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Cognitive Computing: Can Computers Learn from Experience? - Deloitte Dbrief, Nov 7, 2013

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With recent advances in cognitive computing, computers may soon be able to help experts make better decisions by making sense of unstructured data. Systems are being trained today to sense, predict, …

With recent advances in cognitive computing, computers may soon be able to help experts make better decisions by making sense of unstructured data. Systems are being trained today to sense, predict, infer and, in some ways, think. Learn about recent advances in cognitive computing and ways it can help you improve business decision making.

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  • 1. The Dbriefs Technology Executives series presents: Cognitive Computing: Can Computers Learn from Experience? Rajeev Ronanki, Principal, Deloitte Consulting LLP David Steier, Director, Deloitte Consulting LLP November 7, 2013
  • 2. Copyright © 2013 Deloitte Development LLC. All rights reserved. Cognitive computing introduction How is it different from traditional computing? Structured vs. unstructured data Cognitive analytics Case studies Convergent solutions Agenda Follow @MarkAtDeloitte or #cognitivecomputing during the webcast
  • 3. Copyright © 2013 Deloitte Development LLC. All rights reserved. Are you familiar with any of these new cognitive computing approaches like IBM’s Watson, Numenta and Google Now? • Had not heard of them prior to this webcast • Have heard of some of these in the news • Have followed them but have not thought of them as representing a new class of computing • Have used some of these tools and look forward to more • Don’t know/Not applicable Poll question #1
  • 4. Copyright © 2013 Deloitte Development LLC. All rights reserved. Historical timeline The evolution of Cognitive Computing • Turing Test published: a computer that exhibits intelligent behavior equivalent to, or indistinguishable from, that of a human. • Scientific community focuses on machine translation • Scientific community focuses on AI • First successful NLP systems • MYCIN diagnosed infectious blood diseases • Semantic classification & probabilistic parsing are combined in machine systems. Can derive rules and their probabilities • First commercial database management system tracks huge amount of structured data for Apollo Moon Mission • Machine learning algorithms for language processing introduced • Judea Pearl brings probability and decision theory into AI • Watson. Question – answering system capable of answering questions posed in natural language • TAKMI (Text Analysis & Knowledge Mining) developed to capture and utilize knowledge embedded in text files – applied to call centers • TAKMI provides insights on patient groups to help doctors treat groups of patients at a time • Watson: IBM, WellPoint, Memorial Sloan Kettering use Watson to give doctors treatment options in seconds • World’s first single molecule computer circuit • The High Performance Computing Act of 2004 was enacted • IBM Content, Predictive and Streaming analytics • Streaming analytics process 5 million messages of market data per second to speed up financial trading decisions 1950’s 1960’s 1970’s 1980’s 1990’s 2000’s 1997 2001 2004 2007 2009-2010 2013 Current Over the decades… The last 10 years…
  • 5. Copyright © 2013 Deloitte Development LLC. All rights reserved. Cognitive computing • Emulates strengths of the human brain, including parallel processing & associative memory • Enables natural language processing of structured and unstructured data. • Understand/leverage big data in real time • Use machine learning to develop context-based hypotheses Basics Current Investments Cognitive Computing can push past the limitations of human cognition, and connect the dots between big data, enabling more informed decisions. A couple of industry examples include: Academic Commercial Consumer The development of computer systems inspired by the human brain Financial Services Implications: Advise in trading, and help identify financial fraud cases Healthcare Implications: Incorporate all new medical evidence, individual patient histories, and eliminate geographic constraints. Potential applications of cognitive computing Boltzmann Machine Never-Ending Language Learning (NELL) Saffron Natural Intelligence Platform Facebook AI Group Kngine IBM Watson Numenta Google Now Apple Siri
  • 6. Copyright © 2013 Deloitte Development LLC. All rights reserved. How is it different? • Sequential processing • Driven by programming language • Not real-time • Predefined logic • Static business rules • Passive • Defined input parameter • Event driven • Machine learning and natural language based • Parallel processing different sources at the same time • Context driven • Dynamic learning algorithm • Sensory & mobile based • Continuous collection and feedback Traditional Computing Cognitive Computing User Interface Application Layer Processing Platform
  • 7. Copyright © 2013 Deloitte Development LLC. All rights reserved. Cognitive computing architecture Analytic Solutions Data & Analytics Platform Content Lifecycle Services Data Corpus Core Engine ContentSources Extract Ingest Discover Curation Services Ingestion Services Enrichment Services Search Indices Semantic Models Derived Knowledge Question Analysis Hypothesis Generation Evidence Scoring Final Merge and Rank Cognitive Analytics Applications Natural Language Processing (NLP) Stack Machine Learning Modules Computing Resources (Cloud/On-Premise) Modeling & Processing Engine
  • 8. Copyright © 2013 Deloitte Development LLC. All rights reserved. Do you see a role for adopting cognitive computing technologies into your business? • Still unclear as to how these fit into our strategy • We are tracking these developments but no plans yet • Beginning to develop a roadmap in some areas • Have active plans or projects beginning now • Don’t know/Not applicable Poll question #2
  • 9. Copyright © 2013 Deloitte Development LLC. All rights reserved. Not all data is created equal Structured data is being rapidly augmented by unstructured data Structured Data Email & blog content Video & social content Patient records 10-Ks & public filings Industry reports & research journals Unstructured Data Transaction & CRM data Research & market data Mainframe data Point-of-sale data AnalysisAnalysis Hypothesis Generation & Scoring Hypothesis Generation & Scoring Final Evidence & Scoring Final Evidence & Scoring Initial Question Initial Question Final Insights Final Insights Advanced processing capabilities such as Natural Language Processing analyze disparate data to yield valuable insights 40-50% annual growth in digital data volume1 ~8x of unstructured data vs. structured data by 20203 1https://www-950.ibm.com/events/wwe/nedc/scesfall12.nsf/RodAdkins.pdf, page 5 2HP Autonomy Whitepaper: Transitioning to a New Era of Human Information, page 3 3https://www-950.ibm.com/events/wwe/nedc/scesfall12.nsf/RodAdkins.pdf, page 2 62% annual growth in unstructured data2
  • 10. Copyright © 2013 Deloitte Development LLC. All rights reserved. Cognitive analytics Cognitive Computing Industry Application Healthcare: A global cognitive analytics provider and major cancer medical center creating a cognitive system that uses cancer patient treatment data to assist oncologists to diagnose and treat patients based on the most current available data. Retail: Cognitive computers serving as customer service lines, in-store kiosks, or digital store clerks providing answers to customers’ questions around products, trends, recommendations, etc. pulled from millions of data points and structured / unstructured data. Financial Services: Narrative Science arming investment managers and financial advisors with customized portfolio intelligence, and clients with regular, mobile-friendly account performance summaries, updates, imbalance alerts, changes in risk, etc. Basic Application • Drive insights with rich context/unstructured data • Form hypotheses and predictions based on machine learning to aid real time decision making • Self-correcting and evolving algorithm that emulates human cognition • Big data processing • Platform for machine based learning • Processing of unstructured data • Natural language processing • Processing power and flexibility Real time decision making Context rich insights/data Multiple Industries CognitiveAnalytics
  • 11. Copyright © 2013 Deloitte Development LLC. All rights reserved. Case study: Health Plan improves patient care ü Combine claims and provider data to gain insight into the true health of the patient ü Use Cognitive Analytics to identify patients most at risk for hospital re- admissions and high-cost events ü Refine and enrich the solution as the dataset evolves ü Augments scarce skillset, and leverages subject matter experts to review/refine instead of performing the primary analysis Ø Proactively identify at-risk patients and prevent disease before it occurs or gets worse Ø Over 100 terabytes of claims data, with 200+ points of correlation Ø Petabytes of medical notes, physical exams, test results, etc. from providers Ø Ability to process a billion new claims each year is constrained by clinical subject matter expert High-Level Process Combine with related population data Combine with related population data Identify key at- risk patients Identify key at- risk patients Refine based on human input Refine based on human input Ingest large volumes of claims & provider data Ingest large volumes of claims & provider data Final candidate list of at-risk patients Final candidate list of at-risk patients The problem The solution
  • 12. Copyright © 2013 Deloitte Development LLC. All rights reserved. Case study: Financial Services firm improves customer service ü Use Cognitive Analytics to detect customer micro segments ü Track customers with high-value and high attrition risk, and predict future high-value customers ü Develop personalized marketing strategies to maximize responsiveness and create promotions appropriate for each client Ø Firm has vast amounts of transactional data, but is light on data scientists and missing the opportunity to see what drives customer behavior Ø Over 500 terabytes of transactional data and multiple 3rd party data sources High-Level Process Integrate with 3rd party sources Integrate with 3rd party sources Create simulations / generate models Create simulations / generate models Ingest large volumes of transactional data Ingest large volumes of transactional data Targeted marketing for high value customers Targeted marketing for high value customers Identify target candidates / promotions Identify target candidates / promotions The problem The solution
  • 13. Copyright © 2013 Deloitte Development LLC. All rights reserved. What barriers to adoption of these technologies do you see in business? • Too new, we do not have a clear enough understanding of them • There remain doubts about their effectiveness • We do not have a clear vision of how to adapt them to our needs given the small number of examples that exist now • It may just take time to build the business case • Building the business case and measuring value from the solution • Don’t know/Not applicable Poll question #3
  • 14. Copyright © 2013 Deloitte Development LLC. All rights reserved. Case study: Unlocking the full picture of health • Patient has type 2 diabetes • Regular checkup that included a blood sugar test • Reasons for visit: Hypertension; medication and treatment plan non-compliance • Recommendations for medication and lifestyle changes to manage stress, alcohol use. and begin smoking cessation • Perspective into the patient’s lifestyle and reason for medication non-adherence (e.g., does the patient have underlying issues with depression?) • How long has the patient been having symptoms of hypertension and type 2 diabetes? • What triggered this occurrence? Does patient have underlying depression? • What were the final diagnoses? • What were all the costs of the outpatient visit? Structured Data | Claims • Visit Type: Outpatient • Primary Diagnosis: Type 2 diabetes, hypertension • Lab Result: Elevated random blood sugar levels of 240mg/dl Unstructured Data | Medical Records & Notes • Reason for visit: Dizziness and blurred vision for 10 days (B/P 170/96) • Patient Background: o 6 month history of drinking a six pack & smoking a pack daily o Sleeps over 10 hours a day o Recent weight gain of 30 lbs. o Has not refilled prescriptions for 5 months Overview Conclusionsand Hypotheses Unanswered Questions Through the convergence of structured and unstructured data, we can get the full view of the patient, and make recommendations to improve his or her well-being
  • 15. Copyright © 2013 Deloitte Development LLC. All rights reserved. WatsonPaths explores complex scenarios and draws conclusions much like people do in real life. When presented with a medical case, it extracts statements based on the knowledge it has learned from medical doctors and medical literature. As medical experts interact with WatsonPaths, the system will use machine-learning to improve and scale the ingestion of medical information. Through this collaboration, WatsonPaths compares its actions with that of the medical expert so the system can get “smarter”. Case study: IBM WatsonPaths • A result of a year-long research collaboration with faculty, physicians and students at Cleveland Clinic Lerner College of Medicine of Case Western Reserve University • Expected to help physicians make more informed and accurate decisions faster and to cull new insights from electronic medical records (EMR) • Planned to be used by the Cleveland Clinic faculty and students as part of their problem-based learning curriculum and in clinical lab simulations Source: http://www.research.ibm.com/cognitive-computing/watson/watsonpaths.shtml
  • 16. Copyright © 2013 Deloitte Development LLC. All rights reserved. How do these technologies need to develop to become useful tools for your organization? • Provide clarity on business perspective purpose and effectiveness • Showcase more wins in areas that matter to us – stress results not science • Develop packaged offerings for industries that make them easier to adopt • It will take time, we are not early adopters • Don’t know/Not applicable Poll question #4
  • 17. Copyright © 2013 Deloitte Development LLC. All rights reserved. Cognitive Analytics: In summary How convergence will impact solutions Making relevant context-based suggestions and recommendations Ability to make quicker, more informed decisions Access to the right data at the right time Ability to capture and process larger amounts of data Machine Learning Artificial Intelligence Statistics & Decision Science Natural Language Processing Distributed Computing Cloud Computing Database Technology Analytics and Business Intelligence Visualization Various Data Collection Channels Structured and Unstructured Data Real Time Decision Making Cognitive Analytics
  • 18. Question and answer
  • 19. Join us December 5 at 2 PM ET as our Technology Executives series presents: Cloudy With a Chance of Core: Managing Integration in an Increasingly Complex World
  • 20. Copyright © 2013 Deloitte Development LLC. All rights reserved. Eligible viewers may now download CPE certificates. Click the CPE icon in the dock at the bottom of your screen.
  • 21. Copyright © 2013 Deloitte Development LLC. All rights reserved. Rajeev Ronanki Principal, Deloitte Consulting LLP rronanki@deloitte.com David Steier Director, Deloitte Consulting LLP dsteier@deloitte.com Contact info
  • 22. Copyright © 2013 Deloitte Development LLC. All rights reserved. Jim Zhu, Deloitte Consulting LLP Jeff DeLisio, Deloitte Consulting LLP Rui He, Deloitte Consulting LLP Fatema Samiwala, Deloitte Consulting LLP Rich Carelli, Deloitte Consulting LLP Steven Truong, Deloitte Consulting LLP Riddhi Roy, Deloitte Consulting LLP Research Team: Ashish Kumar, Deloitte Consulting LLP Marjorie Galban, Deloitte Consulting LLP William Shepherdson, Deloitte Consulting LLP Lindsey Tsuya, Deloitte Consulting LLP Eugene Chou, Deloitte Consulting LLP Thanks to our Dbriefs team
  • 23. Copyright © 2013 Deloitte Development LLC. All rights reserved. • Application Programming Interface (API) • Customer Relationship Management (CRM) • Enterprise Resource Planning (ERP) • Natural Language Processing (NLP) Acronyms used in presentation
  • 24. Copyright © 2013 Deloitte Development LLC. All rights reserved. This presentation contains general information only and Deloitte is not, by means of this presentation, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services. This presentation is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision or taking any action that may affect your business, you should consult a qualified professional advisor. Deloitte shall not be responsible for any loss sustained by any person who relies on this presentation.
  • 25. About Deloitte Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited, a UK private company limited by guarantee, and its network of member firms, each of which is a legally separate and independent entity. Please see www.deloitte.com/about for a detailed description of the legal structure of Deloitte Touche Tohmatsu Limited and its member firms. Please see www.deloitte.com/us/about for a detailed description of the legal structure of Deloitte LLP and its subsidiaries. Certain services may not be available to attest clients under the rules and regulations of public accounting. Copyright © 2013 Deloitte Development LLC. All rights reserved. Member of Deloitte Touche Tohmatsu Limited