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Smart Data Webinar: Knowledge as a Service

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Building a successful ModernAI application often requires large volumes of data for training ML models or data that has been organized into knowledge using taxonomies or ontologies to support specific vertical markets (healthcare, insurance, pharma, etc.) or horizontal functions (HR, legal, supply chain, etc). While tools do exist to help developers ingest and organize the required data into meaningful knowledge stores, using pre-built data or knowledge packages can make application development faster, more reliable, and less expensive than starting from scratch.

In this webinar we will look at trends and examples of specific proprietary and open source data sets that offer prebuilt knowledge, representations, or models to serve these markets.

Publié dans : Technologie
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Smart Data Webinar: Knowledge as a Service

  1. 1. APRIL 12, 2018 Knowledge as a Service An Introduction to the Emerging Pre-Built Knowledge Market Adrian J Bowles, PhD Founder, STORM Insights, Inc. Lead Analyst, AI, Aragon Research info@storminsights.com
  2. 2. AGENDA What Problem Are We Solving? Designing For Change Procuring Data Watch Out For…
  3. 3. Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved. WHY IS THE AVAILABILITY OF KNOWLEDGE & DATA SUCH AN ISSUE TODAY? PERCEPTION UNDERSTANDING LEARNING Big Data Classic AI Deep Learning
  4. 4. Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved. Systems Controls Model Data Mgmt Human Machine Input Output Gestures Emotions Language Narrative Generation Visualization Reports Haptics Sensors (IOT) Systems Controls DATA IN THE MODERN AI LANDSCAPE Learn Reason Understand Emotions Meaning Concepts Intent Context
  5. 5. Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved. Systems Controls Model Data Mgmt Human Machine Input Output Gestures Emotions Language Narrative Generation Visualization Reports Haptics Sensors (IOT) Systems Controls DATA MANAGEMENT IN THE MODERN AI LANDSCAPE Emotions Meaning Concepts Intent Context
  6. 6. IDENTIFYING THE RIGHT DATA SOURCES IS INCREASING IN IMPORTANCE Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved. DATA More Data + Faster HW make Deep Learning Practical Deep Learning Success With Recognition Spurs Investment ALGORITHMS & RULES Caution for Applications Where Transparency is Critical Investment Leads to Investigation Broaden the Scope of Applications New “Explainability” Research Emerges Hybrid Solutions to Augment Intelligence Will Thrive for Critical Applications
  7. 7. DATA REQUIREMENTS VARY WITH DOMAIN/TASK REQUIREMENTS Domain Task General General Intelligent Apps Healthcare Customer Service Reorder Rx Speak to a Pharmacist Pharma Artificial General Intelligence Chatbot
  8. 8. THE SEMANTIC WEB: ALL DATA SHOULD BE ASSOCIATED WITH SEMANTIC ATTRIBUTES (MEANING) Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved. RDF - Resource Description Framework - A directed, labeled graph. DFS - RDF Specifications Suite Recommendations (Language for representing RDF vocabularies) SPARQL - A Semantic Protocol & Query Language for RDF Data OWL - The Web Ontology Language is a Semantic We language designed to represent knowledge about things and relationships between things on the Web. An OWL Document is an Ontology. https://www.w3.org/2013/data/ BASICS OF THE W3C SEMANTIC WEB ONTOLOGY STACK
  9. 9. DEEP STRUCTURE REQUIRES STRONGER METHODS FOR ANALYSIS TO FIND CONCEPTS Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved. Perception: obvious structure is easy to process… but most of the interesting stuff isn’t obvious to a computer.
  10. 10. START WITH A TAXONOMY Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved. A taxonomy represents the formal structure of classes or types of objects within a domain. •Generally hierarchical and provide names for each class in the domain. •May also capture the membership properties of each object in relation to the other objects. •The rules of a specific taxonomy are used to classify or categorize any object in the domain, so they must be complete, consistent, and unambiguous. This rigor in specification should ensure that any newly discovered object must fit into one, and only one, category or object class.
  11. 11. ONTOLOGIES Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved. An ontology formalizes and specifies the names, definitions, and attributes of entities within a domain. An accepted ontology may define the domain.
  12. 12. ONTOLOGIES EVOLVE - SYSTEMS MUST BE FLEXIBLE Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved. TRUTH VS BELIEF - DESIGN ACCORDINGLY
  13. 13. DATA SOURCE INTEGRATION IS A DESIGN CONSIDERATION Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved. DataSources Integrate CRM ERP Enterprise Apps Streaming Historical/ Static/Batch Required Optional IoT Sensors Social Media Streams Log Data Other Streams Deliv er Visualize Analyze
  14. 14. DETERMINE YOUR NEED OR IDENTIFY RESOURCES FIRST? Domain Rate of Change General Streaming Specific Static Natural Language Traffic Stock Prices Weather APA Diagnostics Disaster/Battlefield Monitoring Twitterverse
  15. 15. USE PRE-BUILT KNOWLEDGE RESOURCES, SAVE TIME (30 YEARS?) Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved.
  16. 16. OPENCYC Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved.
  17. 17. PREBUILT CONTENT FOR FASTER DEPLOYMENT Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved. Watson Conversation and Virtual Agent Source: IBM
  18. 18. PROCURING DATA Commercial Providers Open Source Customers Public/Government Open Data
  19. 19. YAGO - YET ANOTHER GREAT ONTOLOGY Semantic knowledge base derived from Wikipedia, WordNet, and GeoNames s://www.mpi-inf.mpg.de/departments/databases-and-information-systems/research/yago-naga/yag Joint project of the Man Planck Institute for Informatics and the Telecom Paris Tech University > 10M entities > 120M facts Facts & Entities may have Temporal and Spacial Dimensions Open Source: Available on Github (8/31/2017) Graph Browser
  20. 20. Extracting “structured data” from Wikipedia. The DBpedia data set describes > 4.58 million entities >4 million are classified in a consistent ontology, including 1,445,000 persons, 735,000 places, 123,000 music albums, 87,000 films, 19,000 video games, 241,000 organizations, 251,000 species and 6,000 diseases. ~50 million links to other RDF datasets, 80.9 million links to Wikipedia categories, and 41.2 million YAGO2 categories. DBpedia uses the Resource Description Framework (RDF) to represent extracted information and consists of 3 billion RDF triples, of which 580 million were extracted from the English edition of Wikipedia and 2.46 billion from other language editions. Derived from "DBpedia." Wikipedia, The Free Encyclopedia. Wikipedia, The Free Encyclopedia, 17 Nov. 2017. Web. 12 Apr. 2018.
  21. 21. NEED TO ASSOCIATE/RECOGNIZE/UNDERSTAND TO ORGANIZE/REPRESENT Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved. Wordnet(R) Princeton University "About WordNet." Princeton University. 2010. <http://wordnet.princeton.edu>
  22. 22. Source: https://aws.amazon.com/public-datasets/ REPRESENTATIVE DATA SETS
  23. 23. Source: https://cloud.google.com/public-datasets/ REPRESENTATIVE DATA SETS
  24. 24. Source: https://docs.microsoft.com/en-us/azure/sql-database/sql-database-public-data-sets REPRESENTATIVE DATA SETS
  25. 25. CUSTOMERS CAN BE RICH DATA SOURCES Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved. Type Typical Current Use Potential Use Accelerometer/motion Rotate screen, Switch screen to landscape/portrait Ambient Light Adjust screen brightness Barometer Measure altitude Geo-Location (wifi/cellular) Location/Alerts 3-Axis Gyroscope Rotation rate for games, VR… Proximity Turn off screen when phone is by your head Touch ID fingerprint, Facial Recognition Security
  26. 26. CUSTOMERS CAN BE RICH DATA SOURCES Copyright (c) 2012-6 by Dark Sky Company LLC. All Rights Reserved.
  27. 27. OPEN DATA Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved.
  28. 28. PUBLIC USE OF OPT-IN DATA https://www.boston.gov/departments/new-urban-mechanics/street-bump Smarter Cities Collaborative Intelligence The Borg Lives!
  29. 29. DISTRIBUTED DATA AND INTELLIGENCE Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved. Intelligence can be Local to the device Distributed Aggregated
  30. 30. OPT-IN FREE DATA Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved.
  31. 31. LOCATION AND PROXIMITY DATA Copyright (c) by Qualcomm. All Rights reserved.
  32. 32. A WORD OF CAUTION Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved. Sometimes the wisdom of crowds leads to Unintended Consequences
  33. 33. BE CAREFUL USING COMMERCIALLY ACQUIRED DATA Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved. According to MaxMind… This farm is home to 600,000,000 IP Addresses Watch Out for Unintended Consequences, Especially With Big Data
  34. 34. “THAT’S A BIG HOUSE” - MEANING MAY BE DIFFERENT FOR DIFFERENT SPEAKERS Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved. Bob Mary Al (Capone) Wikipedia contributors. "Alcatraz Federal Penitentiary." Wikipedia, The Free Encyclopedia. Wikipedia, The Free Encyclopedia, 30 Oct. 2017. Web. 8 Nov. 2017.
  35. 35. DRAW A QUARTER, TO SCALE - RESULTS DIFFER ACCORDING TO HIDDEN CONTEXT Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved.
  36. 36. IT’S (ALMOST) ALL OUT THERE Domain Rate of Change General Streaming Specific Static Wikipedia OpenCyc Public OpenData NOAA Data
  37. 37. FIND NEW USES FOR EXISTING DATA SOURCES Copyright (c) 2018 by STORM Insights Inc. All Rights Reserved. Copyright (c) 2014 by Umbrellium Ltd. No Shortage of Data How will you create value?
  38. 38. adrian@storminsights.com Twitter @ajbowles Skype ajbowles KEEP IN TOUCH Upcoming SmartData Webinar Dates & Topics May 10 Case Studies: Transforming Industries with AI (Manufacturing & Retail) June 14 Natural Language Processing: From Chatbots to Artificial Understanding with Affective I/O COMING SOON… AGEOFREASONING.COM BOOK, VIDEOS, PROFESSIONAL SERVICES WWW.AGEOFREASONING.COM

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