the big picture on nano - etouches · the big picture on nano head consultant, management &...

2015 ACS State Conference 1

2015 ACS State Conference

Rosehill Gardens, Sydney | 6+7 May 2015

The Big Picture on nano

Head Consultant, Management & Technology | GDN consulting firm

Your future has already started, integrate technology to deliver on your vision


Major risks

Responses

nano tech impact on AC industry

Mantra

Preamble


content, credits & references


2015 global risks landscape


2015 Global Risks Map

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2015 Global Risks Correlation Map

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Human population

Biosphere

regeneration

Human

consumption

~ 1.3 times

what

the planet

can sustain

Net loss

28%

Steadily growing since mid 80’s

Source: Simms A., NEF (New Economics Foundation), London

Earth Profit & Loss 2014 based on Averaged human lifestyle


disconnected physical, financial & geopolitical worlds

ETR (Ecological tax reform)??

EIA (Environmental impact assessment)??

Inter-sector policies, new institutions, legal reform?? IM (Industrial metabolism) ??

VA (Voluntary agreement) ??

EE (Ecological economics) ??

Climate change

Financial crises

Social instabilities

Major fiscal imbalances

Ineffective multi-polar geopolitics


90% due to human

errors

failure of urban planning (10m lives each year)

29b barrels fuel wasted per year ***

450b hours smoked in traffic equivalent to:

0.76 million lives each year **

* source: WHO 2015 report on worldwide road death toll ** worldwide fuel consumption is 33b per year

*** based on 67.2 years or 588k hours worldwide average life expectancy

**** source: 2013 assessment by WHO’s International Agency for Research on Cancer (IARC)

1.24 million lives each year * #1 cause of death for aged 15-29 years*

20~50 millions injured*

Worldwide road death toll

Worldwide road congestion Air pollution (in & outdoors)

8 millions lives each year ****


Potential

reforestation

Food growing

Habitable

zones

Inhabitable

deserts

Inhabitable floods, droughts

extreme weather

Land lost to

rising waters (2m assumption)

a map of climate change risks

The World 4ºC warmer

Source: New Scientist

Climate Change Report, 2009


ageing population & major fiscal imbalance risks Worker (15 to 64) to Retiree (64+) dependency ratios

Source: UN, Department of Economic & Social Affairs, 2014


smart economics

smart machines

smart cities


share economy, co-creation + 3D manufacturing

Disruptive global digital neo-economics, barter resurgence & dematerialization

Share Economy (Internet, Uber, Airbnb) unused value is wasted value

Generalised crowdsourcing along the entire value chain (co-creation)

The latest Maslow’s


share economy, co-creation + 3D manufacturing

Co-creation + 3D manufacturing Communities of Passion (psychographics vs demographics)

3D printing of medicines (Prof. Lee Cronin, Uni of Glasgow)

3D printing of live tissues & organs (bio-printing)

Local Motors (Rally Fighter) | General Motors (Chevy Volt) | Fisker Automotive (Karma) | Tesla (Roadster)

co-creation + 3D

the automotive

industry example

Source: 2015, CEO Jay Rogers, Local Motors


conventional mass-produced drug supply chain


on-demand 3D-printed personalized medicine prescription

more direct well-suited 3D-printed drug value chain


rise of the machines The IoT (Internet of Things) or

IoE (Internet of Everything) IPv4 (4.3b addresses) IPv6 (3% in 2014)

Big Data Analytics Deep domain expertise & learning algorithms

merging genomics & informatics

6, 7 & 8th level normalization

unstructured data

Mobile connecting

technology

smart information

smart machines

smart cities


evolving from net emitters to

CO2-capture mega-systems

smart cities | the big picture



smart cities | extramuros

2015 AeroFarms case in New Jersey US:

• 95% water needs reduction

• 75 times more productive

• biosphere size increase

• carbon-capture system

• 0-pesticide & 0-soil

• 16 days cycle

integrated vertical urban

farming (edible + bio-fuels)*

new mobility

paradigm shift

average private cars

unused 92% of the

time **

existing infrastructure

3 times more efficient

with driverless ***

* Based on 2015 AeroFarms results in New Jersey

** 2014 Stanford Energy Institute research

*** 2011 Google Driverless Car Project, Sebastian Thrun


smart cities | intramuros

autonomous, automated, alive,

sustainable, re-configurable

modular buildings

smart information

from GUI* to NUI**

& M2M*** (web 3.0)

* Graphical User Interface ** Natural User Interface *** Machine-To-Machine

India (31% urbanization) 2015 budget 70.2b INR**** to build 100 new smart cities

**** 1.2b US$


Major risks

Responses

from emerging nano to web 4.0

Mantra

Preamble


nano scale


emerging nano tech & impact on AC

1. BCI (brain computer interface)

2. 4D (smart materials)

3. nanotheranostics

4. neuromorphic IT

5. reverse Moore’s law & web 4.0

6. new challenges

7. AC take away

8. Q & A


BCI (Brain Computer Interface)

a short video summary

Click here

https://www.youtube.com/watch?v=QRt8QCx3BCo


4D printing (self assembly)

Skylar Tibbits | MIT

4D = 3D + 1D (time / transformation)

Self-Assembly = process

by which disordered parts

build an ordered structure

only via local interaction

Programmable matter =

material that can change

form or behave in a

programmable fashion

smart material (robot without robots)

Robots

Click here

https://youtu.be/a1J7aMJkfcI


4D printing applications

Self-repairing active pipes (no mechanical pumps)

Self-transforming reconfigurable buildings

Other building / Construction applications

Aviation

Adaptive, supporting & assistive

textile, apparel & footwear

Self-assembling products from 2D to 3D

Lower-engineered adaptive furniture

Self-adaptive packaging

Automotive



nanotheranostics

nanotheranostics = nano + therapies + diagnostics

nanomedicine

nanodrug delivery

nano regeneration

nanotheranostics

Related disciplines, concepts & terminology

• zero-incision or non-invasive surgery

• precision or personalized medicine


nanodrug basic building block metaphor

Bio-markers

Container/s

Cargo/s (inside the container/s)


nanotheranostics vs conventional treatment

In vivo

via nanotheranostics

Ex vivo (In vitro) interrogation

+ chemotherapy

Detection entire circulation interrogation sample-based interrogation

vs



In vivo



+ chemotherapy


Progression dynamic monitoring -

X vs



In vivo



+ chemotherapy



Therapy

narrow target & destruction upon

recognition of pathogenic cells +

real-time response monitoring

broad range & mass destruction

with collateral damages to healthy

cells + asynchronous monitoring

vs




In vivo



+ chemotherapy



Therapy

narrow target & destruction upon

recognition of pathogenic cells +

real-time response monitoring

broad range & mass destruction

with collateral damages to healthy

cells + asynchronous monitoring

vs

vs



more advanced nanotheranostics

From rudimentary multiplexing nanodrugs to smarter bio-computing ones

Versatile built-in computing/robotics using DNA origami nanobots

More advanced computing based on swarms of nanobots

• Hand shakes

• Quorum sensing

• Swarm computing


nanobots

Ido Bachelet, Shawn Douglas, Daniel Levner & the research team


nanobots swarms computing

≈ Commodore 64


wifibots



First Human trials

starting from 2015

nanobots zero-incision or non-invasive surgery

or


nanobots zero-incision or non-invasive surgery

or

“Big Pharma spends trillions of dollars

attempting to build ‘sophisticated guns’

(drugs) that shoot only ‘bad people’

(pathogens). This is difficult and indeed

fails most of the time. We already have

enough guns (both used & unused drugs):

what we need is to teach the soldier

(nanodrug platform) how to use them”

2014 Ido Bachelet


Next from DNA origami to RNA/DNA 3D nanofactory

Deliver drugs directly to the pathogenic site Responsively manufacture tailored drugs

Use DNA as a building block for nanomachine Let DNA (RNA) be THE nanomachine


brain research & neuromorphic computing

conventional IT | a very brief history

https://www.youtube.com/watch?v=dfIN6jcmfuI

https://www.youtube.com/watch?v=PCql2DgW5sE

“It is comparatively easy to make computers exhibit adult

level performance on intelligence tests or when playing

checkers, and yet very difficult or impossible to give them the

skills of a 1-year old when it comes to perception & mobility”

1980 | Hans Moravec | Carnegie Mellon University | Robotics & Artificial Intelligence

George Boole

1815 – 1864 Charles Babbage

1791 – 1871

Alan Turing

1912 – 1954 John Von Neumann

1903 – 1957


brain research & neuromorphic computing

advent of non-Von Neumann machines Qualcomm Zeroth NPU

Neural Processor Unit

* 86b neurons + 100t synapses in a Human brain

IBM TrueNorth

1m neurons + 256m synapses*

Artificial Intelligence

Deep Learning algorithms

Yann LeCun Geoff Hinton

€ 1.2 billion over 10 years (2013 – 2023)

US$ 3 billions over 10 years (2013 – 2023)

Both projects triggered by

too lengthy delays in

solving brain disorders and

degenerative conditions via

cognitive & neuroscience

2015 ACS State Conference 42 Gordon E. Moore

Moore’s Law

1965 1990 2015 2020 2050 2080 …

Macro

Nano


Moore’s Law

1965 1990 2015 2020 2050 2080 …

Macro

Nano

4D

neuromorphic

biocomputing

where it all collides reverse


predicting the next (easy-to-swallow) gizmo



1. Rewrite your cells internal clock • cell regeneration beyond 40 subdivision cycle

• prolong existence to 150, 200, 300 years or

• … until you get bored to (literally) death

2. Your 24/7 personal bodyguard • protect dynamically against all diseases

• DNA-tailored nanotheranostics

• universal built-in nanofactory

3. Instant knowledge access • merged neuromorphic processes

• bio-synthetic knowledge storage

4. Tele-kinetic powers • Wirelessly control 4D objects

5. Telepathic powers • subvocalized brain-2-brain

• Cloud-connected brains

• BrainNet aka web 4.0


new emerging challenges


bio-hacking

Erwin Schrödinger Craig Venter

1944 First DNA model proposal

“What is Life?” Erwin Schrödinger

2000 Genome mapping completed

2010 First synthetic life created

“Life is a DNA software

system and I created it” Craig Venter


the smarter-than-human AI* conundrum

“The core problem is one of aligning AI goals with human goals.

If smarter-than-human AI’s are built with goal specifications that

subtly differ from what their human inventors intended, it is

unclear that it will be possible to stop those AI’s from using all

available resources to pursue those goals, any more than

chimpanzees can stop humans from doing what they want ” Stuart Russel Professor of Computer Science

Smith-Zadeh Professor in Engineering

University of California, Berkeley

* Artificial Intelligence


Societal, ethical & economic impact of technology

an example | AI* learning machines

47% of jobs to be automated Source: 2014 Carl Benedikt Frey & Michael A. Osborne | Oxford University

* Artificial Intelligence


1. Inconsistencies example: self-flying objects 2. Space Cross-border harmonization?

3. Speed multi-stage adaptive regulations to

manage uncertain future of emerging technologies

4. Ownership which regulatory body should take

initiative with cross-disciplinary emerging technology?

5. Regulative vacuum religious powers, action

groups, future generations, industries self-regulations

6. Societal, ethical & economic impact is

technology a Human right? Or a market choice? What

is an economic transaction? How to measure value?

law-making process inadequacies

“It took 80 years for the

international community to

reach legal consensus on

chemical weapons ban”

“A driverless world would mean a

world without any road accidents:

this would prove catastrophic for

our car insurance business.” 2014

Warren Buffet (Geico Car insurance)

“Who is liable to the injured

when driverless cars choose

between pedestrian, cyclist

or passenger in any life-

threatening events?”


smart politics democracy 3.0


Industry associations | engaged catalysts

Eldercare pivotal to most 21st century social conundrums

Source: 2015 World Happiness Report


Industry associations | engaged catalysts

• Eldercare pivotal to most 21st century social conundrums

• Trust + Time = the new currencies Democracy 3.0

• Co-created Law-centric engagement platforms

co-creation +

communities of

passion

Source: 2015, CEO Jay Rogers, Local Motors


aged care providers | 360° engagement

• Shift to CDC more competition + new marketing streams

• Co-creation engagement platforms with core audiences

• Extend 360° engagement via & beyond your boards

Are you already co-creating your

next product / service with your

own communities of passion?

new mobility

paradigm shift

Are you engaged into the

strategic conversations

such as those on smart

cities, aged care laws,

social ethics?


residential providers | long-term assets strategies

sustainable, re-configurable & modular buildings


How nanotheranostics

might impact demand

for high care needs?

Contingency planning for disruptive technologies

on long-lifecycle onerous investments (buildings)

How new economics might

impact the supply-demand

entire graph itself?


renewed focus on lifestyle & leisure activities for the super-healthy, hyper-knowledgeable, brain-connected

(and most probably … bored to death) 300-years-young


[email protected]

the big picture on nano - etouches · the big picture on nano head consultant, management &...

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