moore's law doesn't matter anymore

A/Prof Jeffrey FunkDivision of Engineering and Technology Management

National University of Singapore

For information on other technologies, see http://www.slideshare.net/Funk98/presentations

Implications for Smart Phones, Big Data and Software.

What is the future of work?

Improvements in microprocessors (Moore’s Law) are probably slowing

But not improvements in other components, partly because they lag microprocessors• Graphic processors and 3D camera chips

• Wireless chips and Data Centers

What does this mean for future of Information Technology….. and Businesses?• Smart phone becomes dominant device

• Internet of Things provides new data

• Most IT processing (i.e., big data) and storage moves to cloud

More types of data will be collected and analyzed

New sources of data• “Things,” thus Internet of Things in Session 5

• Bio-sensors for health care data in Session 6

New forms of smart phones and wearable computing can manage data• Better touch displays, voice recognition, Session 7

• Virtual and augmented reality, wearable, Session 8

What opportunities will be created? • What types of data will become important to your

business?

Session Technology

1 Objectives and overview of course

2 How/when do new technologies become economically feasible?

3 Two types of improvements: 1) Creating materials that better

exploit physical phenomena; 2) Geometrical scaling

4 Semiconductors, ICs, electronic systems

5 Sensors, MEMS and the Internet of Things

6 Bio-electronics, Health Care, DNA Sequencers

7 Displays, including touch displays

8 Voice and gesture interfaces, AR, VR, wearables, neural

9 Information Technology and Land Transportation

10 Smart Cities: lighting, food, water, 3D printing

This is Fourth Session of MT5009

What do numbers say about Moore’s Law?• Microprocessors and Flash memory

• Graphic processors and 3D camera chips

• Wireless chips, Data Centers

What does this mean for: • Smart phones?

• Software and Big Data?

Alternatives to Silicon and von Neumann• Organic transistors

• Carbon nanotubes, Graphene

• Atomic transistors

• Synapse, AHaH

• Quantum computers

Is Moore’s Law Ending?

Economist, March 12-18, 2016

People Have Been Talking About These Problems for

Many Years; Is this a Real End for Moore’s Law?

Becoming increasingly expensive

Without further reductions, hard to • increase the number of transistors per chip

• reduce cost per transistor

Main problem is photolithography• See below

If photolithography and other problems

can’t be solved, • New solutions are needed (see below)

Source: Chuck Moore, Data Processing in Exascale-Class Systems, April 27, 2011. Salishan Conference on High Speed Computing

Power and Heat Problems Led to Multiple Cores and

Prevent Further Improvements in Speed

Can the number continue to be increased?

Many say NO

Hard to break up problems into still

smaller ones for general purpose

processors

Additional problem is whether costs have

stopped falling• Related to problems with reducing feature sizes

and increasing number of cores?

http://www.economist.com/blogs/economist-explains/2015/04/economist-explains-17

Intel Says Differently

(1 Feb 2016)

Intel reiterated its claim it

has reduced cost per

transistor at its 22 and

14nm nodes at a rate

slightly better than the

industry’s 30% historical

trend. That’s despite the

fact the cost of developing

each new process has

risen to 30% in the last

few nodes up from a

historical trend of 10%.

http://www.eetimes.com/document.asp?doc

_id=1328835

If Costs are no Longer Falling,

There is Big Problem

Intel Says Costs Continue to Fall

http://www.alixpartners.com/en/Publications/AllArticles/tabid/635/articleType/ArticleView/articleId/941/Cashing-in-with-Chips.aspx#sthash.QDcy503U.dpbs

Some Costs Rise as Feature Sizes Become Smaller

http://www.chipdesignmag.com/bursky/

Cost of Photolithography (Litho) is Rising

Faster than other Process Equipment

Photolithography Used to Form Patterns in Layers

Width of this “line”

is one type of

feature size.

Another is thickness

Note: Masks are made with

Electron Beam,

which is even more

expensive

Bottleneck in photolithographic process is wavelength of light.

Feature sizes are now smaller than wavelength of visible light

Source: http://www.soccentral.com

/results.asp?CatID=488&EntryID=30894

http://www.soccentral.com/

Must compensate with strong optical

lenses and error correction software

Basically putting a supercomputer in a

photolithographic equipment

This is one reason for rising cost of

fabrication facilities

Light is emitted

by a plasma

Need

1) Vacuum since

air absorbs

small wave-

length light

2) stronger light

source to

speed up

processing

Raises costs

Need fast

processing to

justify high costs

Recent Development of

Extreme Ultraviolet

Latest

EUV

lithography

system

achieves

28 wafers

per hour

but needs 200

wafers per hour

to be

economical

Intel says it

will use

EUV for

7nm

Source:

http://nextbigfuture.com

/2014/06/extreme-

ultraviolet-lithography

-hopes.html#more









• Synapse, AHaH


http://ieeexplore.ieee.org/ieee_pilot/articles/96jproc11/jproc-MSanvido-2004319/article.html

Memory Also Depends on Smaller Feature SizesAnd thus Faces Same Problems as Microprocessors do

nm

http://www.theregister.co.uk/2012/10/12/nand_shrink_trap/

Additional Problem for Flash Memory:Number of electrons available to hold the

binary data in each cell decreases

It can be cheaper to add more layers than to reduce feature sizes

This is particularly true for memory chips, which are architecturally simple

Samsung is moving the fastest in memory

Other firms and chips are expected to follow

Continued Increases in

Flash Memory Size

Continued Reductions

in Flash Memory Cost

Reductions in Feature Size Continue to Proceed Over time

TSV: through silicon via

TSV: Through Silicon Via

Can Combine Different Types of

Designs on a Single 3D Chip

In addition to problem of electron numbers,

Flash Memory has Slow Read Write Speeds

http://isscc.org/doc/2013/2016_Trends.pdf

(Non-

Volatile

http://isscc.org/doc/2014/2016_Trends.pdf

But Flash Continues to Win

New form of non-volatile memory 1,000 times faster than NAND flash

memory 10 times more data stored than in DRAM Unique way to store data, using vertical

columns of circuitry linked by crisscross grid of microscopic wires

Companies will initially offer two-layer chips that have 128 Gb, matching some NAND chips

http://www.micron.com/about/innovations/3d-xpoint-technology

They can replace flash memory, SRAM, and

DRAM and thus enable new and better

architectures

Most electronic products use all three• SRAM (fastest and most expensive volatile memory) and

DRAM (slower and cheaper) store data for

microprocessors

• Flash memory: non-volatile memory

Combining them on single chip

• can reduce overall access and processing times

• can eliminate bottleneck that currently exists between

memory and processor chips (see below)

What do numbers say about Moore’s Law?• Microprocessors and flash Memory



What does this mean for: • Smart phones and Biometrics?

• Big Data, Internet of Things?




• Synapse, AHaH


May 7, 2016

http://www.wsj.com/articles/nvidia-pushes-chip-speed-higher-price-lower-1462594938

Launch Year 2010 (GTX 580)2014 (GTX Titan

Black)2016 (GTX Titan X) Pascal 2017

GPU Process 40nm 28nm 28nm16nm (TSMC

FinFET)

Flagship Chip GF110 GK210 GM200 GP100

GPU DesignSM (Streaming

Multiprocessor)

SMX (Streaming

Multiprocessor)

SMM (Streaming

Multiprocessor

Maxwell)

SMP (Streaming

Multiprocessor

Pascal)

Maximum

Transistors3.00 Billion 7.08 Billion 8.00 Billion 15.3 Billion

Maximum Die Size 520mm2 561mm2 601mm2 610mm2

Stream Processors

Per Compute Unit32 SPs 192 SPs 128 SPs 64 SPs

Maximum CUDA

Cores512 CCs (16 CUs) 2880 CCs (15 CUs) 3072 CCs (24 CUs) 3840 CCs (60 CUs)

FP32 Compute1.33

TFLOPs(Tesla)

5.10 TFLOPs

(Tesla)

6.10 TFLOPs

(Tesla)

~12 TFLOPs

(Tesla)

FP64 Compute0.66 TFLOPs

(Tesla)

1.43 TFLOPs

(Tesla)

0.20 TFLOPs

(Tesla)5.5 TFLOPs(Tesla)

Maximum VRAM 1.5 GB GDDR5 6 GB GDDR5 12 GB GDDR5 16 / 32 GB HBM2

Maximum

Bandwidth192 GB/s 336 GB/s 336 GB/s 1 TB/s

Maximum TDP 244W 250W 250W 300W

Feature sizes lag those on micro-processors by about 5 years

Easier to break down graphics processing into smaller problems and thus use multiple cores• >3,500 cores on GPU

• About 20 on general purpose microprocessor

Future of GPUs is machine learning Nvidia, AMD, and new entrants are pursuing

this market• New entrants such as Movidius and Nervana offer

special-purpose processors for machine learning

Use GPUs to

• analyze medical images, spot anomalies on CT scans

• study photos, audio files social media posts

Blue River Technology, Nervana customer

• analyzes crop and weed photos to determine where to

spray (5,000 decisions a minute)

Market growth between 2015 and 2024

• For GPUs: from $43.6 million to $4.1 billion

• Software spending by enterprises: from $109 million to

$10.4 billionhttp://www.wsj.com/articles/new-chips-propel-machine-learning-1463957238









• Synapse, AHaH


Pix

el S

ize (

µm

2)

Resolution of Camera Chips

Continues to Increase, Far from Limits

International Solid State Circuit State Conference, Technology Trends, 2016 http://www.future-fab.com/documents.asp?d_ID=4926

Microprocessor

feature

sizes are less than

20 nm

Cost of 3D sensors falling quickly

Intel’s Real Sense in more than 25 models of

laptops and will be in Android phones by 2017

RealSense gives 3D vision via a four-

millimeter-thick strip that includes two

cameras and one processor

• By comparison, Kinect required a foot-long box that

relied on Xbox’s processors

Other sources claim that cost of 3D vision has

dropped from $200 to $20http://www.wsj.com/articles/more-devices-gain-3-d-vision-1444859629

Intel released

• F200 in 2015

• SR300 in 2016

Both create high quality 3D depth video stream

SR300 adds IR laser projector, fast VGA, shorter

exposure time, dynamic motion up to 2m/second

Applications

• Gesture interfaces, augmented reality

• Robotics, 3D scanning

• Driverless vehicles, drones

https://software.intel.com/en-us/articles/a-comparison-of-intel-realsensetm-front-facing-camera-sr300-and-f200









• Synapse, AHaH


Reductions in feature sizes lag

microprocessors by many years

Thus are slower, and have fewer cores, partly

because lower power consumption is required

Parallel data transfers being implemented for

cellular and WiFi, just like multi-cores of GPUs

In future, WiFi will dominate smart phones,

with most processing in the cloud• More bio- and environmental sensors

• More image sensors for 3D reconstruction

• More data mining of user behavior

Speed

of PC

Micro-

processors

W

Improvements are Still Occurring

Along Many DimensionsSource: International Technology Roadmap for Semiconductors

Other Sources are also Optimistic(International Solid State Circuits Conference)

LiFi = Light Fidelity

LiFi will become economical in near future

as LEDs become cheaper (see Session 10)

LiFi enables much faster speeds

• Twenty times!

Much lower power consumption

• 100 times!

Previously required line of sight

But new forms of LiFi can handle reflections

What do the numbers say about Moore’s Law?• Microprocessors and Flash memory








• Synapse, AHaH


Everything is going

to cloud

Data centers are

more efficient than

stand-alone

computers

Computers operate

24/7 in data centers

New architectures

and new software are

making them even

more efficient

Virtualization

• split computers into virtual

machines, each with OS and

programs

• VM ware has been largest success

• Enables higher work loads

Other methods such as

• Containerization

• Orchestration

http://www.cisco.com/c/en/us/solutions/collateral/service-

provider/global-cloud-index-gci/Cloud_Index_White_Paper.html

progress without profits, economist, sept 19, 2015. P. 61

New architectures and software enable faster

analysis of unstructured data

GFLOPS (giga-floating operations per unit)/Watt

• 0.4 in 2010 to 67.8 in 2021

Bandwidth

• 1 Gb/second in 2010 to 100 Gb/sec in 2021

In combination with smart phones and WiFi, these

rapid improvements will enable

• many new types of applications

• automation of many functions

• Machine Learning

Source: International Technology Roadmap for Semiconductors

IBM has made quantum computing

available on the cloud (2016) http://flip.it/chi2D

This has much higher speeds, for some

applications

Speeds continue to rise and costs continue

to fall

Will quantum computing dominate cloud

computing in 10 years?

See http://www.slideshare.net/Funk98/superconductivity-15131282 and a few

slides at the end of tonight









• Synapse, AHaH


The Smart Phone Will be Used

Much More than PCs

Internet Advertising has Moved to the Internet

And Will Now Move to the Smart Phone

to Smart Phones

Though Data is Still Expensive for Poor Countries

it will get cheap, let’s look at how this occurred

and will continue to occur

How did they become economically feasible?• What are main costs for smart phones?

• What determines their performance?

• What levels of performance and cost were needed in the microprocessors and memory for smart phones to become feasible?

• When did this happen?

What happens as the components become better and cheaper? • What types of high performance phones?

• What types of low-cost phones?

Type of

Product

Final Assembly Standard Components1

Number of

Data Points

Average

(%)

Number of

Data Points

Lower Estimate for

Average2 (%)

Smart Phones 28 4.2% 26, 28 76%, 79%

Tablet

Computers

33 3.1% 33, 33 81%, 84%

eBook Readers 6 4.9% 6, 9 88%, 88%

Game Consoles 2 2.4% 2, 2 64%, 70%

MP3 Players 2 3.4% 2, 9 74%, 75%

Large Screen

Televisions

2 2.4% 2, 2 82%, 84%

Internet TVs 2 5.7% 2, 2 57%, 61%

Google Glass 1 2.7% 1, 1 62%, 64%

Cost Breakdown for Electronic Products

1 Values as a percent of total and material costs

2 Excludes mechanical components, printed circuit boards, and passive components

Type of

Product

# of

Data

Point

Mem

ory

Micro-

Proc-

essor

Displ

ay

Camer

a

Connecti

vity,

Sensors

Bat-

tery

Power

Mgmt

Phones 23 15% 22% 22% 8.2% 7.9% 2.3% 3.8%

Tablets 33 17% 6.6% 38% 2.9% 6.3% 7.3% 2.5%

eBook

Readers

9 10% 8.1% 42% .30% 8.3% 8.3% Not

available

Game

Console

2 38% 39% none none Not

available

none 5.8%

MP3

Players

9 53% 9% 6% none Not

available

4% 3.5%

TVs 2 7% 4.0% 76% none Not avail. none 3.0%

Internet

TVs

2 16% 31% none none 10.5% none 3.5%

Google

Glass

1 17% 18% 3.8% 7.2% 14% 1.5% 4.5%

Contribution of “Standard Components” to Costs

of Selected Electronic Products

Measure iPhone iPhone 3G iPhone 4 iPhone 5 iPhone 6

Operating

System

1.0 2.0 4.0 6.0 8.0

Flash

Memory

4, 8, 16GB 8 or 16GB 8, 16, 64GB 16, 32, 64GB 16, 64, or 128GB

DRAM 128MB 128MB 512MB 1GB 1GB

Application

Processor

620MHz Samsung 32-bit RISC 1 GHz dual-

core Apple A5

1.3 GHz dual-core

Apple A6

1.4 GHz dual-core

Apple A8

Graphics

Processor

PowerVR MBX Lite 38 (103

MHz)

PowerVR

SGX535 (200

MHz)

PowerVR

SGX543MP3 (tri-

core, 266 MHz)

PowerVR GX6450

(quad-core)

Cellular

Processor

GSM/GPRS/

EDGE

Previous plus

UMTS/HSDPA

3.6Mbps

Previous plus

HSUPA

5.76Mbps

Previous plus LTE,

HSPA+, DC-HSDPA,

4.4Mbps

Previous plus LTE-

Advanced, 14.4Mbps

Display

resolution

163 ppi (pixels per inch) 326 ppi 401 ppi

Camera

resolution

Video speed

2 MP (mega-pixels) 5 MP

30 fps, 480p

8 MP

30 fps at 1080p

8 MP

60 fps at 1080p

WiFi 802.11 b/g 802.11 b/g/n 802.11 a/b/g/n 802.11 a/b/g/n/ac

Other Bluetooth 2.0 GPS,

compass,

Bluetooth

2.1,

gyroscope

GPS, compass, Blue-

tooth 4.0, gyroscope,

voice recognition

Previous plus finger-

print scanner, near-

field communication

Evolution of iPhone in Terms of Measures of Performance

Fps: frames per second

480p: progressive scan of 480 vertical lines

What Levels of Performance and cost

were needed in each Component?• Memory

• Microprocessors

• displays

760 songs, 4000 pictures (4 megapixel JPEG), four hours of video, or 100 apps/games, or some combination

Equal usage• 190 songs

• 1000 pictures

• one hour of video

• 25 apps/games

Was this necessary, would 1GB have been sufficient?

The Average User Downloaded 58 Apps or a Significant

Fraction of Memory Available in 4GB Phone

Cost of iPhone 5 varies from $207 to $238

depending on flash memory capacity

• 16GB, 32GB, or 64GB

For iPhone 4s, costs range from $196 to $254 for

same range in flash memory

For iPhone 3GS, 16GB of flash memory are $24

thus suggesting costs for same change in capacity

would range from $179 to $251

In percentage terms, same changes in flash

memory capacity led to increase of 40% in iPhone

3GS and increase of only 15% in iPhone 5

Needed sufficient processor to have 3G

network capability

Needed sufficiently inexpensive

processor

What about camera, WiFi, gyroscope,

other sensors?

What components are experiencing rapid

improvements?

Can they tell us something about “next big thing”

Improvements will probably continue in

• Microprocessor, memory and other ICs

• MEMS, bio-electronic ICs

• Displays including flexible ones

• Lasers, LEDs, photo-sensors, and other sensors

• Speeds of cellular networks and WiFi

• New forms of user interfaces (gesture, touch)

Open source software is becoming more

available

New features, perhaps for high-end phones

• Health care: phones monitor health (heart rate, brain

wave, blood pressure) using sensors

• Home automation: use phones to control homes

• Voice-activated assistant for unfree hands (e.g., drivers)

• Engineering assistant: environmental data (temperature,

pressure, air and water quality)

Different phones for different applications?

• Or one phone does everything?

• Specific phones must be defined for specific users

What are entrepreneurial

opportunities?

Will Apple be

Disrupted?

Apple has

highest prices

Does it Deserve

High Prices?

Why might

Apple be

disrupted?

Type of

Product

# of

Data

Point

Mem

ory

Micro-

Proc-

essor

Dis

play

Cam-

era

Connect-

ivity,

Sensors

Bat-

tery

Power

Mgmt

Phones 23 15% 22% 22% 8.2% 7.9% 2.3% 3.8%

Includes

WiFi

Contribution of “Standard Components” to Phone Costs

Can any of these components be eliminated to create a much

cheaper phone (and perhaps a much cheaper phone service?

Are there improvements in components and/or

technological trends that can help us think

about components to eliminate?

How about a Low-End Phone: what might emerge?

Can microprocessors and memory be eliminated to create low-end phones that bypass network providers (SingTel, StarHub)• Lower cost phones

• Lower cost services

If WiFi is main connection and it works good enough• Can we reduce memory capacity?

• Can we reduced performance of application processor?

Lower resolution cameras, displays, and other components will also reduce costs

How might open source software enable lower costs?

What are the entrepreneurial

opportunities?

Concept of service

• Combine WiFi routers into integrated services

• Access cellular network when WiFi isn’t available

• How long will cellular service providers continue selling network

space to new entrants?

In U.S., Republic Wireless, Scratch Wireless,

FreedomPop, Google, soon cable companies. In France,

service called “Free”

But Korea may be leader – large use of WiFi, great phones

from Samsung, and great mobile content and services

In India, Uber will Offer Free Wi-Fi in taxis, Google also (http://blogs.wsj.com/digits/2016/01/22/google-brings-wi-fi-to-mumbais-railway-station/?mod=ST1)

http://www.wsj.com/articles/google-unveils-wireless-service-called-project-fi-1429725928; http://nyti.ms/1AFMiFW; http://nyti.ms/1HI2BkW;

http://www.economist.com/news/business/21654602-wi-fi-first-technology-will-be-great-consumers-disruptive-mobile-firms-change

http://www.wsj.com/articles/uber-to-offer-india-passengers-free-wi-fi-1440136803

Messaging Apps are

most widely used

function on most

smart phones

Some used for more

than messaging

• Particularly in China

• For payments, hotel,

rides sharing, food

delivery, restaurant

Voice recognition is

future (Session 7)http://www.wsj.com/articles/the-future-of-texting-e-commerce-1451951064

http://www.economist.com/news/business-and-finance/21696477-market-apps-maturing-now-one-text-based-services-or-chatbots-looks-poised

http://www.wsj.com/articles/global-telecoms-struggle-to-answer-challenge-from-

messaging-apps-1464038370

$40 billion in apps downloaded in 2015

(100 billion apps available)

20 most successful developers grab nearly

half of revenues

For using apps to order things, • services must understand chat, thus AI is required

Interact with bank accounts, get news, do

bookings, find sports shoes, respond to

health care questions, interact with doctors

Hard to switch between messaging apps

• Inconvenient for many users

• Hard to move data between them

Similar to incompatible word processing,

spreadsheet and power point software in 1980s

Microsoft Windows integrated them in late

1980s

Whose apps will become the ‘hub’ for many

services? FB, Uber, or somebody else?

What will be roles for AI and bots?

Better Apps Support Growth in Demand Economy

1. Finger print

2. Palm veins

3. DNA

4. Iris recognition

5. Facial recognition

6. Voice recognition

7. Signature recognition

8. Palm print

9. Hand geometry

10.Retina scan

11.Ordure/Scent

Google will begin testing an alternative

to passwords next month• With a goal to eliminate complicated logins for

Google introduced new feature to

developers at company’s I/O conference

in May 2016

Called the Trust API

To be initially tested with several very

large financial institutions

http://flip.it/gPoep

89

Biometric

Technology

Accuracy Cost Device Required Social

Acceptability

DNA High High Test Equipment Low

Iris recognition High High Camera Medium -Low

Retina scan High High Camera Low

Facial recognition Medium -

Low

Medium Camera High

Voice recognition Medium Medium Microphone,

telephone

High

Hand geometry Medium -

Low

Low Scanner High

Finger print High Medium Scanner Medium

Signature

recognition

Low Medium Optic pen,

touch panel

High

http://kaitleencrowe.com/2015/01/22/bi

ometric/

• Compared with other Bio Technologies, Finger Print is the best choice

How Fingerprint are acquired?

Source: http://360biometrics.com/faq/fingerprint_scanners.php

Optical Sensor

Ultrasonics with RF

Sensor

Optical Sensor

module

Capacitive Sensor

Thermal Sensor

http://360biometrics.com/faq/fingerprint_scanners.php

91

Fingerprint Sensors Comparison

Optical Capacitive Ultrasound

Size Relatively big and

require camera

Can embed into

small devices

Can embed into

small devices

Method Image capture RF Field RF Field

Cost Middle Low High

Accuracy May be affected by

dirt or water

May be affected by

dirt or water

Will not be

affected by dirt or

water

Working Current 120 mA 200 mA 6 µA

Source: http://yourbusiness.azcentral.com/comparison-fingerprint-scanners-27754.html

http://artofcircuits.com/product/optical-fingerprint-sensor-module-fpm10a

http://www.techshinobiometrics.com/products/fingerprint-identification-products/fingerprint-oem-modules/ http://www.sonavation.com/ultrasound-biometric-sensor

The most commonly used are:1. Minutiae matching (commonly used)

2. Pattern matching

http://www.biometric-solutions.com/solutions/index.php?story=fingerprint_recognition

http://biometrics.mainguet.org/types/fingerprint/fingerprint_algo.htm

93http://biometrics.mainguet.org/types/fingerprint/fingerprint_sensors_manufacture.htm

Average Selling Price of Fingerprint

Sensors are Dropping

94https://www.tractica.com/newsroom/press-releases/fingerprint-readers-in-mobile-devices-to-surpass-1-billion-unit-shipments-annually-by-2021/

Demand for Finger Print Sensor is Growing


opportunities?

Mobile phones

Mobile phone banking, e-commerce,

stock trading

Banking

Cars

Houses

thumb drives

Offices

97

Applications for Biometrics

Payment$$$

Public Transport Convenient Stores

Vending

Machines

Computers









• Synapse, AHaH


Routine Non-Routine

Manual Assembly line:

being automated

Nail Salon; won’t be

automated

Cognitive Many Jobs are

being Auto-

mated!!!!

Hardest to Automate.

Where you want to be

Easier to make computers exhibit adult (calculations)

than child (perception and mobility) behavior

Low-level sensorimotor still require much

computational resources

What types of software and other

automation should be used?

What jobs should be done by humans?

Not a question just for MIS

A question for top management

Want low costs, high quality, fast

response and many other things

Let’s look at what is happening

Apple has never been a big player in the $2 trillion annual spending on workplace technology

But now Apple is inviting firms to develop such programs (working with Cisco and others)

Encouraging providers of complementary apps to collaborate

20% of tablets used globally in 2018 will be owned by businesses, up from 12% in 2014

High expectations for retailers, restaurants, sales presentations, government offices

http://www.wsj.com/articles/with-ipad-sales-cooling-apple-leans-on-partners-1439422814

Slack is more like

messaging apps

Focus on people or

projects, not time

More like a

conversation!

Easy to understand

internal vs. external

Easier to see most of

your conversations in

one view

Slack allows third parties

to build apps

• Order lunch is one

• Other small tasks will be

automated

• Intelligent personal assistant

for groups?

Will it absorb functions

from other software?

Will similar things happen

with other enterprise

software?

• Sales software?

• Marketing software?

Zenefits Changed Human Resource Management,

Replacing Benefits Brokers

Examples: journalism, accounting, engineering,

architecture, legal, education

Previously face to face and customized services;

• Now mass customization and telepresence with computers

Software automates work, transforms work

(enabling people to be more proactive), and

enables customers to bypass professionals

• Nurses do doctors work

• Paralegals do lawyers work

• Students learn without teachers

See The Future of the Professions, Daniel and Richard Susskind)

The number of articles written by robots is

growing rapidly

Associate Press uses Automated Insights’

Wordsmith platform to create more than 3,000

financial reports per quarter

Kristian Hammond, Narrative Science’s co-

founder, estimates that 90 percent of news could

be algorithmically generated by the mid-2020s,

much of it without human intervention

Just input a few facts and let the algorithm write

the paperhttp://www.nytimes.com/2015/03/08/opinion/sunday/if-an-algorithm-wrote-this-how-would-you-even-know.html?rref=opinion

&module=Ribbon&version=origin&region=Header&action=click&contentCollection=Opinion&pgtype=article

Accounting continues to become more automated,

particularly tax compliance

• Cash flow done with QuickBook, Xero, Kashflows

• Internal accounting work focuses on problem solving, like

collecting payments

Tax work changing from compliance to planning

• Compliances done with TurboTax, H&R Block, At Home

TaxACT

• But even planning is threatened; planning and compliance

are different sides of same coin

• Compliance works forward from rules and regulations while

planning works backwards from these rules and regulations

Continuous auditing is next step

• Samples (chosen by heuristics) used in past to

minimize calculations

• Big Data enables software to analyze 100% of the data,

and continuously

Governments use software and big data to assess

tax returns, estimate chances of fraud

• Many require original electronic records, as opposed to

paper

• Electronic invoices are harder to fake than are paper

ones

Better software continues to emerge, enabling

• more high level design work

• more design options can be considered

Lower cost software also becoming available

• Enables more design options to be considered by small

firms, individuals, emerging economies

• For example, water flow analysis for fish farms

Can you think of other examples?

• Maybe your job should be automated

• Better to provide the solution than to have your job

eliminated by someone else’s solution

Software eliminates wooden models

• Use CAD and CAE ( VR and AR discussed in Session 8)

• Software creates more design possibilities; input objectives and

designs are proposed

• Computations carried out to test more radical designs

Cheap forms of software are emerging

• Individuals use software to become their own architects

• Open source designs becoming widely available:

Sketchup3d has one million designs while Grab Cad has 660,000

designs. Designs shared on many sites (even Pinterest)

Different people do different tasks

• Less need for vertical hierarchy. Use network model

• Can probably have designs checked by city governments

Most work involves paper work

Filling out forms, asking questions• Much of this can be done with online

questionnaires

Large cases involves lots of research,

which can now be done with computer

searches

Computers and artificial intelligence will

continue to eliminate legal jobs

ABA: American Bar Association

BLS: Bureau of Labor Statistics

http://www.mybudget360.com/law-school-bubble

-law-tuition-law-degrees-in-bubble-applications-down/

Graduates

Big move towards Pre-Fab/Modular Housing

• To reduce construction time, http://www.dirtt.net/

• No screws, nails, snap fits

• Change dimensions of one part, CAD system

automatically changes dimensions on other parts

• Uses ICE software, borrowed from video games

• Easy to reconfigure designs and rooms

Can augmented reality software help? See

session 8

Pre-fab Housing Method is one reason

some Chinese companies can construct

large buildings in less than one month

Many such articles and videos but here

are two of them http://www.theguardian.com/world/2015/apr/30/chinese-

construction-firm-erects-57-storey-skyscraper-in-19-days

http://www.dailymail.co.uk/news/article-2083883/Ark-Hotel-

construction-Chinese-built-30-storey-hotel-scratch-15-days.html

Many ways to learn without schools and

teachers

More than 10 million unique visitors each

month in 2014 for Khan Academy

700,000 education related videos on YouTube

750,000 educational apps installed in 2014

70 million unique visitors to slideshare 2014

New philosophy for education: need guide on

the side, not sage on the stage

See these slides for more details: http://www.slideshare.net/funk97/is-a-new-business-model-for-universities-needed









• Synapse, AHaH


Even

Museums

are Talking

about

Big Data

Sales Software

They mine sales staff

emails, calendars, social-

media feeds, as well as

news articles and

customer databases

Proposes potential

customers, ranking them in

order of likelihood to buy

Can tell sales staff when

client is reading their email

Google (and others) use data to determine

the ads that are displayed when you

• use search engine

• visit website

Ad sites compete to provide ads each time

you click

• They propose ads and prices based on your cookies.

• Amazon and other web sites also use this data to adjust

prices depending on customer characteristics, time of

day and other things

Humans Need Not Apply: A Guide to Wealth and Work in the Age of Artificial Intelligence, August 4, 2015, Jerry Kaplan

Mobile ads work differently

• InMobi offers questions based on all

your on-phone activity

• Can somebody do this better?

What about ad blocking

software?

• Many startups provide this software

• Is there a better way to do this?

• One that can satisfy both users and

advertisers?

• How will this war end?

Block Shock, Economist, June 6, 2015, p. 52

In one study of 140,000 test emails,

researchers at Verizon reported that 23%

of recipients opened and 11% clicked on

attachments

Training doesn’t help

Solution is to automate around them• Better email filtering

• Something else?

http://www.wsj.com/articles/how-to-improve-cybersecurity-just-eliminate-the-human-factor-1453125602?mod=LS1

Many billion dollar club startups use Big Data• Peer-to peer lending: Lufax, Prosper

Marketplace, Social Finance, Funding Circle, Lending Club

• E-commerce payment: Klarna

• Other: Zhong an Online (insurance), HanhuaFinancial (credit guarantor), Credit Karma (credit scores), Sunrun (solar leasing)

But what is next? What about smart phone apps?

As firms manage more money, aren’t they becoming like banks?

Klarna• Offers simple payment system (e-mail

identifiers) for smart phone users that is easier than inputting credit cards

• 65,000 online merchants, 45 m users

• It allows users to pay after receiving products and Klarna assumes the risk

• Klarna judges risk based on Big Data

• Now it is extending loans (also PayPal is)

Getting more ambitious, Economist, Feb 6, 2016

Evaluates

creditworthiness of

prospective borrowers

Big Data analysis finds

patterns of credit

worthiness and apps

look for this

creditworthiness

Very popular in Africa

where mobile banking

is popular http://www.wsj.com/articles/lending-startups-look-at-borrowers-

phone-usage-to-assess-creditworthiness-1448933308

In U.S. poor people often paid by checks

• but banks charge a lot for checks when bank account

balances are small

Governments should

• pay workers in another way

• require companies to pay in another way

What should the other way be?

• Messaging apps?

• Other mobile phone apps?

• Security may be the biggest issue

Individuals are coding decision rules at home

More than 170,000 people enrolled in a popular

online course, “Computational Investing” taught at

Georgia Institute for Technology

What types of decision rules?

For example, if stock volumes hit minimum

threshold

• and price crosses above 200-day moving average, buy

• And price falls below 200-day moving average, sell

http://www.wsj.com/articles/an-algo-and-a-dream-for-day-traders-1439160100

Two big challenges• High regulation

• High capital requirements, which bring risk

Solutions• Lemonade uses peer-to peer approach, like FinTech

banks Get friends to adopt risk, since they understand situation

of friends

• Metromile tracks mileage More mileage, higher the risk

Many others (Progressive, Aviva) track braking and speed

Against the Odds, Economist, January 30, 2016, P. 59

Satellite Data - utilize image data from orbiting satellites to

measure number of cars in Walmart parking lots or farm health

based on color of crops.

Web/App/Social Media Data –mine social media or use data

firehoses from web/ mobile to understand what’s happening in

world or how people are interacting with their devices.

Weather Data –developing weather models and utilizing more

sensors to get better localized data or improve weather

forecasting.

Location/Foot Traffic Data –use different means to

understand where consumers are going by measuring foot

traffic via check-ins, video analysis, etc.

https://www.cbinsights.com/blog/alternative-data-startups-market-map-company-list/?utm_source=CB+Insights+Newsletter&utm_

campaign=5442a1353d-Top_Research_Briefs_5_21_2016&utm_medium=email&utm_term=0_9dc0513989-5442a1353d-86622821

Alternative Credit - new credit models that utilize sources

of alternative data (like mobile usage).

Credit Card Transactions – use anonymous aggregate

transaction data to understand trends in consumer

purchasing habits.

Alternative Data Monetizers/Aggregators – companies

who pay for access to individual data streams which become

more valuable in a bundle, and then sell those packages to

investors

Local Prices – what’s happening to prices and inflation by

aggregating data from ground-level sources.

https://www.cbinsights.com/blog/alternative-data-startups-market-map-company-list/?utm_source=CB+Insights+Newsletter&utm_

campaign=5442a1353d-Top_Research_Briefs_5_21_2016&utm_medium=email&utm_term=0_9dc0513989-5442a1353d-86622821

E-commerce sites vary prices by time,

day, and location

Trying to maximize profits through small

changes in prices

Some of this is personalized pricing

Some of this is time of day pricing

Can this be applied to physical stores?

What is next?

http://www.wsj.com/articles/now-prices-can-change-from-minute-to-minute-1450057990

Uber’s System Uber’s System

Not Working Working

• Dynamic pricing for parking• Price changes over day and different quarter

• Drivers can check for vacant spots and price on smartphone to make

better choices

• Real-time physical location data can also help make better

decisions about parking garages

Price Display by Smartphone

In future, smart phones can replace traditional paper or

electronic screen price tag and act as price display tool

Customers obtain dynamic price as well as other

information of goods by just tapping NFC tag or scanning

the QR code


opportunities?

1. Smartphone design and mfgwith NFC ID identificationfunction

2. NFC chip manufacturing

3. Mobile Apps to read QRcode & NFC tag, combinedwith price analysis function

4. Data processing platformthat deals with massdynamic pricing dataanalysis

Future Opportunities for Price Display

by Smartphone

Google, IBM, Facebook made their machine-learning software available for free under and open-source license• Google: TensorFlow system

• IBM: SystemML

They want their systems to be • tested, tuned, and adapted

• built upon, improved, and extended

Open source is necessary to attract academics

http://blogs.wsj.com/digits/2015/11/09/why-google-is-willing-to-give-away-its-latest-machine-learning-software/?mod=ST1

http://www.wsj.com/articles/ibm-turns-up-heat-under-competition-in-artificial-intelligence-

1448362800?mod=WSJ_TechWSJD_NeedToKnow

Computers have beaten best chess and

Jeopardy players

Computers can help doctors diagnose patients

Computer matches medical knowledge with

patient’s symptoms, medical histories with test

results• formulates diagnosis and treatment plan

• Doctors cant read all journals nor remember everything

they read

Discussed more in Session 6

Sources: The Second Machine Age: Work, Progress, and Prosperity in aTime of Brilliant Technologies, Erik Brynjolfsson, Andrew McAfee

http://www.research.ibm.com/cognitive-computing/watson/watsonpaths.shtml#fbid=NAFH6hHnYVY

Learning about my music likes, partly

through my friends likes

Searching through my photos• find photos that match “wedding” and “mom”

What do the numbers say about Moore’s Law?• Microprocessors and flash Memory








• Synapse, AHaH


Built from organic molecules rather than silicon Advantages

• greater flexibility

• lower manufacturing temperature (60-120° C)

• lower-cost processes such as roll-to roll printing

Disadvantages• lower mobility and switching speeds compared to silicon

• usually do not operate under inversion mode

Current Market• Circuits for Electronic paper (e.g., e-Books),

OLEDs and other displays

Future Market• Greater use of organic transistors in cases where flexible

electronics are useful

• Replacement of ICs

Huanli Dong , Chengliang Wang and Wenping Hu, High Performance Organic Semiconductors for Field-Effect

Transistor, Chemical Commununications, 2010,46, 5211-5222

http://pubs.rsc.org/en/content/articlelanding/2010/cs/b909902f#!divAbstract

Dramatically lower costs

But also lower performance

Other types of materials can also be

printed• Conductive inks

• Electronic paste

Also other applications for such

materials









• Synapse, AHaH


Very high conductivities

In medium term, can be used in channel area

(under gate) in place of silicon for faster

transistors

In long term, can they be designed with

different properties (e.g., conductors,

insulators, semiconductors) so that transistors

can be built with them

Improvements in Purity of CNTs (and Increases in Density)

Source: Electronics: The road to carbon nanotube transistors, Aaron D. Franklin

Nature 498, 443–444 (27 June 2013)

http://www.nature.com.libproxy1.nus.edu.sg/nature/journal/v498/n7455/fig_tab/498443a_F1.html

http://www.nature.com.libproxy1.nus.edu.sg/nature/journal/v498/n7455/fig_tab/498443a_F1.html

IBM Says they are five times faster and will be ready around 2020 when feature lengths reach 5nm (now 14 nm)• Built on top of silicon wafers

• Each transistor uses six nanotubes lined up in parallel to make a single transistor

• Challenge is to make them self-assemble

Nantero has shipped samples of nanotube based memory (NRAM)• Produced in CMOS fabs (20 ns access times)

Source: Technology Review, http://nextbigfuture.com/2014/07/ibm-says-nanotube-transistors-chips.html#more

http://nantero.com/mission.html; http://blogs.wsj.com/digits/2015/06/02/carbon-nanotube-chips-spark-investment/

http://www.nytimes.com/2015/10/02/science/ibm-scientists-find-new-way-to-shrink-transistors.html?_r=0

Graphene

Also very high conductivitiesIn short term replace silicon with graphene in channel area

In long term combine graphene with other ultra-thin materials

As of April 2013, >10 materials found; some can be integrated with Graphene or each other

Boron nitride (insulator) has been fabricated in one-atom sheet as has Molybdenum Sulfide• Molybdenum Sulfide is semiconductor, Boron Nitride is

insulator, Graphene is for interconnect

• Together one atom thick flash memory devices have been constructed

More recently (April 2015), three-atom thick semiconducting films (transition metal dichalcogenide) with wafer-scale homogeneity have been constructed

http://thessdreview.com/daily-news/latest-buzz/flash-memory-to-be-based-on-2d-materials-a-single-atom-thick/









• Synapse, AHaH


IBM created an array of 96

iron atoms that contain one

byte of magnetic information

in

“anti-ferromagnetic” states.

But making them is still a

major challenge………….

Source: John Markoff, New Storage Device Is

Very Small, at 12 Atoms

NY Times, Jan 13, 2012

http://www.nytimes.com/2012/01/13/science/small

er-magnetic-materials-push-boundaries-of-

nanotechnology.html









• Synapse, AHaH


This chip uses a million digital neurons and

256 million synapses to process information

Potential replacement for microprocessors

Requires completely new forms of computer

architectures and software

For more details, see presentation on

synaptic chips:

http://www.slideshare.net/Funk98/neurosy

naptic-chips

159

Performance Improvements - IBM Cognitive Chip

From MT5009 Group Presentation, Spring 2015

http://research.ibm.com/cognitive-computing/neurosynaptic-chips.shtml#fbid=tVSs3tKj1tw

http://www.research.ibm.com/articles/brain-chip.shtml

http://research.ibm.com/cognitive-computing/neurosynaptic-chips.shtml#fbid=i9UhV_HagUs

http://www-03.ibm.com/press/us/en/pressrelease/44529.wss



http://www.research.ibm.com/articles/brain-chip.shtml

http://research.ibm.com/cognitive-computing/neurosynaptic-chips.shtml#fbid=i9UhV_HagUs

http://www-03.ibm.com/press/us/en/pressrelease/44529.wss









• Synapse, AHaH


Limitations of von-Neumann Architecture

Memristors Are the Key to AHaH Computing

Their Resistance Changes According to their History

Widely Used Ones Become Less Resistive (i.e., Learning)









• Synapse, AHaH


http://nextbigfuture.com/2013/05/dwave-512-qubit-quantum-computer-faster.html; http://www.dwavesys.com/en/dev-tutorial-hardware.html

Quantum Computers are Also Becoming Economically Feasible:

See Session 10 on Superconductivity

Bit Energy = power consumed per clock period x number of active devices

RSFQ: rapid single flux quantum, relies on quantum effects in superconducting devicesSource: superconductivity web21, January 16, 2012. www.istec.or.jp/web21/pdf/12_Winter/E15.pdf

Improvements in Power Consumption and

Speed of Superconductors

This is obviously a very difficult question…….

Will all chips have 3D layers of transistors or

memory cells by 2020? How many layers of

transistors or memory cells by 2025?

Will MRAM, PCM, ReRAM, or FeRAM replace

flash memory and which one will win?

Will carbon nanotubes, graphene, or other ultra-

thin materials be widely used in ICs by 2025 or

2030?

Will organic materials gain share from inorganic?

When might Synapse chips become widespread?

Improvements in ICs, Computers, and

Electronic Products are not over

Improvements in ICs will continue at a

rapid rate, but perhaps slower than in the

past

New forms of Moore’s Law will Emerge

These improvements will enable better

computers and other electronic products

Rapid improvements in electronic products and

the Internet are not over

Microprocessors may be slowing

But other components and Internet are not

slowing

Smart phone and cloud computing are future

They will enable many new types of content and

services

• These new services will change the way work is done

• And change the definition of a business

• Big Data will become even more important