The document discusses the evolution of computing and cognitive systems from the past to the projected future. It describes how cognitive assistants are beginning to appear for various occupations currently, and how they will become more advanced and ubiquitous over time, with tools being available for nonexperts to build their own assistants. The talk outlines a vision of Reality 2.0 where cognitive systems are integrated into most areas of work and life to enhance productivity and creativity by 2035 and beyond.

1. Cognitive Systems Institute Group (CSIG)
Jim Spohrer (IBM)
Washington, DC USA,
Wednesday March 23, 2016
http://www.slideshare.net/spohrer/spohrer-aaas-reality2-20160214-v3
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2. Why I am in town
3/23/2016
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CSIG

4. Computing: Then, Now, Projected
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2035
2055

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1955 1975 1995 2015 2035 2055

6. What exists in 2016?
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360,000 100,000 120,000 60,000 150,000

7. Cognitive Assistants for all occupations
are beginning to appear
3/23/2016
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Cognitive Assistants
for all occupations

9. Occupations = Many Tasks
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10. Watson Discovery Advisor
3/23/2016
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Simonite, T. 2014. Software Mines Science Papers to Make New Discoveries. MIT. November 25, 2014.
URL: http://m.technologyreview.com/news/520461/software-mines-science-papers-to-make-new-discoveries/

11. User Models
3/23/2016
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13. How fast is Reality 2.0 approaching?
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What might it look like?

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What might Reality 2.0 look like?

15. Courses
2015
– “How to build a cognitive system for Q&A task.”
– 9 months to 40% question answering accuracy
– 1-2 years for 90% accuracy, which questions to reject
2025
– “How to use a cognitive system to be a better professional X.”
– Tools to build a student level Q&A from textbook in 1 week
2035
– “How to use your cognitive assistant to build a startup.”
– Tools to build faculty level Q&A for textbook in one day
– Cognitive mediator knows a person better than they know themselves
2055
– “How to manage your workforce of cognitive assistants.”
– Most people have 100 cognitive assistants working for them.
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16. By 2035, T-Shaped Makers will with great
Building Blocks and Cognitive Mediators
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Empathy & Teamwork
sector
region/culture
discipline
Depth
Breadth
STEM
Liberal Arts

17. Learning to program:
My first program
3/23/2016
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Early Computer Science Class:
Watson Center at Columbia 1945
Jim Spohrer’s
First Program 1972

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20. Reality 2.0 Service Platform
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Service Platform
CM1
P2
CM1
P1
100x
100x 100x

21. In Summary
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“A service science
perspective considers
the evolving ecology of
service system entities,
their value co-creation and
capability co-elevation
interactions, and their
capabilities, constraints,
rights, and responsibilities.”
Cognitive Systems
Entities
Service
Systems
Entities With
Cognitive
Mediators
Add Rights &
Responsibilities

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Smart Service System:
All entities’ in network
use cognitive mediators
to enhance
value co-creation interactions
Cognitive Mediators:
Cognitive systems
with deep knowledge of both
customer (user) and provider (expert)
as co-creators of win-win value
Entity augmentation boosts both creativity and productivity of interactions

24. Sciences provide…
• Frameworks for people to ask and answer
questions systematically
• Explanations with instructions on “how to re-do”
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Kline: Conceptual Foundation of Multidisciplinary Thinking -
“To our children and children’s children,
to whom we elders owe an explanation of the world
that is understandable, realistic, forward-looking, and whole.”
Proenneke:
Alone in the Wilderness -
To do a thorough testing,
should each generation
be required to rapidly rebuild
from scratch?
A re-makers movement?

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Explain external
phenomena

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Explain internal
phenomena

27. 3/23/2016
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Explain
value co-creation
phenomena

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Physics Chemistry Biology
Neuroscience Psychology Artificial
Intelligence
Engineering Management Public
Policy
Education Design Humanities
Natural Systems
Cognitive Systems
Service Systems

29. Watson Platform on BlueMix
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30. New Era of Computing:
Cognitive Technologies & Componentry
30
 Natural Language
– Reasoning, Logic & Planning
– Symbolic Processing
– Natural Language Processing
– Ranking of Hypotheses
– Knowledge Representations
– Domain-Specific Ontologies
– Information Storage/Retrieval
– Machine Learning, Reasoning
– Von Neumann Componentry
– OpenPOWER Systems
 Pattern Recognition
– Recognition, Sensing & Acting
– Pattern Processing
– Image & Speech Processing
– Ranking of Hypotheses
– Pattern Representations
– Domain-Specific Neural Nets
– Information Storage/Retrieval
– Machine Learning, Perception
– Neuromorphic Componentry
– TrueNorth & Corelets Systems
AI for IA:
Intelligence
Augmentation
(Engelbart’s Visiion)
Cognitive Assistants
(“Cogs”) that boost
creativity and
productivity of people in
smart service systems.
Cognition as a Service
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IBM Cloud Bluemix

31. The Maker Movement &
Open Source Ecology
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32. So what does this have to do with
programming and computation?
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Both Turing and von Neumann dreamed of universal machines and constructors

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1955 1975 1995 2015 2035 2055
2035 one human brain/2055 all human brains

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35. What exists in 2016?
3/23/2016
© IBM 2015, IBM Upward University
Programs Worldwide accelerating regional
development
35
360,000 100,000 120,000 60,000 150,000

36. Cognitive Assistants for all occupations
are beginning to appear
3/23/2016
© IBM 2015, IBM Upward University
Programs Worldwide accelerating regional
development
36

37. 3/23/2016
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development
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Cognitive Assistants
for all occupations

38. Occupations = Many Tasks
3/23/2016
© IBM 2015, IBM Upward University
Programs Worldwide accelerating regional
development
38

39. Watson Discovery Advisor
3/23/2016
© IBM 2015, IBM Upward University
Programs Worldwide accelerating regional
development
39
Simonite, T. 2014. Software Mines Science Papers to Make New Discoveries. MIT. November 25, 2014.
URL: http://m.technologyreview.com/news/520461/software-mines-science-papers-to-make-new-discoveries/

40. User Models
3/23/2016
© IBM 2015, IBM Upward University
Programs Worldwide accelerating regional
development
40

41. Brief History
of AI
1956 – Dartmouth Conference
1956 – 1981 Micro-Worlds
1981 – Japanese 5th Generation
1988 – Expert Systems Peak
1990 – AI Winter
1997 – Deep Blue
1997 – 2011 Real-World
2011 – Jeopardy! & SIRI
2013 – Cognitive Systems Institute
2014 – Watson Business Unit &
True North Brain Chip
2015 – “Cognition as a Service”
on IBM Bluemix
3/23/2016
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43. 3/23/2016
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44. IBM TrueNorth Chip
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45. 3/23/2016
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46. Assisting individuals and organizations
to close their service innovation skills gap
and co-create smarter service systems
empowering employees, customers, citizens
with cognitive mediators
in the collaborative service economy

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48. © 2011 IBM Corporation
Dharmendra S. Modha, PhD
Senior Manager, Cognitive Computing; Principal Investigator, SyNAPSE
SyNAPSE

49. © 2008 IBM Corporation
The brain is very good at integrating and co-ordinating
multiple sensory inputs and motor outputs…
while occupying a
small volume…
…and consuming
very little power

50. © 2010 IBM Corporation
IBM Research
Computers and the Brain: Different & Complementary
10 Hz, parallel, high fanout,
event-driven
Integrates memory,
computation, communication
10 mW/cm2
~5 GHz, sequential, linear,
clocked
Separates memory,
computation, communication
100 W/cm2

51. © 2010 IBM Corporation
IBM Research
DARPA SyNAPSE End Goal
“develop electronic neuromorphic machine technology that scales to
biological levels”
1014 synapses
neurons firing at 10Hz in 2 liters, 1kW at real-time

52. IBM Research
© 2010 IBM Corporation52
Phase 0, 1, 2, 3, 2008-, $53.5M

53. © 2010 IBM Corporation
IBM Research
53
Summary

54. © 2010 IBM Corporation
IBM Research

55. © 2010 IBM Corporation
IBM Research
IBM Confidential
How It Works:
“neurons”, “synapses”, “axons”, “dendrites”
• Integrates
memory
computation
communication
• Local data
movement
• Event-driven
• Reconfigurable
• Ultra-low power
• Compact

56. © 2010 IBM Corporation
IBM Research
56
Synapses
Neurons
Scheduler
256 neurons, 64K synapses, 1MHz
field-adaptable
Seo et al., 2011
256 neurons, 256k synapses,
asynchronous, 45 pJ/spike
field-programmable
Merolla et al., 2011; Arthur et al., 2012
Demonstrated Two Neurosynaptic Cores

57. © 2010 IBM Corporation
IBM Research
57
TrueNorth Architecture

58. IBM Research
© 2010 IBM Corporation
Von Neumann versus TrueNorth for brain-like computation
Neuron(s) Bus
Neuron Synapse
Communication
Neuron Synapse
Communication
Neuron Synapse
Communication
Neuron Synapse
Communication
Neuron Synapse
Communication
Neuron Synapse
Communication
Neuron Synapse
Communication
Neuron Synapse
Communication
Neuron Synapse
Communication
Memory Wall / Bottleneck
Synapse Synapse Synapse
Synapse Synapse Synapse
Synapse Synapse Synapse
CPU Memory

59. IBM Research
© 2010 IBM Corporation
SyNAPSE Stack

60. IBM Research
© 2010 IBM Corporation
NeoVision

61. IBM Research
© 2010 IBM Corporation
SyNAPSE Stack

62. IBM Research
© 2010 IBM Corporation

63. IBM Research
© 2010 IBM Corporation

64. IBM Research
© Copyright IBM Corporation 2009
IBM Proprietary
Von Neumann:
“Left Brain Computing”
SyNAPSE:
“Right Brain Computing”
Sequential,
Analytical
Text, numbers,
symbolic
Front-end,
back-end
intelligence
Von Neumann
Architecture
High Power and
Area
Simultaneous,
Synthetic
Sense-act, sub-
symbolic
In-situ,
physical
intelligence
Non-von
Neumann
Arch
Low Power and
Area