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Ml, AI and IBM Watson - 101 for Business
The document discusses machine learning, artificial intelligence, and IBM Watson. It provides an agenda that includes what IBM Watson is, the benefits for business, and how to get started. It then discusses how IBM Watson is used in different industries and technologies like cloud computing, analytics, and cognitive systems. The document outlines when cognitive computing should be used and not used. It also provides examples of how organizations have used IBM Watson and the benefits they achieved. Finally, it provides recommendations on how to get started with cognitive technologies and resources for learning more.
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Ml, AI and IBM Watson - 101 for Business
- 1. Machine Learning, Artificial Intelligence and IBMWatson jouko.poutanen@fi.ibm.com Cognitive Solution Architect Country Technical Leader Machine Learning morning TTY 21.2.2017
- 2. Agenda • What isIBM Watson • Benefits for Business • How to Get Started © 2017 IBM jouko.poutanen@fi.ibm.com
- 3. IBM Watson inDifferent Industries Today https://youtu.be/PujCkDAXji8 © 2017 IBM jouko.poutanen@fi.ibm.com
- 4. Digitalisation Cloud Social Internet of Things Mobile Cognitive Security Analytics Cyber-PhysicalSystems Smart Service Systems Industry 4.0 Servitisation © 2017 IBM jouko.poutanen@fi.ibm.com
- 5. Why Cognitive Computing? 4Vof Data (Volume, Variety, Velocity, Veracity) CapabilitytoChange Performance Gap Opportunity …new ways of working, operating, thinking Achievement …but riding by the constraints of limited capabilities, organization achievements would be at slower pace Cognitive computing © 2017 IBM jouko.poutanen@fi.ibm.com
- 6. What is aBiological Cognitive System? © 2017 IBM jouko.poutanen@fi.ibm.com Common capability: to use language for communicating and coordinating reasoning and interactions and the accumulation of knowledge for collectively better outcomes.
- 7. What is theGoal of Digital Cognitive Systems? Artificial Intelligence = Machine Intelligence Augmented Intelligence = Human Intelligence + Machine Intelligence © 2017 IBM jouko.poutanen@fi.ibm.com Star Trek: Mr Data Iron Man: Tony Stark & Jarvis This is the Goal An individual smart machine vs Man and machine co-operation Capability to use language with machines for coordinating and reasoning for better outcomes. Increases human intelligence by use and not diminish it.
- 8. We Need aNew Way of Computing … Tabulation 1900 - 1950 - 2011 - Programmatic Era Cognitive Era Traditional IT • Structured data (local) • Deterministic Applications • Machine Language • Systems of records • Structured & unstructured (global) • Probabilistic Applications • Discovery Oriented • Natural Language • Systems of engagement Industry Solutions Business Analytics Big Data Watson Learn by example Learn by programming Cloud Computing © 2017 IBM jouko.poutanen@fi.ibm.com
- 9. IBM Watson Isa Cognitive System That… 99% 60% 10% Understands natural language and human speech Adapts and Learns from user selections and responses Reasons for better outcomes 3 2 1 © 2017 IBM jouko.poutanen@fi.ibm.com
- 10. 10 Contributing Technologies © 2017IBM jouko.poutanen@fi.ibm.com
- 11. When to UseCognitive Computing? © 2017 IBM jouko.poutanen@fi.ibm.com • When problems are complex, information and situation are shifting, and outcome depends on context • Diverse, changing data sources, including unstructured (text, images) • No clearly right answers: Data is complex and ambiguous, conflicting evidence • Ranked (confidence scored), multiple answers are preferred (alternatives) • Context dependent: time, user, location, point in task • Human-computer partnership and dialog are required When NOT to Use Cognitive Computing? • When predictable, repeatable results are required (e.g. sales reports) • When all data is structured, numeric and predictable When a probabilistic approach is not desirable • When existing transactional systems are adequate • When interaction, especially in natural language, is not necessary
- 12. © 2017 IBMjouko.poutanen@fi.ibm.com Watson Discovery APIWatson Retrieve and Rank API
- 13. © 2017 IBMjouko.poutanen@fi.ibm.com
- 14. Relationship Extraction Conversat ion Language Detection Personality Insights Keyword Extraction Image Link Extraction Feed Detection Visual Recognition Concept Expansion Concept Insights Discovery Sentimen t Analysis Textto Speech Tradeoff Analytics Natural Language Classifier Author Extraction Speech to Text Retrieve & Rank Watson News Language Translatio n Entity Extraction Tone Analyzer Concept Tagging Taxonomy Text Extraction Message Resonance Image Tagging Face Detection 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 Adaptation Knowledge Studio Service Statistical Dialog Q&A Qualification Factoid Pipeline Case Evaluation IBM BlueMix Watson APIs Watson has 29 APIs, more to come... Natural Language Processing Machine Learning Question Analysis Feature Engineering Ontology Analysis © 2017 IBM jouko.poutanen@fi.ibm.com LEGO bricks to build cognitive solutions
- 15. Benefits for Business ©2017 IBM jouko.poutanen@fi.ibm.com
- 16. The Goals WhyCognitive Technology is Used © 2017 IBM jouko.poutanen@fi.ibm.com https://public.dhe.ibm.com/common/ssi/ecm/co/en/cow03020usen/COW03020USEN.PDF
- 17. Achieved Benefits © 2017IBM jouko.poutanen@fi.ibm.com
- 18. Examples © 2017 IBMjouko.poutanen@fi.ibm.com
- 19. Examples © 2017 IBMjouko.poutanen@fi.ibm.com
- 20. How to GetStarted © 2017 IBM jouko.poutanen@fi.ibm.com
- 21. Is This theReality Today… © 2017 IBM jouko.poutanen@fi.ibm.com
- 22. How to GetStarted – Business Value Focused Increments • The secret to getting ahead is getting started, and getting started is easier than you might think • Cognitive technology adoption comes in all shapes and sizes, and most often starts relatively small • What the most successful projects have in common, no matter how ambitious, is they begin with a clear view of what cognitive technology can and cannot do • Consider how to leverage cognitive technology. Adoption only makes sense if it aligns with strategic priorities • Your adoption strategy should support profitable outcomes like saving money, gaining customers or increasing revenue. © 2017 IBM jouko.poutanen@fi.ibm.com
- 23. Why Should Ibe Interested? • Unarguably ML, AI & cognitive technologies will have a key role in future society • The technology is available today to start learning and gaining expertise • Early adopters can leverage the window of opportunity © 2017 IBM jouko.poutanen@fi.ibm.com
- 24. Resources © 2017 IBMjouko.poutanen@fi.ibm.com
- 25. Get Started https://developer.ibm.com/startups/ © 2017IBM jouko.poutanen@fi.ibm.com