Technological Paradigm Shifts Updated

Future Visions of the European Electronics Industry towards 2020

Technological Paradigm Shifts

Joachim Hafkesbrink, Innowise Germany

http://en.wikipedia.org/wiki/Image:Duck-Rabbit_illusion.jpg

Getting It Wrong: Prophecies From The Past

Lord Kelvin, Mathematician and Physicist 1897: „The radio has no future.“

Why the Record Company Decca turned down the Beatles in 1962: „We don‘t like your sound, Guitargroups are a thing of the past.“

Bill Gates, 1981: „640k should be enough for anybody.“

The US-Magazine Popular Mechanics, 1949: „The Computer of the future will maybe still weigh 1.5 tons.“

Kaiser Wilhelm II: „I believe in the horse. The automobile is just a temporary occurence.“

Karl Benz around 1920: „The car is now completely developed. What else can still to come?“

Irving Fisher, Professor of Economy on Oct. 17th 1929: „It looks like the stock markets have reached a permanent high level.“

Table of Contents

Paradigm Shift: Definition and Examples

Innovation Theory: trajectories, path-dependancies, disruptive technologies

Paradigm Shifts and the Law of Acceleration

Systems Innovation and Transition

Societal Paradigms as a Framework for technological development

Drivers and Barriers of Transition

Technological Paradigm Shifts 2020

Paradigm Shift: some definitions

What is a Paradigm?

“a constellation of concepts, values, perceptions, and practices shared by a community, which forms a particular vision of reality and a collective mood that is the basis of the way the community organizes itself”

What is a Paradigm Shift?

“a change from one way of thinking to another with a profound and irreversible change to a different model of behavior or perception”

Paradigm Shift: some examples

moving scientific theory from the Ptolemaic system (the earth at the center of the universe) to the Copernican system (the sun at the center of the universe)

moving from Newtonian physics to Relativity and Quantum Physics

Invention of fire, wheel etc.

Paradigm Shift in Innovation Theory

Joseph A. Schumpeter*:

Talks about „disruptive technologies“ or „radical innovation“

= new technological innovation, product, or service that eventually overturns the existing dominant technology or product in the market

* Famous Austrian Innovation Researcher

http://www.flickr.com/photos/83496054@N00/149325435/

Sou

rce:

Ray

Kur

zwei

l

Moore‘s Law:

Information Technologies (of all kinds) double their power (price, performance, capacity, bandwith) every year.

Paradigm Shift in Innovation Theory

technological revolutions do not occur abruptly

they come only after longer periods of traditionally bound technology, where technological improvements follow a more or less fixed path of development

http://www.flickr.com/photos/83496054@N00/149325435/

Evolution of a Technology(A technological Trajectory)

Degree of Maturity (Performance)

Radical Innovation

Birth Growth Maturity

Path dependency

Time

New technology (new trajectory)

Radical Innovation

Incremental Innovation

Evolution of a Technology(A technological Trajectory)

Degree of Maturity (Performance)

Radical Innovation

Birth Growth Maturity

Path dependency

Time

New technology (new trajectory)

Radical Innovation

Incremental Innovation

Technological trajectory: industry sticks to a given trajectory (technology path) as long as incremental innovation are favoured to prevent sunk costs from changing the basic technology

Law of Acceleration (Ray Kurzweil)

Paradigm shift rate (i.e., the overall rate of technical progress) is currently doubling (approximately) every decade.

That is, paradigm shift times are halving every decade (and the rate of acceleration is itself growing exponentially).

So, the technological progress in the twenty-first century will be equivalent to what would require (in the linear view) on the order of 200 centuries.

In contrast, the twentieth century saw only about 20 years of progress (again at today's rate of progress) since we have been speeding up to current rates.

So the twenty-first century will see about a thousand times greater technological change than its predecessor.

Sou

rce:

Ray

Kur

zwei

l

Sou

rce:

Ray

Kur

zwei

l

Systems Innovation: Transition Phases and Levels

Systems Innovation: Multidimensional Shifts

Change in production / technology

Cha

nge

in m

arke

t-/ a

ctor-

rela

tions

IncrementalinnovationsExample:

Improvement of plasticrecognition technology

System innovationsExample:

New Business Models forProduct-Service Systems

Radical processinnovationsExample:

Non-destructive automaticdisassembly

Radical structuralinnovationsExample:

Re-Use of electronic devices, components and parts

Change in production / technology

Cha

nge

in m

arke

t-/ a

ctor-

rela

tions

IncrementalinnovationsExample:

Improvement of plasticrecognition technology

System innovationsExample:

New Business Models forProduct-Service Systems

Radical processinnovationsExample:

Non-destructive automaticdisassembly

Radical structuralinnovationsExample:

Re-Use of electronic devices, components and parts Fusion of

technologies, products with new services and new use models

Systems Innovation: Long Waves of Development

reactive receptive constructive system

Sustainability Systemic Competitiveness

Automatisation Comparative Advantages

Time to MarketCompetitive Advantages

Taylorism Standardized production

A) response phase C) main actors

B) focus of attention D) driving philosophy

E) trajectory

VisionAccelerationOptimisationMinimisation

SocietySectorManagersSpecialists

SystemProductProcessEnd of pipe

Sustainability Systemic Competitiveness

Automatisation Comparative Advantages

Time to MarketCompetitive Advantages

Taylorism Standardized production

A) response phase C) main actors

B) focus of attention D) driving philosophy

E) trajectory

VisionAccelerationOptimisationMinimisation

SocietySectorManagersSpecialists

SystemProductProcessEnd of pipe

A)

C)

B)

D)

t1970 1980 1990 2000

E)

Paradigms shifts in the Electronics Industry 1970-2000

„From a linear to a circular valua-added chain based on new paradigms with service extensions.“

Seeds of transition from a production-and-throw-away Economy to a service oriented knowledge based Industry

Macro-level: new governance Portfolio - WEEE, EuP, RoHS ....

Meso-level: new alliances - joint-cooperative innovation networks, change in cultural and belief regimes

Micro-level: actors from different sectors are driving innovation (communication and content provider, suppliers, OEMs, waste management and recycling companies, science/consulting)

Barriers of transition

Macro-level: some regulation is more a barrier than a driver

Meso-level: loss of ownership may hinder diffusion of product-service shift

Micro-level: technical barriers (end of Moore‘s Law 1 in 2015, barriers in multi-disciplinary cooperation – barriers in knowledge transfer)

Technological paradigm shifts towards the year 2020

„New trajectories are things we are researching today and which will be reality tomorrow“

Sources:

Research and development programs (national, EU-level, US...)

Industry Roadmaps

European Technology Platforms

Foresight Studies, Delphis, Scenarios

...

What happens in a technological paradigm shift?

Way of thinking: vision, basic philosophy, view, mindset

Technological kernels: models, basic technology, miniaturization and acceleration...

Crossover Trends: convergence, cross-fertilization, embeddedness, computation...

Dialogue: connectivity, networks, communication...

Capabilities: learning, mimicking, self-sustaining...

Environment: way of using it, work organization, energy issues...

“The farther backward you can look, the farther forward you can see.” (Winston Churchill)

Technological based Paradigm Shifts in the Electronics Industry Part 11960-1980 1981-2000 2001-2020 2021- ...

Vision

Technology "out-there" (technology alien to nature - technology to control the world)

Technology in support to mankind

Technology as interface to nature

Technology becoming a second nature

basic philosophy

maximisation optimisation sufficiency, adaptation, learningself-organizing, self-repairing, fault-tolerance, redundancy, fuzziness

viewevolutionary, bottum-up, open distributed and mobile architecture

evolutionary, self-organized, evolve-able systems

mindset adaptation to user's environmentself-understanding, self-awareness, self-learning ("knowbots")

focus of software development and models

fixed-parameter models, top-down algorithmic, unportable, tied to one kind of hardware or particular operating system

fixed-parameter models, structural algorithmic for large systems to manage dependencies between different parts of programms, limited portability

variable-parameter models, distributed structural algorithmic to build distributed, concurrent systems, portability, object orientation, adaptability to different environments with limited effort

adaptive algorithms to operate in large, open and non-deterministic environments (adaptive embedded systems), software that can adapt to different circumstances with limited, or even without, intervention by a developer

basic technology processing systems

vacuum tube and discrete transistors

Integrated Circuits/Chips

CMOS and additional throughput by parallelisation/distribution techniques

Post CMOS era: Photonics, processing systems based on biological neural networks linked to quantum computing systems

technocratic, top-down, centralized control

analysis, planning, control behaviour to be thought in statistical terms


miniaturization

macro meso, micronano-scale devices reaching a scale below 10 nanometres (2D-nanosheets)

quantum promise, “information carriers” based on electrons, photons, spins, ions, molecular dynamics, neurons, etc. (qubits); 3D Nanoelectronics

law of acceleration

Moore's LawMore of Moore, End of Moore's Law for CMOS

Beyond Moore; technological singularity (PC will achive human brain capacity)

processing speed

kilobyte, 0.25 MIPS in the year 1967

megabyte, gigabyte, 1.00 MIPS in the year 2003

terabyte and peak performance of TeraFLOPS for standard chip;

peta device computing

analog-digital-bio shift

analogue society

bio-society linking the realms of information, material and life, combination of digital and analgous computation

cross-fertilization

mono-disciplinarity inter-disciplinarity

"Bio-ICT Convergence", managing the "wet frontier" (interface between organic and non-organic; neuro-electronic interfaces)

completely integrated bio-electronic systems, combination of living and artificial systems, technological artefacts increasingly involving and exploiting the properties of living material

data complexity

small quantities of datalarge data and knowledge repositories

managing diversity in data and knowledge by adaptation, convergence of digital data, quanta with bio-nano-technologies

digital society

Sou

rce:

Ray

Kur

zwei

l

Remember?

The Matrix

http://en.wikipedia.org/wiki/Image:MouseBCI.jpg

http://docinthemachine.com/wordpress/wp-content/uploads/2006/09/matrix.jpg


computation

bio-chemically based computation, ubiquitous computation (anywhere, anytime), morphological computation with distributed intelligence, M3P Systems ("Many level, Many Unit, Many Purpose")

pervasive adaptation ('change' of ICT-systems as fundamental property so that they can develop, grow, self-assemble, replicate, evolve, adapt, repair and self-organise over long periods of time, life-like computation, emotional computation, biological & biohybrid modules for new forms of computation and enhanced interaction with the environment, programmable & intelligent materials (computational materials)

role of operating systems

connectivityunidirectional connectivity, cable-based

bi-directional connectivity, cable-based, fixed-wireless convergence, 1G/2G voice centric wireless (GPRS)

beyond fixed end-to-end connectivity paradigm: multi-directional connectivity, 2.5G/3G data-ventric wireless communication (UMTS)

pervasive communication and connectivity: flexible multi-directional decentralized connectivity, 4G wireless (Open Wireless Architecture); seamless unification of different kinds of networks (wireless, optical)

communication

one-to-one one-to-many

optimal scheduling and memory utilizationmanaging input-outputs from multiple networks (WiFi, Bluetooth, UMTS, etc.), managing mobility (who are the neighbours? Where are they?), managing reconfigurability (energy saving), managing

number-based, "turing computation", "one level, one unit, one purpose"

many-to-many, ubiquitous instant messaging online

Hey Baby – what‘s about having a

walk?

Ubiquituous computing:

You‘re boring!

http://www.flickr.com/photos/razorbern/273718609/

http://www.limsi.fr/

ERCIM News No.47, October 2001


networking attributes

no networkshomogenous proprietary fixed network structures

heterogenous interconnected networks, massively distributed interoperable pervasive computing, GRID-technology, 'middleware' as mediator between structure and content, seamless broadband communication networks spanning from the personal area to the regional and global area.

global networks on planetary scale, self-aware IT-networks, total interoperability of mobile, fixed, personal and corporateheterogeneous resources and applications with ubiquitous access, networked societies of artefacts

user attention

high user attentionuser more and more detached from application

agents single-agent approach multi-agent approach

complete agent' approach (agents that are embodied and self-sufficient, situated, e.g. able to acquire information through their own sensors and act accordingly, and autonomous, i.e. functioning independently without external control)

intelligent artificial agents with free association, creativity and empathy that can perceive, understand, and interact with their environment, but also evolve and learn in order to achieve human-like performance activities requiring context-specific knowledge

"away from user's attention", ubiquitous, subconsciously, embedded


intelligence stupid maturing

ambient intelligence (built-in) with contextual awareness, RFID tags/sensors as part of all-pervasive environment with intelligent interfaces, "towards natural cognition"

intelligent agent technology, configurable by metadata, representing the end-user, able to recall behaviours in context, to link to system-centric environment for contextual, historical and domain knowledge and utilise this in improving the interaction, "New cognitive paradigm", "Embodied Intelligence", "Swarm Intelligence"

internet not existing

Web1.0 (genesis of websites-1995) Web1.1. (Mass-capable 1998) Web 1.2. (More Service 2000)

Web 2.0 (blogs bringing dramatic changes in news and publishing; Wikipedia, OpenBC, Ajax etc.) 2005; Web 3.0 (melting pot; deeply integrated in physical environments) 2010

Web 4.0 and higher (trustful: managing and operating critical infrastructure; bridge between physical and virtual world via instrumented and managed sensorized physical environment; supporting pervasive computing, seamless access to networked instruments, supercomputers, storage etc.)

information selection

byte search string search semantic searchcontext-sensitive semantic search

trust and confidence

fragile single unit systems

vulnerable interdependent ICT systems, efforts in simplification, universality and convergence

eternal systems ("software that lasts 200 years"), extremely long-lived systems requiring minimal intervention and management to survive in spite of changes in usage, host device or network context

security of nanotechnologies and biocomputing (Quantum Cryptography, security of intelligent dust like future computer swamrs and massive nano-computers), security of reconfigurability and update of hardware and software at runtime

http://www.ics.forth.gr/ami/index.html


features of devices

one device for one purpose

multifunctional devices

ICT-devices learning from sophisticated perception systems mimicking humans and natural behaviour, ICT-devices involving properties of living materials including cognition, perception and action

self-repairing, healing ICT-devices with reconfigurable structures (self-designing, self-decision-making and self-maintaining software IT systems)

examples

audio cassettes, compact disk, handheld calculator, computer mouse, floppy disk, microprocessor, ethernet, laser printer, cellular phone, walkman, cray computer

mobile phones with multiple functions like camera, music player, PDA etc

Situated and cooperating smart devices (artefacts) with sensing, acting and computational capabilities 'hidden' in environment and communicating with each other, ICT everywhere – packaging, clothes, domestic devices, leisure devices, business systems, environmental systems, health systems, Smart Dust (large networks of sensors); "content everywhere and at anytime"

bio-electrical robots, nanobots, smart drugs, Artificial intelligent entities („artilects“) able to interpret and respond to human emotions


product-service shift

products; Data Poorproduct-service systems, Data Rich

personalized and context-aware services adopted to the user's environment ('Situated Services'), new solutions that combine technology and markets with geography and users, dynamic digital services to users anywhere anytime; Information Rich - Service Rich

universal personalized services, networks of cooperating services, seamless adaptive service systems

work-organization

centralized dezentralizedvirtual corporation, physical-virtual confluence

delegation to AIE (Artificial Intelligence Entitites)

shift from tera device computing with high energy consumption to a larger number of parallel but slower cores with less complexity; implementation of fuel cells for mobile applications

reducing computation to a minimal physical process, e.g. using natural dynamics of molecules (qubits)

energy issues

large energy consumption as a result of macro systems in place

increasing energy consumption as a result of economic growth and increasing number of high-performance chips (Giga device computing)

managing reconfigurability to reduce energy consumption,

http://www.flickr.com/photos/loobiloo/252373452/

Thank you for your attention

Joachim Hafkesbrink

Innowise GmbH, Germany

RIAS – Rhein-Ruhr Institute for Applied Systems Innovation e.V.

[email protected]

Tel. +49-171-12 0 11 77