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Cost of dw 20170909 v18

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Cost of Digital Workers - Moore's Law is spooky

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Cost of dw 20170909 v18

  1. 1. Preparing for the Future of Artificial Intelligence (AI) September 9, 2017 https://www.slideshare.net/spohrer/ai-futures-20170909-v18 9/10/2017 (c) IBM 2017, Cognitive Opentech Group 1
  2. 2. Cost of Digital Workers: Narrow (Petascale) and Broad (Exascale) • Moore’s Law can be thought of as lowering costs by 1000 every 20 years, and a million every 40 years • AI Pattern Recognition • Narrow AI (Fast) I-Shaped • Petascale • AI Reasoning • Broad AI (Slow) T-Shaped • Exascale 29/10/2017 (c) IBM 2017, Cognitive Opentech Group 2080204020001960 $1K $1M $1B $1T 206020201980 +/- 10 years $1 Person Average Annual Salary (Living Income) Super Computer Cost Mainframe Cost Smartphone Cost
  3. 3. IBM-MIT $240M over 10 year AI mission 9/10/2017 (c) IBM 2017, Cognitive Opentech Group 3 Sept 7, 2017
  4. 4. Questions • What is the timeline for solving AI and IA? • Who are the leaders driving AI progress? • What will the biggest benefits from AI be? • What are the biggest risks associated with AI, and are they real? • What technologies may have a bigger impact than AI? • What are the implications for stakeholders: individuals, businesses and other organizations, industries, cities, states, and nations? • How should we prepare to get the benefits and avoid the risks? 9/10/2017 (c) IBM 2017, Cognitive Opentech Group 4
  5. 5. AI Trends 9/10/2017 © IBM Cognitive Opentech Group (COG) 5 Dota 2 “Deep Learning” for “AI Pattern Recognition” depends on massive amounts of “labeled data” and computing power available since ~2012; Labeled data is simply input and output pairs, such as a sound and word, or image and word, or English sentence and French sentence, or road scene and car control settings – labeled data means having both input and output data in massive quantities. For example, 100K images of skin, half with skin cancer and half without to learn to recognize presence of skin cancer.
  6. 6. AI to IA Timeline: Hard unsolved AI problems • 2012-2019 AI Pattern Recognition and Learning from Massive Labeled Data • Speech, image, translation, driverless, games • Chatbots as digital assistants • 2020 Video Understanding • 2021 Episodic Memory • 2022 Learning from Watching • 2023 Commonsense Reasoning ** • 2024 Learning from Doing • 2025 Fluent Conversation • 2026 Learning from Reading • 2027-2035 Cognitive Collaborator and Mediator; Intelligence Augmentation (IA) 9/10/2017 (c) IBM 2017, Cognitive Opentech Group 6
  7. 7. AI Leaders • Who is winning?* (depends on search terms) • Nations by Publications • Companies by Publications and Patents • Leaderboards • SQuAD – Question Answering • EFF Measuring AI Progress 9/10/2017 (c) IBM 2017, Cognitive Opentech Group 7
  8. 8. History of AI • The Dartmouth Conference of 1956[39] was organized by Marvin Minsky, John McCarthy and two senior scientists: Claude Shannon and Nathan Rochester of IBM 9/10/2017 (c) IBM 2017, Cognitive Opentech Group 8 Today’s Challenge: Scaling to Democratize AI
  9. 9. Brief History of Deep Learning • 1943 Threshold Logic • 1958 Perceptron • 1986 Hinton Backprop • 1989 Lecunn for digits • 2009 Ng GPUs • 2012 Hinton ImageNet • 2014 Facebook DeepFace • 2016 DeepMind AlphaGo • 2017 IBM Scaling 95% 9/10/2017 (c) IBM 2017, Cognitive Opentech Group 9
  10. 10. Hillery Hunter (IBM) Distributed Deep Learning 9/10/2017 (c) IBM 2017, Cognitive Opentech Group 10
  11. 11. IBM Research TrueNorth Chip • Extremely Low Power • Fast Inference • High Accuracy • 6000 frames/sec/watt 9/10/2017 (c) IBM 2017, Cognitive Opentech Group 11
  12. 12. AI Benefits • Access to expertise • “Insanely great” labor productivity for trusted service providers • Digital workers for healthcare, education, finance, etc. • Better choices • ”Insanely great” collaborations with others on what matters most • AI for IA = Augmented Intelligence and higher value co-creation interactions 9/10/2017 (c) IBM 2017, Cognitive Opentech Group 12
  13. 13. AI Risks • Job Loss • Shorter term bigger risk = de-skilling • Super-intelligence • Shorter term bigger risk = bad actors 9/10/2017 (c) IBM 2017, Cognitive Opentech Group 13
  14. 14. Other Technologies: Bigger impact? • Augmented Reality (AR)/ Virtual Reality (VR) • Game worlds grow-up • Blockchain/ Security Systems • Trust and security immutable • Advanced Materials/ Energy Systems • Manufacturing as cheap, local recycling service (utility fog, artificial leaf, etc.) 9/10/2017 (c) IBM 2017, Cognitive Opentech Group 14
  15. 15. Stakeholders • Individuals • Businesses and other Organizations • Industries • Regions: Cities, States, Nations 9/10/2017 (c) IBM 2017, Cognitive Opentech Group 15
  16. 16. Prepare • Open AI code + data + models + stacks + community • Ethical conduct • Learn 3 R’s of IBM’s Cognitive Opentech Group (COG) • Read arXiv • Redo with Github • Report with Jupyter notebooks on DSX and/or leaderboards • Improve your skills of rapidly rebuilding from scratch • Build your open code eminence 9/10/2017 (c) IBM 2017, Cognitive Opentech Group 16 1972 used Punch cards 2016 used IBM Watson Open APIs to win…
  17. 17. Cupertino Teens • IBM Watson on Bluemix 9/10/2017 (c) IBM 2017, Cognitive Opentech Group 17 AI for NLP entity identification
  18. 18. 9/10/2017 © IBM 2015, IBM Upward University Programs Worldwide accelerating regional development 18
  19. 19. 9/10/2017 © IBM 2015, IBM Upward University Programs Worldwide accelerating regional development 19 Future of Skills
  20. 20. Future-Ready T-Shapes 9/10/2017 © IBM UPWard 2016 20
  21. 21. In Summary 9/10/2017 © IBM 2015, IBM Upward University Programs Worldwide accelerating regional development 21 “A service science perspective considers the evolving ecology of service system entities, their value co-creation and capability co-elevation interactions, and their capabilities, constraints, rights, and responsibilities.” Cognitive Systems Entities Service Systems Entities With Cognitive Mediators Add Rights & Responsibilities

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