Build a Future with Ai
Jerry O’Brien
Cognitive Entrepreneur
President of the Boston
Machine Learning
Society
IBM Cloud & Cognitive
Evangelist
Origin's of Artificial Intelligence
Expert Systems
Statistical Learning
Contextual Adaptation
Programed rules system that
emulates the decision-making
ability of a human expert.
Finding a predictive function
based on data.
Systems construct exploratory
models for classes of real world
phenomena
Eliza, MIT, 1964
Self Driving Cars, 2004
Self Driving Cars, 2005
THE FUTURE
Statistical
Learning
"A computer program is said to learn from
experience E with respect to some class of tasks
T and performance measure P, if its performance
at tasks in T, as measured by P, improves with
experience E.”
~Tom Mitchell
Linear Algebra
Probability Theory
Statistics
Multivariate Calculus (Differentiation/gradients)
The biggest taxi company
owns no cars.
The largest accommodation company
owns no real estate.
The biggest media company
owns no content.
The largest retailer
carries no inventory.
Disruption is upon us.
This disruption is fueled by three forces.
The powerful capabilities and
outcomes brought on by
cognitive computing.
The ability to build
business in code with the
API economy.
The proliferation of different
types of data.
Oil & Gas
80,000 sensors in a facility
produce 15 petabytes of data
Public Safety
520 terabytes of data are produced
by New York City's surveillance cameras each day
Energy & Utilities
680m+ smart meters will produce
280 petabytes of data by 2017
Healthcare
The equivalent of 300 million books of health
related data is produced per human in a lifetime
Watson
Narrative
2010 2020
Sensors
& Devices
Text
Data
Images/
Multimedia
Gap
Enterprise Traditional
You are here
2017
>2.5PB
of customer data
stored by Walmart
every hour.
292 exabytes
of mobile traffic by
2019, up from 30
exabytes in 2014
1TB
of data produced by a
cancer patient every
day.
WE FACE AN OVERWHELMING AMOUNT OF DATA IN EVERY INDUSTRY
44 ZETTABYTES
1,200,000
lines of code in
a smartphone
80,000
lines of code in
a pacemaker
100,000,000
lines of code in
a new car
5,000,000
lines of code in
smart appliance
More devices are creating
more information.
Three capabilities differentiate cognitive systems from
traditional programmed computing systems…
Reasoning
They reason. They understand
underlying ideas and concepts. They
form hypothesis. They infer and extract
concepts.
Learning
They never stop learning getting more
valuable with time. Advancing with
each new piece of information,
interaction, and outcome. They
develop “expertise”.Understanding
Cognitive systems understand like
humans do.
…. allowing them to interact with humans.
Cognitive systems democratize
innovation by scaling knowledge.
Sensors Data Analytics Information Cognitive
Ingestion, Integration, Governance
Humans excel at:
Dilemmas
Compassion
Dreaming
Abstraction
Imagination
Morals
Generalization
Cognitive Systems
excel at:
Common Sense
Natural Language
Locating Knowledge
Pattern Identification
Machine Learning
Eliminate Bias
Endless Capacity
Cognitive systems forge a new partnership
between man and machine.
13©2016 IBM Corporation
of not knowing.
The price
Examples include:
Analyst reports
tweets
Wire tap transcripts
Battlefield docs
E-mails
Texts
Forensic reports
Newspapers
Blogs
Wiki
Court rulings
International crime database
Stolen vehicle data
Missing persons data
Data, information, and expertise create the
foundation.
Cognitive systems rely on collections of data
and information:
Complicated
Retrieve and Rank
Entity Extraction
Sentiment Analysis
Emotion Analysis (Beta)
Keyword Extraction
Concept Tagging
Taxonomy Classification
Author Extraction
Language Detection
Text Extraction
Microformats Parsing
Feed Detection
Linked Data Support
Concept Expansion
Concept Insights
Dialog
Document Conversion
Language Translation
Natural Language Classifier
Personality insights
Relationship Extraction
Retrieve and Rank
Tone Analyzer
Emotive Speech to Text
Text to Speech
Face Detection
Image Link Extraction
Image Tagging
Text Detection
Visual Insights
Visual Recognition
AlchemyData News
Tradeoff Analytics
50 underlying technologies
… then leverage Watson APIs to apply
cognitive capabilities.
Natural Language Cl
assifier
Tone Analyzer
Watson at work in the world.
"Woodside to tap into
IBM's Watson” - CIO
"IBM’s Watson Now Powers AI
For Under Armour”
- TechCrunch
"SoftBank's Pepper robot is getting an
intelligence boost from IBM's Watson"-
The Verge
"Medtronic, IBM team up on diabetes app to
predict possibly dangerous events hours
earlier."- The Washington Post
"IBM’s Watson Helped Pick Kia’s
Super Bowl ‘Influencers’”
- Wall Street Journal
"How Can I Help You? IBM's Watson
Powers Hilton's Robotic Concierge" -
Fast Company
"IBM and Apple can put Watson's
A.I. insights inside Apple Watch"-
ComputerWorld
"Thomson Reuters to deploy IBM
Watson technology”
- InfoTechLead
"IBM's Watson Lands A Job With
KPMG.” -InformationWeek
"The North Face Uses IBM's
Watson to Make Online Shopping
Smarter" -The Street
Watson at work in the world.
The market is validating the benefits of
cognitive.
“IBM Crafts a Role for Artificial
Intelligence in Medicine.”
“IBM Watson represents a bold
technological and visionary step”
“What is distinctive about IBM is the breadth
of its effort to create Watson tools … for a
wide range of developers.”
‘You can't do this without Watson. -Former Sun
CEO Scott McNealy. His startup, Wayin, uses
Watson to trawl and drag photos.
“The worldwide cognitive software platforms
market will grow to $30 billion by 2018, at a
CAGR”
IDC: Worldwide Cognitive Software Platforms Forecast, 2015-2019: The
Emergence of a New Market (#258781, September 2015, David
Schubmehl)
“[Watson] is specifically designed to support
the development of a broad range of enterprise
solutions.”
“No doubt, Watson has the means to radically
change the industry. “
IDC: IBM’s Go-to-Market Transformation – Deeper, Wider, Newer
(#AP257527, April 2015, Chris Zhang, Sabharinath Balasubramanian, Mayur
Sahni)
“IBM’s [Watson] can help banks with complex
financial operations and attack important
health care problems.”
“…it’s not just AI algorithms themselves that have
improved, but the ability to deliver them”
© 2015 INTERNATIONAL BUSINESS MACHINES CORPORATION
Where do I start?
A Frame of Mind
Outcome
Outcome Workflow
Data
Decision
Outcome
• What Outcome am I predicting?
• What Question am I answering?
• Who needs to know?
• Where should it be known?
Outcome Workflow
Outcome
Outcome Workflow
• Where do I go for information?
• Who do I ask?
• How do I get it?
• What database do I query?
• What Outcome am I
predicting?
• What Question am I
answering?
• Who needs to know?
• Where should it be
known?
Data
Outcome
Outcome Workflow
Data
• What format is the information in?
• How is it Structured?
• Is it protected information?
• Where do I go for information?
• Who do I ask?
• How do I get it?
• What database do I query?
• What Outcome am I
predicting?
• What Question am I
answering?
• Who needs to know?
• Where should it be
known?
Example: Title Insurance Provider
Outcome
Outcome Workflow
Data
• What format is the
information in?
• How is it Structured?
• Is it protected information?
• Can I, Or Can’t I offer
Title Insurance?
• What Outcome am I
predicting?
• What Question am I
answering?
• Who needs to know?
• Where should it be
known?
Retrieve and Rank
Entity Extraction
Sentiment Analysis
Emotion Analysis (Beta)
Keyword Extraction
Concept Tagging
Taxonomy Classification
Author Extraction
Language Detection
Text Extraction
Microformats Parsing
Feed Detection
Linked Data Support
Concept Expansion
Concept Insights
Dialog
Document Conversion
Language Translation
Natural Language Classifier
Personality insights
Relationship Extraction
Retrieve and Rank
Tone Analyzer
Emotive Speech to Text
Text to Speech
Face Detection
Image Link Extraction
Image Tagging
Text Detection
Visual Insights
Visual Recognition
AlchemyData News
Tradeoff Analytics
50 underlying technologies
…and then leverage Watson APIs to
apply cognitive capabilities.
Natural Language Cl
assifier
Tone Analyzer
Watson
Narrative 27
What has been done with Ai?
© 2015 INTERNATIONAL BUSINESS MACHINES CORPORATION
Watson
Speaks
Cognitive Chat-Bots for ERP
Conversation
Cognitive & General Motors
+
© 2015 INTERNATIONAL BUSINESS MACHINES CORPORATION
Watson
Listens for
Answers
Cognitive Service
• Active listening along
side of the agent or
associate
• Natural language
understanding
• Real time location of
supporting documents
and data
Conversation Tone
Analyzer
Speech to
Text
Discovery
IBM Watson and Salesforce Einstein Integration
IBM Weather Insights for Salesforce
Bring The Weather Company’s meteorological data into Salesforce
with the Lightning component on the Salesforce AppExchange,
providing you with weather insights that inform customer interactions
and business performance.
IBM Watson and Salesforce Einstein Integration
Integrate IBM Watson APIs into Salesforce to bring predictive insights
from unstructured data inside or outside an enterprise, together with
predictive insights from customer data delivered by Salesforce
Einstein, enabling smarter, faster decisions across sales, service,
marketing, commerce and more.
© 2015 INTERNATIONAL BUSINESS MACHINES CORPORATION
Watson
Understands
Watson is Listening
Develop persona related to
overall product category
Function First (41,800)
Fashion First (2770)
Flare Enthusiast (1470)
Style Me (3465)
Denim Diva (13,150)
Identify trending
styles based on
social mentions and
activity
Identify clusters with
positive sentiment towards
identified trend.
Watson becomes the Expert
30 years of knowledge, 75% faster
Now employees anywhere in the world can access 30
years of expertise and locate technical data to make
quicker, smarter, more fact-based decisions.
Watson ingested the equivalent of 38,000 Woodside
documents — this would take a human over five years to
read. Watson can read 800 Million pages per second.
Watson
Narrative 37
What will you do with Ai?
Watson
Narrative 38

Ai & ibm watson cookbook

  • 1.
  • 2.
    Jerry O’Brien Cognitive Entrepreneur Presidentof the Boston Machine Learning Society IBM Cloud & Cognitive Evangelist
  • 3.
    Origin's of ArtificialIntelligence Expert Systems Statistical Learning Contextual Adaptation Programed rules system that emulates the decision-making ability of a human expert. Finding a predictive function based on data. Systems construct exploratory models for classes of real world phenomena Eliza, MIT, 1964 Self Driving Cars, 2004 Self Driving Cars, 2005 THE FUTURE
  • 4.
    Statistical Learning "A computer programis said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.” ~Tom Mitchell Linear Algebra Probability Theory Statistics Multivariate Calculus (Differentiation/gradients)
  • 5.
    The biggest taxicompany owns no cars. The largest accommodation company owns no real estate. The biggest media company owns no content. The largest retailer carries no inventory. Disruption is upon us.
  • 6.
    This disruption isfueled by three forces. The powerful capabilities and outcomes brought on by cognitive computing. The ability to build business in code with the API economy. The proliferation of different types of data.
  • 7.
    Oil & Gas 80,000sensors in a facility produce 15 petabytes of data Public Safety 520 terabytes of data are produced by New York City's surveillance cameras each day Energy & Utilities 680m+ smart meters will produce 280 petabytes of data by 2017 Healthcare The equivalent of 300 million books of health related data is produced per human in a lifetime
  • 8.
    Watson Narrative 2010 2020 Sensors & Devices Text Data Images/ Multimedia Gap EnterpriseTraditional You are here 2017 >2.5PB of customer data stored by Walmart every hour. 292 exabytes of mobile traffic by 2019, up from 30 exabytes in 2014 1TB of data produced by a cancer patient every day. WE FACE AN OVERWHELMING AMOUNT OF DATA IN EVERY INDUSTRY 44 ZETTABYTES
  • 9.
    1,200,000 lines of codein a smartphone 80,000 lines of code in a pacemaker 100,000,000 lines of code in a new car 5,000,000 lines of code in smart appliance More devices are creating more information.
  • 10.
    Three capabilities differentiatecognitive systems from traditional programmed computing systems… Reasoning They reason. They understand underlying ideas and concepts. They form hypothesis. They infer and extract concepts. Learning They never stop learning getting more valuable with time. Advancing with each new piece of information, interaction, and outcome. They develop “expertise”.Understanding Cognitive systems understand like humans do. …. allowing them to interact with humans.
  • 11.
    Cognitive systems democratize innovationby scaling knowledge. Sensors Data Analytics Information Cognitive Ingestion, Integration, Governance
  • 12.
    Humans excel at: Dilemmas Compassion Dreaming Abstraction Imagination Morals Generalization CognitiveSystems excel at: Common Sense Natural Language Locating Knowledge Pattern Identification Machine Learning Eliminate Bias Endless Capacity Cognitive systems forge a new partnership between man and machine.
  • 13.
    13©2016 IBM Corporation ofnot knowing. The price
  • 14.
    Examples include: Analyst reports tweets Wiretap transcripts Battlefield docs E-mails Texts Forensic reports Newspapers Blogs Wiki Court rulings International crime database Stolen vehicle data Missing persons data Data, information, and expertise create the foundation. Cognitive systems rely on collections of data and information:
  • 15.
  • 16.
    Retrieve and Rank EntityExtraction Sentiment Analysis Emotion Analysis (Beta) Keyword Extraction Concept Tagging Taxonomy Classification Author Extraction Language Detection Text Extraction Microformats Parsing Feed Detection Linked Data Support Concept Expansion Concept Insights Dialog Document Conversion Language Translation Natural Language Classifier Personality insights Relationship Extraction Retrieve and Rank Tone Analyzer Emotive Speech to Text Text to Speech Face Detection Image Link Extraction Image Tagging Text Detection Visual Insights Visual Recognition AlchemyData News Tradeoff Analytics 50 underlying technologies … then leverage Watson APIs to apply cognitive capabilities. Natural Language Cl assifier Tone Analyzer
  • 17.
    Watson at workin the world.
  • 18.
    "Woodside to tapinto IBM's Watson” - CIO "IBM’s Watson Now Powers AI For Under Armour” - TechCrunch "SoftBank's Pepper robot is getting an intelligence boost from IBM's Watson"- The Verge "Medtronic, IBM team up on diabetes app to predict possibly dangerous events hours earlier."- The Washington Post "IBM’s Watson Helped Pick Kia’s Super Bowl ‘Influencers’” - Wall Street Journal "How Can I Help You? IBM's Watson Powers Hilton's Robotic Concierge" - Fast Company "IBM and Apple can put Watson's A.I. insights inside Apple Watch"- ComputerWorld "Thomson Reuters to deploy IBM Watson technology” - InfoTechLead "IBM's Watson Lands A Job With KPMG.” -InformationWeek "The North Face Uses IBM's Watson to Make Online Shopping Smarter" -The Street Watson at work in the world.
  • 19.
    The market isvalidating the benefits of cognitive. “IBM Crafts a Role for Artificial Intelligence in Medicine.” “IBM Watson represents a bold technological and visionary step” “What is distinctive about IBM is the breadth of its effort to create Watson tools … for a wide range of developers.” ‘You can't do this without Watson. -Former Sun CEO Scott McNealy. His startup, Wayin, uses Watson to trawl and drag photos. “The worldwide cognitive software platforms market will grow to $30 billion by 2018, at a CAGR” IDC: Worldwide Cognitive Software Platforms Forecast, 2015-2019: The Emergence of a New Market (#258781, September 2015, David Schubmehl) “[Watson] is specifically designed to support the development of a broad range of enterprise solutions.” “No doubt, Watson has the means to radically change the industry. “ IDC: IBM’s Go-to-Market Transformation – Deeper, Wider, Newer (#AP257527, April 2015, Chris Zhang, Sabharinath Balasubramanian, Mayur Sahni) “IBM’s [Watson] can help banks with complex financial operations and attack important health care problems.” “…it’s not just AI algorithms themselves that have improved, but the ability to deliver them”
  • 20.
    © 2015 INTERNATIONALBUSINESS MACHINES CORPORATION Where do I start?
  • 21.
    A Frame ofMind Outcome Outcome Workflow Data
  • 22.
    Decision Outcome • What Outcomeam I predicting? • What Question am I answering? • Who needs to know? • Where should it be known?
  • 23.
    Outcome Workflow Outcome Outcome Workflow •Where do I go for information? • Who do I ask? • How do I get it? • What database do I query? • What Outcome am I predicting? • What Question am I answering? • Who needs to know? • Where should it be known?
  • 24.
    Data Outcome Outcome Workflow Data • Whatformat is the information in? • How is it Structured? • Is it protected information? • Where do I go for information? • Who do I ask? • How do I get it? • What database do I query? • What Outcome am I predicting? • What Question am I answering? • Who needs to know? • Where should it be known?
  • 25.
    Example: Title InsuranceProvider Outcome Outcome Workflow Data • What format is the information in? • How is it Structured? • Is it protected information? • Can I, Or Can’t I offer Title Insurance? • What Outcome am I predicting? • What Question am I answering? • Who needs to know? • Where should it be known?
  • 26.
    Retrieve and Rank EntityExtraction Sentiment Analysis Emotion Analysis (Beta) Keyword Extraction Concept Tagging Taxonomy Classification Author Extraction Language Detection Text Extraction Microformats Parsing Feed Detection Linked Data Support Concept Expansion Concept Insights Dialog Document Conversion Language Translation Natural Language Classifier Personality insights Relationship Extraction Retrieve and Rank Tone Analyzer Emotive Speech to Text Text to Speech Face Detection Image Link Extraction Image Tagging Text Detection Visual Insights Visual Recognition AlchemyData News Tradeoff Analytics 50 underlying technologies …and then leverage Watson APIs to apply cognitive capabilities. Natural Language Cl assifier Tone Analyzer
  • 27.
    Watson Narrative 27 What hasbeen done with Ai?
  • 28.
    © 2015 INTERNATIONALBUSINESS MACHINES CORPORATION Watson Speaks
  • 29.
    Cognitive Chat-Bots forERP Conversation
  • 30.
  • 31.
    © 2015 INTERNATIONALBUSINESS MACHINES CORPORATION Watson Listens for Answers
  • 32.
    Cognitive Service • Activelistening along side of the agent or associate • Natural language understanding • Real time location of supporting documents and data Conversation Tone Analyzer Speech to Text Discovery
  • 33.
    IBM Watson andSalesforce Einstein Integration IBM Weather Insights for Salesforce Bring The Weather Company’s meteorological data into Salesforce with the Lightning component on the Salesforce AppExchange, providing you with weather insights that inform customer interactions and business performance. IBM Watson and Salesforce Einstein Integration Integrate IBM Watson APIs into Salesforce to bring predictive insights from unstructured data inside or outside an enterprise, together with predictive insights from customer data delivered by Salesforce Einstein, enabling smarter, faster decisions across sales, service, marketing, commerce and more.
  • 34.
    © 2015 INTERNATIONALBUSINESS MACHINES CORPORATION Watson Understands
  • 35.
    Watson is Listening Developpersona related to overall product category Function First (41,800) Fashion First (2770) Flare Enthusiast (1470) Style Me (3465) Denim Diva (13,150) Identify trending styles based on social mentions and activity Identify clusters with positive sentiment towards identified trend.
  • 36.
    Watson becomes theExpert 30 years of knowledge, 75% faster Now employees anywhere in the world can access 30 years of expertise and locate technical data to make quicker, smarter, more fact-based decisions. Watson ingested the equivalent of 38,000 Woodside documents — this would take a human over five years to read. Watson can read 800 Million pages per second.
  • 37.
  • 38.