Steve Mills Executive Vice President

IBM Software and Systems

Your Cognitive FutureHow Next-gen Computing

Changes the Way We Live and Work

What Is Driving the Need for Cognitive Computing?

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Percentage of unstructured data

We are here

Sensors & Devices

Social Media

VOIP

Enterprise Data

44 zettabytes

2010 2015 2020

We are Entering a New Era of Computing

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Programmable Systems Era

Cognitive Systems Era

Tabulating Systems Era

cog.ni.tive: of or pertaining to the mental process of perception, memory, judgment, learning, and reasoning

1997: Deep Blue IBM Deep Blue defeats World Chess Champion

1950: Turing Test Turing introduces way to test for intelligent behavior

Pioneers and Significant Events Have Shaped Where We Are Today …

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1950s 1960s 1970s 1980s 1990s 2000s 2010…

1956: “Birth” of AI John McCarthy coins term artificial intelligence (AI) at Dartmouth Conference

1965: First Expert System Stanford team led by Ed Feigenbaum creates DENDRAL

1987 - 1993: 2nd AI “Winter”

1990s: AI on www AI-based extraction programs prevalent on www

2011: Watson IBM’s Watson competes and wins on Jeopardy!

2005: Autonomous Car Stanford-built autonomous car wins DARPA Grand Challenge

2014: Key Market Moves IBM formation of Watson Group and Google acquisition of Nest Labs

1974 - 1980: 1st AI “Winter”

Alarmists? …. or Realists?

6Bill Gates

Stephen Hawking

Elon Musk “The  development  of  full  artificial  intelligence  could  spell                    the  end  of  the  human  race  ……  It  would  take  off  on  its  own,  and  re-­design  itself  at  an  ever  increasing  rate  ……  Humans,  who  are  limited  by  slow  biological  evolution,  couldn’t  compete,  and  would  be  superseded.”      

“I  think  we  should  be  careful  about  artificial  intelligence  ….  If  I  had  to  guess  at  what  our  biggest  existential  threat,  it  is  probably  that  …..  With  artificial  intelligence,  we’re  summoning  the  demon.”  

“First  the  machines  will  do  a  lot  of  jobs  for  us  and  not  be  super  intelligent  …..That  should  be  positive  if  we  manage  it  well  …..  A  few  decades  after  that  though  the  intelligence  is  strong  enough  to  be  a  concern.”      

Man versus Machine

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Man versus Machine

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So, What Is Cognitive Computing?

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▪ Cognitive computing and cognitive based systems accelerate, enhance and scale human expertise by:

Learning and building knowledge,

Understanding natural language and

Interacting more naturally with humans than traditional programmable systems

▪ Over time, cognitive systems will simulate more of how the brain actually works and help us solve the world's most complex problems by penetrating the complexity of Big Data

käg-nəә-tiv (adjective): of, relating to, or involving conscious mental activities (such as thinking, understanding, learning, and remembering)

What are Cognitive Systems Good At?

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▪ Cognitive systems learn by extracting and organizing the signals emitted in the natural world, and evaluating patterns that convey meaning

▪ Cognitive systems are especially valuable when dealing with large quantities of unstructured information (such as text, audio, or video) and disparate information sources that would otherwise overwhelm the time and space constraints of human assimilation

Exploration

Collect the information that you need to explore your problem area better

Engagement

Dialog with end users to answer the

questions needed around products and

services

Discovery

Help find the questions you’re not thinking to ask and

connect the dots that you’re missing that

will lead to new inspiration

Evaluation

Evaluate a presented condition against a set of written policy

assertions

Decision

Assess the choices that enable you to

make better decisions

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Core Technologies

Question & Answer

Natural Language Processing

Machine Learning

Question Analysis

Feature Engineering

Ontology Analysis

Watson for Jeopardy Comprised a Single API Built on Five Core Technologies

Since Then We Have Grown to 28 APIs – Based on ~50 Core Technologies

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Watson News

Speech to Text Image

Link Extraction

Tradeoff Analytics

Concept Tagging Image Tagging

Natural Language Classifier Retrieve and

Rank Author Extraction Visual

Recognition

Message Resonance Language

Detection Tone Analyzer Question

& Answer

Entity Extraction

Concept Expansion Sentiment

Analysis Personality Insights Feed Detection

Face Detection Dialog Keyword Extraction Taxonomy

Language Translation Concept

Insights Text Extraction

Text to Speech Relationship Extraction

Question & Answer

Author Extraction Colloquialism Processing Concept Expansion Convolutional Neural Networks Deep Learning Dialog Entity Extraction Entity Resolution Feature Engineering Feature Weighting HTML Analysis

Core Technologies

Draws on Five Core Technologies

Speech to Text Image

Link Extraction

Tradeoff Analytics

Concept Tagging Image Tagging

Natural Language Classifier Retrieve and

Rank Author Extraction Visual

Recognition

Message Resonance Language

Detection Tone Analyzer Question

& Answer

Entity Extraction

Concept Expansion Sentiment

Analysis Personality Insights Feed Detection

Face Detection Dialog Keyword Extraction Taxonomy

Language Translation Concept

Insights Text Extraction

Text to Speech Relationship Extraction

Case Evaluation Q&A

Qualification

Video Augmentation

Policy Identification Knowledge

Graph Criteria Classification

Risk Stratification

Factoid Pipeline Usage Insights

Easy Adaptation Answer

Generation

Decision Optimization Knowledge

Studio Service

Fusion QA

Emotion Analysis Knowledge

Canvas

Statistical Dialogue

Decision Support

Core TechnologiesAuthor Extraction Colloquialism Processing Concept Expansion Convolutional Neural Networks Deep Learning Dialog Entity Extraction Entity Resolution Feature Engineering Feature Weighting HTML Analysis

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Watson News

In 2016, We Will Add an Additional 15 - 20 APIs

Watson for Oncology Provides clinicians with confidence-ranked, evidence-based personalized treatment options based on expert training from MSK physicians

Ingests 300+ medical journals, 200+ textbooks, 15M+ pages of text, thousands of historical cases and thousands of hours of MSK physician and analyst training (in conjunction with Watson application Knowledge Studio).

Connects treatment recommendations to supporting evidence from MSK-curated literature and provides physicians ranked, personalized evidence-based cancer treatment options for consideration.

Entity Extraction

Concept Insights

Retrieve and Ranke

Together, these APIs power the summation of attributes from longitudinal patient records to extract meaningful information from natural language – including the unstructured data in clinician's notes.

Document Conversion

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Relationship Extraction

Finds relationships between ingredients from a corpus of recipes to suggest new kinds of pairings that may not be intuitive to chefs. Helps Watson understand information about ingredient parts and fabrication (e.g., a lobster has a shell, but a salmon has skin; oranges are peeled but blueberries are not).

Parses unstructured English language of the recipes’ content into structured text and then maps recipes to dish types (i.e. to understand what recipe is a taco, a dessert pie, a savory pie, etc.).

Natural Language Classifier

Entity Extraction

Identifies all the ingredients in a recipe, the purpose of each ingredient and how it complements other ingredients.

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Chef Watson Assisting chefs in choosing the right combination of ingredients considering flavor, texture, and chemical composition of millions of ingredients

Question

& Answer

Allows the Digital Virtual Assistant to draw responses from its corpus of thousands of pages of GEICO training manuals, policies, and employee expertise.

Allows customers to ask contextual questions (e.g., “where can I find my vehicle information number” or “VIN number”), in a very natural way. This API also learns about the customer from client records, and guides them through the process based on their unique situation.

Dialog

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Watson-powered "Digital Virtual Assistant" Helps guide Geico's customers through the experience of selecting an insurance policy

Watson Platform Built on IBM Bluemix

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▪ Build your application using callable Watson Service APIs

▪ Can be combined with the 100s of other available services on Bluemix

Language Translation

Speech to TextText to Speech Dialog Tradeoff Analytics

Personality Insights

Natural Lang Classifier

Concept Insights

Concept Expansion

Question and Answer

Relationship Extraction

Visual Recognition

Tone AnalyzerRetrieve and Rank

Document Conversion

Message Resonance

AlchemyAPI

▪ Community of 11,500 developers - 1,600 daily visitors

- 7,600+ non-IBM organizations

- 10,200+ applications bound to Watson Services

- 20M+ API calls served in the last 30 days

U.S. and EU Governments Investing in Cognitive Computing

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U.S. Government Agencies

Mission: Understand brain and its diseases; develop brain-like technologies

135 partner institutions in 26 countries

Funding: 1.2 billion euros over 10 years

Mission: Partnership with IBM to further cognitive computing and big data research

Funding: UK Government: £ 113M IBM: £ 200M in people, hardware & software

Mission: DARPA SyNAPSE Build computer with similar form and function to dog or cat brain

IARPA, DARPA, DoD, NSF AI, knowledge discovery, neuroscience

Funding: $ 15M per year in NSF funding > $100M funding for understanding brain

Mission: Advance cognition, human-robot interaction, mechatronics, navigation, perception

Funding: 80B euros, 2014 - 2020, from government and EU private industry

The Great Decoupling

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Trends in US GDP, Profits, Investments, and Employment

1995 - 2011

Preparing for Tomorrow

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▪ Digital technologies will continue to accelerate

▪ Business-as-usual won’t solve the problem

▪ A major commitment to increasing education and skill levels as well as fostering business and organization innovation is required

▪ Need to reinvent our economy and society to keep up with accelerating technology

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