We will kickoff the 2017 series with an overview of the current state of commercial artificial intelligence (AI) and cognitive computing. The research and commercial communities are far from consensus on a few important definitions, so we will start with two that are critical to our understanding and analysis. #ModernAI applies research from computer science, psychology, mathematics, linguistics and neuroscience to develop problem-solving applications that supplant or augment human intellectual performance. Unlike more traditional AI R&D, #ModernAI typically leverages machine learning and big data. Cognitive computing is a problem-solving approach based on #ModernAI that focuses on processes for understanding, reasoning, learning and planning. In this webinar, we will present a framework for analyzing modern AI/cognitive computing tools and technologies, with an emphasis on the risks and reward of adopting them at varying stages of maturity.

1. #ModernAI and Cognitive Computing
Boundaries and Opportunities
Adrian Bowles, PhD
Founder, STORM Insights, Inc.
info@storminsights.com
Copyright (c) 2017 by STORM Insights Inc. All Rights Reserved.
JANUARY 12, 2017

2. #ModernAI
Cognitive Computing
Trends
Technology & Market Maturity
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AGENDA

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#MODERNAI
Conventional
AI

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#ModernAI
Conventional
AI
PERCEPTION
UNDERSTANDING
LEARNING
PLANNING
MOTIVATION PROBLEM-SOLVING

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#ModernAI
Conventional
AI
PERCEPTION
UNDERSTANDING
LEARNING
PLANNING
Hardware
Software
Mimic Model
MOTIVATION PROBLEM-SOLVING

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#ModernAI
Conventional
AI
Machine
Learning

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#ModernAI
Conventional
AI
Machine*
Learning
SUPERVISED
UNSUPERVISED
REINFORCEMENT
DEEP
*April 13 Webinar: Machine Learning:
Moving Beyond Discovery to Understanding

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#ModernAI
Conventional
AI
Machine
Learning
Big
Data
STREAMING
COMPLEX
YUGE

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#ModernAI
Conventional
AI
Machine
Learning
Big
Data
Hardware
Software
Neuromorphic
TPUs
NPUs
GPUs
Mimic
GPUs
?
Model
HTM
MBR
Neural Nets

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THE #MODERNAI HARDWARE MARKET IS REAL
Facebook
FAIR
NVIDIA
Google
TPU
IBM
TrueNorthQualcomm
NPU
Neuromorphic
GPU/
Memory Acceleration
Ready Now
Much More in the Pipeline
Promising -
Ready Now At Handset Level
Proven approach for ||ism
Easy interoperability
with conventional systems
+Natural behavioral process model
+Lower power requirements
- Requires new software model
& skills
Nvidia
Intel
AMD
Facebook (FAIR)
Nervana Systems/Intel
Movidius - Intel (Vision processing)
Google TPU
IBM
Qualcomm

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A FRAMEWORK FOR COGNITIVE COMPUTING
Motivation
reflection
inference
Natural Cognitive Processes
deduction
reasoning
Learning
Perception
Foundation
Experience-
Based
Learning
Learn
Interact
Expand
Integrate
Augmented/Virtual
Reality
Confidence-
weighted
Reporting
Hypothesis
Generation
& Testing
Natural
Language
Processing
Cloud
…
Analytics
Data Management
Neuromorphic
Architectures

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Hearing (audioception)
~12,000 outer hair cells/ear
~3,500 inner hair cells
Vision (ophthalmoception)
Photoreceptors - Per Eye
~120,000,000 rod cells
(triggered by single photon)
~6,000,000 cone cells
(require more photons to trigger)
~ 60,000 photosensitive
ganglion cells
Touch (tactioception)
Thermoreceptors, mechanoreceptors,
chemoreceptors and nociceptors for touch, pressure, pain,
temperature, vibration
Smell (olfacoception)
Chemoreception
Taste (gustaoception)
Chemoreception
Human Cognition
~100,000,000,000 (100B) Neurons
~100-500,000,000,000,000 (100-500T) Synapses
NEUROSYNAPTIC PROBLEM SOLVING SCOPE: PERCEPTION VS COGNITION
Learn
ModelReason
Understand
Plan

13. Model
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COGNITIVE COMPUTING FUNDAMENTALS

14. Model
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COGNITIVE COMPUTING FUNDAMENTALS
A Model is an Abstract Representation of Reality

15. Model
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Model
The Corpus, Assumptions, Algorithms
Used to
Generate & Score Hypotheses
or
Calculate Associative Distance
COGNITIVE COMPUTING FUNDAMENTALS

16. Model
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Model
The Corpus, Assumptions, Algorithms
Used to
Generate & Score Hypotheses
or
Calculate Associative Distance
Corpus
The complete machine-readable
record of a domain.
Associative Distance
A metric for the similarity of two items
based on their relative locations in n-
space according to an algorithm.
Assumptions
Implicit or explicit data or
relationships held to be valid.
Hypothesis
An evidence-based testable
assertion that explains a
phenomenon or relationship.
COGNITIVE COMPUTING FUNDAMENTALS

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PROXIMITY/DISTANCE ALGORITHMS
Mapped with vectors,
proximity algorithm
based on purpose.
Mapping for autocorrect/complete vs Mapping for meaning
Boy
Bay
Map
Mop
Man
Nay May
Mope
Buy
Hop Hope
Boy
Bay
Map
Mop
Man
Nay
May
Mope
BuyHop
Hope
Similar structure ->
similar meaning in
vision, not always
in language.

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PREDICTIVE ANALYTICS: RELATED CONCEPTS
The use of statistical algorithms and a set of assumptions - the
model - to identify the likelihood of future outcomes or missing
values based on patterns in historical data.
Linear regression
Logistic regression
(categorical dependent variable)
Time-series analysis
Classification trees
Decision trees…
Historical
Data
Predicted
Data
Assumptions

19. Learn
Understand
Model
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COGNITIVE COMPUTING FUNDAMENTALS

20. Learn
Understand
Model
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Understand
Awareness of the
meaning of data.
Learn
To acquire understanding
of data.
COGNITIVE COMPUTING FUNDAMENTALS

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THE LINGERING QUESTION: WHAT IS UNDERSTANDING?
Sentiment/Emotion/Theme/Concept Analysis
Don’t let the search for perfection interfere with the path to progress.

22. MULTI-DIMENSIONAL UNDERSTANDING
Source: IBM Bluemix

23. Learn
Plan Reason
Understand
Model
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Understand
Awareness of the
meaning of data.
Learn
To acquire understanding
of data.
Plan (v)
Identify a goal/desired state
and a set of steps/activities
to reach that state.
Reason (v)
An evidence-based process
for determining the truth or
probability of a conclusion.
Reasoning
Deductive
Inductive
Abductive…
COGNITIVE COMPUTING FUNDAMENTALS

24. Learn
Plan Reason
Understand
Model
Data Mgmt
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COGNITIVE COMPUTING FUNDAMENTALS

25. Systems
Controls
Learn
Plan Reason
Understand
Model
Data Mgmt
Human
Machine
Input Output
Sensors
(IOT)
Systems
Controls
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COGNITIVE SYSTEMS: COMMUNICATIONS & CONTROL

26. Systems
Controls
Learn
Plan Reason
Understand
Model
Data Mgmt
Human
Machine
Input Output
Gestures
Emotions
Language
Narrative Generation
Visualization
Reports
Haptics
Sensors
(IOT)
Systems
Controls
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COGNITIVE SYSTEMS: COMMUNICATIONS & CONTROL
Perception

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KEY TRENDS
Open Source and ML
ML as a Service
Perception as a Service

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KEY TREND: OPEN SOURCE ML

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MACHINE LEARNING AS A SERVICE

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MACHINE LEARNING & PERCEPTION AS A SERVICE
Source: IBM BlueMix

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KEY TREND: PERCEPTION AS A SERVICE
Source: Affectiva
Affectiva: Emotion Detection
Anger
Sadness
Disgust
Joy
Surprise
Fear
Contempt

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#MODERNAI MATURITY TRENDS
Maturity
BigData
Management
Machine
Learning
Perception Motivation
4
3
2
1
0

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COGNITIVE COMPUTING MATURITY TRENDS
Maturity Understanding Learning Reasoning Planning
4
3
2
1
0

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THEY’RE HERE. WHERE DO WE GO NEXT?
Alexa, who’s smarter,
you or Siri?
Alexa, how old is
Dan Rather?

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FOR MORE INFORMATION
adrian@storminsights.com
Twitter @ajbowles
Skype ajbowles
Upcoming 2017 Webinar Dates & Topics
February 9 Artificial General Intelligence - When I Can I Get It?
March 9 Data Science and Business Analysis:
A Look at Best Practices for Roles, Skills, and Processes
April 13 Machine Learning - Moving Beyond Discovery to Understanding