This webinar will explore emerging technologies that enable a new generation of intelligent applications and enterprise systems. It will also act as a roadmap for evaluating and integrating these technologies and practices, and set the stage for our 2016 series of Smart Data webinars. In the last few years, we have witnessed an AI renaissance with significant advances in areas such as machine-learning/deep learning, natural language processing, and biologically-inspired processor architectures. Simultaneously, the rise of the Industrial Internet of Things - which together with the “traditional” Internet form the Internet of Everything – foreshadows a connected world of smarter homes, cities, and even business relationships. These “cognitive connections” are supported by advanced analytics and smart data. Join the discussion to see how you and your organization can benefit from getting started now.

1. Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Smart Data - The Foundation for Better Business Outcomes
Adrian Bowles, PhD
Founder, STORM Insights, Inc.
info@storminsights.com

2. Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Smart Data - The Foundation for Better Business Outcomes
4 Major Themes for This Series
Cognitive Computing
Smart Data and the Internet of Things
Smart Data Management
Transforming Business with Smart Data

3. Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
(c) 2015 by STORM Insights, Inc.
Internet of
Everything
Analytics
Smart Data
Modern AI
Cognitive
Connections

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8. Theme I. Cognitive Computing
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“Cognitive computing is an approach to problem-solving using hardware or software that approximates the form or function of natural cognitive processes.”

9. 0. Foundation
Experience-
Based
Learning
1. Learn
2. Interact
3. Expand
Integrate
Augmented/Virtual
Reality
Confidence-
weighted
Reporting
Motivation
reflection
inference
Natural Cognitive Processes
deduction
Hypothesis
Generation
&Testing
reasoning
Natural
Language Processing
Cloud
…
Analytics
Data Management
Neuromorphic
Architectures
Learning
Perception
A Framework for Cognitive Computing
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10. Machine Learning
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11. Human
Sensors/
Systems
Infrastructure
Input Output
Data
Management
Alt/Neuromorphic
Hardware
Professional
Services
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Machine Learning
Metamind
IBM
Ersatz Labs
Scaled
Inference
Microsoft
IP Soft
Numenta
Digital Reasoning
Google
Nervana Systems
BigML
Sentient
Technologies
VicariousSkymind wise.io
Dato
Kimera SystemsH2O
LoopAI Labs
AIBrain

12. Machine Learning
Human
Sensors/
Systems
Infrastructure
Input Output
Visualization
Narrative Generation
Voice/NLP
Video/Images
Reports
Gestures
Emotions
Text/NLP
Surface Structured Data
Surface Structured Data
Reports
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Data
Management
Alt/Neuromorphic
Hardware
Professional
Services

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Machine
Learning
Human
Sensors/
Systems
Infrastructure
Input Output
Voice/NLP
Gestures
Emotions
Data
Management
Alt/Neuromorphic
Hardware
Professional
Services
Video/Images
Text/NLP
Surface Structured Data
Surface Structured Data
Reports

14. Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Machine
Learning
Human
Sensors/
Systems
Infrastructure
Input Output
Visualization
Narrative Generation
Video/Images
Reports
Text/NLP
Surface Structured Data
Surface Structured Data
Reports
Data
Management
Alt/Neuromorphic
Hardware
Professional
Services

15. Narrative Generation
Voice/NLP
Video/Images
Gestures
Emotions
Text/NLP
• Affectiva
• BeyondVerbal
• Emotient Apple!
• Limbic
• Nviso
• Gridspace
• IBM
• Maluuba
• MindMeld
• Nuance
• PopupArchive
• Skymind
• Viv Labs
• Wit.ai
• ABBYY
• Altilia
• Cortical.io
• IBM
• Kaypok
• Luminoso
• Maluuba
• Wit.ai
• BRS Labs
• Clarifai
• Dextro
• Madbits (twitter)
• Mindops
• Skymind
• Teradeep
• Visenze
• Narrative Science
• OnlyBoth
• APX Labs
• EyeSight
• GestureTek
• LeapMotion
• Nod
• Intel
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Analytics/Visualization
• 1010data
• Adatao
• Alpine Data Labs
• Alteryx
• Altilia
• Angoss
• Attivio
• Birst
• Civis Analytics
• ClearStoryData
• Connotate
• Context Relevant
• Dataiku
• Datameer
• Emerald Logic
• Finch Computing
(was Synthos)
• First Rain
• ForeSee
• Fractal Analytics
• Guavus
• IBM
• indico
• KNIME
• KXEN (SAP)
• LiftIgniter
• MathWorks (Matlab)
• Microsoft
• Mu Sigma Nara Logics
• NuTonian
• Opera Solutions
• Oracle
• Palantir
• Pentaho
• Prediction IO
• Predixion
• Qliktech
• Quid
• Rapid Miner
• Revolution Analytics(MSFT)
• Salford Systems
• SAP
• SAS Institute
• SiSense
• Spark Beyond
• Spotfire (Tibco)
• StatSoft (Dell)
• Teradata
• Versium
• Wolfram Mathematica
• Yhat
Data Management
• Actian
• Aerospike
• Alation
• Basho
• Caspio
• Cognizant Technology
• Couchbase
• CrowdFlower
• CumuLogic
• Data Bricks
• DataRPM
• DataStax
• DataWeb, Inc.
• DDN
• diffbot
• GigaSpaces
• GridGain
• Hortonworks
• IBM
• import io
• kimono
• MapR
• MarkLogic
• MongoDB
• NeoTechnology
• Oracle
• Paxata
• RainStor
• SAP
Alt/Neuromorphic
Hardware
• Artificial Learning
• DWave
• HRL Laboratories
• IBM
• Nervana Systems
• Nvidia
• Qualcomm
• Teradeep

16. Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Technology Builders App/System Builders
Investors Consumers/Users
Analytics/Insights
as a Service
Delivery is migrating
to a service-oriented
business model.
“app store” models call for revenue
sharing. Revenue/profit splits need to
reflect current value so contracts
should allow for changes to reflect
market conditions.
For paid subscription sites, buyers
may place a premium on owning/
licensing results with personally
identifiable data, or simply want
perpetual access to results. This will
drive new business models.
Investors are driving this
movement - no specific action
recommended.
Pay as you go analytics and
CC services will be a big market.
The insights gained during operation
hold real value, so capturing them
for future engagements should be a
strategic goal.
Analytics as a Service
Insights as a Service
Business Trend:

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Predictive analytics: 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

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• Identify the assumptions
• Validate the assumptions
THERE ARE ALWAYS ASSUMPTIONS…They are often wrong
• Customers with common buying histories will have common buying futures
• Past is prelude - if consumption of a commodity has been cyclical, it will
remain cyclical
• If we find a correlation in demand (beer/diapers) we can ignore causation
Predictive analytics: 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.
If you’re not predicting, you’re just reporting

19. Theme II. Smart Data and the Internet of Things
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“The Internet of Things
is the new Industrial Revolution.”
Dr. John Bates, 11/17/2015

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When everything is connected…
New sources of data emerge
New sources of value emerge
Old assumptions must be challenged
The Impact of the IOT

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IOT enables
New technologies
New models
New ecosystems

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Intelligence can be
Local to the device
Distributed
Aggregated

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Smarter Cities
IOT Meets Cognitive

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Smarter Cities
IOT Meets Cognitive

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Smarter Cities
IOT Meets Cognitive

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Smarter Cities
Collaborative Intelligence
The Borg Lives!

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Citizens
Government
Public Sensors
&
Systems
Open Data
Open Knowledge
Proprietary
Knowledge
Commercial
Enterprises:
Private Sensors
&
Systems
Commercial Proprietary
Data
Government Proprietary
Data
Voluntary
Involuntary - Includes
social media
Foundations of Cognitive Computing for Smarter Cities
from Cognitive Computing and Big Data Analytics, Hurwitz, Kaufman & Bowles, 2015
IoT As a Cognitive Enabler

30. Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Copyright (c) 2014 by Umbrellium Ltd.

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Copyright (c) 2014 by Umbrellium Ltd.

32. Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Copyright (c) 2014 by Umbrellium Ltd.

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Copyright (c) 2014 by Umbrellium Ltd.

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Principle: The IOT creates high-value opportunities for low-latency applications.
Example: Devices that can communicate with an individual (via mobile device,
wearable, etc) can create value if they have the right information about the
individual. From variable pricing of soda in a machine to suggesting a purchase
to offering a discount if a customer walks past an item believed to be of interest,
the applications need to be able to run the analytics in time to make a
recommendation.
Implication: Data needs to be close enough to process while the results are still
valuable. Availability is critical.

35. Theme III. Smart Data Management
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Two Things Nobody Tells You About Data…
• All data is structured
Google used a neural network with16,000 processors to search
10,000,000 images from YouTube to identify…cats.
• Beliefs change, truth doesn’t
Representing belief as fact will eventually trip up any system
“Facts change in regular and mathematically understandable ways.”
Samuel Arbesman, The Half-life of Facts, 2012, Penguin Books.

37. Copyright (c) 2014-2016 by STORM Insights Inc. All Rights reserved.
Perception: obvious structure is easy to process…
but most of the interesting stuff isn’t obvious to a computer.

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1952 DSM I
1968 DSM II
Pervasive Developmental Disorder (PDD)
Childhood onset PDD Infantile Autism Atypical Autism
1980 DSM III
Taxonomies Evolve
The History of Autism in the Diagnostic & Statistical Manual of the American Psychiatric Association
Pervasive Developmental Disorder (PDD)
PDD-NOS Autistic Disorder
(Not Otherwise Specified)
1987 DSM III-R
Pervasive Developmental Disorder (PDD)
PDD-NOS Autistic Disorder Asperger Disorder Childhood Disintegrative Disorder Rett Syndrome
1994 DSM IV
2000 DSM IV-TR
Autism Spectrum Disorder (ASD)
2013 DSMV

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40. Theme IV. Transforming Business with Smart Data
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.

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Cognitive
Commerce
The Bazaar
e-commerce
Retail
Skill-based
Standard-based
Information-based
Knowlege/Learning-based
Exchange Models
Time
Buyer
Value
Your
Opportunity
Has
Arrived

42. Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Business Model Framework
Biz Model
Market
Opportunity
Revenue
Model
Delivery
Mechanism
Operational
Keys
Goods/Svcs
Content (IP)
Business
Consumer
Business
Consumer
Commerce
Subsidy
Consumer
Data
Ads
Sponsors
Sales
Auctions
Demographics
Behavioral
Psychographics
Commissions
Transaction fees
Commissions
Transaction fees
English
Dutch
Reverse Commissions
Transaction fees
Strategy Creative/
Branding
Technology
Infrastructure
COTS
Applications
Custom Apps

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Do you have a good candidate app?
Start with the hard questions!
Do you have the skills?
Do you have the data?
Are your customers ready for probabilistic or non-deterministic answers?
(can they deal with uncertainty and multiple possible answers?)
Does anybody else have the data?
Will NLP add value in the eyes of your customers?
How important is it to be able to explain how the system got an answer or made a
recommendation…? (medical diagnosis - HIGH, recommending a sweater, not so much)
How important is it for the system to improve its performance over
time? (vs consistent answers)

44. For more information:
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
adrian@storminsights.com
Twitter @ajbowles
Skype ajbowles

45. Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Smart Data - The Foundation for Better Business Outcomes
Upcoming Webinar Dates & Topics
February 11 A Roadmap for Deploying Modern AI in Business
Theme: Transforming Business with Smart Data
March 10 Machine Learning Adoption Strategies
Theme: Cognitive Computing
April 14 Getting Started with Streaming Analytics and the IoT
Theme: Smart Data and the Internet of Things
May 12 Emerging Data Management Options: Graph Databases
Theme: Smart Data Management
June 9 Sense and Sensors- From Perception to Personality to
Themes: Smart Data and the Internet of Things, Cognitive Computing
adrian@storminsights.com Twitter @ajbowles Skype ajbowles