International Business Machines Corporation, Bringing IBM Watson to Life

Transcription

1 1 Bringing IBM Watson to Life

2 2 Agenda 1.Why the world needs Watson 2.What does Watson do? 3.Why is this hard for a computer? 4.Taking Watson to the marketplace 5.I want to be a Watson developer...

3 33 1/ Why the world needs Watson

4 subscribers International Business Machines Corporation, 2014 Transforming how we connect with the world $20B 44 in revenue last quarter Transforming how we consume media 50M

5 5 The volume, variety, velocity and veracity of data is creating an unprecedented opportunity. 2.5B gigabytes of new data are generated every day, 4/5ths of which is unstructured.

6 6 This proliferation of data is driving demand for real-time insights and evidence-based decision making. 1 in 2 CEOs report not having the information they need when making critical decisions

7 Most firms estimate that they only analyze 12% of the data they already have, leaving 88% on the cutting room floor. International Business Machines Corporation, Advances in natural language processing and machine learning are enabling us to transform expertise and professionals. 12%

8 88 2/ What does Watson do?

9 9 Watson is ushering in a new era of computing 1900 Tabulating Systems 1950 Programmable Era 2011 Cognitive Era

10 10 Watson is creating a new partnership between people and computers that enhances, scales and accelerates human expertise.

11 11 Observe Every day, our brains process incredible amounts of information without us even realizing we re doing it. Observe Watson aids the human cognitive process by reading and storing all public and proprietary knowledge across professions, and making insights contained within instantly available. Decide Evaluate Interpret

12 12 Interpret We interpret the data available to us to make connections and frame our choices Observe Watson supports this process by interpreting explicit and implicit relationships and visualizing unexpected patterns within data Decide Evaluate Interpret

13 13 Evaluate We evaluate connections across knowledge and data to draw conclusions and develop our opinions Observe Watson supports this process by testing options against all available evidence, without assumption or bias Decide Evaluate Interpret

14 14 Decide We make decisions based on experience, new evidence, and the integrity of evaluation that we ve done. Observe e Watson puts content into context, pairing confidenceweighted responses with supporting evidence and allowing professionals to make informed decisions at the point of impact. Decide Interpret Evaluate

15 15 3/ Why is this hard for a computer?

16 It is Hard For Computers to Understand Humans International Business Machines Corporation, Welch ran this? Person Organization L. Gerstner IBM J. Welch GE If leadership is an art then surely Jack Welch has proved himself a master painter during his tenure at GE. W. Gates Microsoft

17 It is Hard For Computers to Understand Humans International Business Machines Corporation, Welch ran this? Person Organization L. Gerstner IBM J. Welch GE If leadership is an art then surely Jack Welch has proved himself a master painter during his tenure at GE. W. Gates Microsoft Noses that run and feet that smell? How can a house can burn up as it burns down? Does CPD represent a complex comorbidity of lung cancer? What mix of zero-coupon, non-callable, A+ munis fit my risk portfolio?

18 What is the Difference Between Watson and a Search Engine Ask Google How Smart it is? Ask Watson How Smart He Is? 18

19 How Watson works: DeepQA architecture 19 Learned Models help combine and weigh the Evidence Inquiry Answer Sources Primary Search Candidate Answer Generation Answer Scoring Evidence Sources Evidence Retrieval Deep Evidence Scoring Models Models Models Models Models Models Inquiry/Topic Analysis Inquiry Decomposition Hypothesis Generation Hypothesis and Evidence Scoring Synthesis Final Confidence Merging & Ranking Hypothesis Generation Hypothesis and Evidence Scoring Responses with Confidence

20 How Watson works: DeepQA architecture 20 Inquiry Inquiry/Topic Analysis Answer Sources Primary Search 100 s of sources Multiple interpretations of a question Candidate Answer Generation Inquiry Decomposition 100 s of possible answers Hypothesis Generation Hypothesis Generation Answer Scoring 1000 s of pieces of evidence Evidence Sources Evidence Retrieval Hypothesis and Evidence Scoring Hypothesis and Evidence Scoring Deep Evidence Scoring 100,000 s of scores from many deep analysis algorithms Synthesis Learned Models help Balance combine and & weigh the Evidence combine Models Models Models Models Models Models Final Confidence Merging & Ranking Responses with Confidence

21 Watson leverages multiple algorithms to gather deeper evidence 21 Question In May 1898 Portugal celebrated the 400th anniversary of this explorer s arrival in India. celebrated Portugal May th anniversary arrival in India explorer 21 Source: IBM Research International Business Machines Corporation, 2014

22 THIS IS NOT HOW WATSON WORKS: Keyword Matching 22 Question In May 1898 Portugal celebrated the 400th anniversary of this explorer s arrival in India. celebrated Possible evidence In May, Gary arrived in India after he celebrated his anniversary in Portugal arrived in celebrated Legend Keyword Hit Reference Text Answer In May 1898 In May 400th anniversary arrival in India explorer Portugal Gary India anniversary in Portugal This evidence suggests Gary is the answer BUT the system must learn that keyword matching may be weak relative to other types of evidence

23 Watson leverages multiple algorithms to gather deeper evidence May 1898 Question In May 1898 Portugal celebrated the 400th anniversary of this explorer s arrival in India. celebrated 400th anniversary Portugal Date Match Possible evidence On the 27th of May 1498, Vasco da Gama landed in Kappad Beach landed in 27th May 1498 Legend Temporal Reasoning Statistical Paraphrasing GeoSpatial Reasoning Reference Text Answer 23 arrival in Paraphrases Stronger evidence can be much harder to find and score Search far and wide Explore many hypotheses India Geomapping Kappad Beach Judge evidence Many inference algorithms 23 Source: IBM Research explorer Vasco da Gama and the evidence is still not 100% certain

24 Cognitive computing is changing the game Understands natural language and human style communication Generates and evaluates evidence-based hypothesis 3 Adapts and learns from training, interaction, and outcomes

25 25 4/ Taking Watson to the marketplace

26 26 Bringing Watson to market Transforming industries Transforming industries and professions and professions with services-led with engagements. services-led engagements. Advancing cognitive Advancing cognitive computing across computing the enterprise across with the repeatable solutions. enterprise with repeatable solutions. Bringing the cognitive Bringing the cognitive experience to market to market through an ecosystem of partners. through an ecosystem of partners.

27 Watson s Evolution 27 Jeopardy Jeopardy Cognitive Products Cognitive Ecosystem Open Cognitive Platform Single user system 2-3 sentence questions 2-3 word answers 5+ days to retrain Wikipedia, general corpus 1000s of users 20 page questions < 1 day to retrain Medical corpus Millions of users Conversational dialog Few hours to retrain Broad industry corpus 8 cognitive services Watson cloud service Taught at 10 universities Thousands of business partners 50+ cognitive services Multi-lingual Scalable cloud platform Taught at 100+ universities

28 Watson Engagement Advisor 28 Transform Customer Experiences Customers For brands and their consumers Simple to use Support answers with evidence Dialog with person builds context IBM Customers have been Enterprises B2B2C, B2B2E Personalization of Interaction Call Center Assist, Self Help, ecommerce

29 Accelerate Research and Insights Watson Discovery Advisor 29 Experts Test hypotheses Find Evidence Discover New Facts At Scale Law Enforcement, Pharma Law, Education, Material Discovery

30 Watson Decision Advisor 30 Improve Decisions and outcomes Practioners Let practitioners consult with an expert Support a differential diagnosis Reason through possible actions Evidence-based decisions Primary Focus has been chronic disease Oncology Treatment support, not pure diagnosis MSK expertise codified via case studies

31 Watson Policy Advisor 31 Validate adherence to policy guidelines Providers, Payers & Regulators Determine if: - Policy adhered to - Policy violated - More data needed Provide supporting evidence Clinical Trial Matching 170,000 active clinical trials world wide Does a patient qualify for one? Should an Insurance Company pay out? Is there a potential issue with a medication?

32 32 5/ I want to be a Watson developer...

33 Award-Winning Examples of Watson Applications 3 of 50+ Watson Ecosystem Partners Built Applications Using Watson Services Platform 33 Train and support sellers in real time by understanding products and customers Children talk to their toys. This one talks back, teaching and observing Deliver personalized healthcare recommendations to me

34 Watson Services Platform 34 IBM Watson Solutions Healthcare Financial Services Public Sector Other IBM Watson Products Engagement Discovery Policy Other IBM Watson Platform (built on BlueMix ~ IBM Cloud Foundry) Domain Specialization Models Annotators Content Cognitive Services Perceiving Gaining insight into our world Reasoning Inferring new conclusions Learning improving insight with experience Relating Personalizing individual nteractions Tooling Assemble Ingest Train Deploy Admin Data Lake Data Curation Requirements Inventory Prioritization Preparation

35 Watson Services Platform: Delivered Via the Cloud /

36 A Watson Application: Polylingual Question and Answer for IT International Business Machines Corporation, Questions can be asked in either English or Spanish English questions are answered in English Spanish questions are answered bilingually Better or worse answers to a question can be browsed

37 Application Fragment: Polylingual Question and Answer for IT (Written in Ruby Sinatra) # # EXTRACT THE ANSWERS FROM A WATSON QUERY # watsonquery = JSON.parse(...)["question"] answers = watsonquery["evidencelist"] answer = answers[@answerindex] = answer[ value = answer[ text = answer[ value ]

38 Application Statistics: Polylingual Question and Answer For IT 38 AnswerPage.haml: QueryPage.haml: AskWatsonQuestionsInLotsaLanguages.rb 36 lines 20 lines 180 lines

39 Tool set for Watson Question and Answer Service 39 Ingest Train Build App Deploy

40 Watson Services Platform: Question and Answer Service 40

41 Watson ServicesPlatform: Question and Answer Service Documentation International Business Machines Corporation,

42 Watson Goes to University (Teaching Watson) Universities in 2014, 100+ in 2015 Analogous to a familar senior undergraduate course build an O/S, Compiler, or Data Management System Content, Training, Testing, Mobile Application Development, Business plan Inter-collegiate competition at conclusion: The top 3 individuals/teams from each school compete Grand prize of $100,000 in startup seed money Access to Watson, and support form IBM in getting to market International Business Machines Corporation, 2014

43 43