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Ml, AI and IBM Watson - 101 for Business

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What is IBM Watson, what are the benefits for business and how to get started.

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Ml, AI and IBM Watson - 101 for Business

  1. 1. Machine Learning, Artificial Intelligence and IBM Watson jouko.poutanen@fi.ibm.com Cognitive Solution Architect Country Technical Leader Machine Learning morning TTY 21.2.2017
  2. 2. Agenda • What is IBM Watson • Benefits for Business • How to Get Started © 2017 IBM jouko.poutanen@fi.ibm.com
  3. 3. IBM Watson in Different Industries Today https://youtu.be/PujCkDAXji8 © 2017 IBM jouko.poutanen@fi.ibm.com
  4. 4. Digitalisation Cloud Social Internet of Things Mobile Cognitive Security Analytics Cyber-Physical Systems Smart Service Systems Industry 4.0 Servitisation © 2017 IBM jouko.poutanen@fi.ibm.com
  5. 5. Why Cognitive Computing? 4V of 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. 6. What is a Biological 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. 7. What is the Goal 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. 8. We Need a New 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. 9. IBM Watson Is a 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. 10 Contributing Technologies © 2017 IBM jouko.poutanen@fi.ibm.com
  11. 11. When to Use Cognitive 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. 12. © 2017 IBM jouko.poutanen@fi.ibm.com Watson Discovery APIWatson Retrieve and Rank API
  13. 13. © 2017 IBM jouko.poutanen@fi.ibm.com
  14. 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 Text to 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. 15. Benefits for Business © 2017 IBM jouko.poutanen@fi.ibm.com
  16. 16. The Goals Why Cognitive Technology is Used © 2017 IBM jouko.poutanen@fi.ibm.com https://public.dhe.ibm.com/common/ssi/ecm/co/en/cow03020usen/COW03020USEN.PDF
  17. 17. Achieved Benefits © 2017 IBM jouko.poutanen@fi.ibm.com
  18. 18. Examples © 2017 IBM jouko.poutanen@fi.ibm.com
  19. 19. Examples © 2017 IBM jouko.poutanen@fi.ibm.com
  20. 20. How to Get Started © 2017 IBM jouko.poutanen@fi.ibm.com
  21. 21. Is This the Reality Today… © 2017 IBM jouko.poutanen@fi.ibm.com
  22. 22. How to Get Started – 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. 23. Why Should I be 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. 24. Resources © 2017 IBM jouko.poutanen@fi.ibm.com
  25. 25. Get Started https://developer.ibm.com/startups/ © 2017 IBM jouko.poutanen@fi.ibm.com

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