cognitive computing: the art of the possible,calit2.uci.edu/uploads/media/text/ibm watson art...

Cognitive Computing:

The Art of the Possible,Innovation and Inspiration through IBM Watson

Ali Arsanjani, PhD

IBM Distinguished Engineer,

Chief Technology Officer,

IBM Analytics

[email protected]

@AliArsanjani

mailto:[email protected]

© 2015 IBM Corporation 2

Please Note

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The information mentioned regarding potential future products is not a commitment, promise, or legal obligation to deliver any material, code or functionality. Information about potential future products may not be incorporated into any contract. The development, release, and timing of any future features or functionality described for our products remains at our sole discretion.

Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will experience will vary depending upon many factors, including considerations such as the amount of multiprogramming in the user’s job stream, the I/O configuration, the storage configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve results similar to those stated here.


Topics

• Preface

• Cognitive Computing

• IBM Watson

• Adoption Patterns

– Engagement

– Watson Platform

– Exploration

– Discovery

– Decision

• Few Demos


Let’s get started

Preface


Cognitive is the new

competitive advantage.


Chapter 1

Cognitive Computing?


Not …

Yet !

Cognitive Systems


Cognitive systems amplify human

cognition.


Cognitive systems don’t do your

thinking for you. They augment &

aid your research so that you have

more time to innovate.


To do that, cognitive systems attempt

to reason about a problem space in a

way that is

similar to human thinking

so that the conclusions are intuitively obvious, transparent, and immediately

useful.


Provides answers not links and webpages

Answers with evidence not guesses

Not restricted to a predefined question-answer set

Learns from every interaction


In 20 years, cognitive systems will be to computing what

transaction processing is today

• Amplify human creativity

– Inspiring us to new alternatives to decision options

– Bringing the breadth of all human knowledge to the tip of our

tongue

• Learn their behavior through formal and informal training processes

• Interact with humans on our terms – in the language of humans

• Demonstrate their expertise through trust and depth of

character

• Evolve strategies of success – adapting to ever changing

knowledge and understanding


What is Cognitive Computing?

• Cognitive systems are able to learn their behavior through education

• That support forms of expression that are more natural for human interaction

• Whose primary value is their expertise; and

• That continue to evolve as they experience new information, new scenarios, and new responses

… and does so at enormous scale.


Principles of Cognitive Computing

• Cognitive Systems –– Applying human-like characteristics

– to conveying and manipulating ideas,

– that when combined with the inherent strengths of digital computing

– can help users to address problems with • higher accuracy, • more resilience, and • on a massive scale • over very large bodies of information.

• Watson is a Cognitive System– Teases apart the human language to identify inferences between text

passages

– Can demonstrate human-like accuracy

– Performs at speeds far faster, and at a scale far bigger, then a human.


How does it work?

• Cognitive systems interpret the natural world by listening to the signals emitted in that world, and evaluating patterns in strong and weak signals that convey meaning

– Algorithmic annotators detect and score the strength of the features (signals) relevant to the domain

– Machine Learning algorithms then use the resulting vector of feature scores to learn which patterns represent meaning

– These Machine Learning algorithms are taught to recognize meaningful patterns through training data representing ground-truth in the domain of natural experience

• Cognitive systems are able to boost their comprehension through metaphorical comparison to models of the real world that are constructed from shared contextual history

• Confidence is reinforced through redundancy and supporting evidence

• Different combinations of features and Machine Learning represent different reasoning strategies that can be useful for different situations


A Key driver for Cognitive Computing… we want to interpret

overwhelmingly large amounts of increasing data

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Watson began from DeepQA invoking the need for multiple reasoning

strategies for answering questions

Num

be

r o

f tim

es a

sim

ilar

qu

estio

n is

aske

d

Different questions that might be asked (including similar variations)

The “long tail” of

questions

Passage QA

Pipeline

Prediction

QA Pipeline

Knowledge QA

Pipeline

Factoid QA

Pipeline

FAQ QA

Pipeline

Query QA

Pipeline

Yes/No QA

Pipeline

Directed QA

Pipeline

Action QA

Pipeline

• Some questions are asked frequently

• We call this the ‘long tail’ of the question space

• Different types of questions demand different types of answers

• Note: Jeopardy questions only ever demanded Factoid answer types

• WEA engagements most often demand FAQ and Passage answers

• Each pipeline is responsible for reasoning about how to yield the type of answers it is responsible for

• There is a point of diminishing returns for covering absolutely every question type … some questions will never be covered and will be redirected

Jeopardy!

WDA

AlchemyAPI

WEA

WEA

What are your visiting hours?

Can you walk me through

installing a new app on my

phone?

What are the

requirements for car

insurance in Kentucky?

I want to submit a

claim

Do I need a visa to

enter Brazil?

What is the capital

of Texas? Who is known as the

father of modern

psychology?

What level of customer

churn will we see next

quarter?

What is the highest

priced phone offered

by Samsung?

19

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 are creating a new partnership between humans and technology.

20

20

21

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:

22

There are three capabilities that differentiate cognitive systems from traditional programmed computing systems.

Reasoning

They reason. They can understand

information but also the underlying ideas

and concepts. This reasoning ability can

become more advanced over time. It’s

the difference between the reasoning

strategies we used as children to solve

mathematical problems, and then the

strategies we developed when we got into

advanced math like geometry, algebra

and calculus.

Learning

They never stop learning. As a

technology, this means the system

actually gets more valuable with time.

They develop “expertise”. Think about

what it means to be an expert- - it’s not

about executing a mathematical

model. We don’t consider our doctors to

be experts in their fields because they

answer every question correctly. We

expect them to be able to reason and

be transparent about their reasoning,

and expose the rationale for why they

came to a conclusion.

Understanding

Cognitive systems understand like

humans do, whether that’s through

natural language or the written

word; vocal or visual.


What will an inquisitive mind want to know from text?

Rarely has there been a better time for start-ups to raise

money from Silicon Valley venture capitalists. But this

golden age may not last long. At least that is what Bill Gurley

says. Mr. Gurley is a prominent investor who has spent a

career betting on who the winners and losers will be in the

future of technology. Ciao!

Entities /Concepts & Relationships

Expand

Concepts

Exploreinformation

based on Concept

Associations

Sentiment & Sentiment

Targets

Deeper understanding

on author’s personality

Languageidentification

Ask questions & interact in

natural language

Resonance of the text


I want to …

Classify Text Extract Entities & Relationships

Search & Rank Results Understand Utterances & Act

Expand


• To pass the Turing Test and qualify as artificially intelligent, a

machine should be able to do for example: natural language

processing (i.e. communicate with no trouble on a given

language); automated reasoning (using stored information to

answer questions and draw new conclusions) and machine

learning (the ability to adapt to new circumstances and detect

patterns).


So what are the

Characteristics of a

Cognitive System?

Scale in

Proportion

Provide Supporting Evidence

IngestVariety of (Big) Data

Respond with

Degree of Confidence

Learn with Every

Interaction

Offer Contextual

Guidance & Insights

Support for Decision Making

Generate & Evaluate

Hypothesis

UnderstandNatural

Language

Understand personality

at a Deeperlevel

Relatebetween Terms &

Concepts

Engage in a Dialog


Chapter 2

IBM Watson


Watson is creating a new

partnership between people

and computers that

enhances, scales and

accelerates human expertise.


What is IBM Watson?

Cognitive Technology

Read & Understand

Natural Language

Generate multiple

hypothesis with

Evidence

Support for several

usage patterns

Natural extension of

what humans can do

at their best

Learns over time

Engagement Discovery Decision Exploration Platform


Bringing IBM Watson to market

PlatformAlchemyLanguage Concept Expansion Concept Insights Dialog Language Translation

Natural Language Classifier Personality Insights Retrieve and Rank Tone Analyzer AlchemyVision

Visual Insights Visual Recognition AlchemyData News Tradeoff Analytics

Relationship Extraction Document Conversion Speech to Text Text to Speech

Frameworks

• IBM Watson Engagement Advisor

• IBM Watson Explorer

• IBM Watson Discovery Advisor

• IBM Watson Care Manager

• IBM Watson Decision Advisor

• IBM Watson Policy Advisor

Health Solutions

• IBM Watson for Oncology

• IBM Watson for Genomics

• IBM Watson for Clinical Trial Matching

• IBM Watson for Clinical Trial Matching Express

• IBM Watson Health Cloud for Life Sciences Compliance

X Industry Solutions

• Watson Explorer Content Miner

• Watson Curator

• Watson Analytics

• Watson Knowledge Studio

Watson Industry Apps


Chapter 3

Adoption Patterns


IBM Watson enables various adoption patterns

ENGAGE DISCOVEREXPLORE DECIDE PLATFORM

• Engage with

customers in a NL

conversation

• Ask questions for

greater insight

• Answer with context

• Guide consumers

to an outcome

• Merge of enterprise

search with content and

text analytics

• 360-degree Information

apps at the point of

impact

• Use Platform services to

further enhance

cognitive processing

• When finding the

question is as

important as finding

the answer

• Find rationale for

given responses

• Scaling to millions of

documents

• Ingest and analyze

domain sources,

info models

• Evidence-based

decisions with

greater confidence

• Multiple reasoning

strategies to enable

decision support

• Build your application

using callable Watson

Service APIs

• Can be combined with

the 100s of other

available services on

Bluemix

Transform customer

experiences

Search, consolidate &

analyze

enterprise data

Accelerate

Research into

Insight

Evaluate possible

options & choose

the best one

Enrich apps with Cognitive,

NLP, Vision & Machine

Learning capabilities


ENGAGE DISCOVEREXPLORE DECIDE PLATFORM

• Engage with customers in a NL conversation

• Ask questions for greater insight

• Answer with

context

• Guide consumers to an outcome

• Merge of enterprise search with content and text analytics

• 360-degree Information apps at the point of impact

• Use Platform services to further enhance cognitive processing

• When finding the question is as important as finding the answer

• Find rationale for given responses

• Scaling to millions of documents

• Ingest and analyze domain sources, info models

• Evidence-based decisions with greater confidence

• Multiple reasoning strategies to enable decision support

• Build your application using callable Watson Service APIs

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

Transform

customer

experiences

Search, consolidate

& analyze

enterprise data

Accelerate

Research into

Insight

Evaluate possible

options & choose

the best one

Enrich apps with Cognitive,

NLP, Vision & Machine

Learning capabilities

IBM Watson enables various adoption patterns

Watson

Engagement

Advisor

Watson

Explorer

Watson

Discovery

Advisor

Oncology,

Clinical Trials

Matching,

Wealth

Advisor

Watson API’s on

Bluemix


Pattern Description Client success stories

EngagementLeading insurance company in US introduced

Watson to answer questions from membersTransform customer experiences

DiscoveryLeading medical research institution, Baylor,

publishes breakthrough in protein targetingAccelerate Research into Insight

DecisionMemorial Sloan Kettering Cancer Center

partnered with IBM to build an Oncology

solution

Evaluate possible options and choose

the best one

Cognitive Exploration

700+ clients using the product across

industries

Search, consolidate and analyze

enterprise data

Cognitive Services

6000+ developers and 200+ partners are

building on Watson today

Enrich new or existing applications with

NLP, Vision and Machine Learning

Capabilities

Watson Adoption Patterns


Engagement


How Watson works: DeepQA Architecture

Multiple interpretations Hundreds of answer

sources• Primary search• Candidate answer

generation

Tens of thousands of evidence

sources and scores• Answer scoring• Evidence retrieval• Deep evidence scoring

Learned models• Combine and weigh evidence

Inquiry analysis Decomposition Hypothesis generation SynthesisHypothesis and evidence scoring

Final confidence merging & ranking

Question

Answer? !


How Watson works: DeepQA Architecture

Multiple interpretations Hundreds of answer

sources• Primary search• Candidate answer

generation

Tens of thousands of evidence

sources and scores• Answer scoring• Evidence retrieval• Deep evidence scoring

Learned models• Combine and weigh evidence

Inquiry analysis Decomposition Hypothesis generation SynthesisHypothesis and evidence scoring

Final confidence merging & ranking

Question

Answer? !

Natural language processing

Information retrieval

Knowledge representation and reasoning

Deep analytics

Parallel and distributed computing

Machine learning


Watson understands natural language

• Uses natural language processing and

DeepQA technology to break down &

understand a customer’s question

• There may be 100 ways to phrase the

same question – Watson is able to

learn them….


Watson understands context

• Questions may only make sense if you

understand context

• E.g.

– Previous question

– Information about the consumer

– Surrounding environment


Watson engages consumers in a conversation

• Watson understands that dialog is

iterative

• Show a personality representative

of the brand

• Clarification questions to carry a

conversation and get user’s intent

• Guide consumers to an outcome


Watson can take action

• Watson is able to integrate

business processes into customer

conversations

– Inject the right offers or promotion

based on context

– Submit an application

– Retrieve information about a

consumer


Chapter 4

Watson Platform


WATSON

EXPLORER

WATSON

DEVELOPER

CLOUD

WATSON

ENGAGEMENT

WATSON

DISCOVERY

WATSON ECOSYSTEM

Web-based APIs

Message, Sentiment, and

Personality insights

Relationship Extraction

Questions&

Answers

Language

Detection

PersonalityInsights

Keyword Extraction

Image LinkExtraction

Feed Detection

VisualRecognition

Concept Expansion

ConceptInsights

DialogSentiment Analysis

Text to Speech

Tradeoff Analytics

Natural Languag

eClassifier

Author Extraction

Speech to

Text

Retrieve&

Rank

WatsonNews

LanguageTranslation

EntityExtraction

Tone Analyzer

ConceptTagging

Taxonomy

TextExtraction

MessageResonance

ImageTagging

FaceDetectio

n

Answer Generation

Usage Insights

Fusion Q&A

Video Augmentation

Decision Optimization

Knowledge Graph

Risk Stratification

Policy Identification

Emotion Analysis

Decision Support

Criteria Classification

Knowledge Canvas

Easy Adaptatio

n

Knowledge Studio

Service

Statistical Dialog

Q&A Qualification

Factoid Pipeline

CaseEvaluation

The Waston that competed on

Jeopardy! in 2011 comprised what

is now a single API—Q&A—built

on five underlying technologies.

Since then, Watson has grown to

a family of 28 APIs.

By the end of 2016, there will

be nearly 50 Watson APIs—

with more added every year.

Natural

Language

Processing

Machine Learning

Question Analysis

Feature

Engineering

Ontology Analysis

Watson Platform

built on Bluemix


Discovery


Published Knowledge

Knowledge-Driven Method Data-Driven Method

ObservationalData

• Longitudinal records

• Claims, Rx, Labs

• Patient reported data

• Scientific papers

• Books

• Guidelines

Closing the translational knowledge gap Personalized Insights from institutional data

From population averages … To insights for individual patient!

Watson for healthcare and life sciences spans all aspects of

knowledge and data


Genes

Chemical

Compounds

Diseases

Patient

s

Animal Models

FDA Orange

Book/Moieties

Cells PatentsDrugs

Plant

Biology

®™

Meaningful insights are only gained when data reveals a

universe of relationships


1New Cancer Drug targeting

p53 per year

5Potential New Cancer

Drugs in 30 days

Leveraging Watson Cognitive Capabilities toAccelerate the Discovery of New Drugs to Fight Cancer

WW Research IBM Watson

Baylor / IBM Study on p53


Most Likely

Targets

Results were “Too Good to be True?” Re-ran experiment with pre 2003 information.

Only 10 known kinases triggered p53 at that time

Of the 9 found in the next decade…

Watson accurately predicted 7

Showing Researchers Where to Look


Decision


Business challenge:

• Clinicians have no easy way to search across eligibility criteria of relevant clinical trials for their patient; affecting research advancement and patient care

• Less than 10% of clinical studies are completed on time

• 30% of sites for clinical trials fail in enrolling even a single patient

Watson solution:

• Use patient data to instantly check eligibility across all relevant clinical trials, which can improve research and treatment outcomes

Two Use Cases

• Point of care: Cognitive Physician assistant to assess patient eligibility against all available trials

• For Pharma: Identify potentially productive sites (potentially eligible patients) help recruit patients for a specific trial

IBM Watson for OncologyTrained by Memorial Sloan Kettering

Initial focus is oncology, Watson is

trained in breast, lung and

colorectal cancer, with other tumor

types to follow


IBM Watson for Clinical Trial Matching

Business challenge:

• Ability to assess quickly the best treatments for an individual patient based on latest evidence and clinical guidelines

Watson solution:

• A tool to assist physicians make personalized treatment decisions

• Analyzes patient data against thousands of historical cases and trained through thousands of Memorial Sloan Kettering MD and analyst hours

• Suggestions to help inform oncologists’ decisions based on over 290 medical journals, over 200 textbooks, and 12M pages of text

• Evolves with the fast-changing field

• Currently supports first line treatment (Breast, Lung, Colorectal cancers)


Exploration


Watson Explorer addresses information challenges across

your enterprise

Scaling expertise

Pressure to increase performance and innovation—while doing more with less

Insights from unstructured data

80% of data is unstructured but only a small percentage leveraged for business insights

Information access

100s of TB of data but employees struggle to get the information they need in context

ExploreInformation at the point of impact,

in 360-degree information

applications

AnalyzeContent analytics to aggregate

and analyze vast amounts of

unstructured data for business

insights

InterpretCognitive capabilities from Watson

Developer Cloud to enhance, scale

and accelerate human expertise

Cognitive ExplorationInformation, analytic insights and cognitive services to improve business outcomes

Watson Explorer V10Challenges Watson Explorer Delivers…


• Discovery and navigation across disparate sources for timely data “findability”

• Merge of enterprise search with content and text analytics

– Sentiment Analytics

– Social Search/Analytics

– Social media crawler

– Domain-adaptive search

– Compound Document support

• Explore: Securely connects and explores data, regardless of format or location

• Analyze: Mines unstructured content to reveal trends, patterns and insights

• Interpret: Delivers cognitive capabilities via the Watson Developer Cloud

• Enables integration of Watson Developer Cloud services to further enhance the cognitive processing of unstructured information

• A single point of access for information and services - On-premise enterprise systems, Public and private cloud, Public and private Internet sources

Watson ExplorerAllow for exploration of easily consumable data across multiple systems


Watson Explorer Use Cases

• Community policing

• Investigation analytics

• Incident management

• Antigang initiatives

• Antiterrorism initiatives

• Cyber crime investigation

• Customer experience

• Customer satisfaction and

survey analysis

• Product and service quality

• Churn prediction

• Marketing campaign

development and execution

• New revenue opportunities

• Product enhancements

• Diagnostic assistance

• Clinical treatment

• Critical care intervention

• Research for improved disease

management

• Fraud detection and prevention

• Voice of the patient

• Claims management

• Prevention of readmissions

• Patient discharge and follow-up care

• Risk assessment

• Fraud detection

• Policy and underwriting analysis

• Claims analysis, payment

validation and loss review

• Reserve trending and

optimization

• Anti–money laundering

• Internet banking fraud

• Operational efficiency

• Risk management and

compliance

Customer

InsightCrime

Analytics Healthcare Insurance Finance


Cognitive Cooking

http://www.ibmchefwatson.com

http://www.ibmchefwatson.com


Watson Health is working to enhance,

scale, and accelerate expertise across the

domains of health and wellness, and to

facilitate collaboration across the

communities of care.

SolutionsPopulation Health

Management

Condition

Specific Care

Health

and Wellness

Social

Programs

Discovery

Solutions

Real World

Evidence

Ecosystem

Population Health

Management

Condition

Specific Care

Health

and Wellness

Social

Programs

Discovery

Solutions

Real World

Evidence

Individual

Social

Programs

Education

Governments

Home Health

Agencies

Practitioners

Hospitals

Therapists

Health

Plans

Family

Public Health

Medical Devices

and Diagnostics

Bio-Pharma

Employers

Payers

Data

Insight

61

As the Watson technology evolves and deepens,

so too are the ways it’s being put to work in the world.

36Countries

50,000Studentsin Melbourne

5.5MCitizensin Singapore

5LanguagesLearned by Watson

160Universitiesoffering Watson courses

400+PartnersPowered by Watson

1.1MPatientsat Bumrungrad

29Industries

80KDevelopers building with Watson

What will you do with Watson?

cognitive computing: the art of the possible,calit2.uci.edu/uploads/media/text/ibm watson art...

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