smart data - the foundation for better business outcomes
TRANSCRIPT
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Smart Data - The Foundation for Better Business Outcomes
Adrian Bowles, PhDFounder, STORM Insights, Inc.
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Smart Data - The Foundation for Better Business Outcomes4 Major Themes for This Series
Cognitive Computing Smart Data and the Internet of Things Smart Data Management Transforming Business with Smart Data
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
(c) 2015 by STORM Insights, Inc.
Internet of Everything
Anal
ytic
s
Smart Data
Modern AICognitive
Connections
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.”
0. Foundation
Experience-Based
Learning1. Learn
2. Interact
3. ExpandIntegrate
Augmented/VirtualReality
Confidence-weightedReporting
Motivation
reflection
inference
Natural Cognitive Processes
deduction
Hypothesis Generation& Testing
reasoning
Natural Language Processing
Cloud
…Analytic
s
Data Management
Neu
rom
orph
icAr
chite
ctur
es Learning
Perception
A Framework for Cognitive Computing
Copyright (c) 2015-2016 by STORM Insights Inc. All Rights reserved.
Human
Sensors/Systems
Infrastructure
Input Output
DataManagement
Alt/NeuromorphicHardware
ProfessionalServices
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Machine Learning
Metamind
IBM
Ersatz Labs
Scaled Inference
Microsoft
IP Soft
Numenta
Digital Reasoning
Nervana Systems
BigML
Sentient Technologies
VicariousSkymind wise.io
Dato
Kimera SystemsH2OLoopAI Labs
AIBrain
Machine Learning
Human
Sensors/Systems
Infrastructure
Input Output
Visualization
Narrative Generation
Voice/NLP
Video/Images
Reports
Gestures
Emotions
Text/NLP
Surface Structured DataSurface Structured Data
Reports
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DataManagement
Alt/NeuromorphicHardware
ProfessionalServices
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Machine Learning
Human
Sensors/Systems
Infrastructure
Input Output
Voice/NLP
Gestures
Emotions
DataManagement
Alt/NeuromorphicHardware
ProfessionalServices
Video/Images
Text/NLP
Surface Structured DataSurface Structured Data
Reports
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 DataSurface Structured Data
Reports
DataManagement
Alt/NeuromorphicHardware
ProfessionalServices
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
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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
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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 regressionLogistic regression
(categorical dependent variable)Time-series analysisClassification treesDecision 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
Theme II. Smart Data and the Internet of Things
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
“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 Collaborative Intelligence
The Borg Lives!
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Citizens
Government Public Sensors
& Systems
Open Data
Open KnowledgeProprietary 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
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Copyright (c) 2014 by Umbrellium Ltd.
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Copyright (c) 2014 by Umbrellium Ltd.
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Copyright (c) 2014 by Umbrellium Ltd.
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Copyright (c) 2014 by Umbrellium Ltd.
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
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.
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Two Things Nobody Tells You About Data…
• All data is structuredGoogle 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.
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 I1968 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 IV2000 DSM IV-TR
Autism Spectrum Disorder (ASD)2013 DSM V
Theme IV. Transforming Business with Smart Data
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Cognitive Commerce
The Bazaar
e-commerce
Retail
Skill-based
Standard-based
Information-based
Knowlege/Learning-based
Exchange ModelsTime
Buyer Value
Your Opportunity
Has Arrived
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Business Model Framework
Biz Model
Market Opportunity
Revenue Model
Delivery Mechanism
Operational Keys
Goods/Svcs
Content (IP)
BusinessConsumer
Business
Consumer
Commerce
Subsidy
Consumer Data
AdsSponsorsSales
AuctionsDemographicsBehavioral
Psychographics
CommissionsTransaction feesCommissionsTransaction fees
EnglishDutch
Reverse CommissionsTransaction fees
Strategy Creative/ Branding
Technology
Infrastructure
COTS Applications
Custom Apps
Copyright (c) 2015 by STORM Insights Inc. All Rights reserved.
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)
For more information:
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Twitter @ajbowles Skype ajbowles
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Smart Data - The Foundation for Better Business OutcomesUpcoming 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 ThingsMay 12 Emerging Data Management Options: Graph Databases
Theme: Smart Data ManagementJune 9 Sense and Sensors- From Perception to Personality to
Themes: Smart Data and the Internet of Things, Cognitive Computing
[email protected] Twitter @ajbowles Skype ajbowles