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Steve Mills - Your Cognitive Future
- 1. Steve Mills Executive VicePresident IBM Software and Systems
- 2. Your Cognitive Future HowNext-gen Computing Changes the Way We Live and Work
- 3. What Is Drivingthe Need for Cognitive Computing? 3 Percentage of unstructured data We are here Sensors & Devices Social Media VOIP Enterprise Da 44 zettabytes 2010 2015 2020
- 4. We are Enteringa New Era of Computing 4 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
- 5. 1997: Deep Blue IBMDeep 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 … 5 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”
- 6. Alarmists? …. orRealists? 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at an ever increasing rate …… Humans, who are limited by slow biological evolution, couldn’t compete, and would be superseded.”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.”
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- 9. So, What IsCognitive Computing? 9 ▪ 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)
- 10. What are CognitiveSystems Good At? 10 ▪ 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
- 11. 11 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
- 12. Since Then WeHave Grown to 28 APIs – Based on ~50 Core Technologies 12 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 ExtractionTaxonomy 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 Core Technologies
- 13. Draws on FiveCore 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 ExtractionTaxonomy 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 Technologies Author Extraction Colloquialism Processing Concept Expansion Convolutional Neural Networks Deep Learning Dialog Entity Extraction Entity Resolution Feature Engineering Feature Weighting 12 Watson News In 2016, We Will Add an Additional 15 - 20 APIs
- 14. Watson for Oncology Providesclinicians 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 13
- 15. Relationship Extraction Finds relationships betweeningredients 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. 14 Chef Watson Assisting chefs in choosing the right combination of ingredients considering flavor, texture, and chemical composition of millions of ingredients
- 16. Question & Answer Allows the DigitalVirtual 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 15 Watson-powered "Digital Virtual Assistant" Helps guide Geico's customers through the experience of selecting an insurance policy
- 17. Watson Platform Builton IBM Bluemix 17 ▪ 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
- 18. U.S. and EUGovernments Investing in Cognitive Computing 18 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
- 19. The Great Decoupling 19 Trendsin US GDP, Profits, Investments, and Employment 1995 - 2011
- 20. Preparing for Tomorrow 20 ▪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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