of software and analytics

We profile key

innovations that are foundational in nature




Figure 37

Building blocks - Prominent players Company Ticker Rating Currency Last

close EPS

FY14CL EPS

FY15CL PE (x)

FY14CL PE (x)

FY15CL Market cap

(US$m) Google GOOGL US BUY USD 562.63 22.66 29.30 24.8 19.2 383,062 Microsoft MSFT US O-PF USD 43.85 2.64 2.63 16.6 16.7 359,736 General Electric GE US N-R USD 25.99 1.65 1.73 15.8 15.0 261,587 Facebook FB US BUY USD 78.97 1.13 0.86 69.9 92.2 222,801 IBM IBM US O-PF USD 161.94 16.54 16.00 9.8 10.1 160,065 Intel INTC US SELL USD 33.25 2.31 2.11 14.4 15.7 157,472 HP HPQ US U-PF USD 34.84 3.74 3.71 9.3 9.4 63,670 Lockheed Martin LMT US N-R USD 200.05 11.40 11.16 17.5 17.9 63,133 Adobe Systems ADBE US N-R USD 79.10 1.29 2.08 61.3 38.0 39,623 Northrop Grumman NOC US N-R USD 165.71 9.75 9.45 17.0 17.5 32,878 Autodesk ADSK US N-R USD 64.24 1.68 1.17 38.2 54.9 14,616 Red Hat RHT US BUY USD 69.12 1.49 1.58 46.5 43.9 12,678 Staples SPLS US N-R USD 16.77 1.16 0.96 14.5 17.5 10,735 3D Systems DDD US N-R USD 30.47 0.70 0.97 43.5 31.6 3,389 FEI Co Us FEIC US N-R USD 78.99 2.97 3.60 26.6 21.9 3,303 Stratasy SSYS US N-R USD 62.06 2.00 2.12 31.0 29.3 3,160 RENISHAW RSW LN N-R GBP 2,610.00 82.30 153.32 31.7 17.0 2,936 Adv Micro Dev AMD US U-PF USD 3.11 (0.53) (0.15) na na 2,417 Proto Labs PRLB US N-R USD 71.08 1.73 2.09 41.1 34.0 1,839 Veeco VECO US BUY USD 30.49 (0.10) 1.15 na 26.5 1,231 Hortonworks HDP US N-R USD 23.03 (14.37) (3.31) na na 984 Organovo Holding ONVO US N-R USD 5.92 (0.35) (0.36) na na 476 Data for not-rated (N-R) companies based on consensus. Source: CLSA, Thomson Reuters

Small things with big impact: Nanotech Advances in nanotechnology underpin an enormous range of innovations in materials that promise new solutions in medicine and healthcare, electronics, industrial design and the military. Nanotechnology refers to the engineering of functional systems at the nanoscale, dimensions between approximately 1 and 100 nanometers, where unique phenomena enable novel applications. At the nanoscale, the physical properties of materials differ from the properties of matter either at larger scales from the atomic level to millimeters to inches. Physicist Richard Feynman first proposed the manipulation of matter at the atomic level in 1959, but it was not until the identification of fullerenes in 1985 that the field of nanotechnology really took off. Fullerenes paved the way for the discovery of carbon nanotubes in 1991.

Figure 38 Figure 39

A nanotube Microgripper holding silicon nanowires

Source: Wikimedia Commons: Health Sciences and Nutrition, Commonwealth Scientific and Industrial Research Organisation (CSIRO) Australia

Source: Wikimedia Commons: Nanowire sample by Erik Bakkers; SEM image by Kristian Mølhav

Fullerenes paved the way for the discovery of

carbon nanotubes in 1991




Nanotechnology was first popularized by Eric Drexler in the mid-1980s through his book Engines of Creation and initially referred to a radical molecular manufacturing concept. This involved scientists and engineers creating a vast number of “assemblers,” which are molecular-scale programmable machines that would be capable of building functional objects (including other assemblers) from the molecules up. Drexler’s work was criticized by Nobel-Prize-winning chemist Richard Smalley and debates have ensued on the seemingly insurmountable difficulties of the chemical bonding level, among other complexities. Inventor/futurist (and newly hired Google strategist) Ray Kurzweil devoted four pages in his book, The Singularity is Near, to dispute Richard Smalley’s arguments and support Drexler’s vision.

Current research in nanotechnology focuses most practically on creating materials and composites, while evangelists like Drexler predict the advent of High-Throughput Atomically Precise Manufacturing (HT-APM) technology that would underpin a fundamental revolution in manufacturing. Drexler believes that the foundation of APM lies at the juncture of mechanical and chemical engineering. In his view, the ability to assemble composite materials and machines at the molecular level, using basic “building blocks” will give rise to the most significant technological advances in human history. The vision of APM is that materials can be created at the molecular level, reducing the need for raw materials and shrinking the footprint of manufacturing to a very small scale.

Figure 40

Four revolutions compared: Agriculture, industry, information and APM

The Agricultural Revolution

Provided new means of producing food and materials by exploiting the productive capabilities of the molecular nanosystems found in living organisms.

Encouraged stable settlement and land improvement, multiplied population densities by factors on the order of 10. Made possible the development of cities and civilization.

The Industrial Revolution

Provided new means of producing material objects by exploiting the potential of artificial mechanical systems on a human scale.

Multiplied productive capacity by a net factor now on the order of 100, during a period of 200 years. Made possible new products, new ways of life and ongoing changes in the structure of civilization.

The Information Revolution

Provided new means of processing information using tiny, high-frequency components to manipulate and organize information in ultimate detail: patterns of bits in data.

Multiplied information-processing capacity at an exponentially growing factor (roughly two per year), now >109. Made possible new kinds of information products and new ways to organize the material and human world, resulting in ongoing changes in the structure of society.

The Atomically Precise Manufacturing (APM) Revolution

Will provide new means of producing material objects: Like the Agricultural Revolution, it will exploit molecular nanosystems. Like the Industrial Revolution, it will use artificial mechanical systems. Like the Digital Revolution, it will use tiny, high-frequency components to manipulate and organize something in ultimate detail: patterns of atoms in products.

Compared to present industry, HT-APM will enable an enormous increase in throughput and efficiency of converting raw materials into high-performance, high-efficiency, zero-emission products, potentially multiplying productive capacity (measured by delivered product function, not mass) by a large factor (10 to 100) in a short time. Compared to present digital systems, the high performance of products of APM can increase machine capacities by >10 to the 9th power. Compared to present agriculture, abundant but conventional capital stock can be used to optimize growing conditions. Experimental results have demonstrated the potential to increase grain production per hectare by a factor of roughly 10. Can avert disastrous environmental effects of the Industrial Revolution and will make possible new products, new ways of life and ongoing changes in the structure of civilization.

Source: Erik Drexler - excerpted from the report, NANO: Nano-Solutions for the 21st Century

Nanotechnology was first popularized by scientist

Eric Drexler in the mid-1980s

Drexler predicts the advent of High-

Throughput Atomically Precise Manufacturing




Microscopic machines in the future Futurist Ray Kurzweil believes the “killer app” for nanotechnology will be nanobots, computer-based robots small enough to travel in the human body to destroy pathogens and cancer cells, repair DNA errors, eliminate toxins and debris, and otherwise reverse the aging processes - ultimately providing radical life extension. His predictions are extrapolated from historical trends. Within two decades, we will be able to manufacture powerful computers we carry today in sizes no larger than a blood cell. As genomic sequencing transforms biology into an information science, we should see the same exponential pace of invention. Inevitably, our machines would be so effective at fixing and augmenting our bodies that we would incorporate them ever deeper into our lives. Memory prosthetics will feed our brains data, and nanobots in our blood will download the latest anti-virus software for fighting real viruses.

While much of the vision of nanobots remains futuristic, there has been very real progress towards engineering nanoscale machines. Leading corporations, including GE, HP and Lockheed Martin, are researching the development of nanorobots, while the most promising advances are occurring in the field of medicine and biology. In 2014, a team of Stanford bioengineers led by assistant professor of bioengineering Zev Bryant designed a suite of protein motors that can be controlled remotely by light. When exposed to light, these protein motors can change direction or speed with fine spatial control. A new Defense Advanced Research Projects Agency (DARPA) program called Atoms to Product (A2P) hopes to develop miniaturization and assembly technologies at scales 100,000 times smaller than today’s most advanced techniques. The goal is ‘to develop the technologies and processes required to assemble nanometer-scale pieces, whose dimensions are near the size of atoms, into systems, components or materials that are at least millimeter-scale in size.’

Figure 41

DARPA’s Atoms to Product program seeks to bridge the ”Assembly Gap”

Source: DARPA

Carbon nanotubes at the forefront of utility Carbon nanotubes are composed of carbon atoms linked in hexagonal shapes, with each carbon atom covalently bonded to three other carbon atoms. Like buckyballs, carbon nanotubes are strong but flexible - they can be bent and when released, spring back to their original shape. With twice the strength of steel and one-sixth the weight, there are myriad applications of this technology.

The “killer app” for nanotechnology will

be nanobots

Carbon nanotubes are composed of carbon

atoms linked in hexagonal shapes

There has been very real progress towards

engineering nanoscale machines

Atoms to Product hopes to develop miniaturization

and assembly technologies 100,000 times smaller




According to estimates from MarketsandMarkets, the global carbon nanotube (CNT) market will see a Cagr of 15.5% from 2013-18, reaching US$2.4bn, with demand driven from electronics & semiconductors, chemical & polymers, batteries & capacitors, energy, medical, composites and aerospace & defense industries. There are scores of companies developing applications of nanotubes, including Bayer MaterialScience, BASF, Mitsui, IBM, Thomas Swan, Nanotero, Natural Nano, Nanocomp, Nanocyl, Surrey Nanosystems and Unidym. CNTs have other potential uses in wind turbines, textiles, body armor, concrete, synthetic muscle, light-bulb filaments, solar cells, superconductors, displays and transistors.

Figure 42 Figure 43

Carbon nanotubes Carbon nanotubes at 10,000x

Source: Journal of Nuclear Medicine Note: Here, the nanotubes are ~10nm in diameter and well over 20

microns in length. Source: Nanolab.com

In September 2014, an international research team led by Dr Alejandro Briseno of the University of Massachusetts (U Mass) Amherst announced a major step in developing long-sought polymer architecture to boost power-conversion efficiency of light to electricity for use in electronic devices. By mimicking blades of grass (one of nature's most efficient light-harvesting structures), single-crystalline organic nanopillars or "nanograss”, they found a way to get around technological obstacles for harvesting energy in organic solar cells.

Led by Jennifer A Lewis, PhD, Harvard School of Engineering and Applied Sciences, a team of researchers from Harvard and University of Illinois at Urbana-Champaign announced they had figured out how to 3D print miniature batteries about 1mm across. The researchers developed printable electrochemically active materials that when stacked in layers during 3D printing created working anodes and cathodes. The nano-scale batteries could be used in applications such as biomedical sensors, skin-based monitoring devices and embedded into hearing aids.

IBM has been working on atomic-scale storage technologies, demonstrating the ability to store a bit of information with 12 atoms. In October 2012, IBM Labs demonstrated initial steps towards the commercial fabrication of carbon nanotubes as a successor to silicon. The company announced that over 10,000 transistors made of carbon nanotubes have been precisely placed and tested in a single chip using standard semiconductor processes. Researchers’ modeling of electronic circuits suggests a possible 5-10x improvement in performance compared to silicon circuits.

IBM has been working on atomic-scale storage

technologies

Using nanotech to improve conversion of

light to electricity

3D printing batteries 1mm across




Nanotech advances promise public health benefits Recent advances in materials have applications in public health, medicine and the military. Advances in nanotech are targeting the lack of availability of clean water in developing countries, a major obstacle to economic development. Thalappil Pradeep and colleagues at the Indian Institute of Technology Madras have developed a US$16 nanoparticle water-filtration system that promises potable water for even the poorest communities in India. With roughly 780m people globally lacking access to clean drinking water, contamination from bacteria, viruses as well as toxins such as chemicals and heavy metals affect millions each year. The new device combines microbe-killing capacity with the ability to remove chemical contaminants such as lead and arsenic using a microbe filter that employs silver nanoparticles embedded in a cage made of aluminum and chitosan, a carbohydrate derived from the chitin in crustacean shells.

Computing beyond Moore's Law: The new chips on the block As the computing industry approaches the physical limits of performance improvement in silicon chips, there are ongoing efforts to extend the exponential trend through new technologies. There are varying estimates as to when the limits of Moore’s Law would be reached, anywhere from 2018 to several hundred years in the future. Futurist Ray Kurzweil believes that photolithography will run its course by 2019, but quantum or optical computing will continue the exponential growth in computing power. Some of the most promising research involves graphene, organic transistors, 3D stacking, neurosynaptic chips and quantum computing.

In July 2014, IBM announced plans to invest US$3bn in R&D for two research programs that will extend computing capabilities beyond Moore’s Law. The company believes that scaling from today’s 22 nanometers to 14 then 10 will occur over the next several years, but scaling to 7 nanometers by the end of the decade will demand new semiconductor architectures, tools and techniques for manufacturing. Investments will focus on carbon nanotubes, graphene, silicon photonics, III-V (Three-Five) technologies and next-generation low-power transistors. Other technologies include quantum computing and neurosynaptic computing.

Organic transistors promise cheaper and more transparent computing For years, scientists have been exploring ways to use carbon-rich molecules and plastics to create organic semiconductors with capabilities approaching costlier silicon. Potentially these would enable 90% transparent high-performance electronics built on substrates such as glass and flexible plastics. Researchers from the University of Nebraska-Lincoln and Stanford (UNL), with funding from DARPA, have created thin-film organic transistors that are five times faster than previous versions of this technology. A special solution containing carbon-rich molecules and plastic are dropped onto a spinning glass platter, which distributes the materials in a thin coating. The work is experimental, but progress here looks promising.

Graphene: Taking computing beyond silicon? Graphene has been discussed as a “wonder material” that could make possible increasingly smaller computing chips, and it’s being researched heavily because of its different properties at different thicknesses. The International Technology Roadmap for Semiconductors (ITRS) predicts that by 2015, the copper wiring that connects together the billions of transistors in modern CPUs or GPUs will reach the physical limits where they cannot be

Scientists at the Indian Institute of Technology

developed a US$16 nanoparticle water-

filtration system

Quantum computers compute on atoms, not silicon, measuring the

spin of electrons

Graphene has been discussed as a “wonder

material”




miniaturized further. Graphene has the theoretical potential to scale down to a few nanometers or less, which would pave the way for computer chips that are orders of magnitude more dense, powerful and energy efficient. In 2014, IBM announced that it had created a graphene radio frequency receiver based on a silicon chip from a 200nm silicon wafer using a standard fabrication process. The chip has a radio frequency receiver, but the transistor channels are made of graphene, accomplished by depositing a layer of graphene after the passive components have been built first. A team at the University of California, Santa Barbara, has proposed an all-graphene chip with transistors and interconnects.

Based on their work on graphene, researchers Deji Akinwande and Rodney Ruoff of the University of Texas at Austin foresee graphene-based transistors and circuits that can be made flexible and bendable. The team is working with Corning and 3M to demonstrate printed graphene circuits on a large scale that would be able to be manufactured in five to 10 years. Recently a team of MIT researchers found potential for graphene that could make it suitable for quantum computing. By applying a powerful magnetic field at extremely low temperature, graphene can filter electrons according to the direction of their spin, which cannot be achieved with any conventional electronic system. The challenge for the medium term is that manufacturing of graphene is currently time consuming and expensive, and will need to be more scalable before it’s a practical alternative to silicon.

3D integration with through-silicon vias CLSA analysts Srini Pajjuri and Mark Heller have explored the implications of the end of Moore’s Law in their collaborative CLSA U Blue Book Moore no more: The future of IC manufacturing with Dr Chris Mack of the University of Texas at Austin. We excerpt the following section on 3D integration from their report:

‘An exciting direction that is now taking off in the semiconductor industry is 3D chip integration, also known as die stacking. There are many approaches to 3D integration, and their description is beyond the scope of this report. However, there are two basic ideas at work and both of these ideas make use of an enabling technology: through-silicon vias (TSVs).

First, for many applications, the overall time to complete a computational task, and the power consumed by that task, is limited by the communication between chips rather than the processing done within each chip. For example, there are some tasks where the communication between a microprocessor and Dram, carried out along the printed circuit board that the chips are mounted on, consumes the majority of both time and power. For these tasks, 3D integration can dramatically cut the time and power consumed in the communication.

That integration would work something like this. The Dram chip is made with TSVs, micron-sized pillars of conducting material that head straight down into the silicon wafer substrate. The memory cells are built on top of these pillars. When the chip fabrication is completed, the wafer is thinned from the backside until the TSV pillars are reached. Thus, the memory on the top of the chip can be accessed by wires accessible from the bottom (the TSVs). This Dram chip could be mounted directly on top of the microprocessor, so that a very short, direct connection from the microprocessor to the memory can be made. This speeds the time required to access the memory and reduces the power consumed by the signal as it travels. More than just one memory chip could be stacked on top, so that an entire system’s worth of memory could find its way directly on top of the microprocessor that needs to access that memory.

TSVs allow chips to be stacked, reducing power

and increasing speed

Recent findings suggest graphene could be

suitable for quantum computing

Through-silicon vias are soon to enable 3D

integration





Figure 44

Stacked memory die using TSV

Source: Amkor

In this way, 3D chip stacking is a better packaging solution for the chips. But such integration can be much more than that. Today, a Dram chip has about 30% of its area consumed by the “periphery,” the logic circuits that control the access to the memory cells. The same is true for flash chips. In a 3D chip stack, that logic circuitry could be a part of the microprocessor. In addition, with the immense number of access points to the memory cells that the TSV arrays can provide, the access to the memory can be made much faster. The result is that the memory can be made cheaper, faster and lower power.

There are many difficulties with 3D chip stacking, the most fundamental being thermal management. Chips get hot as they are run, and chip packaging is designed to remove the heat from the chip so that its operation is not impaired. However, when chips are stacked, it is very difficult to remove the heat from those chips in the middle of the stack. Also, there are a huge number of standards and integration issues that must be worked out, most of which are application dependent, before multiple chips can be successfully integrated into one stack. Still, the momentum for solving these issues is strong, and 3D chip-stacking products are already beginning to emerge.’

Reverse engineering nature for neurosynaptic chips IBM is working to design a fundamentally new architecture of silicon chips based on biological design principles. Led by scientist Dharmendra Modha, the SyNAPSE project (Systems of Neuromorphic Adaptive Plastic Scalable Electronics) is an interdisciplinary initiative that involves very large-scale integration (VLSI) of electronic components on a single chip, asynchronous VLSI, circuit designers, nano-materials experts, psychologists, neuroscientists and theoretical computer scientists at the university level. IBM’s objective is to reverse engineer and replicate a biological brain, which has 1010 synapse, firing at 10khz, with the volume equivalent to a two-liter bottle, consuming 10 watts of power.

Figure 45 Figure 46

Visualization of a simulated network of neurosynaptic chips

“Jellyfish” prototype sensor buoy to monitor shipping lanes for safety and environmental protection

Source: IBM

TSVs may enable faster memory access

With TSV, multiple memory chips can be

stacked (memory cube) or memory can be stacked with logic

Thermal management is one of the problems that

must be solved for 3D integration

IBM is working to design a new architecture of silicon chips based on

biological design




All of computer science has been oriented around bypassing the von Neumann computer architecture, which links internal memory and a processor with a single data channel. This approach allows for data to be transmitted at high but limited rates and is not particularly power efficient. This is known as the von Neumann bottleneck. IBM has integrated memory directly within the processors, combining software and hardware in a design that more closely reflects the cognitive structure of the brain. While this limits data transfer speed, it enables multiple processes in parallel, similar to humans, with far lower power consumption.

In 2013, the IBM team introduced an ecosystem to help programmers program SyNAPSE chips. This consists of a functional simulator for the new architecture, new neuron mode, programming model, library of cognitive algorithms and applications, end-to-end software development environment, teaching curriculum and conceptual models for cognitive systems. In August 2014, IBM announced a neurosynaptic computer chip with one million programmable neurons, 256mn million programmable synapses and 46 billion synaptic operations per second per watt. The chip has 5.4 billion transistors and is one of the largest commercial off-the-shelf (CMOS) chips ever built, while it consumes only 70 milliwatts, orders of magnitude less power than modern microprocessors.

Figure 47

DARPA’s vision for SyNAPSE

Source: DARPA

Quantum leaps? More like step by step One of the most intriguing and controversial approaches is the concept of quantum computing. Quantum computers compute on atoms, not silicon, measuring the spin of electrons. Quantum computing systems are largely theoretical systems that use the behavior of subatomic particles to conduct calculations now performed with transistors on a chip.

IBM has demonstrated a prototype chip with 1mn

neurons and 256mn programmable synapses

von Neumann computer architecture links internal

memory and a processor with a single data channel

An intriguing and controversial approach:

quantum computing




Classic computers are built with transistors that work with information “bits” that can be in either an “on” or an “off” state, representing either a 1 or a 0. A quantum bit, or “qubit,” can be in “superposition,” representing 0 and 1 at the same time. The potential of quantum computing lies in performing a mathematical operation on both states simultaneously. This would allow for exponential increases in the power of computing. A 2-qubit system can hold four distinct states at once, a 4-qubit system can hold eight states at once, 10 qubits can hold 1,024 states and so on. In time, researchers expect machines with thousands of qubits. The science behind quantum computing has been extremely challenging. Research efforts have sought to realize qubits in a variety of ways. These include test tubes of molecules in between powerful magnets to trap ions manipulated by lasers. The challenge has been to keep qubits in superposition long enough to do anything useful, as the issue of interference from vibration or electromagnetic sources is particularly difficult to manage. Additionally, the act of measuring or observing a qubit can neutralize its potential for computing. Researchers have been using quantum entanglement, which links particles so that the property of one reveals information about the other.

Quantum systems are suited to perform certain types of calculations more rapidly than traditional computers and solve a class of problems addressing machine learning, artificial intelligence (AI) and logistics that are not well suited to conventional computers. Potential applications include software verification and validation, financial-risk analysis, affinity mapping and sentiment analysis, object recognition in images, medical imaging classification, compressed sensing and bioinformatics.

Based on an approach initiated at Yale University, IBM has been experimenting with a “three dimensional” superconducting qubit (3D qubit). The IBM team has used a 3D qubit to extend the amount of time that the qubits retain their quantum states up to 100 microseconds - an improvement of two to four times upon previously reported records.

Figure 48 Figure 49

D-Wave processors on a wafer D-Wave One

Source: D-Wave

Private Canadian firm D-Wave Systems has raised over US$100m in funding and launched its first US$10m quantum computing system in 2011 in deals with NASA, Google and Lockheed Martin. The latest model includes a superconducting 512-qubit processor chip that is housed inside a cryogenics

The science behind quantum computing has

been extremely challenging

Quantum systems are well suited to perform

machine learning, AI and logistics calculations

D-Wave Systems has sold its quantum computing

systems to Google and NASA




system within a 10-square-meter shielded room. Researchers have been developing applications for protein folding, image detection, video compression, sentiment analysis and other uses. Quantum computing software startups have recently emerged, such as 1Qbit (which develops software for financial services) and DNA-Seq (focused on cancer therapy based on new drugs).

There has been quite a bit of debate regarding benchmarking tests of quantum computing systems versus traditional supercomputers. Benchmarking tests at the University of Zurich suggested that quantum computing machines were actually slower, but customers like Google and Lockheed Martin are finding that their D-Wave machines are good at very specific types of problems. It remains early days for quantum computing, and we believe it will take time for the hardware and software to mature to identify the best possible use cases.

3D printing - Through the hype, real technology emerges In early 2014, the interest and hype around 3D printing reached fever pitch, as the public awakened to the promise of astonishing low-cost desktop fabrication reviving the moribund US manufacturing sector. The year 2013 saw ExOne (XONE) and VoxelJet (VJET) join 3D Systems (DDD) and Stratasys (SSYS) as public companies, while 3D saw its shares continue to make robust gains throughout the year. HP announced plans to enter the 3D printing market. In June 2013, Stratasys acquired privately held consumer 3D printer maker MakerBot for US$403m. The 2015 Consumer Electronics Show dedicated a separate section to 3D printing, and there were near daily news stories about uses of 3D printing whether for food, hobbyists, aerospace, healthcare and other uses. HP announced that it would enter the 3D printing market and test machines in 2015 before launching in 2016.

Figure 50

3D printing units and market revenue

Source: Gartner

Gartner’s market estimate for 3D printers is US$923m in 2014, up 43% from US$576m in 2013. Enterprise accounts for 78% of the market with consumer accounting for 22%. Gartner projects the number of units shipped to rise at a 106% Cagr to 2.3m units through 2018, with revenue at an 88% Cagr to over US$13.4bn. Most of the growth is expected to occur in lower-priced units, with sub-US$1,000 printers rising at a 152% Cagr to over 500,000 units by 2018. Printers priced between US$1,000-2,500 should see a 102% Cagr to 1.35m units in 2018.

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

0

500

1,000

1,500

2,000

2,500

2012 2013 2014 2015 2016 2017 2018

Thousandshipments

(US$m)Shipment totals (LHS)

End-user spending totals

In 2014, the interest around 3D printing

reached the mainstream

Gartner estimates the market for 3D printers was US$923m in 2014

Gartner estimates the 3D printer unit shipments at

a 106% Cagr through 2018




3D printing has attracted widespread attention from the media and investment community. Along with the three US publicly traded pure-play 3D printing firms (3D Systems, Stratasys and ExOne), there are also service bureaus including VoxelJet and Proto Labs. Dozens of privately held firms are making use of the open-source RepRap technology to reduce the price of 3D printers to make them accessible to average consumers.

Figure 51 Figure 52

Objects printed with Autodesk Spark MakerBot Replicator 2

Source: Autodesk Source: MakerBot Industries

Autodesk is one of the premier software firms offering design tools for 3D printing. In May 2014, the company announced it would open source and freely distribute Spark, its 3D printing software platform. The company also plans to produce and sell its own Ember 3D printer.

Moving beyond the hype 3D printing has benefited from enormous media hype, but it is real technology with real relevance. 3D printing drives the evolution in prototyping and manufacturing, but the promise of a revolution for the consumer remains far off. Industrial 3D printing is increasingly mainstream for prototyping, though uses for manufacturing remain niche. Companies are eagerly exploring commercial uses for 3D printing. According to McKinsey, only 25% of the additive-manufacturing market involved direct manufacture of end products in 2011, but this segment was growing at a 60% annual rate. A recent PwC survey of over 100 industrial manufacturers found nearly 2/3 using 3D printing technology. Twenty-five percent were using 3D printing for prototyping, 3% for building products that couldn’t be built from traditional methods, 10% for prototyping and production, 1% for production only and 29% were experimenting to see how the technology might be applied.

In 2012, GE purchased Morris Industries to help with fabrication of jet engine parts and the company expects 100,000 engine parts to be made using 3D printing processes. Several well-known automakers are using 3D printers for around 100,000 prototype parts per year, according to SmarTech analyst Scott Dunham. Boeing uses printers to make 200 part numbers for 10 different types of aircraft.

3D printing has the potential to transform the way we manufacture things. The technology offers a more efficient, less costly means of producing custom items by using significantly less raw material and avoiding the expensive retooling required by mass production lines. In other words, rather than mass producing for customers, it brings custom production to the masses. 3D printing has the potential to be highly disruptive to the manufacturing industry by enabling “mass customization” and just-in-time manufacturing.

The price of entry-level 3D printers continues to

drop towards the US$1,000 range

Dozens of privately held firms are making use of

the open-source RepRap technology

Companies are eagerly exploring commercial

uses for 3D printing

3D printing offers a more efficient, less costly means of producing

custom items




The term 3D printing is interchangeable with additive manufacturing. The technology has its origins in stereolithography, which debuted in the late 1980s. Rapid prototyping persists today, while rapid tooling didn’t catch on in the industry. Rapid manufacturing is at a nascent stage of adoption. 3D printing encompasses these three applications.

Over the last two-and-a-half decades, additive manufacturing has become more common as a prototyping tool in the development process across many industries, including all sectors under the manufacturing umbrella - those that have a heavy design component. The technology has also reached into non-traditional areas like sculpture and art, special effects for movies, jewelry making and other applications.

Originally used to construct prototypes and models, the technology has now advanced to the point of producing much more complex final goods. 3D printing works much in the same way as a traditional printer, except that the “ink” used can be any range of materials, from plastics to powdered metals. Depending on the method, an object can be created, for instance, by depositing molten plastic layer by layer or by blasting powdered metals with lasers that melt and bond the material.

Advantages lie in uniqueness and complexity There are many conversations about the potential for 3D printing among those with a financial interest in the industry: manufacturers of the equipment (OEMs), materials and software, as well as distributors. The whole value chain anticipates when additive manufacturing becomes commonplace as a tool for production because there will be more systems sold and more material consumed compared to the one-off use cases of prototyping. In prototyping, machines will make only a few units versus making tens of thousands or millions of units for production. Equipment initially designed for a prototyping machine does not have the same constraints as a production device in terms of repeatability - ensuring everything comes out exactly the same. Prototyping machines can lack throughput at higher volumes; accuracy can be a concern; and certainly material choices are key.

Currently, only a small percentage of industrial firms use 3D printing for manufacturing. However, a June 2014 survey conducted by Tech Pro found that 12% of 624 respondents were actively using 3D printers for business operations, with another 19% evaluating the technologies with plans to implement in the next 12 months.

There is a lot of diversity in the classes of materials that can be processed; however, in each class, there are only a few available materials. In the thermoplastic class, there is commercially available polycarbonate, nylon, acrylonitrile butadiene styrene (ABS), and a few specialty materials like PEEK or ULTEM, trademarked names for mechanically sound, temperature-resistant materials used on aircraft.

There is a wide variety of materials for use in 3D printing, including thermoplastics, thermoplastic elastomers, ferrous alloys, non-ferrous alloys, sand, ceramic, paper, glass, electrical inks and even biological materials.

The term 3D printing is interchangeable with

additive manufacturing

Additive manufacturing has become

more common as a prototyping tool

The “ink” used can be any range of materials

from plastics to powdered metals

A small percentage of industrial firms use 3D

printing for manufacturing

In each class, there are only a few available

materials for 3D printing




Available materials are limited for each class and there is no standardized way to categorize or evaluate them, no standardized codex exists for defining their characteristics. By contrast, traditional injection molding enjoys greater variety of materials. With injection molding, not only is there more selection of thermoplastic families, but within each one of those families, there may be 50 or 100 different choices from 10 different vendors. Not so with 3D printing.

Figure 53 Figure 54

Objet Eden 350 3D printer Printerbot

Source: Wikipedia (Zorro2212, Gordon Wrigley)

Defining when additive manufacturing is appropriate According to industry expert Todd Grimm, an ideal production application for additive manufacturing needs at least three of four characteristics. These are:

Low volume. For quantities of one, a hundred or possibly a thousand. 5,000 pieces would be an upper limit.

High complexity. This is when a design becomes challenging or expensive to manufacture through traditional methods. If this is combined with low volume, this translates into high-value components, expensive with very few produced.

Flexibility. This refers to where a product or the business itself can enjoy freedom of design. This is not unlimited but there are fewer flexibility constraints with additive manufacturing. Flexibility includes changing a design at any time with very little friction. It’s different from the cost in tooling or a production line with trained people; all that is involved is to change computer-aided-design (CAD) data, engage the machine and produce a new version. There’s also total flexibility of production schedules, production rates and inventory.

Efficiency. This reflects reduced time, effort and fewer steps. One of the hallmarks of additive manufacturing is that a machine can be in production in some cases within a minute and a half of having a CAD model exported to a stereolithography (STL) file because there’s no need to have a human generate tool paths, there’s no need to build fixtures to hold the part. It’s just “process the data, get it on the machine and hit the go button.”

When is additive manufacturing ideal?

Traditional injection molding enjoys greater

variety of materials

At least three of four characteristics needed




Industries that lead manufacturing adoption are aerospace, dental, hearing aids and motor sports. Aerospace seeks to drive out as much weight as possible and that typically means either advanced materials or sophisticated designs that maintain strength and have much less weight. There are challenges for additive-manufactured parts on an aircraft (eg, regulations for safety). Companies like Boeing are manufacturing only non-critical components. Motor sports (eg, Formula 1, motorcycles, race cars, boats) love additive manufacturing because of their low volume and high complexity.

The dental industry is a high-profile poster child for success. There are smaller components, which are good for additive manufacturing because they are typically time dependent and cost is size dependent. It’s not feature dependent like traditional manufacturing. Align Technologies’ InvisAlign braces for teeth straightening are printed and work for a week or two at a time. This is facilitated by additive manufacturing. The hearing-aid industry has been using additive manufacturing for 12 to 15 years; over 90% of all ear-hearing-aid shells are produced through additive manufacturing.

Print me up a car One of the most impressive demonstrations of the technology is 3D printing a car. Local Motors designs “kit cars” that are crowd-sourced designs, and the components can be machined for easy assembly by customers who are also hobbyists. Local Motors’ Strati is an electric vehicle with just 25 parts.

Figure 55

3D printing parts for the Strati

Source: CLSA

Local Motors publicly demonstrated printing and assembling a drivable car in just four days at the International Manufacturing Technology Show in Chicago in September 2014 and at the Detroit Auto Show in January 2015.

Industries that lead adoption are aerospace,

dental, hearing aids and motor sports

Dental is a high-profile poster child for success

The Cincinnati printer can print a car body

Local Motors publicly demonstrated printing

and assembling a drivable car in just four days

Local Motors’ Strati is an electric vehicle with

just 25 parts




Figure 56

Milling and finishing the body of the Strati

Source: CLSA

In the future, customers may be able to walk into a mall, choose the configuration and style and have it complexly printed within a few hours. While this may seem very far off, the technology is on a trajectory that could realize this vision within a few years.

Figure 57

Assembling the Strati

Source: CLSA

The Strati electric car has 25 discrete parts versus

1,700 for the average automobile

Finishing the body of the 3D printed car took

less than a day




Bioprinting offers a lot of promise There is no potential application more exciting than in the emerging subfield of 3D bioprinting. Medical researchers and startups are already developing methods of printing human organs using genetically identical tissue from patients. Organovo (ONVO) is developing techniques to print human tissues for skin grafts and surgery. Jennifer Lewis at Harvard University is developing chemistry and machines to enable multimaterial 3D printing that could include living cells (eg, tissue interwoven with a complex network of blood vessels).

Researchers at Princeton University have developed a proof of concept for a 3D-printed bionic ear. The scientists seeded a culturing cartilage with human cells in the shape of a human ear, then embedded an inductive coil made of polymer with silver nanoparticles to allow signal processing from cochlea-shaped electrodes. Joseph Jacobson, head of the Media Lab's Molecular Machines research group, is bio-fabricating genes using CMOS chips with integrated sending electrodes on silicon. This brings the error rate down to one in every 10,000 base pairs, which will increase gene-fabrication capacity and accelerate the ability to design and innovate biological devices. Although implementation of printed organs remains some years off, replacement parts for humans - as there already are for machines - may someday be readily available at the touch of a button.

Key issues around 3D printing include intellectual property (IP) rights. The question is who owns the designs to objects if they can be scanned and converted into a 3D file? Current law does not protect the digital rendering of a physical object, only the associated brands and trademarks. Without established IP laws, we expect continuing skirmishes to arise over ownership and rights for 3D schematics. 3D printing marketplaces like Shapeways or Makerbot’s Thingverse include digital renderings of copyrighted characters, but under the Digital Millennium Copyright Act, marketplaces have a safe harbor provision as long as they have a posted policy that says they will remove infringing material if the copyright holder requests it.

Falling prices stimulate growing consumer market The consumer market for 3D printing continues to attract dozens of startups as prices fall. Designers use printers like the MakerBot to start consumer-oriented businesses selling shoes and jewelry (often on sites like Etsy) and we are seeing 3D printing devices and services developing a consumer market. The MakerBot Replicator Mini is priced at US$1,375, less than half the price of the full-size Replicator at US$2,899. 3D Systems’ Cube 3D printer can be purchased for US$999. There is also a plethora of startups offering sub-US$500 devices including Solidoodle 2 Pro, XYZ Printing Da Vinci 1.0 and PrintrBot Simple Maker Edition Kit. Startup New Matter is offering its Mod-T printer through Kickstarter initially at US$149 with a final price settling at US$249.

A diverse, fragmented landscape The market remains fragmented with over 40 manufacturers selling 3D printers and over 200 startups worldwide developing and selling consumer-oriented 3D printers. Key industrial providers are 3D Systems, Stratasys, ExOne, Arcam (Sweden), envisionTEC, EOS (Germany) and Renishaw (UK). For bioprinting, there is Organovo. In the consumer market, players are 3D Systems, Bits from Bytes, MakerBot (Stratasys), Lulzbot, FormLabs, Sculpteo, Leapfrog and Solidoodle. HP’s inkjet-based technology will be coming to market in the next few quarters. RepRap is an open-source solution. Most software is bundled, though Autodesk is leading the charge to become a standard with its

Researchers have developed ways to

fabricate genes using new types of chips

Key issues around 3D printing include

intellectual property rights

3D printing devices and services are rapidly

developing a consumer market

The market is fragmented with over 40 3D printer manufacturers and over

200 startups




Spark software. Microsoft, Adobe and others have added support for 3D printing to their software. Hundreds of resellers and distributors globally typically resell CAD/CAM software. Service bureaus include Proto Labs, Kraft Wurx, Shapeways, Staples Easyprint and others.

Open-source everything Open-source software is a key vector for disruption, particularly for cloud computing since so much of the infrastructure in the new cloud-based architecture is based on open-source components. Open-source principles inherently enable innovation, not just in software, hardware and services, but through the derivative benefits to technology users in any endeavor. Black Duck Software estimates over 1.8bn lines of freely available open-source code in 2015 that developers and business users can access to create applications and new businesses. Free open-source software reduces costs for startups as well as new projects within IT organizations. Even with paid technical expertise and support, the ROI tends to be overwhelmingly favorable for open-source users. Some of the most commonly used software in the world is open source, including the Linux server operating system, Apache Web Server and Android operating system.

Venture investments in open source continue to grow. According to Dow Jones/Venture Source, venture investments increased from US$398m across 49 deals in 2011 to US$920m across 51 deals in 2013. Intel led a US$900m round of investment in Hadoop vendor Cloudera in March 2014. The IPO of Hadoop specialist Hortonworks was the first major open-source software company to go public in the last decade.

Open source is a double-edged sword for software vendors Open source commonly refers to intellectual property, most commonly software that can be freely shared and modified by users and programmers. The open-source ethos is fundamentally collaborative, with modifications and contributions from developers occurring concurrently, contributed back to the project. The open-source model allows users to reduce overall IT costs, accelerate collaboration and development across the organization, ultimately lowering barriers to innovation and facilitating value creation.

The role of the user/developer community is self-reinforcing as enhancements shared with the community accelerate the pace of technological innovation. Under the GNU Public License (GPL), the most common open-source license, software can be copied or given away without requiring a fee; the source code (essentially the operating instructions for the software) can be modified by anyone and any derivative works must be subject to the same license.

Flexibility of open source offers significant value to users One of the primary advantages of the open-source model is the ability for users to make changes, modifications and additions to the code at will - and these changes often find themselves incorporated as enhancements in newer versions of the software. Customers of traditional closed-source vendors typically must wait for upgrades from the vendor and are limited in the ability to modify, integrate and extend the software according to how open the vendor decides to be.

Open source has proven a highly disruptive force in technology, not just in software but increasingly in hardware and other businesses (like manufacturing, medicine, digital content, robotics and even beer). Proprietary

Open source has been critical to enable

innovation, not just in software

Open source is a highly disruptive force not just

to software but hardware and even manufacturing

Open source reduces overall IT costs,

accelerates collaboration and development

A primary advantage to open source is the flexibility to make

changes and modifications at will

Open source attracts new investment




standards allow vendors to focus on tight integration, and the close coupling of hardware and software create frictions that allow an enormous amount of value to accrue to vendors. This has been a core aspect of value creation for mainframe and high-end Unix server vendors.

Over the past decade, Linux has made significant inroads into the Unix and mainframe markets. From 2009-14, Linux server shipments increased at a 14.9% Cagr, well ahead of Windows Server’s 3.6% and Unix’s 12.2% decline. The trend is likely to continue through 2018.

Figure 58

Worldwide server shipments by OS

(000 units) 2009 2010 2011 2012 2013 2014E 2015E 2016E 2017E 2018E % Cagr 2013-18

Linux 1,793 2,119 2,479 2,887 3,308 3,585 3,571 3,839 4,090 4,327 5.5

UNIX 440 403 360 304 250 230 201 192 193 179 (6.5)

Windows 5,213 6,252 6,571 6,382 6,231 6,214 6,535 6,701 6,827 6,936 2.2 Source: Gartner, December 2014

The value from Linux accrues to users, not vendors However, the economics of open source illustrate the disruptive impact on business models. Revenue associated with Linux is based on subscriptions for support and services, not for the software (which can be downloaded for free). From 2006 to 2013, Linux increased from 6.5% to 13.0% of server OS revenue, while accounting for 33% of unit shipments.

Figure 59

Revenue share of server market

Source: Gartner May 2014

The challenge of making money from open-source software The obvious downside to giving away software for free is that it’s hard to build businesses of meaningful scale quickly. Red Hat has built a business model around providing certified versions of its products and support. After nearly 15 years as a public company, revenue is likely to exceed US$2bn in 2015. In contrast, the next largest publicly traded open-source software company Hortonworks reported just US$41.5m in gross billings for the nine months ending 30 September 2014.

6.5 7.6 8.4 9.3 9.9 10.5 11.7 13.0

37.6 34.9 32.2 30.0 29.9 27.3 24.4 19.3

55.9 57.5 59.4 60.7 60.2 62.2 63.9 67.7

0

20

40

60

80

100

120

2006 2007 2008 2009 2010 2011 2012 2013

(% of total market)

Linux Server UNIX Server Windows Server

Linux accounted for 33% of server units in 2013 . . .

. . . while representing just 13% of revenue

From 2009-14, Linux server shipments saw a

14.9% Cagr




Peter Levine of VC firm Andreesen Horowitz makes the argument that while open source is great for users, the business model breaks down because it takes too long to grow revenue to scale to fund investment. As CEO of XenSource, Levine saw other companies take advantage of the benefits of the code with no revenue benefits coming back to them. Other companies like Big Switch (network controller software) and Acquia (Drupal content management) have built business models around selling proprietary add-on software that extends the functionality of the underlying open-source projects.

Profit margins in open source tend to be narrower, because of the free nature of key components of the technology offering. The main objective of open-source projects is to undercut proprietary technology vendors. The net effect is deflationary to the total market opportunity. Mike Volpi, former Cisco executive with Index Ventures, believes that open-source competition from the likes of Big Switch will diminish the total switching market from US$18bn to US$10-15bn with much narrower margins.

Venture-capital investor Mark Andreessen famously said that ‘software is eating the world’ in a 2011 Wall Street Journal Op-Ed. In many respects, open source is eating the infrastructure software world. Open-source databases like Hadoop, Cassandra, MongoDB and others provide alternatives to traditional data warehousing and transactional databases. CloudFoundry has displaced many of the proprietary Platform-as-a-Service software offerings, while projects like MuleSoft and Red Hat’s JBoss have displaced traditional application server software. It’s our view that the PaaS layer is the dividing line; infrastructure software and hardware below this layer are being steadily commoditized by open source and “Everything as a Service”. The inherent business logic in applications and analytics provides cushion against commoditization.

Open source powers the cloud Open-source software is foundational for the current generation of applications built on the de facto standard LAMP stack (Linux, Apache Web server, MySQL database and PHP programming language). Key foundational technologies for cloud computing are open source: the Linux OS, the Xen hypervisor for server virtualization, CloudFoundry PaaS software, the OpenStack cloud computing software platform, and most recently Docker, the application container software. A survey of 200 US enterprise decision makers reveals that 84% are considering OpenStack for their private cloud plans. In many respects, the leading edge of technology innovation for infrastructure software is happening among open-source projects. OpenStack has been embraced by VMware, IBM, Rackspace, Red Hat and other vendors. Docker is supported by Microsoft, Red Hat, VMware and others as well, and the pace of innovation appears to be accelerating.

Maturing open-source software is increasingly competitive With Linux past its 20th anniversary and other leading open-source projects well into their second decade or more, the resilience and usability of open-source technologies have become established and vetted by broad adoption. There are increasingly viable open-source alternatives to proprietary software all the way up the stack from OS (Linux, FreeBSD) to database (MySQL, MongoDB, Cassandra), Big Data/data-warehousing management (Hadoop, Talend), content management (Drupal), application server (JBoss), analytic tools (R language, Pentaho, Jaspersoft), CRM (SugarCRM) and many more. In fact, it is not unusual for startups, particularly in the internet or e-commerce arena, to avoid the use of proprietary software entirely.

While open source is great for users, the

business model breaks down

Profit margins in open source tend to

be narrower

Open source is eating the infrastructure software

world

Open source is foundational technology

for the cloud

The resilience and usability of open-source

technologies are well established




Extending the open-source vision into hardware Open-source hardware extends the concept of open source to hardware devices. The open-source principle applies not just to related software, but also to design elements such as mechanical drawings, schematics, printed circuit board (PCB) layout data, hardware description language (HDL) source code and integrated circuit layout.

The business case for open-source hardware is in many ways more straightforward than software because vendors make money by directly selling the hardware. Other potential revenue streams include support and maintenance, related services (such as wireless and GPS) and project-based consulting. Open-source hardware initiatives encompass input/output (I/O), circuit boards (Arduino), 3D printers (RepRap), DJ mixers (Aurora 224) and video-game consoles (Uzebox).

Open Compute project promotes the Silicon Valley sharing culture The Open Compute project originated among a team of Facebook engineers who spent two years designing a datacenter from the ground up, with the goal to scale and manage in the most efficient manner possible. The project produced custom-designed servers, power supplies, server racks and battery-backup systems, which were designed with datacenter needs in mind. The team decided to make the specifications available to everyone and launched the Open Compute project with the goal of delivering hardware that is 24% more energy efficient and 38% more cost efficient.

Major financial firms including Fidelity and Goldman Sachs are collaborating with Intel and AMD to develop new boards to meet their specifications. George Brady, executive VP of IT for Fidelity, estimates that HP and Dell are manufacturing motherboards and blade servers to the new specs. Open Compute publishes open specifications and CAD drawings for virtual I/O, hardware management, Intel and AMD motherboards and power supplies, datacenter electrical and mechanical designs, a rack standard, battery cabinet and storage. Other manufacturers working on Open-Compute-compliant components include Applied Micro, Calxeda, Delta, Emerson and Hyve Solutions, Microsoft, IBM, Yandex, VMware and Box.

Figure 60 Figure 61

Open vault storage hardware V0.5 Open Compute datacenter electrical design

Source: OpenCompute.org

The business case for open-source hardware is

more straightforward than software

Microsoft, IBM, VMware, Yandex and Box joined

the Open Compute consortium

Open Compute originated among a team of

Facebook engineers




Open source moving into networking The Open Compute project has so far focused on servers, storage, cooling and physical design, but the project is now moving into networking with the goal of developing along similar principles of open, disaggregated technologies. The aim to produce a switch that could threaten Cisco is coming from Facebook, Intel and Broadcom, while Broadcom, Mellanox and Cumulus Networks are contributing specs and software.

Open-source business models work outside of pure technology The open-source model extends beyond information technology. Crowdsourcing is a form of open-source product development at companies like Quirky and Local Motors, where potential customers vote on products and designs to be produced. Tesla’s CEO Elon Musk effectively open sourced the company’s battery patents, promising to share the technology and not seek any compensation for other automakers that seek to incorporate Tesla’s developments into their models.

3D Robotics is an open-source drone company making quadricoptors. Founder Chris Anderson described the dynamics of the business in his book Makers, The New Industrial Revolution. By open sourcing the schematics of the drones and building a business based on a modest profit from the product, he was able to identify talented engineers across the globe (including a high school student from Mexico who joined as an employee). The open-source model also allows 3D Robotics to compete on quality and price against competition using the designs in China because the global cost of materials is the same. Because of the open-source nature of the designs, 3D Robotics was able to incorporate contributions from Chinese competitors, who became active participants in the open-source community.

Connectors In an environment of accelerating change, certain technologies play the role of connectors, acting as enabling catalysts that harness new innovations and pave the way for entrepreneurs. The convergence of advanced mathematics, access to massive computing power through peer-sharing, the open-source ethos and powerful new software gives rise to technology-based currency alternatives like Bitcoin. Advances in artificial intelligence, notably “deep learning”, pervade increasingly powerful systems and applications. With ever-evolving threats in a connected world, IT security is highly dynamic, hospitable to startups and fertile ground for innovation and investment. The combination of mobile connectivity and analytics enables the rise of “sharing economy” applications like AirBnB and Uber that create value by connecting demand with idle assets while threatening disruption across industries.

Open Compute moving into networking

The open-source model proves a good way to

identify global engineering talent

Certain technologies play the role of connectors,

acting as enabling catalysts




Figure 62

Connectors


Bitcoin, cryptocurrencies and blockchain

Open-source currencies provide alternative payment systems not tied to governments

Startup businesses, low-income workers, citizens in unstable countries, investors

Banks, credit card and money transfer firms

Private companies for now: CoinDesk, Coinbase, BitPay, many others

Deep learning and the next phase of AI

Artificial intelligence governs everything from speech recognition, to search, airplane navigation and auto-pilot systems, motion-detection systems and intelligent assistants for smartphones

Advertisers, businesses, consumers, government, society at large

Jobs across a wide range of capacities from blue-collar drivers, security guards and others to knowledge workers like translators, paralegals, medical professionals, investment analysts

Google (GOOG), Microsoft (MSFT), IBM (IBM), Baidu (BIDU), Facebook (FB), Amazon (AMZN), LinkedIn (LNKD), many startups

Security Trust is paramount in a connected world. Rising levels of increasingly complex IT security threats compel increasingly innovative defenses

Consumers, businesses, government, society at large

Everyone and everything connected to the internet, including consumers, businesses, utilities, governments

AVG (AVG), Barracuda Networks (CUDA), Check Point (CHKP), CyberArk (CYBR), FireEye (FEYE), Fortinet (FTNT), Imperva (IMPV), Imprivata (IMPR), MobileIron (MOBL), NQ Mobile (NQ), Palo Alto Networks (PANW), Qihoo360 (QIHU), Symantec (SYMC), Qualys (QLYS), Proofpoint (PFPT), Cisco (CSCO), IBM (IBM), CA (CA), EMC (EMC) and many others

The sharing economy

Everything becomes a service as people create new communities for sharing

Consumers, advertisers, startups

Retailers, hotels, asset vendors

Netflix (NFLX), Avis/Zipcar (CAR), Ebay (EBAY), Amazon (AMZN), Groupon (GRPN), Chegg (CHGG), BMW, Yelp (YELP); startups like Uber, AirBnB, TaskRabbit, Lyft, others

Source: CLSA

Figure 63

Connectors - Prominent players Company Ticker Rating Currency Last

close EPS

FY14CL EPS

FY15CL PE (x)

FY14CL PE (x)

FY15CL Market cap

(US$m) Google GOOGL US BUY USD 562.63 22.66 29.30 24.8 19.2 383,062 Microsoft MSFT US O-PF USD 43.85 2.64 2.63 16.6 16.7 359,736 Facebook FB US BUY USD 78.97 1.13 0.86 69.9 92.2 222,801 Amazon.com AMZN US O-PF USD 380.16 (0.52) (1.28) na na 176,540 IBM IBM US O-PF USD 161.94 16.54 16.00 9.8 10.1 160,065 Cisco Systems CSCO US N-R USD 29.51 2.06 2.16 14.3 13.7 150,641 BMW BMW MU N-R EUR 112.55 9.02 9.64 12.5 11.7 81,468 Baidu1 BIDU US BUY CNY 203.75 37.61 45.96 5.4 4.4 71,437 eBay EBAY US U-PF USD 57.91 (0.03) 2.45 na 23.6 70,074 EMC Corp EMC US O-PF USD 28.94 1.90 1.99 15.2 14.5 58,890 LinkedIn Corp LNKD US BUY USD 267.20 (0.13) (0.81) na na 33,396 Netflix NFLX US N-R USD 474.91 3.69 3.43 128.7 138.3 28,731 Symantec SYMC US N-R USD 25.16 1.92 1.89 13.1 13.3 17,169 Chk Pnt Sftwre CHKP US N-R USD 83.49 3.72 3.98 22.4 21.0 15,345 CA CA US N-R USD 32.52 3.07 2.49 10.6 13.1 14,179 Palo Alto PANW US N-R USD 142.22 0.40 0.74 355.6 192.7 11,455 FireEye FEYE US N-R USD 44.27 (1.97) (1.86) na na 6,659 Avis Budget Grp CAR US N-R USD 60.62 2.96 3.53 20.5 17.2 6,447 Qihoo 3601 QIHU US BUY USD 45.73 2.53 3.95 18.1 11.6 5,759 Fortinet FTNT US N-R USD 33.61 0.48 0.50 70.0 67.8 5,541 Groupon GRPN US N-R USD 8.18 0.08 0.15 102.3 55.6 5,524 Yelp YELP US N-R USD 48.00 0.14 0.13 342.9 372.1 3,594 Proofpoint PFPT US N-R USD 56.64 (0.40) (0.34) na na 2,209 Barracuda CUDA US N-R USD 38.09 0.10 0.27 380.9 141.6 2,000 Qualys QLYS US N-R USD 46.03 0.46 0.53 100.1 86.2 1,546 Imperva IMPV US N-R USD 46.10 (0.74) (0.86) na na 1,240 AVG Tech AVG US N-R USD 22.57 1.91 1.87 11.8 12.0 1,200 MobileIron MOBL US N-R USD 8.93 (1.03) (0.62) na na 691 Chegg CHGG US N-R USD 8.12 (0.24) (0.05) na na 682 1 Covered by CLSA; all other ratings by CLSA Americas; data for not-rated (N-R) companies based on consensus. Source: CLSA, Thomson Reuters




Bitcoin, cryptocurrencies and blockchain - Fad or new fiat? In 2014, media and speculative frenzy around Bitcoin reached its peak. As currencies, the value of Bitcoin and other cryptocurrencies plummeted after reaching a peak early in the year, as security flaws and the collapse of the Mt Gox exchange shook confidence in investors. Despite the hype, the technology underlying Bitcoin has promise for a range of different types of applications, and the acceptance of Bitcoin by traditional merchants is growing steadily. At the end of 2014, over 82,000 merchants were accepting Bitcoin as a form of payment, including Microsoft, Overstock.com, Dell, Dish Network, Expedia, Intuit and others. However, the US Marshall Service successfully sold US$18m worth of Bitcoin seized from Silk Road, the online marketplace shuttered by the US government because of transactions in illegal drugs and other contraband.

Notably, interest in Bitcoin as a foundational technology has increased as the price of cryptocurrencies declined. Coinmarketcap.com tracks the market value of 100 top currencies representing a total market cap of US$4.2bn as of 23 February 2014. Bitcoin’s total currency value represents the predominant share at US$3.2bn, far greater than Ripple at US$450m and Litecoin at US$70m. Bitcoin was the worst-performing currency, down 67% in 2014 and another 18% in YTD 2015. VC investments in Bitcoin-related companies continued to grow in 2014, with over US$130m in 4Q14, up from US$64m in 3Q14, resulting in US$433m total VC investment in cryptocurrency startups to date, according to Crunchbase. On the regulatory front, there was increased interest in regulating Bitcoin as a commodity in the USA, Finland and New Zealand.

What are cryptocurrencies? Cryptocurrencies are digitally generated alternatives to traditional currencies that are being used in transactions with increasing frequency. The creation of Bitcoin and other modern cryptocurrencies is made possible by the combination of advanced mathematics, connectivity and the availability of massive (often distributed) computing power used to run cryptographic algorithms.

Figure 64

Bitcoin transaction visual

Source: Wikimedia Commons (Graingert)

Bitcoin employs cryptographic “hash” functions to validate

transactions

In 2014, media and speculative frenzy around

Bitcoin reached its peak

Interest in Bitcoin as a foundational technology

increased as the price declines

Cryptocurrencies are digitally generated

alternatives to traditional currencies




Bitcoin is a peer-to-peer payment system that was introduced as an open-source system by an unknown developer(s) using the pseudonym Satoshi Nakamoto. Bitcoin is a digital file that lists accounts, like a ledger. Copies of the files are maintained on every computer in the Bitcoin network. The numbers have value only in that they are able to be exchanged for other goods and services at a higher or lower value on an account. A transaction reduces a balance from one account and adds it to another, with security features around it. The master ledger is maintained in distributed fashion, and the nature of the network provides for every balance and transaction to be verified without a central authority.

Bitcoins are essentially long digital addresses and balances that are stored in a shared ledger called the blockchain. The system is designed to create new coins by applying computational power so that the currency could slowly expand. The software for Bitcoin is designed to run across a large number of machines, dubbed Bitcoin miners. Bitcoin miners track all transactions and add them to the blockchain ledger. In return, miners are awarded Bitcoins (currently 25 to each miner around six times a year). The entire Bitcoin “money supply” is capped at 21m coins and is defined by the Bitcoin protocol. Currently there are around 13m.

Owning a Bitcoin equates to owning a private cryptography key associated with an internet address that contains a balance in the public ledger. This address and the private key are what enable holders to conduct transactions. For a user to send Bitcoins to someone else, they need the addresses for the sender and receiver as well as the private cryptography key used to authorize a payment. Based on these keys and addresses, the Bitcoin miners (the peer-to-peer computer network running the system’s software) check every transaction that happens on the network. If the math is not correct, the transaction is rejected.

Figure 65

Bitcoin ATM on display in Boston

Source: Wikimedia Commons (Martin E Walder)

Owning a Bitcoin equates to owning a private

cryptography key

There are over 320 Bitcoin ATMs globally and

expected to more than double in 2015

Bitcoins are essentially long digital addresses

and balances

Bitcoin is a digital file that lists accounts,

like a ledger




Managing these addresses and keys is complicated. A wallet is one of a number of software programs that handles and manages these transactions. These can be web, desktop, hardware or smartphone apps. Apple restored Bitcoin wallet apps to its App Store in July 2014, six months after disallowing them. At the end of 2014, there were approximately 8m Bitcoin wallets worldwide, according to data from Blockchain.info, MultiBit and Coinbase.

There are a number of services that enable people to buy and sell Bitcoins. Coinbase is a website that links to a customer’s bank account and charges a 1% fee to buy and sell Bitcoins on an exchange. The best-known service was Japan-based Mt Gox, which closed down on 25 February 2014 with some 744,408 Bitcoin (US$350m) missing. There are now over 320 Bitcoin ATMs around the world, predominantly located in restaurants, retailers and coffee shops.

Unlike a traditional banking network where transactions are maintained, with Bitcoin every node sees everyone else’s transaction. Transactions are conducted between two strangers. Holders use digital signatures to “unlock” their Bitcoins. The system is designed so no trust is needed. The integrity of the Bitcoin protocol prevents any duplication of Bitcoins, so theoretically there’s no opportunity for fraud, as is the case with credit cards.

To arrive at a balance requires analyzing all transactions ever made and tallying up the unspent inputs. No records of account balances are kept; instead balances are aggregated by tracking prior transactions to ensure there are enough inputs to cover an output. For each input, nodes check every other transaction in what is call the “blockchain”. To speed things up, Bitcoin nodes keep an indexed list of transaction. Sources and inputs are validated by the owner using a digital signature to assert ownership of the key.

The advantages of Bitcoin in a digital world Venture capitalist Marc Andreesen of the firm Andreesen Horowitz is a prominent believer in Bitcoin. He has highlighted four promising use cases for Bitcoin:

International remittances, which account for US$400bn in transfers from expatriate workers sending money to families. Often fees can be 10% and higher. Bitcoin could offer very low or no fees for money transfers.

Bitcoin can address the problems of the “unbanked”, who have to deal with high fees for basic banking services.

Micropayments are an opportunity for Bitcoin because they are infinitely divisible. Currently, they are divisible to eight decimal places, but this will increase in the future. Theoretically, transactions as small as a fraction of a penny can be sent all over the world free or near-free. This could potentially open up opportunities for content monetization and developing countries.

Public payments are a unique use case. A spectator at a televised sports event held up a sign with a quick response (QR) code that asked people to send Bitcoin, and within 24 hours he had received over US$25,000. This opens up the opportunity for protest movements and organizers to solicit funding.

Unusual risks to cryptocurrencies There are risks to Bitcoin users that are not characteristic of other currencies and payment systems. Theft is one - if someone gets access to a Bitcoin wallet or private key, the Bitcoins can be stolen for good. There have been successful hacking attempts to services that store Bitcoins. In one instance,

Holders use digital signatures to “unlock”

their Bitcoins

To arrive at a balance requires analyzing all

transactions ever made

There are risks to Bitcoin users that are not

characteristic of other currencies

There are a number of services that enable

people to buy and sell Bitcoins

Managing addresses and keys is complicated and

can be managed by wallet software

Bitcoin can address the problems of the

“unbanked”




hackers targeted a site called inputs.io and took US$1.2m in Bitcoins. The collapse of Bitcoin exchange Mt Gox and the disappearance of US$350m worth of Bitcoin prominently realized a worst-case scenario, and helped precipitate the decline in value during the year as speculators shied away from cryptocurrencies. Another risk is loss of the key, which many users store on a USB drive that’s not connected to the internet. If the drive malfunctions or is damaged or lost, the Bitcoins are gone. It’s possible to copy the key on a piece of paper or engrave it on a metal coin, but this can be lost, too.

Subverting authority with an open-source model Currency as an exchange medium of value is currently controlled by governments, subject to the whims of central bankers with political considerations. Bitcoin is an open-source approach to currency. There is no central authority. The entire system is virtual. There is at once no trust and total trust among participants because Bitcoins are created, tracked and transacted according to the open-source protocol.

Bitcoin’s early advocates were often informed by a libertarian political bent, with advocates seeing the idea of a distributed alternative currency as a vehicle to disrupt the prevailing banking and payments industry. The current banking and payments industry appears ripe for disruption from technology-driven innovation. Credit-card companies generate over US$500bn a year in revenue from the frictions associated with processing payments (at pennies per transaction at times) and collecting interest on unpaid balances can exceed 20% per annum.

Supporters of Bitcoin point to several advantages that make it attractive. Low transaction costs contrast with typical credit-card fees that range 2.5-4% for most merchants, making online sales often prohibitive for merchants that may clear only single-digit margins on certain products. Bitcoin transaction fees are generally de minimus, even free, providing cash-like portability with very low transaction fees.

Anonymity an advantage, but it attracts rogues The anonymity factor has benefits and disadvantages depending on the perspective. As Bitcoin is a digital bearer instrument, there are no identifying data connecting the holder to Bitcoin, so the receiver of a payment gets no personal information from the sender that can be stolen or misused.

Of course, it’s the anonymity that has attracted the attention of those engaged in illicit activity, such as Silk Road, the e-commerce trading site that was accused of facilitating transactions in illegal drugs. Because of anonymity, Bitcoin has been widely associated with ties to illicit activity. Early on, there were reports that rogue “hacker gangs” targeting the websites of financial firms threatened repeated denial-of-service attacks, with the “ransom” to be paid in Bitcoin. In late 2013, the FBI shut down Silk Road, seizing 144,000 Bitcoins worth US$28.5m, which was sold for US$18m in June 2014.

Regulators still trying to figure this out Not surprisingly, there has been a lot of debate over regulation of Bitcoin because it is increasingly functioning as a low-cost way to move money. There are ongoing regulatory hearings on Capitol Hill and in New York City focused on Bitcoin. The biggest fears concern the use of Bitcoin for money laundering or terrorist financing.

The banking and payments industry

appears ripe for disruption

There is no central authority, the entire

system is virtual

Low transaction costs contrast with typical

credit-card fees

As a digital bearer instrument, there are no

data connecting the holder to Bitcoin

Bitcoin is increasingly functioning as a low-cost

way to move money




There are divergent approaches to Bitcoin around the world. Some countries including Australia, Canada, Finland and Germany treat Bitcoin earnings under normal earned-income rules. Others like Singapore, Poland and Denmark have punted, stating that Bitcoin is not regulated in their jurisdiction. On a relative basis, the USA is considered Bitcoin-friendly compared to other governments. Former Federal Reserve Chairman Ben Bernanke recently wrote that cryptocurrencies like Bitcoin ‘promote a faster, more secure and more efficient payment system.’ China has restricted the use of Bitcoin and the European Banking Authority has warned that Bitcoin lacks consumer protections. New York’s BitLicense regulatory proposal has outlined regulatory recordkeeping and liquidity requirements for players that wish to transact Bitcoin. This is widely regarded as a potential framework for other jurisdictions.

Despite volatility, Bitcoin appears to be here for a while Bitcoin has captured an enormous amount of publicity and press interest over the past year, with several price spikes and crashes widely covered by the media. The alternative currency has a reputation as being a “rebel” currency, forged in an open-source crucible of connectivity, transparency and increasingly powerful compute power.

Figure 66

Bitcoin price - Bubble, crash, slow bleed

Source: Thomson Reuters Datastream

Despite the controversy, Bitcoin is gaining usage by the day, and there are a growing number of organizations that accept payments in Bitcoin, including Microsoft, Time Inc, Dell, Overstock.com, TigerDirect, the Sacramento Kings and Zynga, in addition to a growing number of exchanges such as Coinbase, BTC-e, CoinCafe, LakeBTC, CoinX and many others.

The more promising uses for Bitcoin’s blockchain technology occur in the area of contracts and settlement (where the Ripple protocol is emerging as a potentially disruptive threat to the role of foreign-exchange correspondent banks). Over time, the blockchain architecture holds promise as a foundational architecture for next-generation Internet-of-Things use cases.

Deep learning and the next phase of AI Recent months have seen a surge of interest and investment in artificial-intelligence technologies and the latest variant deep learning. The combination of increased computing power, massive influx of data and a new

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The USA is considered Bitcoin-friendly compared

to other governments

Bitcoin has a reputation as being a “rebel”

currency

More organizations now accept payments

in Bitcoin

Bitcoin as an investing vehicle: bubble, crash,

slow bleed

Promising uses for Bitcoin’s blockchain

technology are in contracts and settlement




generation of research is driving innovations and new applications of the technology. While AI brings to mind dystopian science-fiction movies like Terminator and HAL 9000 from 2001: A Space Odyssey, the realities are more mundane - for now. For investors, AI’s value is not as a horizontal technology or tool set, but in the application to specific problems.

AI governs everything from speech recognition to search, airplane navigation and auto-pilot systems, motion-detection systems like Microsoft’s Kinect for Xbox and intelligent assistants for smartphones like Apple’s Siri, Google Now and Microsoft’s Cortana. A new generation of self-learning computing promises to instrument the physical world, and integration with advanced robotics will power a new generation of autonomous and semi-autonomous machines. AI and its related sub-discipline deep learning are the focus of internet companies including Google, Baidu, Facebook and Microsoft, which have helped boost interest and startup activity in the field.

Figure 67

Artificial intelligence is seeing a resurgence

Source: Wikimedia Commons (Alejandro Zorrilal Cruz)

Deep learning has emerged as the hottest

area of AI

A new generation of self-learning computing

promises to instrument the physical world

More data, powerful computing and new

algorithms drive a resurgence of AI




The pace of investment is accelerating Both large and small companies are getting into the act. 2014 saw active M&A: Google acquired UK-based DeepMind Technologies for a reported US$500m, Twitter acquired Madbits and Yahoo acquired LookFlow. Notably, IBM launched a US$100m investment fund to help commercialize its Watson technologies. According to CB Insights, funding for AI startups increased to US$309m in 2014, up 302% from US$102m in 2013 and just US$14.9m in 2010.

By several estimates, over 170 AI startups have received venture funding. Kensho has raised US$15m to train computers to replace expensive white-collar workers, such as financial analysts. Vicarious recently raised US$72m, after demonstrating that it can solve Captchas, the visual puzzles that are used by websites to distinguish humans from computers. Sentience Technologies recently raised US$103m, bringing total funding to US$143m with new investors including Access Industries and Tata Communications. Sentience develops technology to distribute artificial-intelligence software to millions of graphics and computer processors around the world.

The market for predictive analytics is a subset of the broader data analytics market, but is likely to outpace growth for other categories of analytic software, which is generally expected to grow around 10% YoY in the aggregate. Research firm MarketsandMarkets forecasts the predictive analytics market to reach a Cagr of 25.2%, from US$1.7bn in 2013 to US$5.2bn in 2018. BCC Research forecasts the global market for smart machines, which includes neurocomputers, expert systems, autonomous robots, smart embedded systems and intelligent assistance systems, to rise at a 19.7% Cagr to US$15.3bn by 2019. Transparency Market Research forecasts predictive analytics software (including customer intelligence, decision support systems, data mining and management, performance management, security intelligence, risk management and financial intelligence) to see a 17.8% Cagr, from US$2bn in 2012 to US$6.6bn in 2019.

From data to insight to prediction to action Analytics and “Big Data” have been top of mind for businesses and investors for many years. After the business intelligence (BI) market underwent consolidation of leading players Business Objects (by SAP), Cognos (by IBM) and Hyperion (by Oracle) in 2007 with all three vendors approaching or exceeding the US$1bn annual revenue mark, we’ve seen a new generation of vendors emerge including QlikTech and Tableau. While BI is typically historical facing, predictive analytics is forward looking and driven by statistics and mathematics. The largest predictive analytics vendor SAS has annual revenue in excess of US$3bn, and IBM acquired the only publicly traded predictive analytics pure-play SPSS in 2009. Artificial intelligence is an extension of predictive analytics, applied to specific tasks or problems.

Since it was initially conceived at a conference in 1956, AI has experienced waves of excitement and periods of disfavor. Interest has been gradually picking up in the past several years and in 2014 momentum accelerated. AI research saw initial commercial success in the early 1980s in the form of expert systems, which simulated the skills of human experts. With the collapse of the Lisp Machine market in the 1980s, AI fell out of favor. The late 1990s and early 2000s saw a resurgence of AI for logistics, data mining and other areas in technology. In 1997, IBM’s Deep Blue became the first computer chess-playing system to defeat world chess champion Gary Kasparov. In 2011, IBM’s Watson DeepQA system defeated the two all-time champion contestants of the Jeopardy quiz show game.

Over 170 AI startups have received venture funding

Growth forecasts for AI-related technologies are

in the 20-25% range through 2019

Artificial intelligence is an extension of predictive

analytics

AI has experienced waves of excitement and periods

of disfavor

Funding for AI startups increased from US$102m

in 2013 to US$309m in 2014




Watson focuses on increasingly intelligent interactions IBM’s DeepQA technology is best known for powering Watson in its triumph on the game show Jeopardy, defeating all-time champion Ken Jennings over a three-night demonstration that aired in March 2011. Proving Watson could defeat a Jeopardy champion was only a proof point to demonstrate the viability of a real-time natural language system. The Watson project incorporates a plethora of natural language, artificial intelligence and machine-learning technologies to sift through and analyze the equivalent of roughly 200m pages of data to deliver precise responses in less than three seconds.

For computers, looking up a database is easy. Hard questions challenge the computer to interpret the terms and phrases. IBM designed the Watson system to derive intelligence from the capability of many approaches. Massive parallelism is a key enabler as the system pursues many hypotheses independently over large data sets. The system simultaneously deploys many hypotheses, defers commitments, focusing on reducing early biases with many algorithms. No single algorithm or hypothesis is perfect or complete. By analyzing evidence from different perspectives, Watson strives for balanced combinations that are continually learned, tested and refined.

Figure 68

Even clever CLSA analysts are no match for IBM’s Watson

Note: Ed Maguire pictured (right). Source: CLSA

Deep learning emerges at the cutting edge of AI Deep learning has become one of the hottest disciplines in computing over the past decade, largely due to the work of Geoff Hinton, who is now at Google. The principle is that if one feeds a computer a lot of images of cats, for instance, the computer will eventually learn to recognize cats from video and pictures. Extrapolating this further is the view that machines will be able to understand language and images, with the hope that these techniques can be applied to helping spot tumors, avert financial risks and gauge the mood of a restaurant, for instance.

Watson can analyze roughly 200m pages of

data to deliver responses in less than three seconds

Hard questions challenge the computer to interpret

the terms and phrases

Competing against IBM’s Watson feels like hitting

an “iron wall” in Gary Kasparov’s parlance




The term “deep learning” refers to an approach to building and training neural networks, an essential component of artificial intelligence. Neural networks are essentially algorithms that take different inputs such as words, pixels or audio waveforms, run a series of tests, then generate output in the form of predictions (such as the identification of a word or type of image). What’s key is that the networks are trainable. They improve their accuracy the more data is fed through the function. Certain problems involve complex algorithms and involve large amounts of data - with millions of numbers in the case of image recognition - so the increasing speed and power of computation is a key enabling factor. Speech recognition is a real-world example of how multiple iterations and more powerful processing improve accuracy over time.

In theory, neural networks should be teachable, but scaling problem solving requires the calibration of an enormous number of inputs, weightings and iterations. In 2012, there was a breakthrough as researchers Alex Krizhevsky, Ilya Sutskever and Geoff Hinton showed in their ImageNet paper (ImageNet is an ongoing research effort to provide researchers with easily accessible image database with 15m images currently) that in a few weeks they could train a very complex network to a level that outperformed conventional approaches to computer vision, similar to what had been accomplished with natural language processing and speech recognition.

Teaching computers to solve problems on their own Deep learning takes neural networks to a new level of automation, using the training process to discover useful patterns. Automatic feature discovery enables the ImageNet network to recognize classes of objects on which it was never trained. This approach is relevant to many kinds of data including audio, seismic data or language. Daniel Nadler of Kensho described deep learning as ‘a paradigm shift from putting commands into a box to a time when computers watch you and learn.’

Baidu has built a vision system called Deep Image that runs on a super-computer optimized for deep-learning algorithms. The company claims a 5.98% error rate on the ImageNet object classification benchmark versus Google’s 6.66% error rate that won the 2014 ImageNet competition. In comparison, humans achieved an estimated error rate of 5.1% on the ImageNet dataset.

Google’s DeepMind has expertise in reinforcement learning, which involves getting computers to learn about the world even with limited feedback. DeepMind recently published a paper showing that its software could learn to play seven 1980s era Atari2600 games using as inputs only the information visible on a video screen, such as the score. The software gets an instruction such as “maximize the score” then learns the steps how to get the highest score. For Breakout, Enduro and Pong, the DeepMind computer played better than an expert human.

The challenge for companies, large and small, is capturing the talent from a pool of experts estimated to be only a few dozen worldwide. Google has been particularly aggressive in acquiring and hiring technologies with deep-learning expertise.

Deep learning involves an enormous number of

inputs, weightings and iterations

Deep learning takes neural networks to a new

level of automation

Baidu has built a vision system called Deep Image

Google’s DeepMind has expertise in

reinforcement learning

The challenge for companies is capturing the talent from a small

pool of experts

Deep learning refers to an approach to building and training neural networks




Staying secure in a connected world With the surge in connections, applications, communications and commerce, information and systems remain increasingly vulnerable to threats. Securing systems becomes increasingly challenging with the exponential growth of users, connected devices and applications as architectures become more distributed. Threats continue to become more pervasive, driven by technological advances and the growing involvement of organized crime and governments.

Security is an ongoing “arms race” between bad actors and security professionals. There are growing challenges involved in protecting private data, transactions and intellectual property. Trust becomes essential as more individuals and businesses rely on connected services online.

Online threats continue to proliferate, with increasing frequency and complexity of new attacks forcing innovation.

Increasing number of connections to the internet, including smartphones, tablets, PCs, servers, automobiles, sensors, industrial equipment and other devices create more vectors for attacks.

Threats are financially motivated, as an increased focus on subterfuge and social engineering makes detection increasingly challenging.

A growing tangle of regulations requires organizations of all sizes to take measures to ensure the integrity of systems, processes, networks and data.

The growing number of users and applications creates more data, which need to be protected, tracked, audited and archived according to business needs and regulatory requirements.

Losses impact consumers and businesses According to estimates by Consumer Reports, 58.2m American adults had at least one malware infection that affected their home computer in 2012, with the overall cost of repairing these damages at nearly US$4bn. For comparison, Americans experienced US$1.2bn in damages from spyware in 2010. According to the PwC US State of Cybercrime Survey, 77% of respondents detected a security event in the past 12 months, with 34% indicating the number of security incidents detected increased over the previous year. The 2012 Ponemon Institute Cost of Cybecrime report found that the median annual cost of cybercrime for 56 large corporations was US$6.1m, an increase from US$5.9m in 2011 and US$3.8m in 2010.

Figure 69

Internet crime complaint center statistics, 2013

Total complaints received 289,874

Complaints reporting loss 114,908

Total loss (US$m) 525.4

Median dollar loss for those reporting a loss (US$) 600

Average dollar loss overall (US$) 1,813

Average dollar loss for those reporting loss (US$) 4,573 Source: Symantec

No “silver bullet” and a robust market for cyber-security companies The security market is enormously broad and complex, with hundreds of public and private companies offering solutions. M&A activity continues to be robust in 2013-14 with VMware’s US$1.43bn acquisition of AirWatch the most notable, Palo Alto Networks’ US$200m acquisition of Cyvera and Akamai

Security becomes increasingly challenging

with the exponential growth of users

Security is an ongoing “arms race” between bad

actors and security professionals

Hundreds of companies, both public and private, offer security solutions

IT security causes significant dollar losses

Security incidents are more frequent and more

costly to targets




Technologies’ US$370m acquisition of Prolexic Technologies. IPO activity has been steady with Cyberark, MobileIron and Imprivata in 2014, FireEye and Barracuda in 2013.

The growing prevalence and complexity of threats to data compel businesses and individuals to defend their devices, networks and information. Attacks are primarily motivated by financial gain as cybercrime has become a multibillion-dollar pursuit. Security has become a sine qua non for anyone seeking to use the internet as vendors engage in an arms race with hackers. Regulatory mandates drive organizations of all sizes to implement policies to protect, back up and archive ever-increasing volumes of data. Proliferation of smartphones, tablets and other connected devices will drive the need for solutions that protect users and data.

IT security at the enterprise is analogous to physical security, demanding a broad-based approach with multiple layers of protection. The market remains dynamic, with new innovations emerging to address constantly evolving threats as maturing subsegments are subsumed into broader, converged offerings. Key trends include increasingly powerful appliances (both hardware and virtual), adoption of Software as a Service and robust M&A activity.

Figure 70

Cryptolocker Ransomware - Pay up or lose your files forever

Source: FBI.gov

The nasties grow more sophisticated Cyber threats have become increasingly complex and financially motivated. High-profile worms and viruses such as Code Red and NIMDA in 2001-02 aimed to establish notoriety and cause disruption out of vandalistic intent. Since then, the nature of attacks is increasingly focused on stealing proprietary or confidential data for financial gain. The complexity, persistence and damaging impact of malicious attacks are similarly growing more difficult to combat. Over the past 15 years, the nature of the most prominent attacks has evolved from simple pieces of code designed for a single function (to disrupt or steal a password) into sprawling, coordinated attacks known as advanced persistent threats (APTs) that harness multiple vectors to steal personal data, financial information and proprietary intellectual property.

Attacks are primarily motivated by financial gain

IT security at the enterprise is analogous to

physical security

Ransomware is an emerging threat for

consumers and businesses

Cyber threats have become increasingly

complex




As state actors enter the fray, China and the USA at odds In February 2013, the security consulting firm Mandiant released a report that tracked a series of ongoing cyber espionage attacks to a specific unit (dubbed APT1) in the Chinese People’s Army, identifying the building location in Shanghai, the details of the modus operandi, timeline and details for over 141 victims across multiple industries. The report reinforced US government and industry concerns over state-sponsored cyber-espionage efforts. China, in turn, has accused the United States of engaging in cyber-espionage as well, and this has touched off a round of protectionism, making it difficult for companies like Huawei to sell to the USA, and IBM, Microsoft and Cisco to China.

Architectural transitions compel new thinking The adoption of virtualization and cloud computing creates challenges for security and compliance. Virtualization creates new vectors for propagation of exploits and demands new approaches to manage backup, replication and availability. Cloud computing impacts multiple areas of concern for businesses: governance (how can organizations ensure that cloud-service providers comply with corporate and regulatory requirements); data (where is the data physically stored, how is it protected); identity (how to federate authentication and access controls across different hosted environments); communications (how to ensure that data in transit is kept secure); and other considerations.

Security is a critical component for IoT applications The Internet of Things (IoT) will see an exponential rise in connections, applications, communications and commerce, information and systems that are increasingly vulnerable to threats. Trust is critical. Securing systems becomes increasingly challenging with the exponential growth of connected devices and applications as architectures become more distributed. Threats continue to become more pervasive, driven by technological advances and the growing involvement of organized crime and governments. The STUXNET worm that attacked and degraded Iranian uranium centrifuges woke up the industry to the threat to industrial systems; it exploited industrial control system weaknesses after using little known Windows vulnerabilities to access and propagate the code. A recent survey by HP’s Fortify division found an average of 25 vulnerabilities per internet-connected device, a sample that included TVs, webcams, thermostats, remote power outlets, sprinklers, door locks, home alarms, scales and garage openers.

One of the biggest issues gating adoption of consumer IoT solutions will be the need for users to be comfortable their privacy and personal data are secure. Trust becomes essential as more individuals and businesses rely on connected services online. For organizations including corporations, utilities and the public sector, the risks of network intrusions, denial-of-service attacks, sabotage and theft of intellectual property rise as operational systems increasingly become connected to the internet. For factory-floor automation, programmable logic controllers (PLCs) that operate robotic systems are potentially exposed to attacks when connected to the internet, as are control systems for nuclear reactors or power grids.

Security information war - Intelligence as the foundation of defense Security is inherently defensive in nature and effectiveness is only as good as the best information. Attackers have many tools at their disposal - deception, scripts to perpetrate hacks, uncover exploits and create malicious code, the

Mandiant tracked a series of cyber-espionage

attacks to the Chinese People’s Army

Virtualization and cloud computing create

challenges for security and compliance

Security is inherently defensive in nature and

only as good as the best information

Security becomes increasingly challenging

with the exponential growth of connections




ability to hijack machines, et al. Without up-to-date signature files, traditional antivirus would be impotent. Much of the innovation in the security market focused on improving the effectiveness of smaller bits of information (hence the development of heuristic techniques, protocol and traffic anomaly detection). The emergence of security and information-management solutions is an effort to address the asymmetrical nature of the security problem.

Data breaches capture headlines Businesses of all sizes need to be concerned with the theft or loss of data and the potential reputational and financial costs. A 2014 study by the Ponemon Institute revealed the average cost of a data breach is US$201 per compromised record at an average notification cost of US$5.85m in 2013. There have regularly been high-profile data breaches in the USA, most notably in December 2013 when Target saw over 70m customers’ credit-card data hacked by outsiders with information sold on the black market.

Figure 71

Average cost per record for a data breach

Country US$ cost per record over two years United States 201 Germany 195 France 183 United Kingdom 158 Italy 141 Australia 135 Japan 127 India 52 Source: “2014 Cost of Data Breach Study: Global Analysis” prepared by Ponemon Institute and sponsored by IBM

Post Snowden, the world protects against US cyber spying In May 2013, former contractor Edward Snowden’s disclosures that the NSA PRISM project had engaged US tech companies to cooperate in the NSA’s data-gathering operations have had a chilling effect on trust of US tech vendors overseas, while reinforcing global concerns over state-sponsored threats. Surveillance in the past used to be about targeting and listening. Now with cheap technology, the NSA collects everything and analyzes data afterwards. New revelations indicate that the NSA was tapping into cables underseas and between Google, Apple and Yahoo datacenters. Industry analyst Richard Stiennon expects IT security spending to increase from US$60bn in 2012 to US$639bn in 2023, a Cagr of 24%, as governments and organizations invest to develop independent technologies to protect from mounting state-sponsored threats.

There’s evidence that US firms are investing in encryption to keep prying eyes off their network traffic even though most encryption vendors are based in the USA. RSA/EMC, VeriSign/Symantec and Trend Micro are positioned to benefit. Key management is a priority, benefiting privately held Venafi and Entrust. Finland, France, Germany and Switzerland represent promising locales for security startups as NSA concerns are fueling marketing messaging and investment.

The security market offers rich opportunities for innovators and investors by its dynamic nature. New vectors are constantly emerging for vulnerabilities including Android, industrial control systems and other connected devices

IT security spending will increase from US$60bn in

2012 to US$639bn in 2023

The average cost of a data breach is US$201 per compromised record

There’s evidence that US firms are investing in

encryption to keep prying eyes off

The security market offers rich opportunities

for innovators




Over the past five years, we’ve seen IPOs of CyberArk (CYBR), MobileIron (MOBL), Imprivata (IMPR), FireEye (FEYE), AVG Technologies (AVG), Barracuda Networks (CUDA), Fortinet (FTNT), Imperva (IMPV), Palo Alto Networks (PANW), Proofpoint (PFPT), Qualys (QLYS), NQ Mobile (NQ) and Qihoo360 (QIHU). Other notable deals include Vista Equity Partners taking Websense private for US$902m, IBM’s US$900m acquisition of Trusteer, McAfee’s US$389m acquisition of StoneSoft and Akamai’s US$370m acquisition of Prolexic. Notable private companies include ZScaler, Webroot, CyberArk, LogRhythm, Ping, Rapid7, SailPoint, Veracode and many others.

Trusted peers - The rise of the sharing economy As the world becomes more interconnected through an increasingly mobile internet and cloud-based services, this facilitates a transition away from an ownership to a rental, or sharing, economy. The terms “peer economy”, “collaboration economy” or “sharing economy” are gaining currency as virtual communities drive new business models and disrupt incumbent industries. The trend towards sharing and collaboration has been concurrent with the digitization of content.

Figure 72

Technologies enable asset-sharing, rental and context-based services

Source: Steven Schlafman, RRE Ventures

The sharing economy gets “Uber-fied” Steven Schlafman, a venture investor with RRE Ventures, defines on-demand mobile services as a “closed loop” experience that collapses the value chain, including discovery, order, payment, fulfillment (offline but within an owned network) and confirmation. On-demand mobile services may or may not include an IoT component, but connectivity will enable asset tracking, optimization, predictive maintenance and location-based access and delivery.

There is active IPO and M&A activity in the

security market

From file sharing to Everything as a Service

The rise of on-demand mobile services is an

outgrowth of connectivity and location services

Since 2009, VCs have invested over US$1.75bn

into over 70 “sharing economy” startups




There is ample interest in this category of application: Schlafman has found that since 2009, venture capitalists have invested over US$1.75bn into more than 70 startups in this category.

The share economy takes off The year 2014 saw both the mainstreaming of share-economy businesses as well as pushback from incumbents. Uber’s latest US$1.2bn fundraising round valued the company at US$40bn, while the company took a number of reputational hits from controversies and pushback from regulators, taxi unions and the media. The scale has become significant: AirBnB’s users have logged over 20m stays across over 800,000 listings worldwide, with 10m in 2014. According to Business Insider, Uber expects to generate over US$10bn in revenue in 2015; the 20% net on each transaction would mean that Uber would clear around US$2bn in net revenue.

In January 2013, Avis Budget Group purchased ZipCar for US$491m, signaling the value of the sharing model to traditional incumbents. Sharing sites such as RelayRides and AirBnB allow owners of automobiles property (and even renters) to build income off assets that would otherwise be sitting idle.

BMW’s Drive-Now service is a new example of an IoT-enabled on-demand mobile service. Launched in several German cities and San Francisco initially, the app allows customers to rent from a fleet of cars by the minute or the hour. The cars can be parked in reserved street spaces and users can monitor the electric charge or gas tank levels, mileage and other diagnostics.

Forbes magazine estimated that US$3.5bn of transactions flowed to share-based businesses in 2013, but this could prove conservative if Uber’s revenue is close to reports. A study by PwC estimates that five main sharing-economy sectors (peer-to-peer lending and crowdfunding, online staffing, car sharing, peer-to-peer accommodations and music and video streaming) accounted for US$15bn in revenue in 2013, growing to US$335bn by 2025. The traditional rental sector, including equipment, bed & breakfast (B&B) and hostels, books, cars and DVDs, accounted for US$240bn in 2013 and are also expected to reach US$335bn in 2025.

Digital goods took the lead The rise of peer-to-peer sharing in the late 1990s saw explosive adoption of Napster and other file-sharing services. The ability for users unknown to one another to share content disrupted the music industry and catalyzed a rethinking of other industries. Much of the value in the trade of traditional goods and services is the friction involved with connecting the asset with demand, at the time and place of need. With a world of users connected to the internet, this gives rise to services that intermediate and provide a trusted framework.

Amazon developed software that helped teams of people to eliminate duplicates among its millions of product pages, and this software eventually was released to the public as Mechanical Turk (names after a famous 18th Century chess-playing machine that actually had a human hiding inside it). Mechanical Turk employed crowdsourcing techniques to use distributed labor to solve problems, mostly in software engineering.

Much of the value in the trade of traditional goods

and services is the friction involved

Amazon’s Mechanical Turk crowdsources

software development and other tasks

BMW’s Drive-Now service is a new example of an

IoT-enabled on-demand mobile service

PwC estimates that five sharing-economy sectors

will reach US$335bn by 2025

2014 saw share-economy businesses go

mainstream




Figure 73

The sharing economy addresses solutions

“I don’t need a car, I just need to get where I need to be”

Image by Rgbstock. Source: CLSA, Rgbstock

This ability to source out work has given rise to freelancing communities such as Odesk and Elance. Uber has disrupted the medallion taxi industry by allowing passengers to call “black cars” from their smartphones, with requests based on location data and a rating system for both drivers and passengers. TaskRabbit was founded by Leah Busque, who wanted to create a website where she could name a task, such as going to the store to buy dog food, along with a price - to find people from the community that would be willing to do the job. Zaarly is a peer-to-peer marketplace that focuses on creating stores for sellers to market their services.

In their book, What’s Mine Is Yours: The Rise of Collaborative Consumption, Rachel Botsman and Roo Rogers outlined three models relevant in the sharing economy:

Product service systems allow companies to offer goods as a service rather than being sold as products. This is in many respects what cloud computing is all about. For users that want the benefit of a product but not the cost or burdens of ownership, this addresses the usage mindset. Companies like ZipCar, Zilok.com, Netflix, iTunes and Amazon’s streaming services are examples of product service systems.

Redistribution markets provide for the exchange or sale of used or pre-owned goods from where they are not needed to where they are. Ebay, Amazon Marketplace and Chegg (CHGG) provide markets for used goods, books and media. Other venues like thredUP, Zwaggle and Swaptree enable swapping goods, while markets like Freecycle, Ziilch and Recycletheworld.org provide an outlet for free goods.

Collaborative lifestyles connect people with similar needs or interests to share and exchange less-tangible assets such as time, space, skills and money. These tend to be on a local level in the case of Citizen Space or Hub Culture (for working spaces), SnapGoods (for high-end household items) and ParkatmyHouse (for parking spots). There are also global collaborative markets such as AirBnB, HomeExchange and Roomorama (for peer-to-peer travel), Lyft, Relayrides and Getaround (for car sharing and carpooling), Liquid (for renting bicycles), Cookisto (for homemade food), Lendingclub and Agellist (for loans and funding), Fon (Wi-Fi sharing) and a plethora of others that are transforming industries through global technology.

The sharing economy enables use of assets

without hassles of ownership

Uber has disrupted the medallion taxi industry by

allowing passengers to call “black cars”

Global collaborative markets such as AirBnB and Roomorama enable

peer-to-peer travel

Product service systems allow companies to offer

goods as a service




The sharing economy also reflects both a generational shift and the economic pinch of the Great Recession. Millennials have grown up increasingly comfortable with the concept that digital assets such as music, video and books do not need to be owned per se - that the ability to access assets on demand serves consumers’ needs just as well if not better than owning physical media. The financial pressures of a difficult economy have made it more attractive to seek additional income from an apartment or automobile that may be unused part of the time.

Backlash from the disrupted The growing success of sharing-based businesses is leading to backlash and regulatory scrutiny from incumbent stakeholders. Uber has faced organized opposition in cities like Paris, Washington DC and San Francisco from taxi drivers. The service has been banned in Spain and two cities in India and continues to be involved in disputes with regulatory bodies. AirBnB has seen pushback from local regulators. In New York, a judge fined AirBnB-host Nigel Warren US$2,400 for renting out part of his apartment in violation of a law forbidding short-term rentals by residents, and there have been City Council hearings over the permissibility of AirBnB in condominiums. It’s inevitable that those with a vested interest in businesses that benefit from scarcity of assets like real estate and cars will resist changes to laws that have protected them. However, we’d expect regulations to catch up with changing purchasing practices over time.

There has also been growing scrutiny of the impact that sharing-economy applications have on workers and the economy at large. The freelance nature of being an Uber or Lyft driver means that there are not the typical protections afforded full-time employees (health insurance or worker’s compensation protections, for example). There have been several cases of Uber drivers assaulted by drunken passengers, where the lack of workers’ comp has highlighted the risks of the freelance nature of the business. Uber’s peak usage “surge” pricing was heavily criticized for being put in effect during a terrorist incident in Sydney, Australia. An article in Quartz made the case that the conditions of high degrees of income inequality (such as in the city of San Francisco) gave rise to sharing-economy applications - by matching a pool of underemployed labor with high-income consumers. The management teams of Uber and AirBnB in particular are sensitive to the criticism and are working more actively with local regulators on operating agreements.

Brookings Institution fellow Jennifer Bradley believes that regulations will need to change, as much of the existing law is meant to protect physical assets and intellectual property. While there are undoubtedly losers from the rise of the sharing economy, there are some opportunities in terms of creating economic activity from increasing efficiencies of transportation and other assets. The sharing economy is here to stay.

Human technology People are increasingly interacting with computers in more natural ways, and advances in interfaces, robotics and exoskeletons extend the physical capabilities of humans. Advances in natural user interfaces make controlling compute increasingly seamless, as translation services bridge language barriers closer to real-time, natural language understanding makes interactions more human and motion-sensing advances control computing from the human body. Virtual reality and augmented reality open up new avenues for immersive experiences and applications. The market for wearable

Millennials have grown up increasingly comfortable

with the concept of shared assets

AirBnB has seen pushback from local regulators

Growing scrutiny of the impact that sharing-

economy applications have on workers

Much of the existing law is meant to protect physical assets and

intellectual property

People are increasingly interacting with

computers in more natural ways




computing devices continues to build momentum with fitness bands, smartwatches, glasses, connected clothing and a myriad of other devices. Advances in bionics, prosthetics and exoskeletons empower the physically disabled as well as give industrial workers and soldiers superhuman strength. Computational genomics promise a new era of precision medicine with consumer analysis for US$99 and a fully sequenced human genome available for under US$1,000.

Figure 74

Human technology


Next-generation user interface

Speech, touch, gesture, language translation, brain computer interfaces (BCI), natural language understanding

Anyone that wishes to interact with computing: consumers, business, transportation, healthcare, education, telecommunications, manufacturing, military, etc

Service jobs, especially call centers, legacy hardware providers

Microsoft (MSFT), Nuance (NUAN), Google (GOOG), Apple (AAPL), IBM (IBM)

Virtual reality

Gaming, entertainment, commerce, travel

Consumers, game developers, content creators

na Facebook (FB), Microsoft (MSFT), Samsung, Sony (SNY), Google (GOOG)

Wearables Healthcare, retail, customer service, finance

Healthcare patients, consumers, medical personnel, investors

Administrative, customer-service jobs

Apple (AAPL), Google (GOOG), Samsung, Sony (SNY), Nike (NKE), Intel (INTC), Qualcomm (QCOM), Microsoft (MSFT), GoPro

Body 2.0 Mobility, strength augmentation

Disabled and/or handicapped, military, construction workers, etc

na Raytheon (RTN); private companies including Berkeley Bionics, Ekso Bionics, Rex Bionics, Cyberdyne

Computational genomics

Gene sequencing, genetic analysis

Individuals, health patients, pharmaceutical companies

na Agilent Technologies (A), Bio-Rad Laboratories (BIO), Danaher (DHR), Illumina (ILMN), Life Technologies (LIFE), PerkinElmer (PKI), Safeguard Scientifics (SFE), Sigma Aldrich (SIAL), Techne (TECH), Thermo Fisher (TMO), Waters (WAT)

Source: CLSA

Figure 75

Human technology - Prominent players Company Ticker Rating Currency Last

close EPS

FY14CL EPS

FY15CL PE (x)

FY14CL PE (x)

FY15CL Market cap

(US$m) Apple AAPL US BUY USD 128.46 6.43 8.68 20.0 14.8 748,247 Google GOOGL US BUY USD 562.63 22.66 29.30 24.8 19.2 383,062 Microsoft MSFT US O-PF USD 43.85 2.64 2.63 16.6 16.7 359,736 Facebook FB US BUY USD 78.97 1.13 0.86 69.9 92.2 222,801 Samsung Elec1 005930 KS O-PF KRW 1,357,000.00 153,541.20 146,815.81 8.8 9.2 191,086 IBM IBM US O-PF USD 161.94 16.54 16.00 9.8 10.1 160,065 Intel INTC US SELL USD 33.25 2.31 2.11 14.4 15.7 157,472 Qualcomm QCOM US O-PF USD 72.51 5.27 4.99 13.8 14.5 119,610 Nike NKE US N-R USD 97.12 2.97 3.57 32.7 27.2 83,670 Danaher DHR US N-R USD 87.28 3.75 4.34 23.3 20.1 61,600 Thermo Fisher TMO US N-R USD 130.00 6.96 7.34 18.7 17.7 51,582 Raytheon RTN US N-R USD 108.77 6.97 6.40 15.6 17.0 33,428 Sony1 6758 JP BUY JPY 3,414.50 (127.93) (167.55) na na 32,724 Illumina ILMN US N-R USD 195.46 2.74 3.21 71.3 60.9 28,107 Sigma Aldrich SIAL US N-R USD 138.06 4.37 4.50 31.6 30.7 16,488 Agilent A US N-R USD 42.21 3.04 1.70 13.9 24.8 14,178 Waters WAT US N-R USD 120.38 5.48 5.67 22.0 21.2 9,995 GoPro GPRO US N-R USD 41.98 1.32 1.38 31.8 30.4 6,012 PerkinElmer PKI US N-R USD 47.00 2.47 2.61 19.0 18.0 5,312 Nuance Commns NUAN US N-R USD 14.30 1.12 1.12 12.8 12.8 4,652 Bio Rad BIO US N-R USD 127.18 4.35 3.49 29.2 36.5 3,681 Bio-Techne TECH US N-R USD 97.53 3.39 3.48 28.8 28.1 3,622 1 Covered by CLSA; all other ratings by CLSA Americas; data for not-rated (N-R) companies based on consensus. Source: CLSA, Thomson Reuters




Next-generation UIs - Making computing transparent Interactions with computers are no longer tethered to a keyboard, mouse and screen display. Advancements in non-traditional computing interfaces are driving innovations in new applications that match a tactile or sensory interface to a function or automation. There is a paradigm shift to more intelligent systems in mobile devices, wearables, gaming consoles, automotive and industrial uses. Artificial-intelligence-driven improvements in speech recognition, touch/haptic interfaces and motion detection are making everyday interactions with computing increasingly seamless.

Natural user interfaces (NUIs) promise to expand the experience of computing beyond the traditional keyboard/mouse, touch and speech-based interaction currently available. Multi-touch is mainstream thanks to smartphones and tablets, and with the pending launch of Windows 10 we will see computing fully integrate touch, speech and gestural recognition with holographic computing.

Speech recognition has been available commercially since 1982, but it has taken decades for accuracy and speed to improve, as word error rates have steadily improved over time. NUIs enable a new class of applications, such as virtual assistants. Apple’s Siri is the most prominent consumer application of a speech-powered virtual assistant, but not the only one. Microsoft’s Cortana is a speech-powered virtual assistant and Google offers a range of natural language interfaces for its applications. With more training and usage, accuracy continues to improve (just like with predictive analytics). The use of speech programs in the military for battle management, air traffic control and telephony are well established and it’s difficult to find a utility or retailer’s telephone-based customer service that does not employ speech recognition for call routing. All major smartphone platforms include speech-enabled search and other control functions.

Beyond pure speech recognition (essentially a form of pattern matching informed by mathematician and cryptographer Claude Shannon’s information theory), voice applications pursue natural language understanding (NLU). For a virtual assistant, there are requirements to be successful, such as the ability to anticipate unexpected inputs, understanding of specific subject areas and efficiency in providing answers. NLU can come from machine learning from Big Data, or from hand-crafted rules, although neither approach works well on its own. Vendors like Nuance, Microsoft, IBM and Google are focused on developing speech and NLU interfaces.

Babel fish on the way? In Douglas Adams’ The Hitchhiker’s Guide to the Galaxy, the babel fish is a fictional creature that performs instantaneous translations between any language and any species. This vision is increasingly becoming a reality - Microsoft’s CEO Satya Nadella demonstrated real-time translation of Skype Translator with a conversation between English and German speakers translated in real time at a conference in May 2014. Skype Translator has been in preview release as of December 2014.

New types of interfaces will expand the

computing experience

Beyond keyboard and mouse - more transparent

and powerful

Accuracy of speech recognition continues

to improve

Nuance, Microsoft, IBM and Google are all

developing speech and NLU interfaces




Figure 76

Skype Translator preview screenshot

Source: Used with permission from Microsoft

Microsoft Translator is a platform service that allows users to build, train and deploy automatic translation systems between any two different languages with support for 45 languages currently. The cloud-based backend provides the computational power. The service uses machine-learning technologies to learn language styles and can be used to power a range of custom applications for communities, service providers and businesses. The New York Times reported in January 2015 that Google plans a major update to its Translate App that would provide real-time, automated translation similar to the Microsoft Skype Translate technology. Google Translate supports hundreds of different languages but does not provide automated speech recognition.

There are a number of startups addressing automatic translation. Google offers Word Lens, a free app that works by translating text which the user hovers over with the lens of the smartphone. In May 2014, Google purchased Word Lens' parent company, Quest Visual, and its first move was making the app free to download. ReadSpeaker’s technology combines voice-to-subtitles with subtitles-to-voice to provide full cycle translation, enabling business users to collaborate over Skype in four different languages.

Wave your hands in the air Motion-capture or motion-tracking interfaces became mainstream with Microsoft’s Kinect motion-tracking interface (which has been bundled into the new Xbox One gaming console), particularly in the realm of video gaming. Kinect integrates speech recognition, 3D sensing and motion sensing in an integrated, controller-less user experience. The Kinect Fusion technology included in the software development kit (SDK) gathers and incorporates data viewable from any single view point to enable 3D object model reconstruction, 3D augmented reality and 3D measurements. Microsoft’s HoloLens incorporates motion tracking into 3D rendering on a holographic viewing visor headset.

Real-time translation services are increasingly

becoming a reality

Motion-capture or motion-tracking

interfaces are becoming mainstream

There are a number of startups addressing

automatic translation




Figure 77 Figure 78

Leap Motion interface Touch responsive haptic interface

Source: Leap Motion Source: Kawasaki and Mouri Laboratory at Gifu University

Nintendo’s Wii U and the Sony Move are also technologies that exploit motion-control capabilities. Oblong is a private company whose scientist John Underkoffler designed the computer interfaces in the film Minority Report. The company’s core technology platform, called g-speak, enables applications to be developed that run across multiple screens and multiple devices.

The US$79 consumer-focused Leap Motion device allows users to interact with traditional PCs using a motion-detection interface. The limitation of the Leap controller is that it needs to be used with applications specifically designed for the interface, but the company is expanding the application of motion technology to virtual-reality use cases. The development of new types of touch and haptic interfaces promises to enable new types of applications: gaming, enabling the disabled, medical procedures, industrial processes, training, simulation and therapy. Haptic interfaces have applications in virtual reality (enabling real touch to operate in artificial environments) and through teleoperation (using real touch to operate in real environments via a computer).

Mathias Nordvall, a cognitive scientist and game designer at Linköping University in Sweden, has designed a haptic interface that allows users to react to touch stimuli in games. He has developed Sightlence technology, which incorporates off-the-shelf components to enable gamers and the visually impaired to interact via computers based on tactile stimuli. He has adopted the original video game Pong for the Sightlence platform. Kinea Design has developed a prosthetic haptic interface system that conveys pressure, vibration and shear with the goal of returning a sense of touch to amputees.

There is also growing progress in brain computer interface (BCI) technology. Currently, research is focused on physical implants (mostly to benefit the disabled through physical mobility and prosthetics), but there is also growing progress in non-invasive brain interfaces that track brain activity to control computing and physical devices. Emotiv, a San Francisco-based private firm, has developed a consumer computer interface based on electro-encephalography (EEG) technology that tracks brain waves to control a cursor on a screen.

Sightlence is a new technology that uses

touch stimuli for interactions

Oblong’s chief scientist designed the computer

interfaces in the film Minority Report

New types of touch and haptic interfaces promise

to enable new types of applications

There is growing progress in BCI technology




Figure 79

Making progress developing brain computer interfaces

Source: Brown University - BrainGate

Researchers at Brown University have succeeded in creating a wireless, implantable and rechargeable, long-term brain-computer interface. The wireless BCIs have been implanted in pigs and monkeys for over 13 months without issue. The researchers, in conjunction with Utah-based Blackrock Microsystems, have commercialized the device and will seek clearance for the system from the US Food and Drug Administration, so that the mental remote control can be tested on volunteers. Brown’s BrainGate lab has successfully created a robotic arm controlled by a tethered BCI that enables paralyzed patients to feed themselves.

Virtual reality - The next computing platform? Over the past three years, augmented-reality and virtual-reality technologies have captured public imagination - and we are seeing viable products on the cusp of mass markets. In March 2014, Facebook purchased Oculus VR, a creator of the Oculus Rift headset for US$2bn. The size and scope of the deal created huge waves (on par with Google’s acquisition of Nest) and have catapulted a new generation of VR technologies to the forefront. Google Glass, more of an augmented-reality technology, was widely regarded as a failure as the US$1,500 price of the devices under the Explorer program generated more mockery than partnerships. Microsoft in January introduced its HoloLens technology, which incorporates more of an augmented-reality approach by displaying 3D images onto visor display that can be overlaid and interacted with in the context of the physical world.

3D Systems (DDD) acquired Simbionix, a 3D virtual-reality surgical simulation and training company for US$120m. Next Galaxy (NXGA) hopes to connect all kinds of virtual-reality and augmented-reality devices to access immersive digital environments through its CEEK Platform. Venture-capitalist firm Rothenberg Ventures has launched its River Accelerator dedicated to fostering VR innovations, hosting 10 startups in its facilities in San Francisco that will receive US$100,000 in investment and mentoring during their three-month stay.

Brain computer interfaces are the next step

of evolution for natural user interface

Investments are pouring into virtual-reality

technologies

Augmented reality and virtual reality have

captured public imagination




Figure 80

Microsoft HoloLens prototype


Market research firm KZero estimates the total revenue from virtual-reality hardware and software is at US$90m in 2014, US$2.3bn in 2015, US$3.8bn in 2016, US$4.6bn 2017 and US$5.2bn in 2018 - with US$2.3bn from device sales. MarketsandMarkets estimates that the augmented- and virtual-reality market will reach US$1.06bn by 2018 with augmented reality representing US$660m and virtual reality US$408m.

Virtual reality is about the immersive experience Virtual reality describes a computer-simulated environment with similar physical presence in real or imaginary worlds. The basic idea of virtual reality has been around since the 19th Century stereoscope that combined two images taken from slightly different angles to render a three-dimensional illusion. Virtual-reality environments have been displayed on a computer screen or specialized monitor (such as a headset). Virtual reality is the immersive cousin of augmented reality, which refers to displays that overlay information and images over the physical world.

There are multiple applications being discussed for VR including medical, military and immersive video consumption, but gaming is expected to be the most significant use case. There is a new generation of headsets that includes the Oculus Rift, Google’s Cardboard and Samsung’s Gear VR (a headset that uses the Samsung Note 4 as a display). The new generation of devices benefits from declining cost of processing, memory and advances in 3D design and rendering software. What’s critical is to offer an experience with minimal image latency so that viewers see different images when looking up, down or around a virtual environment.

Yes, it really does live up to the hype Facebook CEO Zuckerberg described his first time using the VR headset as revelatory. Following the announcement of the Oculus deal, he described the technology as one of the few candidates to be the next major computing platform. This analyst shares the sentiment: having tried the Oculus in June 2014, the experience was one of the most powerful I’ve experienced.

The basic idea of virtual reality has been around

since the 19th Century

Microsoft’s HoloLens straddles virtual and

augmented reality

Using the VR headset is “revelatory “

Applications for VR include medical, military

and immersive video consumption




Figure 81

Boy wearing Oculus Rift

Source: Wikimedia Commons (Skydeas)

There are a number of companies developing VR headset devices, including Facebook/Oculus VR’s Oculus Rift, the Razer OSVR, the Samsung Gear VR, Silicon Micro Display’s ST1080 and Sony’s Project Morpheus. Over time, there will be increasing integration with gesture recognition, haptic interfaces and enhanced sound (Oculus touts its 3D sound technology as essential to the immersive experience).

Seeing the world in new layers Augmented reality describes a direct or indirect view of a physical, real-world environment where elements are augmented by computer-generated input, such as sound, video, graphics or GPS data. The concept of AR has existed for decades, notably in the cinema where visuals are augmented with vibrations, smell and sound. AR applications have been used in the aerospace industry and military, helping workers assemble aircraft and assisting pilots with navigation. Augmented reality differs from virtual reality, which replaces the real world with a simulated experience.

Wearable AR applications for military and emergency services can provide information such as instructions, location of enemy fire and maps. Many examples of this type of AR application have been represented in movies. The Terminator and RoboCop films employ augmented-reality systems to “see”. Steve Mann, professor at the University of Toronto, is considered the pioneer of wearable computer and has been wearing computing devices since the 1970s. He refers to his technology as mediated reality rather than augmented reality, but his prototyped designs have provided inspiration of innovation in the space.

The concept of augmented reality has

existed for decades

The VR experience is completely immersive

The Terminator and RoboCop films employ

augmented-reality systems to “see”




Figure 82 Figure 83

Steve Mann’s eyetap glasses Google Glass detail

Source: Steve Mann Source: Wikimedia Commons (Antonio Zugaldia)

The Google Glass Explorer program charged users US$1,500 for the device (with a bill of materials that ran around US$300), and after enormous interest around the device, the lack of applications and unfavorable public reaction caused enthusiasm to wane. Google has folded the program into its Google X initiative, and there is likely to be another iteration over time.

Figure 84 Figure 85

Nokia City Lens Fitting Reality - Augmented reality fitting room

Source: Nokia Source: Fitting Reality

With the proliferation of GPS technology, we are seeing a new generation of applications. Examples include: enhanced auto navigation systems that project overlays of destination details onto the windshield of a car; GPS-enabled ski goggles that show speed, direction, air temperature and even the outline of the course; smartphone applications such as Yelp Monocle, Nokia City View and others that overlay information on restaurants, shops and other metadata on the user’s camera view; and a tourist iPad application for a Civil War battlefield with location-triggered narrations at key sites. There is an increasingly broad range of applications that employs smartphone camera and GPS functions to overlay rich data on the user’s view - with relevant, topical or even promotional information. Virtual fitting-room apps that enable shoppers to try on different styles of clothing are increasingly common, with several tied to Microsoft’s Kinect interface.

Microsoft introduces a holographic computing platform In January 2015, Microsoft demonstrated the HoloLens, a headset with dark lenses that allows the users to see (and most importantly) interact with holograms overlaid across the physical environment.

Google Glass was the first popular attempt to

introduce wearable AR

Smartphone applications such as Yelp Monocle

overlay information on the user’s camera view

We believe the future of Google Glass will be more

commercial applications




Figure 86

Microsoft HoloLens - Playing virtual MineCraft in the living room


HoloLens is not the all-immersive virtual reality of Oculus Rift, nor the mild augmented reality of Google Glass, but an entirely different approach closer to Minority Report than either. The company demonstrated how users could interact with holograms in scenarios such as an architect walking around a building design for his clients watching the holograms. HoloLens projects game images onto the physical world, enabling a gamer to play MineCraft in the living room in 3D, for example. Microsoft management highlights “holographic computing” as a fundamental capability of Windows 10, which should appeal to developers from both the Xbox and Windows platforms. The product is slated to launch sometime this year.

Wearable computing - Strap on and connect 2014 was the year that hype around wearable computing reached fever pitch, and a flood of new market entrants has resulted in a highly fragmented market with no breakout successes. Though fitness trackers are seeing a healthy uptake, Google Glass has shut down its Explorer program and smartwatches do not appear on track to become horizontal computing platforms (though the launch of Apple Watch in April 2015 could open up new use cases). Smartwatches are tethered to smartphones, which offer far superior connectivity and flexibility. We expect Quantified Self, medical monitoring and vertical applications to give rise to a plethora of specialized wearable devices.

The heady optimism that accompanied a glut of product rollouts early in 2014 has receded as adoption has hit some snags. Since then, Nike has exited its Fuelband unit to focus on software, eBay has been flooded with Galaxy Gear devices for sale and early Google Glass users have spurred public backlash and mockery. Abandonment remains an issue with a study from Endeavor Partners finding that a third of fitness tracker users stopped using their device within six months. However, unit shipments are growing at a robust pace, as the market saw 5m smart band units shipped in 3Q14, according to research firm Canalys, representing 37% growth over 2Q14.

2014 was the year that hype around wearable

computing reached fever pitch

A fragmented market in early stages

HoloLens will enable a new class of interactive

applications

Microsoft highlights “holographic computing”

as a fundamental capability of Windows 10




The consumer market is what’s new Wearable computing as a category is not new. Various militaries around the world have been developing headgear for aviators since the 1960s. In the 1980s, Steve Mann was a pioneer in wearable computing, with a backpack-mounted computer for controlling a camera, and in 1994, created a headset that sent images to the web. IBM, Microsoft and many other vendors have experimented with wearable wristwatch computers through the 1990s and 2000s. What’s new is the consumer market, with the recent boom in smartwatches and fitness trackers coming in the past couple of years.

There is an enormous amount of venture activity in the wearable space around personal-tracking devices. According to CB Insights, venture investors put US$362m into wearable companies across 47 deals in 2013, with US$502m in investments in the first nine months of 2014. Deal activity for wearable tech startups increased 135% over 2013, while funding grew nearly 38%.

Industry analyst forecasts paint a picture of near exponential growth over the next few years. Cisco estimates connected wearable devices will grow from 22m units in 2013 to 177m in 2018. Gartner forecasts the total market for wearable computing expanding at a 24% Cagr to reach US$9.8bn by 2016, with several times the revenue opportunity from related services.

Estimates fuel excitement around wearable technologies The market for wearable computing includes healthcare, consumer and entertainment functions. There have been a number of enthusiastic forecasts of growth in wearable connected devices. As mentioned, Cisco estimates these devices to grow eight times from 22m in 2013 to 177m in 2018, with 13% of them having embedded cellular connectivity in 2018, up from 1% in 2013.

Figure 87

Global connected wearable devices

Source: Cisco VNI Global Mobile Data Traffic Forecast, 2013-18

Expectations for a multibillion-dollar wearables market Gartner sees the wearable technology market growing to US$15.8bn by 2020. The relative growth and declines of different subsegments is testament to what we expect will be a continuously dynamic market, with categories merging and being subsumed into one another. The key point is that as hardware gets cheaper, tracking becomes easier and value will migrate to the software and platforms.

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2013 2014 2015 2016 2017 2018

Millions ofwearables

Number of connected wearables (LHS)

% with embedded cellular connectivity

(%)

Optimistic market forecasts attract

new entrants

Cisco forecast a 52% Cagr in wearable devices

from 2013-18

Venture investors put US$502m into wearable in the first nine months

of 2014

Wearable computing is not new

We expect wearable to be a continuously dynamic

market




Figure 88

Wearable technology forecast 2013 2014 2015 2016 2017 2018 2019 2020 Cagr 2013-20 (%) Smart wristband units (m) 30 20 17 19 22 25 30 50 8 Smart wristband revenue (US$m) 4,470 2,580 1,683 1,691 1,518 1,475 1,170 1,450 (15) Sports watch units (m) 14 18 21 24 27 31 36 42 17 Sports watch revenue (US$m) 2,786 3,582 4,179 4,776 5,373 6,169 7,164 8,358 17 Other fitness monitor revenue units (m) 18 20 12 15 18 20 30 40 12 Other fitness monitor revenue (US$m) 1,602 1,780 948 1,035 10,621 980 870 760 (10) Chest strap revenue units (m) 111 12.1 8 7.3 6.4 7.1 8 9 (3) Chest strap revenue (US$m) 539 593 312 212 186 206 232 261 (10) Smart garment revenue units (m) 0.01 0.1 10.1 26 46.5 60 66 72 256 Smart garment revenue (US$m) 1 20 2,010 3,874 5,999 5,940 5,874 4,968 238 Grand total units (m) 73.01 70.2 68.1 91.3 119.9 143.1 170 213 17 Grand total revenue (US$m) 9,398 855 9,132 11,588 14,137 14,770 15,310 15,797 8 Source: Gartner, October 2014

Much of the opportunity for growth will come from athletic shoes, wearable biosensors and communications devices. Beyond devices, the opportunity will be around services including data analytics, entertainment, location-based services and potentially payments.

For the smart band segment (including activity trackers and smartwatches), industry research firm Canalys forecasts 8m total shipments in 2014, increasing to 23m in 2015 and over 45m by 2017. Deloitte forecasts smart glasses, fitness bands and watches to sell 10m units in 2014, generating US$3bn in revenue. Of these devices, smart glasses are estimated to generate the most revenue, with sales of roughly 4m units at US$500 each. ABI Research projects the market for wearables in the sports and health sectors to see a Cagr of 41% to 170m devices by 2017. North America, the largest market with 42% global share in 2013, should represent 34% share in 2018, outpaced by growth in Europe and Asia.

Figure 89

Regional wearable devices share 2013 2018

Region No. of wearable devices

% of global

No. of wearable devices

% of global

Asia Pacific 4,502,201 20.8 43,810,250 24.8 Central and Eastern Europe 1,078,646 5.0 9,864,884 5.6 Latin America 984,497 4.5 9,709,040 5.5 Middle East and Africa 712,403 3.3 7,955,103 4.5 North America 9,063,366 41.8 59,829,286 33.8 Western Europe 5,347,081 24.7 45,775,527 25.9 Global 21,688,195 100.0 176,944,090 100.0 Source: Cisco VNI Global Mobile Data Traffic Forecast, 2013-18

Disillusionment sets in The promise that wearables seemed to hold at the beginning of 2014, when the Consumer Electronics Show was awash in new devices, appears to have faded. Nike laid off around 70 engineers from its Fuelband unit to focus on software. As the Fuelband was arguably the most successful fitness-tracking device, this raised questions about the underlying health of the market. Ebay is flooded with disillusioned consumers trying to sell their Galaxy Gear devices, and Google Glass has been the subject of public backlash and mockery.

North America is the largest market for wearables

ABI Research estimates sports and health

wearables will grow to 170m devices by 2017

The early promise of wearables has faded, with Nike exiting the

Fuelband business




Consumer awareness is growing, but abandonment is a big challenge: a report from Endeavor Partners found that one in 10 Americans own some form of activity tracker, but half are no longer using their device. A third of fitness-tracker users stopped using their device within six months. A 2013 report from CCS Insight surveyed 1,500 UK smartphone owners and found that 40% of users of a smartwatch or fitness tracker had stopped using it.

Expectations may need to be reined in without unique “killer apps” While there’s much value in certain categories of wearable technologies, it’s our view that expectations that these would emerge as markets of magnitude similar to tablets and smartphones are overly optimistic. We would advise investors to maintain conservative expectations for revenue generation, particularly whether smartwatches can approach the kind of unit (and dollar) volumes of smartphones and tablets. High price points, limited battery life, bandwidth limitations and lack of “killer apps” make watches “nice to have” but not yet “need to have”. We’re more optimistic on lower-cost, specialized devices (such as fitness trackers) than general-purpose platforms for at least the medium term.

Smartwatches and personal trackers have their unique advantages, but most devices need to be tethered to a smartphone. Simply put, it’s hard to justify paying US$200 for a smartwatch for the convenience of leaving your smartphone in the bag. Part of the challenge is that most wearables need to be tethered to smartphones, and the amount of incremental bandwidth is de minimus. Connections to 4G/LTE cellular networks or WAN connections use a lot of power, and this impacts battery life. Cisco forecasts traffic from wearables to account for 0.5% of smartphone traffic by 2018.

Figure 90

Wearables to account for a small share of smartphone traffic

Source: Cisco VNI Global Mobile Data Traffic Forecast, 2013-18

A fashion imperative not inherent to other compute form factors For wearable technology, form takes far greater precedence in design, as fashion remains a personal mode of self-expression. To date, smartwatches have trended towards standardized design and limited variety, contrasting the enormous design in traditional watches.

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Petabytes Monthly traffic (LHS)

Percentage of smartphone traffic

(%)

A recent study found 1/3 of fitness-tracker users

stopped using their device within six months

Form takes far greater precedence in design, as

fashion remains personal self-expression

Hard to justify paying US$200 for the

convenience of leaving your smartphone

in the bag

Traffic from wearable devices to see a Cagr of

105% from 2013 to 2018




Figure 91 Figure 92

Ringly offers fashionable wearable technology Microsoft Band

Source: Ringly Source: CLSA

A key to success is that wearables need as few excuses for users to take the devices off as possible. People need to be willing to wear the devices - and they need to be desirable. A wearable has to solve a real use case. Adoption will be dependent on “the Hawthorne effect,” which refers to the phenomenon whereby workers improve or modify behavior based on awareness of being observed. In other words, consumers will adopt wearable devices when they see others wear them.

The success of smartwatches and other wearable devices will also be informed by the origins of the makers. Smartphone companies’ core competency is making phones. The big questions on our minds remain what can users do with a smartwatch that can’t be done with other form factors? What can we put on the body that can’t be done on a smartphone?

Watches seem promising, but it’s not that simple Watches are a US$60bn annual market, with potentially attractive gross margins as high as 60% at the high end. Technology is more powerful, more compact, power efficient and cheaper. The declining cost of components, including compute, connectivity and storage, puts more power in a smaller space. The watch is a good form factor for technology to be incorporated into because it’s visible. Developments like flexible eInk allow for more power-efficient watch displays, while Bluetooth 4.0 significantly reduces the amount of power required.

There is no dominant leader in the smartwatch market, offering opportunity for new entrants. According to estimates by Canalys, Samsung is the leader in the smart band segment as of 3Q14 with 52% share of global shipments, while Motorola has 15% and Pebble has 12%. The market is showing clear interest for well-designed smartwatches such as the Kickstarter-funded Basis watch (since acquired by Intel), which raised over US$7m through customer preorders. Dozens of companies launched smartwatches and bands in 2014. Notable entries include Samsung’s Galaxy Gear (with a microphone), the Pebble (and the more fashionable Steel edition and app store), the Basis Smartwatch (with vital signs monitoring), MetaWatch Frame and Microsoft Band.

The opportunity to remake an established market calls for a forward-looking company like Apple to reinvent the smartwatch, similar to how the iPhone completely changed the dynamics of the mobile-phone market. There are plenty of pros and cons for the smartwatch business. The popularity of wristbands for the iPod Nano points to at least some geek appeal for smartwatches. Apple’s HealthKit has promise; depending on what functions an Apple smartwatch might introduce, this is likely to raise the bar.

Wearables need as few excuses for users to take

the devices off as possible

Samsung is the leader in the smart band segment (including watches) with an estimated 52% share

Watches are a US$60bn annual market, with gross

margins as high as 60%

What can users do with a smartwatch that can’t

be done with other form factors?




Down the hole: Google Glass’ tepid reception There was a lot of anticipation that Google Glass would be the catalyst for a new generation of computing devices, but Google shut down the Explorer program and has folded the project into the Google X business unit. It’s our view that Glass will be most useful for professional applications such as medicine and high-end technology maintenance, but unless the price drops significantly and form factor appears less obtrusive, adoption will lag.

The overall category is seeing enormous investment. There are hundreds of devices and manufacturers straddling dozens of evolving categories. A brief sampling:

Wristbands - These are commonly used for tracking activities and movement, such as the FitBit, Adidas mCoach, Jawbone Up, Sony Core, LG Lifeband Touch, Raser Nabu, Sony Smartband and others.

Smartwatches - These combine email, phone alerts, messaging and telling time with information services such as stocks, news and weather as well as fitness and vital-signs tracking, from Sony, Pebble, Basis, Samsung, ZTE BlueWatch and many others. At the high end are devices like the Polar SmartWatch for triathletes, which retails for US$499.

Glasses/Goggles - The best known is Google Glass. There are also Vuzix M100 and Oakley Airwave Ski goggles.

Helmets - The Skully AR-1 Smart Helmet (for augmented reality) raised over US$1m on IndieGogo; provides a heads-up display roughly 15 feet ahead in the road.

Wearable cameras - These are gaining traction with sports enthusiasts. There’s GoPro, which recently came public, and Liquid Image Apex HD camera goggles, which are capable of video and still photography.

Bracelets and jewelry - Bracelets from Elemoon and jewelry from Ringly offer users the ability to have color-coded lights for fashion’s sake or for alerting.

Smart clothes - These are clothes with embedded sensors or other devices. Examples include AIQ BioMan t-shirt, Solarman vest, Cameraman jacket and Moticon wireless shoe insole. The Under Armour E39 shirt is embedded with sensors, an accelerometer and 2GB of storage. The Zepp sensor can track baseball, tennis and golf performance with 1,000 data points per second.

Medical devices - Quardio makes an electrocardiogram (EKG) heart monitor that transmits data via Bluetooth to smartphones.

Contact lenses - Google has demonstrated a prototype of a contact lens that can monitor blood glucose levels for diabetics with a display that can be read on the cornea. Microsoft and the University of Washington have developed a contact lens for the sight-impaired that can also monitor blood glucose levels.

Heart monitors include a wide variety of electrodes, watches and even earbuds from Garmin, Polar, Suunto and others. Other monitors include the Smart Baby sleep monitor. Animal tracking devices include the Fitbark pet activity trackers.

There are hundreds of devices straddling dozens

of evolving categories

Wearable cameras gaining traction with

sports enthusiasts

Smart clothes are embedded with sensors

or other devices

Response to Google Glass has been decidedly

skeptical




In our view, there’s a lot of promise for different use cases and form factors. For smartwatches, however, we need to see “killer apps” emerge for the market to take off that are NOT just something a smartphone can do. For other form factors, like wearable cameras, eyewear (like Google Glass), clothing, shoes and gloves, we believe there are promising opportunities for a range of niche applications.

Body 2.0 - Technology, health and the extended body Healthcare technology resides at the nexus of several important trends: declining costs of compute, storage and bandwidth; the emergence of wearable form factors that measure, monitor and prompt activities; proliferation of smartphones supporting health-related applications; increasing efficacy of telemedicine and remote monitoring; and greater interest in costs and constraints with the implementation of the Affordable Care Act (ACA). While there continue to be powerful advances in research and discovery (with IBM’s Watson at the leading edge in oncology research and diagnostic assistance), many of the most significant and visible innovations relate to consumer and patient-facing applications.

The term Health 2.0 refers to the potential of technology and web-enabled healthcare. There is both a consumer and professional dimension. The consumer market is seeing an explosion of fitness apps, wearable devices and services, led by the Quantified Self movement at the vanguard of self-tracking. Professional healthcare providers are increasingly adopting connected technologies for consultations and monitoring.

Mobile-driven health tech poised for massive growth Expectations around the mobile health opportunity are high. Transparency Market Research forecasts the global mHealth services market to reach a 23.9% Cagr from US$5.8bn in 2013 to US$23.4bn in 2020 with remote monitoring accounting for 63% of the total. Remote monitoring, collaboration and consultancy is expected to see the highest growth at a Cagr of 28.1% from 2014 to 2020, driven by a growing aged population and need for technology to support unassisted living. A study by Grand View Research forecasts the global mobile health market to grow to US$49bn by 2020 from 2014, representing a Cagr of 47.6%. According to Research2Markets, the number of mHealth apps published on iOS and Android have more than doubled in 2.5 years to more than 100,000 apps in early 2014. Market revenue reached US$2.4bn in 2013 and is forecast to grow to US$26bn by the end of 2017.

Investors are counting on growth. According to a new report from consulting firm Mercom Capital Group, venture funding in the healthcare IT sector in 2014 totaled over US$4.7bn from 670 deals versus US$2.2bn from 571 deals in 2013. Consumer-centric companies raised US$2.3bn from 436 deals, mHealth companies raised US$1.2bn with US$526m going to wearables, US$507m to mHealth apps and US$369m to Telehealth companies.

The very sick and very healthy show most adoption There are two main types of connected solutions: professional-facing and consumer-facing apps. There is increasing convergence between the two. Adoption of mobile health apps tends to be strongest at the extremes of the

For smartwatches, we need to see “killer apps”

emerge

Healthcare technology resides at the nexus of

several important trends

Expectations around the mobile health opportunity

are high

VC funding has grown to an estimated US$4.7bn

in 2014

Technology is being used to improve healthcare in

powerful ways




health spectrum - very healthy people and very sick people. There’s a prevailing view that roughly 5% of the population is chronically ill, 15% is somewhat ill and 80% are reasonably healthy. The challenges are the most expensive patients. With the 5% of chronically ill patients, the opportunity is promising as almost anything that providers can do to reduce utilization of services can improve ROI. There is a lot of opportunity around diabetes and hypertension management in particular. Samsung, Sony and other leading corporations are increasingly getting into mobile health applications. AliveCor is a company that offers an EKG app for the iPhone, while BlueStar is offering patient therapy solutions.

Figure 93 Figure 94

AliveCor’s smartphone EKG for iPhone 5 Also available for other mobile devices

Source: AliveCor

On the professional-facing side, the market is still dominated by enterprise technology including electronic medical records (EMRs), administrative tools and financial systems. There is growing support among medical authorities and regulators, and solutions are slowly gaining regulatory approval. There are over 100 mobile medical apps cleared by the US Food and Drug Administration, according to MobiHealthNews, predominantly as Class 1 and Class 2 devices. On 2 February 2015, the FDA issued draft guidance aimed at reducing oversight for mobile health applications. This should accelerate the availability of commercial solutions for consumers and providers.

The New Body - Beyond the Six-Million-Dollar Man Technological advancements are having a profound impact extending the limits of the human body, particularly for those suffering severe injuries, illnesses and disabilities. This is not just a matter of science; technology holds the key to unlocking human potential, creativity and contributions. The combination of more powerful processors, miniaturization of sensors and improving AI-driven pattern-recognition capabilities is giving rise to an emerging generation of technologies that help the blind/visually impaired navigate the physical world more effectively.

From darkness and silence to light and sound One of the most consequential developments has been the development of new technologies to aid the blind. The Argus II has been approved as a “humanitarian device” for availability in the USA and Canada and to date has been implanted in over 100 patients. The system was developed by Second Sight Medical Products (EYES) with support from the Department of Energy to benefit patients blinded by retinitis pigmentosa, a degenerative eye disease that affects 1 in 4,000 Americans.

Samsung, Sony and other leading corporations are increasingly getting into

mobile health

There is growing support among medical

authorities and regulators

AliveCor’s smartphone EKG provides portable

heart readings

Technological advancements are

extending the limits of the human body

The Argus II is a retinal prosthetic device now

approved in the USA and Canada




Figure 95 Figure 96

The Argus II implant Argus II external equipment

Source: Second Sight Medical Products

The Argus II combines a retinal implant with an eyeless sensor (a la Google Glass) that detects images via a visual processing unit and then sends data to an electrode array implanted in the user’s retina. Electrical stimulation transmits visual information up the optic nerve to the visual cortex of the brain, enabling users to see. The Argus II uses 60 electrodes and the Argus III plans 240 electrodes that promise to provide facial recognition when the next version is released in a few years.

The next step - Prosthetics that feel There have been enormous advances in prosthetics technology that are giving new life to amputees. Prosthetics have long used technology called a myoelectric interface, which uses signals from the muscles in the lower arm, to control prosthetic hand movements, but hand prosthetics typically lacked flexibility, while the “hook” form factor proved awkward physically and emotionally for users.

UK firm RSL Steeper has developed the bebionic hand, a “Terminator” style bionic hand that offers a range of 14 different grip patterns that can be controlled by the existing nerves in the arm. Nigel Ackland is one of the recipients of the bebionic hand, which connects via silicone suction and charges overnight (see Figure 96). The grip is powerful and the hand can do most of the necessary daily tasks. The impact on recipients of the device has been profound, restoring a sense of self-esteem and optimism.

Figure 97 Figure 98

New prosthetics vastly improve quality of life for amputees RSL Steeper’s bebionic hand

Pictured: Nigel Ackland at GF2045 conference. Source: CLSA Source: RSL SteeperX

The Argus II combines a retinal implant with an

eyeless sensor

Hand prosthetics typically lacked flexibility, while the “hook” form factor

proved awkward

The bebionic hand is a “Terminator” style bionic hand that offers a range

of 14 different grips




Touch the world - Sense of touch the next challenge One of the disadvantages of prosthetic limbs is that they do not send back sensory information to the wearer. While there has been progress in developing cochlear implants, which stimulate the auditory nerve to restore hearing, there has been far less progress in stimulating nerves to bring a sense of touch in humans. There are a number of research efforts focused on bringing a sense of touch to prosthetics users. Researchers at the Cleveland Veterans Affairs Medical Center and Case Western Reserve University have developed an interface that can simulate a sense of touch. The technology works by directly stimulating peripheral nerves in the arms of patients from 20 spots on a prosthetic hand.

From neuroprosthetics to memory implants? There are increasing advances in neuroprosthetics for use in cochlear implants, artificial retinas, deep brain stimulation for the treatment of neurological diseases, such as epilepsy, and implants that allow for the control of prosthetics or exoskeletons through the brain. Theodore Berger, a neuroscientist and biomedical engineer from the University of Southern California (USC), has been working on the design of silicon chips that would mimic the signal processing of biological neurons while studying how memories are created in mammals. Berger has been conducting primate experiments involving the prefrontal cortex that researchers believe allowed animals to remember objects they have seen earlier. While efforts are at early stages, Berger hopes ultimately to be able to implant devices that can function as memory prosthetics for the human brain.

Building a better human and repairing damage done The vision of humans enhanced by machine has been the subject of fiction and fantasy, with the TV series The Six Million Dollar Man, the Iron Man series and the fighting machine in Avatar the most notable examples. Several companies are developing usable exoskeleton suits. Some of these are being developed for military use, but others provide real benefits to amputees, paraplegics, quadriplegics and those with other physical disabilities, empowering strength and movement where it was lacking.

Iron Man suits move closer to reality Ekso Bionics has developed eLEGS Pro, an experimental wearable exoskeleton designed to help paraplegics stand and walk. The technology has been tested on patients paralyzed by spinal cord injuries at the Rehabilitation Hospital of the Pacific and the company hopes the technology will be available in 2015. Meanwhile, Raytheon has developed the XOS 2, an exoskeleton intended for military use that would enable soldiers to carry heavy loads over long distances, while reducing the risks of orthopedic injuries. Using high-pressure hydraulics, the suit amplifies the soldier’s strength and endurance, allowing him to do the work of two to three workers. Currently, the suit requires a tethered power source, which limits functionality on the battlefield.

Figure 99

Bionic exoskeleton designed by Ekso Bionics

Source: Ekso Bionics

The six-million-dollar man becomes a reality . . .

for far less

Raytheon has developed the XOS 2, an exoskeleton

intended for military use

A number of research efforts are focused on

bringing a sense of touch to prosthetics

Neuroprosthetics are used for cochlear implants, artificial retinas, deep

brain stimulation

Bionic exoskeletons promise new mobility

to the disabled




Panasonic subsidiary ActiveLink has been making robotic exoskeleton suits since 2003. The company plans to launch the first affordable, mass-produced “Powerloader” robotic exoskeleton suit that is expected to go on sale in 2015 at a price between US$5,000 and US$7,000, according to president Hiromichi Fujimoto. The full-body machine will enable users to lift 100-kilo objects and move at speeds up to 8kph at a price that will it make accessible to smaller businesses, helping people in farming or delivery services carry heavy items.

Figure 100

ActiveLink Exoskeleton Suit

Source: ActiveLink

Computational genomics - Decoding the software of nature Declining cost of computing, more powerful systems and the capacity to store and process massive quantities of data create conditions conducive to accelerating innovation in the life sciences. With the cost of a sequenced human genome falling well below US$1,000, genomics is actively decoding elusive mysteries of DNA, the “source code” for the human body, with promise of proactive avoidance and better treatment for cancer, Alzheimer’s, multiple sclerosis and other chronic diseases.

The growing awareness of the falling price of gene sequencing is driving new research initiatives. In his 2016 budget proposal, US President Obama proposed US$215m for the National Institutes of Health and other organizations to fund collection of the genomes of one million volunteers. The objective would be to advance efforts to identify the molecular drivers of cancer and apply that knowledge to drug development.

According to Francis de Souza, president of Illumina, roughly 228,000 human genomes have been completely sequenced by researchers around the globe as of 2014. Illumina’s estimates suggest that this number will double about every 12 months, reaching 1.6m genomes by 2017, as technology transitions from an era of collapsing prices to expanding adoption for medicine use.

A paradigm shift in healthcare innovation Advances in gene-sequencing instruments have created a paradigm shift in healthcare innovation and in the demand for high-performance computing as well as cloud computing. Second- and third-generation gene-sequencing technology could deliver a paradigm shift in diagnostics, personalized medicine and drug discovery. Academics are advancing innovation in data analysis, while growing access to public cloud resources offers increasingly viable, low-cost and scalable solutions.

Exoskeletons are currently being explored

for military purposes

Innovation accelerating in the life sciences

ActiveLink plans to launch the first affordable, mass-

produced robotic exoskeleton

Democratizing the gene as sequencing goes

mass market

The number of sequenced human genomes doubles

every 12 months




Figure 101

The promise of a sub US$1,000 genome is becoming a reality

Source: CLSA

When the original human-genome sequencing was published around 2001, the computational requirements included 50,000 hours to assemble one human genome, which consists of approximately three billion DNA molecules. Even with the advanced technology that is available today, there’s no way to read a chromosome from one end to the other, which causes inefficiencies in sequencing. It will require several generations of computational technology advancements to read an entire chromosome from end to end.

The most powerful change in the last several years is that sequencing technology has improved so dramatically. It is now possible to regularly sequence many individuals and organisms and perform much larger studies very efficiently and much more rapidly. The rate at which sequencing can be done is increasing at fivefold per year. It took US$3bn and 13 years to sequence the first human genome; now the time has fallen to hours with high-end machines.

Figure 102

The cost of sequencing a human genome has declined faster than Moore’s Law

Source: National Human Genome Institute

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It took 13 years and US$3bn to sequence the

first human genome

Costs of sequencing the human genome have declined dramatically

The rate at which sequencing can be

done is increasing at fivefold per year

Declines in the cost of sequencing accelerated

in 2007




As mentioned earlier, costs of sequencing the human genome have declined dramatically. Celera Genomics in 2001 spent about 50,000 CPU hours, or roughly US$50,000 worth of computation, to assemble the human genome. Illumina’s HiSeq X, introduced in January 2014, reduced the cost of sequencing by a factor of 10 with an output of 20,000 human genomes per year. Assuming all costs, the machine can sequence an entire genome for US$1,000. The HiSeq X machines cost US$1m each and must be purchased 10 at a time, but there is a lot of interest from large hospitals and research efforts. Also, lower-end machines priced at US$250,000 or less are putting sequencing technology in the hands of smaller hospitals and medical practices.

Figure 103

Illumina HiSeq X

Source: Wikimedia Commons (Magnus Manske)

A human genome in three hours - for hundreds of dollars Researchers at Nationwide Children's Hospital have developed software that shrinks the time to search DNA sequences for genetic anomalies from weeks to hours. GenomeNext LLC offers the software at prices ranging from US$250 to US$800 per sample, depending on the quantity of genes to be analyzed. The software, named Churchill, automates processes of identifying patterns and meaning in about three hours for a whole human genome. The software demonstrated 99.99% accuracy and 99.66% effectiveness for diagnostic purposes under National Institute of Standards and Technology standards.

Toward the US$100 genome The National Institute of Health’s Advanced DNA Sequencing Technology Program has provided a grant to a small Californian company, Eve Biomedical, which intends to develop a system intended to sequence an entire human genome for under US$100. The system design is based on using light to sequence DNA using a cellphone camera chip.

New software can take three hours to sequence a

whole human genome

High-end DNA sequencing machines can generate thousands of genomes

per year

Sequencers now deliver a human genome in one day

for under US$1,000




The DNA sequencing machine market is dominated by Illumina (which fended off an acquisition bid from Roche Pharmaceuticals) and Life Technologies (acquired by Thermo-Fisher Scientific). The patent analysis by research firm Marks & Clerk shows Illumina and Life Technologies have a dominant lead in the number of DNA sequencing technology patents filed over the past 10 years: Illumina has filed 80 and Life Technologies has filed 70. BGI Shenzhen (formerly Beijing Genomics Institute) is emerging as another major player in DNA sequencing machines.

Building value as the data get bigger What’s most significant is that growing use of sequencing technologies creates valuable repositories of data that get more valuable the larger they become. Foundation Medicine (FMI) and Genomic Health (GHDX) are changing cancer treatments for adults. Foundation Medicine can sequence a patient’s tumor, compare it to its database of other cases and identify the most effective treatment for that type of tumor.

A repository for the next generation of insights Initiated in 2003 with US$196m in funding, the ENCODE Project was planned as a followup to the Human Genome Project, which initially sequenced the DNA that makes up the human genome. The ENCODE Project is seeking to interpret this sequence. The 21,000 genes that provide instructions for making proteins (such as the dopamine receptor gene that makes dopamine receptors in brain cells, and the insulin gene that makes insulin in the pancreas) account for only about 1% of the human genome, and the goal of the project was to identify the purpose of the other 99%. Scientists have discovered that over 80% that was once considered “junk DNA” actually has a role in regulating activity of particular genes.

Consumer genetic testing faces FDA pushback There are a number of consumer-focused genetic analysis companies that have been offering services that claim to screen for specific diseases, or propensity for certain conditions. 23 and Me is a private company that offers a consumer-genetic-analysis service for US$99. In December 2013, the FDA clamped down on 23 and Me, claiming its service was functioning as an unapproved diagnostic device. Since then, 23 and Me has been prohibited from sharing data, such as the likelihood to contract certain diseases. Several analyses have concluded the tests are not particularly accurate. With over 800,000 customers, 23 and Me has shifted its model to providing paid access to companies like Pfizer and Genentech to aid in their research into Parkinson’s and other diseases.

Hype ahead of reality, but reality is catching up The big promises of genetics-based medicine have been slow to be realized (eg, hype from biotech companies over the past decade that sequencing technology would enable the triggers of disease to be discovered and catalogued, potentially with cures for cancer, Alzheimer’s and other diseases around the corner). As is characteristic with consequential technologies, advocates overestimated the near-term impact, but may underestimate the long-term potential.

Current progress appears to be accelerating, as genome analysis is helping doctors make more rapid diagnoses of conditions such as muscular dystrophy, cystic fibrosis and kidney disease. Doctors hope to be able to sequence children and their parents to treat unusual diseases more quickly and effectively. The ability to determine

Illumina and Life Technologies dominate

the DNA sequencing machine market

Extracting information from sequenced DNA took longer and cost more than

anyone expected

Regulators are scrutinizing consumer-

genetic-testing advertising

Current progress appears to be accelerating

Over 80% of what was once considered “junk

DNA” actually has a role in regulating activity




whether they are predisposed to a certain condition will let patients take preventive steps long before symptoms appear. A new generation of services allows DNA samples to be created from text files, leading to the potential for garage-based biotech startups as the technology gets cheaper and more accessible.

With the declining cost of DNA sequencing and growing repositories of data, the future of genomics offers potentially great promise. We are likely to see the development of DNA screening tests that could provide early identification for risk factors of developing diseases; new technologies that can more quickly identify diseases and infections; the ability to pinpoint the role of specific genes involved cancers and type 2 diabetes and detect gene mutations; the identification of genes associated with autism to help with treatment; the ability to convert plant waste into biofuels; and the ability to engineer strain-resistant crops. The promise of computational genomics becomes closer to reality with the sub-US$1,000 genome. Proponents expect medicine to become personalized, with treatments based on a patient’s individual genome. Over time, gene therapy will be able to cure diseases by replacing faulty genes with non-faulty genes.

Intelligent machines There is a new generation of software-defined machines that will change the fundamental aspects of life and work. Drones, or unmanned aerial vehicles (UAVs), have transformed warfare and are poised to impact consumers and industries as well. The fundamental nature of transportation is changing as autonomous vehicles prove technological viability and sensor-based vehicle communications systems promise to ease traffic jams and improve safety. Advances in robotics are having a transformative effect on manufacturing and industry as a new wave of personal robotics comes to market. The Internet of Things’ ambient intelligence is becoming consumer accessible and at the same time powering the next generation of smart industry. A key thread across each category is the essential role that software and notably analytics play in enabling innovation.

Figure 104

Intelligent machines

Innovation What it means Who could benefit Potentially at risk

Related companies

Drones Drone aircraft, delivery services, consumer hobbyists, precision agriculture, public safety

Merchants, military, residents of remote areas, farmers, transportation companies, public safety

na Google (GOOG), Amazon (AMZN), Lockheed Martin (LMT), AeroVironment (AVAV), Northrop Grumman (NOC), Boeing, Textron (TXT), General Dynamics (GD), SAIC (SAIC), GoPro (GPRO), Ambarella (AMBA), IXYS Corp, (IXYS), InvenSense (INVS) and others

Smarter cars and autonomous vehicles

Self-driving cars, trucks, buses, industrial vehicles

Consumers, businesses, automobile manufacturers, auto supply chain, military

Spare auto parts, the auto industry itself

Google (GOOG), Toyota Motor (TM), Ford Motor (F), General Motors (GM), Raytheon (RTN), AeroVironment (AVAV), Boeing (BA), Northrop Grumman (NOC), Textron (TXT), BAE Systems (BAESY), Adept Technology (ADEP), Bosch, STMicro, InvenSense, Skyworks Solutions, Nvidia, Qualcomm, Broadcom, Infineon, Texas Instruments

Robotics Automated manufacturing, surgical robots, trainable robotic assistants, domestic robots

Manufacturers, healthcare, consumers, military

Labor, especially employees doing repetitive tasks in manufacturing, service, etc

Amazon (AMZN), iRobot (IRBT), Google (GOOG), Raytheon (RTN), Moog (MOG), Intuitive Surgical (ISRG), Cognex (CGNX), Accuray (ARAY), AeroVironment (AVAV), Northrop Grumman (NOC), Rockwell Automation (ROK), General Dynamics (GD), Boeing (BA), Teledyne (TDY), Textron (TXT)

The Internet of Things

Myriad implications for both industrial and consumer

Consumers, businesses, manufacturers, logistics, military, public safety, wireless sensor network providers, analytic software vendors

na IBM (IBM), CA Technologies (CA), Cisco (CSCO), EMC (EMC), GE (GE), National Instruments (NATI), Google (GOOG), Intel (INTC), AMD (AMD), Siemens (SIE), Teradata (TDC), SAP (SAP), Splunk (SPLK), Informatica (INFA), Broadcom (BRCM), Qualcomm (QCOM); wireless network, sensor and analytic software vendors

Source: CLSA

Autonomous vehicles and robotics will remake

transportation and manufacturing

The future of genomics offers great promise




Figure 105

Intelligent machines - Prominent players

Company Ticker Rating Currency Last close

EPS FY14CL

EPS FY15CL

PE (x) FY14CL

PE (x) FY15CL

Market cap (US$m)

Google GOOGL US BUY USD 562.63 22.66 29.30 24.8 19.2 383,062

General Electric GE US N-R USD 25.99 1.65 1.73 15.8 15.0 261,587

Toyota1 TM US O-PF JPY 135.37 575.30 670.79 0.2 0.2 230,535

Amazon.com AMZN US O-PF USD 380.16 (0.52) (1.28) na na 176,540

IBM IBM US O-PF USD 161.94 16.54 16.00 9.8 10.1 160,065

Intel INTC US SELL USD 33.25 2.31 2.11 14.4 15.7 157,472

Cisco Systems CSCO US N-R USD 29.51 2.06 2.16 14.3 13.7 150,641

Qualcomm QCOM US O-PF USD 72.51 5.27 4.99 13.8 14.5 119,610

Boeing BA US N-R USD 150.85 8.60 8.52 17.5 17.7 106,257

Siemens SIE FF N-R EUR 99.55 6.18 6.82 16.1 14.6 93,265

SAP SE SAP US N-R N/A 70.19 3.50 3.63 20.1 19.3 86,329

Ford Motor F US O-PF USD 16.34 1.16 1.58 14.1 10.3 64,640

Lockheed Martin LMT US N-R USD 200.05 11.40 11.16 17.5 17.9 63,133

Texas Instrument TXN US U-PF USD 58.80 2.57 2.81 22.9 20.9 61,572

GM GM US O-PF USD 37.31 3.03 4.45 12.3 8.4 60,083

EMC Corp EMC US O-PF USD 28.94 1.90 1.99 15.2 14.5 58,890

General Dynamics GD US N-R USD 138.78 7.83 8.34 17.7 16.6 46,034

Raytheon RTN US N-R USD 108.77 6.97 6.40 15.6 17.0 33,428

Northrop Grumman NOC US N-R USD 165.71 9.75 9.45 17.0 17.5 32,878

Broadcom BRCM US BUY USD 45.23 2.97 3.41 15.2 13.3 27,093

BAE Systems BA. LN N-R GBP 532.00 38.00 39.07 14.0 13.6 25,934

Intuitive ISRG US N-R USD 500.00 16.10 17.45 31.1 28.7 18,300

Skyworks Solutns SWKS US N-R USD 87.75 3.24 4.89 27.1 17.9 16,744

Rockwell Automat ROK US O-PF USD 117.04 6.18 6.71 19.0 17.4 15,852

CA CA US N-R USD 32.52 3.07 2.49 10.6 13.1 14,179

Infineon Technol IFX FF N-R EUR 10.33 0.44 0.56 23.5 18.6 13,067

Textron TXT US N-R USD 44.31 2.13 2.52 20.8 17.6 12,267

Splunk SPLK US BUY USD 67.25 (0.10) 0.09 na 777.4 8,155

STMicroelectron STM US N-R USD 8.89 0.29 0.42 30.7 21.3 8,150

Teradata TDC US BUY USD 44.52 2.86 2.63 15.5 16.9 6,500

GoPro GPRO US N-R USD 41.98 1.32 1.38 31.8 30.4 6,012

Informatica INFA US BUY USD 42.95 1.58 1.63 27.2 26.4 4,700

National Instr NATI US N-R USD 31.14 0.99 1.04 31.5 30.1 3,990

Cognex CGNX US BUY USD 44.69 1.36 1.47 32.8 30.5 3,868

Teledyne Tech TDY US N-R USD 100.83 5.75 5.73 17.5 17.6 3,556

Moog MOG'A US N-R USD 75.46 3.52 3.90 21.4 19.3 3,012

Science App SAIC US N-R USD 54.68 2.27 2.86 24.1 19.1 2,498

Adv Micro Dev AMD US U-PF USD 3.11 (0.53) (0.15) na na 2,417

Ambarella AMBA US N-R USD 57.39 1.10 1.80 52.2 32.0 1,740

InvenSense INVN US N-R USD 16.67 0.58 0.46 28.7 36.1 1,505

Irobot IRBT US N-R USD 32.85 1.25 1.35 26.3 24.3 975

Accuray ARAY US N-R USD 8.98 (0.47) (0.49) na na 705

Aerovironment AVAV US N-R USD 27.41 0.60 (0.02) 45.7 na 639 1 Covered by CLSA; all other ratings by CLSA Americas; data for not-rated (N-R) companies based on consensus. Source: CLSA, Thomson Reuters




Drones invade the market There has been a dramatic increase in awareness around consumer and commercial drones - technically known as unmanned aerial vehicles - as growing availability of cheaper and more powerful systems makes the technology ever more accessible. Jeff Bezos, CEO of Amazon, surprised the world on a 60 Minutes TV segment in December 2013 when he announced plans to develop drones to deliver products to consumers, which has been dubbed “Amazon Prime Air”. Consumer units have steadily made their way into the marketplace - we’ve previously highlighted TED Talks founder Chris Anderson’s startup 3D Robotics, which manufactures drones using an open-source development model. The cheapest do-it-yourself kit starts at US$550.

Figure 106

3D Robotics X8-M quadracoptor

Source: 3D Robotics

Drones have actually been employed since the 19th Century and used for years by the armed forces for reconnaissance. The US military has been actively employing UAVs for the past 20 years for a range of tasks, including surveillance, intelligence gathering and air strikes against enemies. In the past, drones were large, expensive aircraft, but the size and price have come down dramatically from millions of dollars to US$100,000-200,000 for a state-of-the-art surveillance drone. While UAVs are a substantial market for military aerospace suppliers, it’s the consumer and commercial markets that give rise to new investment opportunities. The proliferation of consumer drones - usually remote-controlled quadracoptors - raises a raft of ethical, regulatory, privacy and public-safety issues. In January 2015, a drone was found to have made its way onto the White House lawn, raising fears of weaponized, light UAVs. The small size of smaller units (often under three pounds) and low altitude make it easy to evade traditional surveillance and air-control systems.

Promising consumer and commercial market opportunity Venture investment in the nascent drone industry grew 104% YoY to US$108m in 2014, according to CB Insights. According to the Consumer Electronics Association, consumers will spend US$103m on personal drones in

High-end consumer drones for photography

can run several thousand dollars

Consumer drones raise new ethical, regulatory,

privacy and public safety concerns

Consumers likely to spend US$103m on drones

in 2015


http://www.cesweb.org/News/Press-Releases/CES-Press-Release.aspx?NodeID=a8cf1815-ad54-4bfd-9e70-62d7e4a1868a



2015, an increase from US$69m in 2014, on pace for the global drone industry to exceed US$1bn with one million units within five years. Research firm Radiant Insights estimates that the worldwide unmanned aerial systems (UAS) market will grow from US$609m in 2014 to US$4.8bn by 2021.

Figure 107

Projected annual sales of commercial unmanned vehicles

Source: Association of Unmanned Vehicle Systems International

Business Insider believes that of an estimated US$98bn in cumulative global spending on aerial drones over the next decade, 12% will be for commercial purposes. A study conducted by Darryl Jenkins and Dr Bijan Vasigh on behalf of the Association for Unmanned Vehicle Systems International found that the economic impact of the integration of unmanned aircraft systems into the National Airspace System would grow sustainably for the foreseeable future, generating cumulative value of more than US$82bn and creating roughly 100,000 jobs between 2015 and 2025.

Drone makers multiply Competition is heating up in the drone market. There were 15 drone companies showcased at the 2015 Consumer Electronics Show, an increase from four in 2014, with over 100 types of drones on display. Companies included DJI, ZANO, Parrot, Qualcomm and Nixie, a drone camera that attaches to your wrist and can be tossed into the air to take a selfie before flying back to you. China-based DJI Innovations, the market leader in the personal drone industry, has gone from 50 employees to 3,000 in just under three years. With Amazon already developing its own drone program, Google outbid Facebook for Titan Aerospace, a small drone manufacturer. Facebook responded by acquiring Ascenta, a UK drone company.

Consumers find new playthings Much of the consumer usage of drones has been by home hobbyists for entertainment and recreation. Many drones come with on-board video cameras - often a GoPro - that can be used to capture overhead views of the neighborhood or take “drone selfies”. This, of course, raises concerns of invasion of privacy as “drone etiquette” evolves. There are many potential practical use cases: campers and hikers may be able to launch a drone in the air to get a view of their surroundings and routes, take videos of rock climbing, biking or other activities, and with the addition of GPS be able to avoid getting lost.

40

70

105110

118125

0

20

40

60

80

100

120

140

2015 2016 2017 2018 2019 2020

Thousands of units

Growth in UAVs is forecast to take off in the

next couple of years

Twelve percent of spending on aerial drones over the next decade will

be for commercial purposes

Competition is heating up in the drone market




Figure 108

Parrot Bebop Drone

Source: Wikimedia Commons (Parrot SA)

Commercial UAVs will transform industries Currently, military applications dominate the global UAV market, but commercial applications are poised to see robust adoption over the next decade. There is a broad range of commercial uses currently being explored for drones:

Precision agriculture - A study conducted by Darryl Jenkins and Dr Bijan Vasigh on behalf of the Association for Unmanned Vehicle Systems International found that precision agriculture and public safety comprise approximately 90% of the most promising commercial and civil markets for unmanned aircraft systems. Sensors can be attached to ground vehicles and UAVs to scan crops with multispectral imaging for health problems, track growth rates and hydration, and locate disease outbreaks. Potentially, UAVs can be used for the precision application of pesticides and fertilizers in the appropriate amount and location to save cost and reduce environmental impact.

Product delivery and logistics – Quick-turnaround product delivery is a key use case. Beyond Amazon’s efforts, UPS and Domino’s Pizza are exploring ways that UAVs can be used to deliver products and food to customers. Drones can deliver items such as medications and supplies to remote areas in emerging countries where there may not be road infrastructure for cars. Military contractors are already delivering loads of front-line supplies greater than 6,000 pounds via aerial drone to remote locations in Afghanistan, so delivery of larger items to consumer and businesses is possible.

Oil and gas - Oil companies such as BP are using drones to generate 3D maps of roads and pipelines to identify problems and strategize repairs. Drones can help move large equipment in difficult weather by providing real-time surveillance and 3D models of terrain.

Drones allow for unprecedented perspective for photographers

Commercial applications are poised to see robust

adoption over the next decade

UAVs can be used for the precision application of

pesticides and fertilizers

UPS and Domino’s Pizza are exploring ways that

UAVs can be used to deliver products and food




Public safety, security and emergency response - Drones can conduct searches to find lost vehicles or identify situations that are too difficult for humans. UAVs can survey locations to help firefighters and emergency responders obtain information to inform tactical and operational decisions that can help ensure the safety of firefighters. Security drones can supplement and enhance foot and vehicle patrols for factories, office parks and power plants.

Journalism, filmmaking and photography - Filmmakers are already using drones for aerial shots, particularly for extreme sports content. Reporters are using drones to capture footage for sporting and other media events. There is a drone journalism lab at the University of Nebraska-Lincoln that is focused on exploring how drones can be used for reporting.

Construction, architecture and civil engineering - 3D Robotics’ CEO Chris Anderson announced a partnership with software firm Autodesk to perform 3D building scanning that can be integrated into digital workflow and CAD systems. Drones will be able to perform 3D scanning that can be easily deployed or even automated on construction sites and private property.

Regulatory obstacles will take time to resolve Outside the USA, open-use policies prevail with few if any regulations regarding the use of drones for commercial use. The Federal Aviation Administration (FAA) has blocked most uses of drones for commercial use. Provisions for commercial exemptions stipulate that drones can’t fly higher than 400 feet in controlled areas, operators must be licensed pilots, devices have to be inspected, fly within line of sight of the operator, while flights in different areas will need to be approved by the FAA.

American regulators have planned to phase in commercial drone flights starting with limited flights of small drones weighing 55 pounds or less. However, the FAA has warned it will miss a September 2015 Congressional deadline set by Congress to legalize the use of unmanned aircraft systems in the USA. In the meantime, the agency is granting exceptions for interested companies that pledge to meet safety guidelines in order to encourage the emerging sector during its rulemaking. So far, the FAA has granted two dozen permissions (with another 200 applications received) for operators of drones in the movie and video industry, real-estate photography, agricultural monitoring, aerial surveying and flare stack inspection (the large towers used to burn off undesired gases at oil wells and refineries).

There are a number of ways for investors to play the drone theme, including Google, Amazon, Lockheed Martin, Northrup Grumman, Aerovironment, Boeing, Textron, General Dynamics, SAIC, GoPro, Ambarella, IXYS Corp, InvenSense and others.

Smarter cars - Let the computers drive In 2014, momentum around self-driving cars - and more broadly autonomous vehicles - gained ground in a big way. Google has been extensively testing its autonomous vehicles, which had logged more than 700,000 driverless miles virtually accident free as of June 2014. Other automakers have been getting into the act: Audi, BMW, Cadillac, Ford, GM, Mercedes-Benz, Nissan, Toyota, Volkswagen and Volvo have all begun testing driverless systems. Tesla has introduced semi-autonomous software updates to its vehicles, and the

Outside the USA, open-use policies prevail with

few if any regulations for commercial use

Vision becoming reality to improve safety

and access

The FAA has granted two dozen permissions (with another 200 applications

received) for operators of drones

3D Robotics announced a partnership with

Autodesk to perform 3D building scanning




company has stated that technology to support autonomous capabilities will be built into every new vehicle with a software update in the future needed to enable the functions.

Google hopes to debut its prototype by 2016, while Audi, BMW, GM, Nissan, Toyota and Volvo have all targeted the introduction of autonomous cars by 2020. Uber announced it will be opening the Uber Advanced Technologies Center on the Pittsburgh campus of Carnegie Mellon University to develop autonomous car technology. Nokia in 2014 launched a US$100m Connected Car Fund. The concept extends beyond passenger vehicles as well. Mining company Rio Tinto is currently using 10 self-driving ore trucks, with plans to expand to 150 vehicles within four years.

Potential safety innovations have the power to be transformative Autonomous vehicles have the potential to solve many of the driving-related problems that occur as a result of human error or negligence. In theory, autonomous cars are safer than driver-operated vehicles because they have a 360-degree range of vision, can react more quickly than humans, cannot be distracted (for instance, by text messaging) and are unable to drive under the influence of alcohol.

According to the National Highway Traffic Safety Administration, over 38,000 people were killed in automobile crashes in 2011. Motor vehicle crashes are the leading cause of death among Americans aged 1 to 34. According to research from the American Automobile Association (AAA), traffic crashes cost Americans US$299.5bn annually. The Federal Highway Administration estimates that 25% of congestion is attributable to traffic incidents, roughly half of which are crashes.

One of the primary goals is to reduce traffic accidents to zero. Google has demonstrated a proof-of-concept scenario where a legally blind person directs the car through voice commands, as the car, for example, takes its passenger to the bank, a drive-thru restaurant and home. It’s easy to come up with scenarios where technology would help, in case of the elderly, impaired or inexperienced drivers.

Self-driving and highly automated vehicles have the potential to save thousands of lives, recover valuable time lost in commuting and increase the efficiency of transport systems. Realizing this vision, however, requires major advances in a number of core technologies in robotics, artificial intelligence, computer vision and human machine interfaces. Investors interested in a deeper view into this topic should consult the work of CLSA’s auto analysts Emmanuel Rosner and Andrew Fung as well as the 1Q14 CLSA U course on self-driving vehicles with John Leonard, professor of mechanical and ocean engineering and associate department head for research at the MIT Department of Mechanical Engineering.

A wealth of technologies at work Current prototype autonomous driving systems employ, for instance, video imaging, GPS, laser scanner, radar and ultrasound technologies that enable the vehicle to recognize everything from surrounding vehicles to traffic light colors and move accordingly. Google makes extensive use of light detection and ranging (LIDAR), an optical remote sensing technology that measures distance and other properties by illuminating an object with light. The systems have built-in redundancies that act as fail-safes and also allow the human driver to override the system at any time.

Autonomous vehicles have the potential to solve many driving-

related problems

Self-driving and highly automated vehicles have

the potential to save lives

Ninety-three percent of automobile crashes are caused by human error

Nokia in 2014 launched a US$100m Connected

Car Fund




Figure 109

Google self-driving car prototype

Source: Google

In a world of driverless, connected cars, the road system could be transformed into something akin to a smart grid, where all vehicles are tapped into the system, monitoring traffic patterns and other vehicle movements. Such a system could conceivably obviate the problems of traffic congestion, as well as the accidents that tend to accompany it. Many of the technologies necessary to produce an intelligent highway system are already in place, including traffic monitoring sensors, fiber optic networks, wireless technologies, motion detectors, etc.

New cars increasingly include sensor-based technologies such as automated parking assist and adaptive cruise control. Coming generations of driver-assist systems will provide greater vehicle autonomy. On the horizon are sensor-based solutions that employ stereo cameras, software and complex algorithms to compute the geometry of situations in front of the vehicle. Like all predictive algorithms, the efficacy will improve with more data. There’s increasing research into connected-vehicle systems that use wireless technologies for real-time vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. V2V and V2I technologies promise to advance crash avoidance and traffic optimization. KPMG’s 2012 report Self Driving Cars, the Next Revolution posits that there will be a convergence of vehicle-based sensor solutions and connected V2V and V2I solutions.

The adoption of V2V and V2I communications could significantly reduce traffic congestion. A report from the Eno Transportation Institute estimates that 10% adoption of autonomous vehicles in the USA could create US$38bn in comprehensive cost savings from reduction of crashes, improved fuel efficiency, lower travel time and parking savings. This would increase to US$212bn at 50% adoption and US$447bn at 90% adoption.

While the technologies to support fully autonomous vehicles are here today, there are numerous hurdles before the technology can become widespread. Cost is one challenge. The LIDAR system used in the Google car, for example,

Many of the technologies necessary to produce an

intelligent highway system are in place

New cars include automated parking assist

and adaptive cruise control

Ten-percent adoption of autonomous vehicles in

the USA could create US$38bn in cost savings

The LIDAR system used in the Google car costs

US$70,000

Prototypes include no pedals or steering wheel




costs US$70,000. This cost would clearly need to decline while the instruments would need to be miniaturized and redesigned to be attractive to consumers.

Fully autonomous vehicles not in the near future MIT professor John Leonard believes that the technology is the most misunderstood part of the outlook for autonomous vehicles. Current technology for driverless driving, including in the Google car, requires a very precise and extensive mapping of the trajectory for the vehicle, which includes all fixed obstacles. This is called an intensity-based map of the road surface. It is required in addition to all the technology required to read the road and obstacles in a live fashion during the driving. This particular technology is not able yet to deal with the multiplicity and complexity of scenarios that may happen on the road. As such, while he believes that the National Highway Traffic Safety Administration’s (NHTSA) Level 3 self-driving cars (which refer to specific driving conditions where there can be complete automation in certain situations, with some human interactions) are coming in the near future, Level 4 could still be years away. This is important because Level 4 (full self-driving automation) is the level where most of the economic benefits to society would occur (driverless taxis and parking, zero accidents, etc).

Automotive active safety suppliers are best positioned for the future In Emmanuel Rosner’s view, automotive suppliers with the best current portfolio of active safety technologies are likely to benefit most from the increased vehicle content in autonomous vehicles. In particular, Delphi Automotive’s collision warnings and avoidance systems already integrate radars and cameras to alert the driver of potential obstacles and offer full brake assistance in the event of an impending collision. One of its differentiated products in this field is the RACam, which combines radar sensing, vision sensing and data fusion in a single sophisticated module. Adoption of these technologies should see strong growth as automotive manufacturers and regulators advance towards the ultimate goal of zero accidents. Below, we summarize the active safety technologies offered by key suppliers.

Figure 110

Technologies offered by key active safety suppliers

Autoliv Bosch Continental Delphi TRW Valeo Forward radar X X X X X Side/360° radar X X X X X X Forward camera X X X X X X Rear/surround camera X X X X Laser X Ultrasonic X X Night vision X X Source: Companies

The biggest challenges are human, not technology Regulations and liability remain the bigger challenges ahead. Google has been actively lobbying lawmakers in the USA to legalize operation of self-driving vehicles with some success. California and Nevada (AB 511) have legislation allowing autonomous vehicle licensing, while Florida and Washington, DC allow testing. Related legislation is pending in several other states. Representatives from Google stated at an industry conference in January 2015 the belief that self-driving cars would be on the road by 2020, downplaying the regulatory obstacles

The NHTSA’s Level 4 (full self-driving automation) could still be years away

Regulations and liability remain the bigger challenges ahead

Automotive suppliers of active safety technologies

are positioned to benefit from autonomous vehicles




Some of the bigger questions concern liability and the role of human operators in conjunction with the technology. For now, the proof of concepts have been a success. The bigger challenges lie ahead with laws, lawmakers and insurance companies. The Vienna Convention on Road Traffic and the Geneva Convention on Road Traffic are two major international treaties that may need to be changed for cars to be used in Europe and the United States, as both require that a driver must be in full control of a vehicle at all times.

A younger generation disconnects from driving The longer-term vision for connected cars will involve rethinking transportation’s role in society. We are already seeing a generational shift related to driving. According to the Department of Transportation’s recent study "Beyond Traffic," the 73m US millennials aged 18 to 34 logged 20% fewer driven miles in 2010 than at the start of the decade. Overall miles driven are declining: on average, Americans drove less in 2006 than in 2005, the first per-capita driving decline since the oil crises of the 1970s. Car sharing is also growing at a rapid rate. According to the Department of Transportation, there were 1.6m members in 24 active programs in the USA in 2014, an over tenfold increase in seven years.

Figure 111 Figure 112

Zoox concept driverless vehicle (interior view) Zoox concept driverless vehicle (exterior view)

Source: Zoox

The future vision of connected cars promises more sharing, as transportation options depend less and less on owning a vehicle. Fleets of shared vehicles, taxis or buses could travel the streets responding to requests from Uber-like services. Campus-based transportation systems could help businesses, schools and the elderly. Reduction in the amount of parking required could drive redesign of urban spaces for greater efficiency and more open space. Even vehicles themselves could see radical redesign to be adapted where there are no human drivers.

Beyond the automakers, potential beneficiaries include Bosch, STMicro, InvenSense, Skyworks Solutions and chipmakers like Nvidia, Qualcomm, Broadcom, Infineon and Texas Instruments.

Robotics - Replacing and working with humans Quietly and steadily, the evolution and advancement of artificial-intelligence software and robotics is having a profound impact on society and the economy at large. Beyond nanorobotics, drones and autonomous vehicles (covered elsewhere in this report), robots are transforming industries like manufacturing, warehousing and distribution, healthcare, retail and other areas. Much of what we see today is an extension of the multicentury trend

The future vision of connected cars promises

more sharing

The road to fully autonomous vehicles

will occur in stages

Some of the bigger questions concern liability

and the role of human operators

Welcome our new AI-enhanced robot

overlords




towards automating human tasks, and the acceleration of progress in technology will have outsize impact on the future economy. Foxconn/Hon Hai, the largest high-tech manufacturer in the world, has had negative media coverage over labor issues, working conditions and rising costs of labor. The company’s president, Terry Gou, has discussed a goal of reducing its 1.3m workers using robots by an unspecified number.

The International Federation of Robotics (IFR) forecasts acceleration in growth for service robots. IFR estimates over 200,000 industrial robots were installed in 2014 worldwide, 15% more than in 2013. Between 2015 and 2017, it forecasts robot sales to grow at a 6% pace in the Americas and Europe, and 16% in Asia and Australia. China in particular has a booming market expected to reach a Cagr of 25% through 2017. By the end of 2017, IFR estimates that about 2m industrial robots will be installed in factories worldwide.

Industrial robots account for 86% of the US$30bn market, with service robots (which perform lighter tasks such as picking and packing, cleaning and assisting in surgery) accounting for the remaining 14%. Industrial robots are expected to grow by 5% a year while service robots should grow 25-30% annually over the next few years.

VC investment in robotics has been taking off, with 2014 funding of US$341m up 36% over the US$251m in 2013, according to Travis Deyle of robotics website Hizook. Total equity funding was US$425m, including crowdfunding. There has been active M&A activity as well. The Robotics Report tracked 45 fundings, M&A transactions, IPOs and failures. KUKA purchased Swisslog for US$357m, while Titan Aerospace was sold for US$60m. Rethink Robotics raised US$26.6m, Restoration Robotics raised US$45m and Anki got US$55m in Series C funding. Home robotics company Jibo raised a US$25m Series A round in January 2015.

New funds target robotics opportunity Dmitry Grishin, CEO of Russia’s largest internet company the Mail.Ru Group, personally launched Grishin Robotics in 2012, a US$25m seed-investment fund. He told the Wall Street Journal that the fund has invested US$6m in eight startups, all of them based in the USA. One of Grishin Robotics’ portfolio companies is Bolt.io, a Boston-based incubator for hardware startups, which raised US$25m for its second fund, following the success of its initial US$4m fund. Kazakh petrochemical mogul and entrepreneur Kenges Rakishev founded Genesis Angels, a US$100m fund dedicated to robotics and artificial intelligence, and launched a second US$102m fund in January 2015.

E-commerce warehouses lead the charge on next-gen robotics E-retail and distribution are leading in the adoption of advanced robotics systems. With the rise of e-commerce and increasingly demanding consumers, companies are scrambling to quickly and accurately move goods, relying on warehouses and distributions centers. While distribution centers often present some degree of automation with conveyor systems, palletizers and sortation systems, they remain largely human labor-intensive operations. The convergence of enabling technologies, such as automated-guided vehicles, robotics, machine vision and plant-wide automation control, is turning e-commerce and warehouses into new engines of growth for automation demand. We’d highlight the work CLSA analysts Jeremie Capron and Morten Paulson have published on the impact of robotics on industrial automation in their July 2013 report, Global Capital Goods - Productivity Never Goes Out of Style.

E-retail and distribution are leading in the

adoption of advanced robotics systems

There has been active M&A and VC activity

as well

By the end of 2017, IFR estimates 2m industrial robots will be installed

worldwide

Service robots are forecast to grow 25-30%

annually over the next few years





Big tech firms double down on investments in robotics Notably, Amazon, Apple and Google have all made significant investments in robots and robotics. Amazon spent some US$775m to buy Kiva Systems and disclosed that it currently uses 15,000 Kiva product-picking robots in its warehouses.

Kiva’s warehouse solutions consist of an army of small forklift robots that lift and move inventory shelves around and bring them to human packers, eliminating the need for human pickers. Meanwhile, a central computer coordinates the robots’ moves and customers’ orders using complex algorithms. Kiva’s robots “know” where they are by scanning barcodes set on the floor using technology from machine-vision leader Cognex (CGNX), which has been providing Kiva with barcode readers since at least 2011. Kiva asserts that a packing operator working with its robots can fulfill over three times as many orders per hour as when it works with human pickers. According to CNN, it costs about US$15-20m to install a system with 1,000 robots in a large warehouse.


Kiva’s robots lifting, moving shelves . . . . . . all the way to packers

Source: Kiva Systems

Machine vision is the key to next-generation industrial robotics According to Jeremie Capron, machine vision is emerging as a crucial enabling technology for robotics applications and advanced manufacturing. Machine vision is coming to the fore as critical technology as industrial robot makers bring to market robots that can see. The vast majority of industrial robots currently in operation is essentially blind - programmed to repeat the same motions with high speed and accuracy. However, in the past few years the focus started shifting to vision-enabled robot applications, such as the high-speed picking and packing of random objects from a fast-moving conveyor. Vision technology is critical to the expansion of the range of industrial robotics applications, particularly in logistics. Massachusetts-based Cognex has long been a leader in machine-vision technology.


Order-picking Delta robot and Motoman’s high-speed dual arm

Logistics automation system with machine vision

Source: Yaskawa Source: Cognex

Robots replacing pickers in warehouses

Robots and machine vision making headway

in logistics

Machine vision is emerging as a crucial

enabling technology for robotics applications

Kiva’s army of forklift robots




Notably, Google established a robotics division after acquiring eight robotics companies. These include Boston Dynamics, whose military-purpose robots have been widely viewed on videos on YouTube; Schaft, a Japanese firm developing humanoid robots; Industrial Perception, which has developed a computer-vision system for loading and unloading trucks; Meka Redwood Robotics, a startup focused on competing with the trainable Baxter robot in the small shop and factory marketplace; and others. Google has not specifically addressed its plans in robotics, but interviews with the firm’s Andy Rubin suggest that its initial markets will be in manufacturing and logistics, potentially to compete more aggressively against Amazon for home delivery. Apple is investing US$10.5bn in technologies that include assembly robots, milling machines and equipment to polish the iPhone 5C, according to Bloomberg.

Figure 117

Boston Dynamics Big Dog robot

Source: Wikimedia Commons (US Marine Corps photo by Lance Cpl. M. L. Meier)

New safety standards open up for new breed of robots According to CLSA analyst Morten Paulsen, collaborative robots are industrial robots that can work next to humans without safety gates, and the addressable market is huge as they target small and medium-sized enterprises with limited space and financial resources.

In Isaac Asimov's robotic-based fiction books, the first law of robotics prohibits robots from doing harm to humans. Unfortunately, robots in the real world are not advanced enough - yet - to perfectly decode its environment and make a judgment based on abstract concepts such as Asimov’s law. Meanwhile, industrial robots are not harmless. Those used in automotive welding are capable of lifting and moving workloads of 200kg.

In the late 1970s and early 1980s, industrial robots caused several accidents and casualities in Japan, the USA and Europe. The most publicized accident happened in 1981 when Kenji Urada, a maintenance engineer working for KHI,

Google established a robotics division after

acquiring eight robotics companies

Robots are not harmless . . .

. . . the Urada incident in 1981 triggered strict

safety regulations

Boston Dynamics’ Big Dog is about 3-feet long,

2.5-feet tall and weighs 240lbs


https://www.clsa.com/member/company/index.asp?clsa_id=70006447



was pushed into a grinding machine by one of the robots he was maintaining. This gruesome industrial accident is often referred to as the first (but wrongfully as there were other incidents in the late 1970s) manslaughter at the hand of a robot. The Urada accident in Japan and other incidents around the world led to rapid implementation of strict regulations for robot safety. In most cases, robots had to be installed in cages and had to stop instantly should the door open. The strict regulations meant that manufacturers had to separate robots from workers, invest heavily in safety equipment and allocate sufficient floor space surrounding the robot to meet the safety standards.

The new regulations kept human workers safe from harm, but at the same time added cost to manufacturers and made it very difficult for enterprises with limited space and capital resources to utilize robots in manufacturing. The development of collaborative robots was also held back as it was impossible to operate robots in proximity to humans without breaching safety legislation.

A regulatory breakthrough for development of collaborative robots came in July 2011 when the International Standards Organization set a new standard for so-called “soft-axi”’ movements that enable robots to operate in close proximity to humans. This amendment made it possible to bring down the physical walls separating humans and robots on the factory floor.


Universal Robots at IMTS Chicago 2015 Baxter at IMTS Chicago 2015

International Manufacturing Technology Show (IMTS). Source: CLSA

Danish company Universal Robots (UR) has sold robots in over 50 countries over the past five years, doubling its staff to 97 worldwide. Universal is recognized for having the first commercialized robots with imbedded force control. The company started operating in 2008, but the concept of its lightweight and safe robots dates back to 2003. The UR robots know the required amount of force needed to perform a certain task like picking up a load and moving it from one point to another. If the robot recognizes an increase in force required for the specific movement, the robot arm automatically stops. As such, the UR robots do not require any sensors to operate safely in proximity to humans.

A regulatory break came in 2011

Robotics can operate next to people if they are categorized as safe

The new generation

Force-control technology




Rethink Robotics launched the US$22,000 Baxter personal robot, which was designed to collaborate with humans, learning tasks by demonstration. Baxter has built-in sonar and camera sensors to detect humans, but the robot also featured some rather unusual safety solutions. The most noteworthy is the robots’ flexible joints. In traditional robot joints, an AC servo motor drives a reduction gear and all the components are rigidly conjoined. Baxter is very different as the joints are equipped with elastic actuators, meaning that the motor and gearbox drive a spring. The spring flexes with the joint and allows the robot to sense resistance based on the deflection of the spring. Should an object obstruct the movement of the robot, the elastic actuator will make the arm move.

Personal robotics - Making progress, still don’t do windows . . . yet Housecleaning robots, such as from Roomba or Neato, are already several generations into the market, with price points under US$300 making adoption accessible to the middle class. One of the big challenges with robotics is to get people and robots to work together. Safety (and liability) is a major concern where machines are programmed to perform fixed and repetitive tasks, while humans tend to perform tasks with more variation.

There is also a growing category of the personal-assistant robot. In collaboration with Fellow Robots, Lowe's Innovation Labs has placed robots (dubbed the OSHbots) in an Orchard Supply Hardware store in San Jose, California, in order to study the benefits of using robotics to assist customers and employees. The OSHbots can help shoppers navigate the store by providing the in-store location of a product, scan physical objects for identification (useful for screws, connectors and other parts), provide real-time information on product promotions and inventory and communicate via multiple languages.

An important development in robotics is the emphasis on open-source software. This is driven by dual motives. Free open software encourages adoption and innovation, but also avoids potential issues of liability in case of accidents or property damage. There are two main open-source efforts: a project called Open Source Computer Vision (OpenCV) Library and Robot Operating System (ROS) developed by robotics research lab Willow Garage, which closed down in 2013 while leaving seven spinoffs.

The Robot Report tracks over 1,000 manufacturers of robotics globally, and we expect this to increase over time. The big four makers include ABB (NYSE:ABB), Yaskawa Motoman (TYO:6506), Fanuc (TYO:6954) and KUKA (ETR:KU2). Many of the industrial conglomerates are active in robotics, but a few focused firms include Intuitive Surgical (ISRG), Accuray (ARAY), Israel’s Mazor Robotics (MZOR:IT) and iRobot (IRBT).

The Internet of Things hits the mainstream 2014 was the year that the Internet of Things as a term became widely adopted in the mainstream media, and our report Deep Field: Discovering the Internet of Things focused on the growing relevance and opportunities across consumers and businesses in a full spectrum of industries. The 2015 Consumer Electronics Show hosted over 900 companies exhibiting Internet-of-Things solutions, primarily in the smart home, automotive and wearable categories.

The vision of the Internet of Things broadly refers to a class of devices that ‘can monitor their environment, report their status, receive instructions and even take action based on the information they receive’, according to a definition by The McKinsey Global Institute. The promise of IoT results from the confluence of powerful technology innovations (eg, sensor networks,

The promise of IoT results from the confluence of

powerful technology innovations

Housecleaning robots are already several

generations along

Robotics emphasizes open-source software

The Robot Report tracks over 1,000 manufacturers

of robotics globally

Safety based on flexible joints





ubiquitous connectivity, cloud computing, Big Data, Internet Protocol version 6 [IPv6] and other protocols, declining chip and compute costs). Miniaturization and declining cost of sensors make it increasingly easy for devices and physical assets to be instrumented; declining cost of connectivity makes it easier to transmit data so it can be collected, analyzed and acted upon based on context and business need - in many cases automatically.

The scope of what’s referred to as the Internet of Things is extraordinarily broad, touching nearly every segment of the economy. Much of the early focus has centered on industrial uses (eg, GE’s Industrial Internet), public infrastructure (IBM’s Smarter Cities) and energy (smart grid initiatives). New services are democratizing access for individuals as well. The automotive and transportation industries are actively adopting connected applications. There is a growing range of products in self-tracking and healthcare (fitness bands and other wearables) and home automation.

Market interest around the Internet of Things is building, but the landscape is still taking shape and difficult to delineate precisely. Initial multitrillion-dollar forecasts have focused on the economic value add. Various sources are forecasting dedicated technology spend on IoT to range between US$300-500m by 2020. Investment is focused around consumer technologies (home automation and health & fitness) and converging industrial and information technologies. It’s likely that hype will outpace reality over the next 12-24 months, but over three to five years we expect meaningful traction to take hold.

Different approaches estimate IoT’s value potential in the trillions of dollars. Most current solutions target cost savings and efficiency gains. New revenue-generating and Everything-as-a-Service apps will create the greatest lasting value. Platform economics will power the long-term winners.

Estimates of aggregate impact are even larger Cisco has prominently publicized its view that there is US$14.4tn of “value at stake” globally over the next decade, driven by connecting people to people, people to machines and machines to people. Value at stake represents potential profits that can be created from improved asset utilization, employee productivity, supply chain and logistics efficiencies, improved customer experiences and innovation. GE forecasts that the Industrial Internet will add US$15tn to the world economy over the next 20 years. McKinsey Global Institute estimates that the Internet of Things has the ability to create potential annual economic impact of between US$2.7-6.2tn annually by 2025.

Forecasts anticipate exponential growth Gartner forecasts the market for Internet of Things will generate US$309bn in incremental revenue for product and service suppliers by 2020, with 26bn units of installed devices and US$1.9tn in global economic value add through sales into diverse end markets. Research firm MarketsandMarkets sizes the machine-to-machine (M2M) market at US$44bn in 2011, growing to US$290bn by 2017. Machina Research estimates “Connected Life Market revenue” will grow to US$2.5tn by 2020. The Connected Life Market includes revenue from the sales of connected devices and related services that are enabled by instrumented connectivity. The Machina forecast for M2M hardware and connectivity is an 8x increase from US$121bn in 2010 to US$948bn by 2020. ABI Research has forecast US$35bn revenue in 2016 for mobile operators, with automotive accounting for the largest sector. Yankee Group has taken a more conservative approach, forecasting connectivity revenue doubling between 2011 and 2015 to US$6.7bn.

New services are democratizing access

for individuals

We know it’s big, but it’s still early

Massive opportunity defined by new business

models

Gartner forecasts the IoT will generate US$309bn in incremental revenue

by 2020

Cisco believes there is US$14.4tn of “value

at stake”




Open-source research effort Wikibon estimates spend on the Industrial Internet to grow from roughly US$20bn in 2012 to about US$514bn in 2020. Value created is forecast to increase from US$23bn in 2012 to US$1.28tn in 2020. According to Wikibon, the cumulative net value created will be US$1.7tn by 2020.

Figure 120

Industrial Internet - Poised for an inflection

Source: Wikibon

There are also forecasts that look at the number of connections. Ericsson, the telecommunications company, has forecast 50bn connected devices by 2020 including M2M and other devices. Cisco forecasts the same number growing from 8.7bn connected objects in 2012 to 10bn in 2013, noting that every second 80 “things” are newly connected to the internet, and this is expected to reach 250 per second by 2020. Machina estimates that M2M devices will increase from 1bn in 2010 to 12bn in 2020, while Gartner’s forecast is roughly 26bn connected devices.

The pace of Internet-of-Things M&A is accelerating Google’s US$3.2bn acquisition of Nest Labs (and the subsequent US$555m acquisition of Dropcam) catalyzed awareness around the strategic importance of the connected home. PTC spent US$390m in two IoT platforms: Axeda and ThingWorx. According to M&A advisory firm Hampleton Partners, there was over US$7.5bn in total disclosed IoT transaction value from January 2012 to September 2014, with over half of the transactions occurring in the first three quarters of 2014 with a median disclosed revenue multiple of 10.5x.

Capital is readily accessible for startups By one estimate, 10% of VC investments are IoT related. There are a growing number of IoT-dedicated efforts from Intel Capital, Frost Capital, McRock, Motus and many other firms. According to CB Insights, IoT companies raised over US$1.1bn across 153 deals in 2013. Crowdfunding is also playing a key role, with IndieGoGo and Kickstarter helping startups test the market for their ideas.

Wikibon forecasts spending on the

Industrial Internet to reach US$514bn by 2020

Spend on the Industrial Internet will grow from

about US$20bn in 2012 to roughly US$514bn in 2020

Ericsson and Cisco forecast 50bn connected

devices by 2020

There was over US$7.5bn in total disclosed IoT

transaction value from Jan 12 to Sep 14

IoT companies raised over US$1.1bn across 153

deals in 2013




Spending will target applications, services and analytics Gartner forecasts over 80% of incremental spending in 2020 will target applications, services and Big Data analytics. With the deflationary dynamics in hardware and components, we see parallels to the enterprise-resource-planning (ERP) market in the late 1980s and early 1990s amplified by near-ubiquitous connectivity. For the near term, IoT relies on customized software and services. Over time, we see a surge of SaaS businesses and connected products.

Software lies at the heart of IoT solutions, with value accruing to applications, the analytics “stack” and platforms. Concerns over heterogeneous standards are overdone. As IoT-specific standards emerge, interoperability is key to success, facilitated by evolving software platforms and cheaper compute cost.

Figure 121

Multiple layers of value - Migrating upward towards data analytics

Source: Gartner

Unique requirements of IoT applications drive innovation in hardware, components, wireless networks and networking architecture. IoT-native devices will benefit from cheap open-source components, improving power management and lean communication protocols. Next-generation architectures will power IoT-designed wireless networks and “fog computing”.

Not a new idea, but getting more expansive The idea that machines can be instrumented with sensors and connected to the internet to transmit data and updates to business has been around for many years, with the term “Internet of Things” commonly used since the 1990s. There are a number of terms used to describe the ideas including machine-to-machine (M2M) communications, ubiquitous computing, embedded computing, smart services and GE’s term Industrial Internet. Cisco refers broadly to “The Internet of Everything” and Salesforce.com has adopted the term “Internet of Customers”.

Software and services are the big opportunities

The IoT spans a broad range of technologies

and use cases

Native innovations plumbing the future

While fragmented, software platforms will

knit the IoT together

The Internet of Things is about people, process,

data and things




‘Sensors and signals and connections in our lives will proliferate in ways we can’t predict, and in ways that would probably seem pointless if described to us,’ stated Benedict Evans of venture-capital firm Andreessen Horowitz.

Figure 122

Benefits accrue broadly from IoT adoption

Category Applications Benefits

Smart cities Street lights that dim when roads are empty, traffic sensors that optimize lights to traffic flow, monitoring bridges and other public infrastructure to monitor maintenance

Energy savings, lower congestion, cost savings from proactive maintenance

Healthcare Remote monitoring of patients, personal health monitoring, diagnostic and surgical procedures assisted by ingestible computing devices

Better quality care, more frequent access to professionals, better health

Automotive Accident alerts (GM OnStar), automated traffic-flow optimization, proactive maintenance alerts

Regulatory requirement

Supply chain and logistics Fleet optimization, supply-chain tracking and product tracking Cost savings, improved logistics

Intelligent buildings Automated monitoring and adjustments of HVAC based on human activity Energy cost savings

Retail/commerce Wireless payments, indoor "geo-fencing" applications, enhanced omni-channel experience

Higher sales, improved customer satisfaction and loyalty

Construction, mining and transportation

Sensors to monitor location, usage of vehicles, anticipate preventive maintenance

Better efficiency, lower repair costs, less downtime

Emergency services Faster, better coordinated disaster response Improved safety, response time

Source: CLSA

Products enable services with the Internet of Things This is perhaps the most subtle, yet most significant benefit in a world of connected “things”. Trane, the 100-year-old heating, ventilation and air conditioning (HVAC) and building systems company, is leveraging the data generated by its systems to build entirely new service revenue streams around predictive maintenance and operational visibility. The Washington Metropolitan Area Transit Authority (WMTA) recently awarded a contract to Philips to upgrade 13,000 lights in 25 of its parking garages to save energy and reduce overhead. This is a “Lighting as a Service” contract. Philips doesn’t sell the LED lamps, rather it maintains ownership of physical assets and charges for lighting services, as the assets can be maintained and serviced by a network of smart sensors. The value is not from connections and instrumentation, it’s the value of the data and the experience it creates for customers. The entire delivery model changes.

Business model shift - From buying and selling to renting While the trend of attaching maintenance and monitoring services is not new, what’s increasingly possible is the business model transition from buying and selling products to renting assets. Internet-of-Things technologies enable a new class of applications that deliver goods and services on demand to customers (mostly consumers) via the smartphone.

Uber is a prime example. Its smartphone app allows customers to order a car service while being able to see where cars are in real time on a map. The ride is paid for on the rider’s account through Uber, so no money changes hands, and both the driver and rider are rated (leveraging social technologies). In many respects, this is a simple location-aware e-commerce app; what could make this truly an IoT experience is if the car were self-driving.

The value is not from connections and

instrumentation, it’s the value of the data

Internet-of-Things technologies enable a

new class of applications




According to a recent Deloitte survey, most current IoT applications target cost savings, visibility, efficiency gains and risk reduction with only 15% focused on innovation and new business models. We believe an inflection point will follow from new services that harness incremental value from data and analytics. Importantly, the Internet of Things allows buying-and-selling businesses to transform to rental businesses, while enabling cities, homes and cars to become platforms at the center of further innovation.

A market at the early stages of exponential growth Much of the activity around Internet-of-Things startups, device adoption and value add is expected to accelerate in the 2017-20 period. Currently, there are early adopters in energy (notably lighting and smart grid), healthcare and industrial equipment, but we expect a broad range of products to be sold into different markets. In healthcare, there will be an increasing range of wearable devices, monitors, surgical tools and even ingestible devices. In physical infrastructure, we will see devices for monitoring all types of transportation (air, rail, shipping, trucks) as well as sensors on roads, bridges and in public spaces. In agriculture, there will be soil, temperature and weather sensors. Factories will increasingly deploy sensors on industrial machinery and robotics. Some of the key industries likely to see massive changes and benefits from adoption of connected devices include healthcare, manufacturing, insurance, banking, retail, computing services, government, transportation, utilities and others.

Figure 123

Internet-of-Things solutions will mature at different rates

Source: Gartner

For investors, the Internet of Things poses a bewildering array of potential winners and losers with a sprawling universe of companies exposed to different layers in the technology stack and different segments in the value chain. There is a broad range of technologies with applicability and varying stages of maturity. The Gartner Hype Cycle provides a useful framework for evaluating sentiment around various innovations, but this can be challenging to extrapolate into investment strategies. Typically, investors would want to buy technologies along the innovation trigger, short at the peak of inflated expectations and buy again at the trough of disillusionment.

New business models and innovation will provide

the catalyst

The Internet of Things poses a bewildering array

of potential winners and losers

Activity around the Internet of Things is

expected to accelerate in the 2017-20 period

Different industries will adopt IoT solutions

at different rates




Figure 124

Hype Cycle for the Internet of Things

Source: Gartner, July 2014

New horizons We look at several trends with profound long-term implications. Education plays a fundamental role in driving future innovations and prosperity and technology may help America’s students battle crushing student debt and close the achievement gap. Information technologies are increasingly focused on energy efficiency in pursuit of the “clean web.” The new space race is privately funded and very real, looking beyond the Moon towards mining asteroids and Martian colonies.

Figure 125

New horizons


MOOCs College-level online courses

Students, education startups

Traditional universities, colleges

DeVry (DV), Strayer Education (STRA), Capella (CPLA), 2U (TWOU), Apollo Education Group (APOL), Rosetta Stone (RST); private companies including Coursera, Udacity, edX

The clean web Energy conservation, smart grid, energy usage analytics

Consumers, businesses, the environment

Utilities ABB Systems (ABB), Badger Meter (BMI), IBM (IBM), CA Technologies (CA), Cisco (CSCO), GE (GE), EMC (EMC), Emerson Electric (EMR), Google (GOOG), Intel (INTC), AMD (AMD), Itron (ITRI), EnerNoc (ENOC), SilverSpring (SSNI), Opower (OPWR); private firms including Gridpoint, Tendril, many others

The new space race

Cargo, exploration, space mining

Aerospace firms, suppliers, scientific research

na Boeing (BA), Northrop Grumman (NOC), Lockheed Martin (LMT), Raytheon (RTN); private companies Virgin Galactic, Planetary Resources, SpaceX

Source: CLSA

IoT technologies are at varying stages of maturity

We explore trends with profound long-term

implications




Figure 126

New horizons - Prominent players

Company Ticker Rating Currency Last close

EPS FY14CL

EPS FY15CL

PE (x) FY14CL

PE (x) FY15CL

Market cap (US$m)

Google GOOGL US BUY USD 562.63 22.66 29.30 24.8 19.2 383,062

General Electric GE US N-R USD 25.99 1.65 1.73 15.8 15.0 261,587

IBM IBM US O-PF USD 161.94 16.54 16.00 9.8 10.1 160,065

Intel INTC US SELL USD 33.25 2.31 2.11 14.4 15.7 157,472

Cisco Systems CSCO US N-R USD 29.51 2.06 2.16 14.3 13.7 150,641

Boeing BA US N-R USD 150.85 8.60 8.52 17.5 17.7 106,257

Lockheed Martin LMT US N-R USD 200.05 11.40 11.16 17.5 17.9 63,133

EMC Corp EMC US O-PF USD 28.94 1.90 1.99 15.2 14.5 58,890

ABB ABB US N-R USD 21.39 1.13 1.25 18.9 17.1 49,933

Emerson Electric EMR US U-PF USD 57.92 3.76 3.72 15.4 15.6 39,687

Raytheon RTN US N-R USD 108.77 6.97 6.40 15.6 17.0 33,428

Northrop Grumman NOC US N-R USD 165.71 9.75 9.45 17.0 17.5 32,878

CA CA US N-R USD 32.52 3.07 2.49 10.6 13.1 14,179

Apollo Education APOL US N-R USD 27.65 2.46 1.36 11.2 20.4 3,010

Adv Micro Dev AMD US U-PF USD 3.11 (0.53) (0.15) na na 2,417

DeVry Education DV US N-R USD 36.55 2.62 2.60 14.0 14.1 2,332

Itron ITRI US N-R USD 36.48 1.60 1.74 22.8 20.9 1,396

Badger Meter BMI US N-R USD 58.40 2.06 2.50 28.3 23.3 844

Caplla Edctn CPLA US N-R USD 64.82 3.17 3.45 20.4 18.8 792

2U TWOU US N-R USD 18.48 (0.55) (0.48) na na 758

Opower OPWR US N-R USD 15.02 (0.49) (0.58) na na 749

Strayer Educ STRA US N-R USD 60.87 4.35 3.45 14.0 17.6 664

EnerNOC ENOC US N-R USD 13.49 0.42 (1.45) 32.1 na 402

Data for not-rated (N-R) companies based on consensus. Source: CLSA, Thomson Reuters

MOOCs - Disrupting the higher-education bubble? Education in the USA is a costly endeavor at every level and school reform remains a hotly debated topic. Debates over the rules of seniority at teachers’ unions and the role of charter schools are contentious at the state and local levels. Over the past 50 years, average spending per pupil has increased in adjusted dollars from US$2,808 per year in 1961-62 to US$12,608 in 2010-11.

However, the results of this higher spending do not appear by most measures to have increased the quality of results. With the cost of an in-state, public-college, four-year degree pushing US$100,000, on average, education costs are pushing students and entrepreneurs to seek alternatives. There is growing awareness that with aggregate student debt in the USA exceeding US$1.2tn, this creates an unprecedented burden on recent graduates in a difficult labor market.

The rise of MOOCs upends the economics of higher education

Education costs are pushing students and entrepreneurs to seek

alternatives




Figure 127

US college tuition versus home prices versus consumer price index

Source: Bureau of Labor Statistics for CPI US City Average, College Tuition and Fees; Federal Housing Finance Authority for Homes - All Transactions Index

It’s unquestionable that education becomes increasingly crucial given the broader shift towards a service economy, but the burden of cost has become untenable for many students with modest incomes. Ironically, college is becoming unaffordable at the time when it is needed most.

The rise of online (and often free) educational resources has potentially disruptive implications, although adoption at the college level has failed to meet initial expectations. A prominent example is Khan Academy, a free online website with thousands of videos in which Salman Khan and others discuss principles of math, science, economics and social science topics. Adoption within the K-12 segment has taken off decisively, complementing existing classroom instruction. Khan Academy is being used in over 200 countries, by 500,000 registered educators with over 4m exercise problems per day. Khan Academy’s approach is attracting mainstream partners such as NASA, Museum of Modern Art, California Academy of Sciences and MIT to offer specialized content. In July 2014, the US Department of Education launched a US$3m randomized control trial to gauge the effectiveness of Khan Academy that will focus on mathematics during the 2015-16 school year.

Massive Open Online Courses (MOOCs) on the rise Massive open online courses have been spreading since 1998 among accredited colleges. Massive refers to scale - many courses have over 100,000 students enrolled at a time. Open refers to free, with a fee required for certifications. The courses are online and often incorporate interactive capabilities and ways to network with other students. Typically, the classes involve videotaped lectures, with varying degrees of interaction with instructors and other students. There are a number of for-profit ventures including Coursera, Canvas Network, NovoEd, Udacity, Udemy and WizIQ, as well as a number of non-profit universities, edX, FutureLearn, Academic Earth, Peer to Peer University, Saylor.org, Stanford online and others.

An explosion of interest The number of MOOCs offered has increased from 1 or so a year from 2008-10 to hundreds in 2014. The surge in interest around MOOCs can be tied to Udacity, which was founded in early 2012 by Stanford University professor Sebastian Thrun, whose fall 2011 online class on artificial intelligence

0

200

400

600

800

1,000

1,200

1,400

1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 2012

Tuition

Homes

CPI

(Index 1979 = 100)

The rise of online (and often free) educational

resources has potentially disruptive implications

MOOCs have been spreading since 1998

College tuition increases have vastly outpaced home prices and CPI




attracted over 150,000 enrollees globally. Thrun left his tenured position to start up Udacity, which offered 26 courses with Computer Science (CS101) the largest to date with over 300,000 students enrolled. As of November 2013, EdX offered 94 courses from 29 institutions. Coursera is currently hosting 900 courses with over 1,000 expected on the platform in 2015 and has registered over 10m learners to its courses at the end of 2014. Apple’s iTunesU is a quiet player in online education, with over 1bn content downloads.

In fall 2014, Georgia Institute of Technology launched the first massive online open degree (MOOD), an MS in computer science for US$7,000 by partnering with Udacity and AT&T. Attendees tend to be college educated to begin with - 75% of Coursera’s 10m users have college degrees.

Figure 128

Collaboration between MOOCs and traditional education is on the rise

Source: Udacity

Sticking with courses is the challenge Despite the immense enthusiasm around MOOCs, there have been some challenges. First among them is the dropout rate, which can be extremely high for many courses. A Harvard and MIT study found that of the 841,687 people that registered for 17 MOOCs from Harvard and MIT, just 5% earned a certificate of completion, 35% never viewed any of the course materials and 54% of those who “explored” at least half of the course content earned a certificate of completion.

By nature, online courses lack the in-person interaction that’s considered essential in many disciplines such as the humanities - and successful students have tended to be self-motivated learners in more quantitative and applied fields such as engineering and computer science. Coursera found that students who paid US$30 to US$90 were substantially more likely to finish the course. According to Robert Ubell, vice dean of Online Learning at New York University’s Polytechnic School of Engineering, paid graduate programs have a 90% completion rate versus 5% or so in the case of MOOCs. A 2014 study of STEM courses published in Proceedings of the National Academy of Sciences found the fail rate for lecture-based courses was 55% higher than classes with approaches encouraging engagement.

Dropout rates can be extremely high for

many courses

Georgia Tech, Udacity and AT&T offer a US$7,000

MS in computer science

Engagement is critical for students to ensure course

completion

Udacity’s CS101 is the largest course to date

with over 300,000 students enrolled




Accreditation is another challenge, as the open approach of MOOCs often does not provide the structure of a sequenced academic program, or the compatibility with seminar-style classes and personalized feedback from instructors. There are efforts afoot to establish verification certificates for completion of specialized courses to provide a tool for employers to value online coursework.

Lastly, there is the question of economics. In a MOOC environment, there is the risk that student interest (and economics) will gravitate towards star professors as the digital curriculum scales and student choice is not constrained by the physical location of instructors. For a professor like Sebastian Thrun, the ability to reach 150,000 students globally far outscales the capabilities to reach a few hundred Stanford students, and the economic benefits of even a modest subscription could create massive winners and many losers. Conversely, the broader societal benefits of identifying talent outside of traditional channels creates new avenues for talent to get noticed; out of the 248 students who received a perfect score in Sebastian Thrun’s AI class, not one was from Stanford.

Funding streams into edtech Investors increasingly see education technology as an attractive sector. Beyond MOOCs, there has been significant investment in technology for education at the K-12 and college level. EdSurge, an education tech information site, estimates US edtech investment increased to US$1.36bn in 2014 from US$1.2bn a year earlier. According to CB Insights, global edtech investment in 2014 was US$1.87bn, up from US$1.2bn in 2013. Ambient Insight, a market research firm, estimates global edtech investment at US$2.34bn, an increase from US$1.64bn in 2013. According to Berkery Noyes, an M&A advisory firm, there were 325 education deals in 2014 with a total value of US$11.4bn, up from 298 deals representing US$9.1bn.

While there’s been a lot of media focus on MOOCs, there’s growing momentum in technologies that can enhance traditional learning processes and open up new markets for specialized continuing education. Pluralsight provides online training to technology professionals seeking to stay current with programming languages or game design tools, charging US$29 monthly subscriptions to individuals. Enterprise clients pay more and, according to the company, 2014 billings reached nearly US$100m. Remind is a messaging app that teachers use to send reminders to students and parents. Started in 2009, the service now has 23m users. With the post-secondary education technology forecast to grow from US$43bn in 2013 to US$66bn in 2019, according to Reportsnreports, there’s ample room for startups and investors to prosper. Education technology companies include DeVry (DV), Strayer Education (STRA), Capella (CPLA), 2U (TWOU), Apollo Education Group (APOL) and Rosetta Stone (RST).

Powering the future with the “clean web” Energy costs have been a hot topic in the technology industry. Despite the recent decline in the price of oil, concerns over the cost and environmental impact of electricity drive interest in measuring and optimizing energy usage for consumers, businesses and operators of power-hungry datacenters. There has been much tangible progress and growing mainstream acceptance of “green” alternatives in traditional industries (the success of electric-car company Tesla is the most visible indication). The solar industry has made

IT turns towards energy efficiency

In a MOOC environment, economics may gravitate

towards a few star professors

Investors increasingly see education technology as

an attractive sector

There’s growing momentum in

technologies that enhance traditional learning




great strides in countries like Germany and Australia, and there is growing interest in the use of technologies like blockchain for emerging networks of distributed, “artisanal” power generation.

Stanford professor Tony Seba has outlined a compelling case for the effects of Moore’s Law in the energy industry in his book, Clean Disruption of Energy and Transportation: How Silicon Valley Will Make Oil, Nuclear, Natural Gas, Coal, Electric Utilities and Conventional Cars Obsolete by 2030. In his view, the declining cost of solar panels (part science, part economies of scale) and batteries will enable electric vehicles and distributed solar-power generation (now dependent to a large extent on local subsidies) to fundamentally undercut the cost structure of fossil fuels and internal combustion engine (ICE) vehicles. There are three key areas where software plays a role and there is significant innovation momentum: technology for energy companies (smart grid, in particular); energy analytics for businesses and consumers; and energy-efficient technologies for the “green datacenter” or the “clean web”.

Energy data analytics come of age The information, communication and technology (ICT) industry consumes a lot of power. According to a study from the University of Southampton, the ICT industry contributes about 2% of global carbon dioxide emissions, the same that the aviation industry produces. Consultancy firm Ecofys estimates that the ICT industry accounts for 8-10% of the EU's electricity consumption and 2.5-4% of its carbon emissions. One of the first challenges for reducing energy consumption is understanding how much energy is consumed and what the usage patterns are. There is growing interest in data analytics for energy use.

Promising growth expected for energy management systems The opportunity for energy management technologies is large and growing. A study by MarketsandMarkets estimated that the energy management systems (EMS) market - which includes utility EMS, industrial EMS, enterprise EMS, demand response, energy management devices, home energy management systems (HEMS) and building energy management systems (BEMS) - will rise at a Cagr of 17.2% from US$17.4bn in 2013 to US$38.5bn in 2018. Navigant Research estimates that spending on industrial energy management and services including software will increase from US$11.4bn in 2013 to US$22.4bn in 2020, a Cagr of 10.3%, with BEMS reaching US$5.6bn by 2020. Pike Research estimates the smart BEMS market will reach over US$1bn by 2020, from US$291m in 2013. GTM Research forecasts the market for HEMS to grow from US$1.5bn in 2013 to over US$4bn by 2017.

Google’s Nest deal brings energy analytics into the mainstream Google’s US$3.2bn acquisition of Nest Labs has underscored the importance of energy management technologies. The Nest self-learning thermostat for homes uses artificial intelligence to “learn” the usage patterns of people living in the home as well as monitor daylight and seasonal patterns to be able to proactively adjust settings to maximize energy efficiency. Honeywell is the market leader in climate control systems, with 75% market share (compared to 12% for Nest) with growing investments and offerings in energy savings performance management for both homes and commercial buildings. Recently, air-conditioning firm Carrier Corp made an undisclosed equity investment in Ecobee, a maker of smart thermostats.

Industry firms forecast promising growth in energy management

solutions

The ICT industry contributes about 2.5-4%

of global carbon emissions

Predicting that solar and electric vehicles will

disrupt the oil and auto industries by 2030

Google’s US$3.2bn acquisition of Nest Labs is

the most high-profile deal yet





Nest - Learning thermostat PlotWatt - Energy management app

Source: Nest Labs Source: PlotWatt

Many of the large technology vendors have acquired software in the energy management space. Cisco acquired JouleX, a provider of energy measurement and analytics software, which has been rebranded as its EnergyWise software. Oracle acquired DataRaker, a provider of cloud-based analytics for utilities. IBM acquired Tririga, a BEMS company. Other companies include PlotWatt and Bidgely, which help individuals track energy costs down to the device level, and Ecofactor, which uses a cloud-based platform and open thermostat APIs to help consumers better manage their own energy consumption.

There are over 200 firms focused on energy measurement and analytics for businesses and commercial buildings, including Tendril (which recently received a US$20m investment from Sun Power), Stem, Viridity, WegoWise and Retroficiency. There are also numerous startups focusing on helping utilities crunch their data, including AutoGrid, EcoFactor, Lavastorm, eSight, Bidgely and Spec-Time Insight.

Smart grid is a Big Data problem Utilities that operate within regulatory restraints must continuously manage and monitor demand, costs of generation and acquisition of power and delivery. Smart grid solutions include demand-response systems where smart meters feed data about energy usage (ideally connected to household appliances using a ZigBee mesh network) and multidirectional power that incorporate clean power sources and allow customers with power-generation capabilities (such as solar panels or windmills) to become power providers to the grid. There is a tremendous amount of software and analytics involved in addition to upgrades of hardware and metering technology.

There is a tremendous amount of software and

analytics involved in the smart grid

Energy monitoring is a significant focus area

Cisco acquired JouleX, a provider of energy measurement and analytics software




For investors, the returns from smart-grid companies have been inconsistent, but this is not surprising given the nascent stage of the markets. Ericsson acquired bankrupt US smart-grid firm Ambient for US$7.5m in 2014. Leading smart-grid and energy-management-related public firms include Badger Meter (BMI), Digi International (DIGI), EnerNOC (ENOC), Itron (ITRI), Sinver Spring Networks (SSNI), Control4 (CTRL) and Opower (OPWR), which came public in 2014. There are other private firms including Simple Energy and GridPoint waiting in the wings. In many respects, smart-grid technologies were both immature technologies and ahead of the market. State subsidies drove investment in smart-meter implementation, but this appears to have abated, while the technology requires a significant amount of customization and services to implement.

It’s our view that the Big Data requirements of the smart grid (involving storage of massive amounts of data and sophisticated and real-time analytics) were both a financial and technological obstacle to success. With declining costs of compute, storage, availability of cloud-based solutions and emergence of open-source data management software (like Hadoop), the backdrop is more favorable for smart-grid success. AutoGrid is focusing on Big Data analytics for utility-energy management. Other vendors with smart-grid capabilities include Building IQ, Ecova, EFT Energy, EnergyCap, eSight Energy and Phoenix Energy Technologies. However, the market remains fragmented and still in the early stages. Due to the lack of standards across the industry, we believe it will take several years for packaged solutions to become commonplace given the high services component of solutions.

Striving for a greener cloud The growth of data, traffic and users connected to the internet will drive demand for datacenter capacity - and hence power consumption for years to come. Datacenter facilities are heavy consumers of energy, accounting for 1.1-1.5% of the world’s total energy use in 2010. According to the Natural Resources Defense Council, US datacenters consumed an estimated 91bn kilowatt-hours of electricity, equivalent to the annual output of 34 large (500-megawatt) coal-fired power plants in 2013. This is expected to increase to 140bn kilowatt-hours annually by 2020, the equivalent output of 50 power plants. The US Department of Energy estimates datacenter facilities consume up to 100 to 200 times more energy than standard office buildings. There is increased focus on energy efficiency within IT from providers of hardware (servers, PCs and other endpoint devices), software (to manage and optimize design, monitoring and management), while designers of datacenters need to be highly versed in managing energy requirements for equipment, heating and cooling.

Part of the issue with energy consumption lies in the inherent inefficiencies of servers and storage, which even when sitting idle draw 70% of the power usage at peak utilization. IT hardware makers are increasingly focused on energy as a component of total cost of ownership (TCO). Companies like SeaMicro (acquired by AMD) have seen strong growth from building servers out of low-powered Atom processors to manage large-scale distributed workloads. Our colleagues Srini Pajjuri and Mark Heller’s Processor Wars report references this trend.

A key measure of datacenter energy efficiency is power usage effectiveness (PUE). A PUE of 2.0 means that for every watt of IT power, an additional watt is needed to cool and distribute power to IT equipment. A PUE closer to 1.0 means nearly all of the energy is used for computing. As of 3Q14, Google claims the trailing 12-month average of all of its sites worldwide has declined

Returns from smart-grid companies have been

inconsistent

Big Data trends provide a backdrop that is favorable

for smart-grid success

Datacenter facilities consume up to 100 to 200

times more energy than standard office buildings

Google is driving new levels of power

efficiencies





to 1.12, with 1.09 the most efficient of its facilities. According to the Uptime Institute's 2014 Datacenter Survey, the average PUE of respondents' largest datacenters averaged 1.7, a decline from 1.89 in 2011.

Tech giants commit to energy-efficient innovation With the rise of “internet scale” datacenters, major vendors are committing to clean power sources and energy-efficient technologies. In February 2015, Apple’s Tim Cook announced that the company will invest US$845m in First Solar to purchase all of the power for its headquarters and stores from a massive solar farm in California over the next decade. Amazon recently updated a statement on its website touting a long-term commitment to achieve 100% renewable energy usage for its global infrastructure footprint.

Figure 131

Yahoo’s “Chicken Coop” datacenters optimize air cooling

Source: Yahoo

Other companies including Box, Facebook, Google, Rackspace and Salesforce.com have committed to 100% clean energy as well. Yahoo has developed a unique “chicken coop” design for its own datacenters. Google has been particularly focused on energy management, sharing publicly the efficiency gains in its own datacenters. Google has invested over US$1.4bn in 15 alternative-energy projects since 2010. About half of its investments are in solar. The company also invested US$350m in wind farms: two in West Texas and one in Iowa.

The new space race - Reaching “escape velocity” There is a new wave of companies and businesses pursuing opportunities in private space travel. When NASA retired the space shuttle program in 2010, this opened the door to a surge of private investment in commercial space flight. Since the last man walked on the Moon over 40 years ago, manned space flight has been confined to shuttle flights and stays on the International Space Station. There is increasing interest in space exploration from new entrants. Space programs are a matter of national pride for many emerging countries, but currently there are only 12 programs with launch capabilities and four with manned spaceflight capability (the USA, Russia, China and the EU).

Yahoo claims its datacenter design is a

tad more efficient than Google’s

To the Moon again . . . and beyond

Major tech vendors are committing to clean power

sources and energy-efficient technologies




A new wave of privately funded companies are pursuing a range of ventures including commercial space cargo flights, low-Earth-orbit space tourism and longer-term plans for manned space ventures to the Moon, Mars and asteroids.

Figure 132

Technicians attach Dragon capsule to a Falcon 9 rocket at the SpaceX facility at Cape Canaveral Air Force Station, FL, during preparations for the CRS-1 mission

Source: NASA/Kim Shiflett

Investments are pouring into space companies. According to market research firm NewSpace Global, the private space industry has increased by over six times since 2010 to over 800 countries with aggregate investment in private ventures expected to reach US$10bn by the end of 2015. For comparison, US$18bn was allocated for NASA in the 2015 federal budget.

In January 2015, SpaceX raised over US$1bn in a financial round that included Google and Fidelity. Global imaging satellite firm Planet Labs raised US$95m, bringing its total to US$160m. Google paid US$500m for Skybox Imaging, an imaging satellite company that had launched only a single small satellite. Amazon founder and CEO Jeff Bezos has invested over US$500m of his own funds into Blue Origin LLC, which he established to decrease cost of access to space and increase the safety of spaceflight. Blue Origin has to date received over US$25m from NASA to develop concepts and technology for spaceflight operations. Accion Systems raised US$2m in seed money to develop penny-size propulsion systems. Spire developed the first crowd-funded satellite and raised US$25m in 2014 to fund plans to launch 20 “cubesats”, or micro-satellites, to track shipping and weather.

Founded in 2002 by Elon Musk, SpaceX is the most prominent among the new generation of private spaceflight companies and has been able to achieve flight benchmarks at far lower costs than competitors. In September 2014, NASA announced it would pay SpaceX US$2.6bn to shuttle two astronauts to the International Space Station (ISS). Boeing is the other company awarded a contract but at far higher cost - US$4.2bn. Most recently, SpaceX has been working on a rocket-recycling effort with attempts to land its Falcon 9 rocket

Privately funded companies are pursuing a

range of space ventures

SpaceX has proven the viability of private-sector

space cargo services

SpaceX is the most prominent among the new

generation of private spaceflight companies

Aggregate investment in private space ventures to

reach US$10bn by the end of 2015




on a floating lander pad in the Atlantic Ocean. The cost of the fuel for a launch is US$200,000 but the rocket itself is US$54m. The first try was unsuccessful, but if these efforts ultimately succeed, the cost savings for launches will be significant. SpaceX has also tested the prototype of Grasshopper, a reusable rocket that would take off and land vertically.

SpaceX charges US$61.2m per launch compared to other providers that charge US$250-400m per launch. NASA currently pays Russia US$70m per astronaut for a ride on the three-person Soyuz spacecraft. Cost per kilogram to low earth orbit is also competitive - SpaceX charges US$4,653/kg versus the US$14-39,000/kg charged by the United Launch Alliance, its primary North American competitor. Currently, SpaceX has 33 commercial launches on its manifest for the next four years, a plan to launch manned missions by 2017, and subsidies from Texas to build its own spaceport to replace leased facilities.

Figure 133

The SpaceX Dragon commercial cargo craft approaches the International Space Station on 23 September 2014 for grapple and berthing

Source: NASA/Expedition 41

There are several firms focused on space tourism for wealthy customers. Richard Branson, founder and chairman of Virgin Group, is launching Virgin Galactic. The suborbital craft SpaceShip Two was designed to be launched from a mothership aircraft and fly up to 99 miles, near the boundary of space. The company is currently accepting booking for suborbital flights. Over 700 people have paid deposits for future flights with tickets that cost US$250,000. Virgin Galactic's suborbital SpaceShipTwo broke up and crashed in a test flight in October, killing one pilot and injuring another, but the company plans to continue its testing program.

Russian space tourism company KosmoKurs plans to send about 7,000 tourists to space in its first decade of operation. Even though testing is not scheduled to start until 2018 with the first tourist liftoff not until 2020 at least, tickets are being bought, with China offering the best market prospects for the space travel industry. With the falling ruble exchange rate, the company may reduce the US$200,000-250,000 price for tickets to outer space.

There are several firms focused on space tourism

for wealthy customers

SpaceX currently has over 50 contracted launches

SpaceX charges US$61.2m per launch vs

other providers that charge US$250-400m

KosmoKurs plans to send about 7,000 tourists to

space in its first decade




Russia’s Soyuz has been ferrying customers 230 miles up to the International Space Station for roughly US$50m per trip. Microsoft co-founder Paul Allen announced the formation of Stratolaunch Systems, an air-launch-to-orbit system that involves the development of an airplane with the world’s largest wingspan. The Spaceship Company is an aerospace joint venture between Virgin Galactic and Scaled Composites that plans to build the world’s first fleet of commercial suborbital spaceships and carrier aircraft.

Asteroids represent an attractive target for space entrepreneurs. According to Planetary Resources, there are over 1,500 asteroids as easy to reach as the surface of the Moon, in Earth-like orbits with small gravity fields. There are significant resources of water as well as valuable and useful materials like iron, nickel, water and rare platinum group metals. NASA has awarded contracts to two private companies to explore the possibility of mining near-Earth asteroids: Planetary Resources and Deep Space Industries.

Figure 134

ARKYD 100 - Space telescope

Source: Planetary Resources

The goal of Planetary Resources is to first access water, then mine rare metals. According to the company, in space, a platinum-rich 500-meter-wide asteroid contains about 174x the yearly global output of platinum and 1.5x the known world reserves of rare metals such as ruthenium, rhodium, palladium, osmium, iridium and platinum. Planetary Resources will launch two test satellites, Arkyd 3 and Arkyd 6, equipped with mid-sized telescopes for identifying near-Earth asteroids for the potential to conduct future robotic mining operations. Deep Space Industries plans to mine asteroids for usable materials and manufacturing on site. The company plans to send a fleet of its low-cost, 55lb “FireFly” spacecraft on exploratory missions targeted to begin in 2015. The 70lb DragonFlies are targeted for round trips to bring back samples starting in 2016.

NASA’s “Inspiration Mars” mission wants to send one man and one woman within 100 miles around Mars, leaving 5 January 2018 because of a special alignment between the two planets to shorten the free return trip to 501 days. The initiative is trying to raise money through a private foundation spearheaded by space tourist Dennis Tito.

NASA has awarded contracts to two private

companies to explore asteroid mining

The goal of Planetary Resources is to first

access water then mine rare metals

The new generation of technologies uses open-

source software and commodity components

“Inspiration Mars” wants to send one man and one woman within 100 miles

around Mars




A one-way ticket to Mars? Mars One is a Dutch company that looks to land humans on Mars in 2023 as the beginning of a permanent colony. The company has received its first funding from sponsors, hoping to fund its activities via a global reality-TV event that will follow the mission from selection of astronauts through first years on Mars. The company took 200,000 applications from would-be astronauts interested in a one-way trip to Mars.

Mars One in 2013 announced that Lockheed Martin is working on a mission concept study for a 2018 Mars lander and aerospace firm SSTL is working on a mission concept study for a Mars orbiter that would act as a relay station between Earth and the lander. Mars One has launched a US$400,000 Indiegogo crowdfunding campaign to fund the studies. It has selected a second-round pool of astronaut candidates of 705 people from some 200,000 who showed initial interest on its website. Mars One seeks financial investment through a bidding process to send company experiments to Mars. The experiment slots will go to the highest bidder.

Mars One aims to launch supplies in 2016 and

prepare supply and habitat units in 2021

Lockheed Martin is working on a mission

concept study for a 2018 Mars lander


Important disclosures Innovation


Companies mentioned 2U (N-R) 3D Systems (N-R) ABB Systems (N-R) Academic Earth (N-R) Accenture (ACN US - US$90.03 - OUTPERFORM)¹ Access Industries (N-R) Accion Systems (N-R) Accuray (N-R) Acquia (N-R) ActiveLink (N-R) Acxiom (N-R) Adept Technology Bosc (N-R) Adidas (N-R) Adobe Systems (N-R) Advanced Nanotech (N-R) AeroVironment (N-R) Agelist (N-R) Agilent (N-R) AirBnB (N-R) Akamai (AKAM US - US$69.51 - BUY)¹ AliveCOr (N-R) Altair Nanomaterials (N-R) Amazon (AMZN US - US$380.16 - OUTPERFORM)¹ Ambarella (N-R) AMD (AMD US - US$2.67 - UNDERPERFORM)¹ American Pharmaceutical Partners (N-R) American Superconductor (N-R) Anki (N-R) Apollo Education Group (N-R) Apple (AAPL US - US$128.46 - BUY)¹ Applied Micro (N-R) Arcam (N-R) Arrowhead Research (N-R) AT&T (N-R) Audi (N-R) Autodesk Inc (N-R) AutoGrid (N-R) Avago (AVGO US - US$127.62 - OUTPERFORM)¹ Avis Zipcar (N-R) Badger Meter (N-R) Bae Systems (N-R) Baidu (BIDU US - US$203.75 - BUY)² Barnes & Noble (N-R) Barracuda Networks (N-R) BASF (N-R) Basis (N-R) Baxter (N-R) Bayer MaterialSciences (N-R) Berkeley Bionics (N-R) Berkery Noyes (N-R) BGI Shenzhen (N-R) Bidgely (N-R) Big Switch (N-R) Bio-Rad Lab (N-R)

BitPay (N-R) Bits From Bytes (N-R) Black Duck Software (N-R) Blackrock Microsystems (N-R) Bloomberg (N-R) BlueStar (N-R) BMW (N-R) Boeing (N-R) Bolt.io (N-R) Boston Dynamics (N-R) Box (N-R) BP (N-R) Broadcom (BRCM US - US$45.23 - BUY)¹ Building IQ (N-R) CA (N-R) Calxeda (N-R) Canvas Network (N-R) Capella (N-R) Carrier Corp. (N-R) Castrol (N-R) Check Point (N-R) Chegg (N-R) Chrysler (N-R) Cisco (N-R) Citizen Space (N-R) Cloudera (N-R) Coca-Cola (KO US - US$43.30 - UNDERPERFORM)¹ Cognex (CGNX US - US$44.69 - BUY)¹ Cognizant Tech (CTSH US - US$62.48 - OUTPERFORM)¹ Coinbase (N-R) CoinDesk (N-R) Concur (N-R) Control4 (N-R) Cookisto (N-R) Coursera (N-R) CSC (N-R) Cumulus Networks (N-R) CyberArk (N-R) Cyberdyne (N-R) Danaher (N-R) Deep Space Industries (N-R) Dell (N-R) Delphi (DLPH US - US$78.84 - OUTPERFORM)¹ Delta (2308 TT - NT$208.0 - BUY)³ Devry (N-R) Digi International (N-R) Dish Network (N-R) DJI Innovations (N-R) Domino's Pizza (N-R) Dropbox (N-R) Dun & Bradstreet (N-R) D-Wave Systems (N-R) eBay (EBAY US - US$57.91 - UNDERPERFORM)¹ Ecobee (N-R)




Ecofactor (N-R) Ecova (N-R) edX (N-R) EFT Energy (N-R) Ekso Bionics (N-R) Elance (N-R) Elemoon (N-R) EMC (EMC US - US$28.94 - OUTPERFORM)¹ Emerson (EMR US - US$57.92 - UNDERPERFORM)¹ Emotiv (N-R) EnergyCap (N-R) EnerNoc (N-R) Entrust (N-R) envisionTEC (N-R) EOS (N-R) Ericsson LM (N-R) eSight Energy (N-R) Eve Biomedical (N-R) ExOne (N-R) Expedia Inc (N-R) Experian (N-R) Facebook (FB US - US$78.97 - BUY)¹ Fanuc (6954 JP - ¥22,860 - BUY)² FEI Company (N-R) Fellow Robots (N-R) FICO (N-R) Fidelity National Fin (N-R) FireEye (N-R) Fitbark (N-R) Fitbit (N-R) FNJN (N-R) Fon (N-R) Ford Motor (F US - US$16.34 - OUTPERFORM)¹ FormLabs (N-R) Fortinet (N-R) Foundation Medicine (N-R) Foxconn Tech (N-R) Frost Capital (N-R) FutureLearn (N-R) Garmin (N-R) Genentech (N-R) General Dynamics Corp (N-R) General Electric (N-R) General Motors (GM US - US$37.31 - OUTPERFORM)¹ Genesis Angels (N-R) GenomeNext (N-R) Genomic Health (N-R) Getaround (N-R) Google (GOOGL US - US$558.40 - BUY)¹ GoPro (N-R) GridPoint (N-R) Groupon (N-R) GrubHub (N-R) GUID (N-R) Hampleton Partners (N-R)

Harris & Harris Group (N-R) Hewlett-Packard (HPQ US - US$34.84 - UNDERPERFORM)¹ HomeAway (N-R) Homexchange (N-R) Hon Hai (2317 TT - NT$87.1 - UNDERPERFORM)² Honeywell Intl (N-R) Hortonworks (N-R) Houzz (N-R) Huawei (N-R) Hub Culture (N-R) Hyve Solutions (N-R) IBM (IBM US - US$161.94 - OUTPERFORM)¹ Illumina (N-R) Imperva (N-R) Imprivata (N-R) Index Ventures (N-R) IndieGoGo (N-R) Industrial Perception (N-R) Infineon (N-R) Informatica (INFA US - US$42.95 - BUY)¹ Intel (INTC US - US$33.25 - SELL)¹ Intuit (N-R) Intuitive Surgical (N-R) InvenSense (N-R) iRobot (N-R) iTron (N-R) IXYS Corp (N-R) Jaspersoft (N-R) Jawbone (N-R) Jibo (N-R) Kickstarter (N-R) Kinea design (N-R) Kiva Systems (N-R) Kodak (N-R) KUKA (N-R) Lavastorm (N-R) Leapfrog (N-R) Lendingclub (N-R) Lenovo (992 HK - HK$12.10 - UNDERPERFORM)² LG Electronics (066570 KS - 60,500 WON - BUY)² Life Technologies (N-R) LinkedIn (LNKD US - US$267.20 - BUY)¹ Liquid Image (N-R) Local Motors (N-R) Lockheed Martin Corp (N-R) LogRhythm (N-R) LSI (N-R) Lucent (N-R) Lulzbot (N-R) Lumera Corp (N-R) Lyft (N-R) Mail.ru (N-R) MakerBot (N-R) Mars One (N-R) Mazor Robotics (N-R)




McRock (N-R) Meka Redwood Robotics (N-R) Mellanox (N-R) Mercedes-Benz (N-R) Microsoft (MSFT US - US$43.85 - OUTPERFORM)¹ Mitsui (8031 JP - ¥1,672 - OUTPERFORM)² MobileIron (N-R) Moog (N-R) Motorola Solutions (MSI US - US$67.94 - UNDERPERFORM)¹ Motus (N-R) Nancomp (N-R) Nancyl (N-R) Nangen (N-R) Nanometrics (N-R) Nanophase Technologies (N-R) Nanotero (N-R) National Instruments (N-R) Natural nano (N-R) Neato (N-R) Netflix (N-R) Netsuit (N-R) New Matter (N-R) NICE Systems (N-R) Nike (N-R) Nintendo (7974 JP - ¥12,975 - SELL)² Nissan Motor (7201 JP - ¥1,252 - BUY)² Nizie (N-R) Nokia (N-R) Northrop Grumman (N-R) NovoEd (N-R) NQ Mobile (N-R) Nuance (N-R) Nutanix (N-R) NVE (N-R) Nvidia (NVDA US - US$22.06 - UNDERPERFORM)¹ Oakley (N-R) Odesk (N-R) Opwer (N-R) Oracle (ORCL US - US$43.82 - UNDERPERFORM)¹ Organovo (N-R) Overstock.com (N-R) Oxo (N-R) Palantir Technologies (N-R) Palo Alto (N-R) Panasonic (6752 JP - ¥1,518 - BUY)² Pandora (N-R) ParkatmyHouse (N-R) Parrot (N-R) Pebble (N-R) Peer to Peer University (N-R) Pentaho (N-R) PerkinElmer (N-R) Pfizer (N-R) Philips (N-R) Phoenix Energy Technologies (N-R)

Ping (N-R) Pinterest (N-R) Planet Labs (N-R) Planetary Resources (N-R) PlotWatt (N-R) Polar (N-R) Proofpoint (N-R) Proto Labs (N-R) PTC (N-R) Pure Storage (N-R) Qihoo 360 (QIHU US - US$45.73 - BUY)² QlikTech (QLIK US - US$32.44 - BUY)¹ Qualcomm (QCOM US - US$72.51 - OUTPERFORM)¹ Qualys (N-R) Quare (N-R) Quario (N-R) Quirky (N-R) Rackspace (RAX US - US$49.67 - BUY)¹ Radio Shack (N-R) Rapid7 (N-R) Raser (N-R) Raytheon Co (N-R) ReadSpeaker (N-R) Red Hat (RHT US - US$69.12 - BUY)¹ RedBox (N-R) RelayRides (N-R) Renishaw (N-R) Restoration Robotics (N-R) Rethink Robotics (N-R) Retroficiency (N-R) Rex Bionics (N-R) Ringly (N-R) Rio Tinto (RIO AU - A$65.60 - OUTPERFORM)² RiskMetrics (N-R) Roche (N-R) Roche Pharmaceuticals (N-R) Rockwell (ROK US - US$117.04 - OUTPERFORM)¹ Roomba (N-R) Roomorama (N-R) Rosetta Stone (N-R) RSA (N-R) RSL Steeper (N-R) Safeguard Scientifics (N-R) SAIC (N-R) SailPoint (N-R) Salesforce.com (CRM US - US$69.38 - BUY)¹ Samsung Elect (005930 KS - 1,379,000 WON - OUTPERFORM)² SAP (N-R) SAS (N-R) Saylor.org (N-R) Scaled Composites (N-R) Schaft (N-R) Sculpteo (N-R) Second Sight Medical Products (N-R) Sentience Technologies (N-R)




ServiceNow (N-R) Siemens (N-R) Sigma Aldrich (N-R) Silicon Micro Display (N-R) Silver Spring Network (N-R) Skyworks Solutions (N-R) SnapChat (N-R) SnapGoods (N-R) Solidoodle (N-R) Sony (6758 JP - ¥3,346 - BUY)² SpaceX (N-R) Spec-Time Insight (N-R) Spire (N-R) Splunk (SPLK US - US$67.25 - BUY)¹ Spotify (N-R) SSTL (N-R) Stanford Online (N-R) Staples (N-R) Stem (N-R) STMicro (N-R) Stratasys (N-R) Strayer Education (N-R) SugarCRM (N-R) Sun Power (N-R) Surrey Nanosystems (N-R) Suunto (N-R) Symantec (N-R) Tableau Software (N-R) Target (N-R) TaskRabbit (N-R) Tata Comm (TCOM IN - RS422.1 - BUY)² Techne (N-R) Teledyne (N-R) Tendril (N-R) Teradata (TDC US - US$44.52 - BUY)¹ Tesla (TSLA US - US$203.34 - OUTPERFORM)¹ Texas Instruments (TXN US - US$58.80 - UNDERPERFORM)¹ Textron (N-R) The Sacramento Kings (N-R) The Spaceship Company (N-R) Thermo Fisher (N-R) Thomas Swan (N-R) TigerDirect (N-R) Time Inc (N-R) Toyota Motor (7203 JP - ¥8,125 - OUTPERFORM)² Trane (N-R)

Trend Micro (4704 JP - ¥4,035 - OUTPERFORM)¹ Twitter (N-R) Uber (N-R) Udacity (N-R) Udemy (N-R) Ultimate Software (N-R) UltraTech (UTCEM IS - RS3,369.8 - BUY)² Under Armour (N-R) Unidym (N-R) United Launch Alliance (N-R) Universal Robots (N-R) UPS (N-R) Varonis Systems (N-R) Veeco (VECO US - US$30.49 - BUY)¹ Veeva (N-R) Venafi (N-R) Veracode (N-R) VeriSign (N-R) Verisk (N-R) Vicarious (N-R) Virgin Galactic (N-R) Virgin Group (N-R) Viridity (N-R) VMware (VMW US - US$85.07 - OUTPERFORM)¹ VOLKSWAGEN VORZUG (N-R) Volvo (N-R) VoxelJet (N-R) Vuzix (N-R) Waters (N-R) Webroot (N-R) WegoWise (N-R) WizIQ (N-R) Workday (N-R) XenSource (N-R) Yahoo! (YHOO US - US$44.28 - OUTPERFORM)¹ Yandex (N-R) Yaskawa Motoman (N-R) Yelp (N-R) Zaarly (N-R) ZANO (N-R) Zilok.com (N-R) Zoox (N-R) ZSaler (N-R) ZTE (N-R) Zynga (ZNGA US - US$2.30 - UNDERPERFORM)¹

¹ Covered by CLSA Americas; ² Covered by CLSA; ³ Covered by CAST




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The analysts included herein hereby certify that the views expressed in this research report accurately reflect their own personal views about the securities and/or the issuers and that unless disclosed otherwise, no part of their compensation was, is, or will be directly or indirectly related to the specific recommendation or views contained in this research report or revenue from investment banking services provided. The analyst/s also states/s and confirm/s that he has/have not been placed under any undue influence, intervention or pressure by any person/s in compiling this research report. In addition, the analysts included herein attest that they were not in possession of any material, non-public information regarding the subject company at the time of publication of the report. Save from the disclosure below (if any), the analyst(s) is/are not aware of any material conflict of interest.

Key to CLSA/CLSA Americas/CA Taiwan investment rankings: BUY: Total stock return (including dividends) expected to exceed 20%; O-PF: Total expected return below 20% but exceeding market return; U-PF: Total expected return positive but below market return; SELL: Total expected return to be negative. For relative performance, we benchmark the 12-month total forecast return (including dividends) for the stock against the 12-month forecast return (including dividends) for the market on which the stock trades. For example, in the case of US stock, the recommendation is relative to the expected return for S&P of 10%. Exceptions may be made depending upon prevailing market conditions. We define as “Double Baggers” stocks we expect to yield 100% or more (including dividends) within three years. "High Conviction" Ideas are not necessarily stocks with the most upside/downside but those where the Research Head/Strategist believes there is the highest likelihood of positive/negative returns. The list for each market is monitored weekly.

Overall rating distribution for CLSA/CLSA Americas/CA Taiwan Universe: Buy / Outperform - CLSA: 63%; CLSA Americas: 63%; CA Taiwan: 68%, Underperform / Sell - CLSA: 37%; CLSA Americas: 37%; CA Taiwan: 32%, Restricted - CLSA: 0%; CLSA Americas: 0%; CA Taiwan: 0%. Data as of 31 December 2014. Investment banking clients as a % of rating category: Buy / Outperform - CLSA: 2.6%; CLSA Americas: 0%; CA Taiwan: 0%, Underperform / Sell - CLSA: 1.6%; CLSA Americas: 0%; CA Taiwan: 0%, Restricted - CLSA: 0%; CLSA Americas: 0%; CA Taiwan: 0%. Data for 12-month period ending 31 December 2014. For a history of the recommendations and price targets for companies mentioned in this report, as well as company specific disclosures, please write to: (a) CLSA Americas, Compliance Department, 1301 Avenue of the Americas, 15th Floor, New York, New York 10019-6022; (b) CLSA, Group Compliance, 18/F, One Pacific Place, 88 Queensway, Hong Kong and/or; (c) CA Taiwan Compliance (27/F, 95, Section 2 Dun Hua South Road, Taipei 10682, Taiwan, telephone (886) 2 2326 8188).

© 2015 CLSA Limited, CLSA Americas, LLC (“CLSA Americas”) and/or Credit Agricole Securities Taiwan Co., Ltd. (“CA Taiwan”)




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This publication/communication is distributed for and on behalf of CLSA Limited (for research compiled by non-US and non-Taiwan analyst(s)), CLSA Americas (for research compiled by US analyst(s)) and/or CA Taiwan (for research compiled by Taiwan analyst(s)) in Australia by CLSA Australia Pty Ltd; in Hong Kong by CLSA Limited; in India by CLSA India Private Limited (formerly CLSA India Limited) (Address: 8/F, Dalamal House, Nariman Point, Mumbai 400021. Tel No: +91-22-66505050. Fax No: +91-22-22840271; CIN: U67120MH1994PLC083118; SEBI




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United States of America: Where any section of the research is compiled by US analyst(s), it is distributed by CLSA Americas. Where any section is compiled by non-US analyst(s), it is distributed into the United States by CLSA solely to persons who qualify as "Major US Institutional Investors" as defined in Rule 15a-6 under the Securities and Exchange Act of 1934 and who deal with CLSA Americas. However, the delivery of this research report to any person in the United States shall not be deemed a recommendation to effect any transactions in the securities discussed herein or an endorsement of any opinion expressed herein. Any recipient of this research in the United States wishing to effect a transaction in any security mentioned herein should do so by contacting CLSA Americas.

Canada: The delivery of this research report to any person in Canada shall not be deemed a recommendation to effect any transactions in the securities discussed herein or an endorsement of any opinion expressed herein. Any recipient of this research in Canada wishing to effect a transaction in any security mentioned herein should do so by contacting CLSA Americas.

United Kingdom: In the United Kingdom, this research is a marketing communication. It has not been prepared in accordance with the legal requirements designed to promote the independence of investment research, and is not subject to any prohibition on dealing ahead of the dissemination of investment research. The research is disseminated in the EU by CLSA (UK), which is authorised and regulated by the Financial Conduct Authority. This document is directed at persons having professional experience in matters relating to investments as defined in Article 19 of the FSMA 2000 (Financial Promotion) Order 2005. Any investment activity to which it relates is only available to such persons. If you do not have professional experience in matters relating to investments you should not rely on this document. Where the research material is compiled by the UK analyst(s), it is produced and disseminated by CLSA (UK). For the purposes of the Financial Conduct Rules this research is prepared and intended as substantive research material.

Singapore: This publication/communication is distributed for and on behalf of CLSA Limited (for research compiled by non-US and non-Taiwan analyst(s)), CLSA Americas (for research compiled by US analyst(s) and/or CA Taiwan (for research compiled by Taiwan analyst(s)) in Singapore through CLSA Singapore Pte Ltd solely to persons who qualify as Institutional, Accredited and Expert Investors only, as defined in s.4A(1) of the Securities and Futures Act. Pursuant to Paragraphs 33, 34, 35 and 36 of the Financial Advisers (Amendment) Regulations 2005 with regards to an Accredited Investor, Expert Investor or Overseas Investor, sections 25, 27 and 36 of the Financial Adviser Act shall not apply to CLSA Singapore Pte Ltd. Please contact CLSA Singapore Pte Ltd in connection with queries on the report. MCI (P) 094-11-2014

The analysts/contributors to this publication/communication may be employed by a Credit Agricole, CLSA or CITIC Securities company which is different from the entity that distributes the publication/communication in the respective jurisdictions.

MSCI-sourced information is the exclusive property of Morgan Stanley Capital International Inc (MSCI). Without prior written permission of MSCI, this information and any other MSCI intellectual property may not be reproduced, redisseminated or used to create any financial products, including any indices. This information is provided on an "as is" basis. The user assumes the entire risk of any use made of this information. MSCI, its affiliates and any third party involved in, or related to, computing or compiling the information hereby expressly disclaim all warranties of originality, accuracy, completeness, merchantability or fitness for a particular purpose with respect to any of this information. Without limiting any of the foregoing, in no event shall MSCI, any of its affiliates or any third party involved in, or related to, computing or compiling the information have any liability for any damages of any kind. MSCI, Morgan Stanley Capital International and the MSCI indexes are service marks of MSCI and its affiliates. The Global Industry Classification Standard (GICS) was developed by and is the exclusive property of MSCI and Standard & Poor's. GICS is a service mark of MSCI and S&P and has been licensed for use by CLSA.

EVA® is a registered trademark of Stern, Stewart & Co. "CL" in charts and tables stands for CLSA/CLSA Americas/CA Taiwan estimates unless otherwise noted in the source.


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©2015 CLSA Limited (for research compiled by non-Taiwan analyst(s)) and/or Credit Agricole Securities Taiwan Co., Ltd (for research compiled by Taiwan analyst(s)). Key to CLSA/CLSA Americas/CA Taiwan investment rankings: BUY: Total stock return (including dividends) expected to exceed 20%; O-PF: Total expected return below 20% but exceeding market return; U-PF: Total expected return positive but below market return; SELL: Total expected return to be negative. For relative performance, we benchmark the 12-month total forecast return (including dividends) for the stock against the 12-month forecast return (including dividends) for the market on which the stock trades. For example, in the case of US stock, the recommendation is relative to the expected return for S&P of 10%. Exceptions may be made depending upon prevailing market conditions. • We define as “Double Baggers” stocks we expect to yield 100% or more (including dividends) within three years. "High Conviction" Ideas are not necessarily stocks with the most upside/downside but those where the Research Head/Strategist believes there is the highest likelihood of positive/negative returns. The list for each market is monitored weekly. 12/01/2015

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