Future of AI: Timeline, Benefits, Risks and How to Prepare
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Future of AI: Timeline, Benefits, Risks and How to Prepare
- 1. Future of AI #OpenTechAI Jim Spohrer Director, IBM Cognitive OpenTech Find my presentations on line at: http://slideshare.net/spohrer
- 2. 6/12/2019 (c) IBM MAP COG .| 2
- 3. Today’s talk • 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 other technologies may have a bigger impact than AI? • What are the implications for stakeholders? • How should we prepare to get the benefits and avoid the risks? • But first… 6/12/2019 IBM Code #OpenTechAI 3
- 4. AI at IBM: Past (Nathan Rochester) 6/12/2019 (c) IBM MAP COG .| 4
- 5. Icons of AI Progress • 1956: Dartmouth Conference organized by: • John McCarthy (Dartmouth, later Stanford) • Marvin Minsky (MIT) • and two senior scientists: • Claude Shannon (Bell Labs) • Nathan Rochester (IBM) • 1997: Deep Blue (IBM) - Chess • 2011: Watson Jeopardy! (IBM) • 2016: AlphaGo (Google DeepMinds) 6/12/2019 (c) IBM 2017, Cognitive Opentech Group 5
- 7. 6/12/2019 © IBM UPWard 2016 7 AI (Artificial Intelligence) is popular again… you see it mentioned on billboards in SF However, pattern recognition does not equal AI Deep learning works if you have lots of data and compute power We finally have lots of data and compute power – hurray!!! So finally, deep learning for pattern recognition is working pretty well However, AI is more than deep learning for pattern recognition… AI requires commonsense reasoning – that will take another 5-10 years of research How do we know this? Look at the AI leaderboards – we will get to that…
- 8. 6/12/2019 (c) IBM MAP COG .| 8
- 9. Smartphones pass entrance exams? When? 6/12/2019 (c) IBM 2017, Cognitive Opentech Group 9 … when will your smartphone be able to take and pass any online course? And then be your coach, so you can pass too?
- 10. IBM-MIT $240M over 10 year AI mission 6/12/2019 (c) IBM 2017, Cognitive Opentech Group 10
- 11. 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 other technologies may have a bigger impact than AI? • What are the implications for stakeholders? • How should we prepare to get the benefits and avoid the risks? 6/12/2019 (c) IBM 2017, Cognitive Opentech Group 11
- 12. Timeline: Short History 6/12/2019 © IBM Cognitive Opentech Group (COG) 12 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.
- 13. Timeline: Every 20 years, compute costs are down by 1000x • Cost of Digital Workers • Moore’s Law can be thought of as lowering costs by a factor of a… • Thousand times lower in 20 years • Million times lower in 40 years • Billion times lower in 60 years • Smarter Tools (Terascale) • Terascale (2017) = $3K • Terascale (2020) = ~$1K • Narrow Worker (Petascale) • Recognition (Fast) • Petascale (2040) = ~$1K • Broad Worker (Exascale) • Reasoning (Slow) • Exascale (2060) = ~$1K 136/12/2019 (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 T P E T P E AI Progress on Open Leaderboards Benchmark Roadmap to solve AI/IA
- 14. Timeline: GDP/Employee 6/12/2019 (c) IBM 2017, Cognitive Opentech Group 14 (Source) Lower compute costs translate into increasing productivity and GDP/employees for nations Increasing productivity and GDP/employees should translate into wealthier citizens AI Progress on Open Leaderboards Benchmark Roadmap to solve AI/IA
- 15. 15September 2018 / © 2018 IBM Corporation
- 16. 6/12/2019 © IBM 2015, IBM Upward University Programs Worldwide accelerating regional development 16
- 17. IBM Quantum 6/12/2019 (c) IBM MAP COG .| 17
- 18. Quantum Risk Assessment 6/12/2019 (c) IBM MAP COG .| 18 URL: https://www.nature.com/articles/s41534-019-0130-6
- 19. Computing: Then, Now, Projected 6/12/2019 19 2035 2055
- 20. Timeline: Leaderboards FrameworkAI Progress on Open Leaderboards - Benchmark Roadmap Perceive World Develop Cognition Build Relationships Fill Roles Pattern recognition Video understanding Memory Reasoning Social interactions Fluent conversation Assistant & Collaborator Coach & Mediator Speech Actions Declarative Deduction Scripts Speech Acts Tasks Institutions Chime Thumos SQuAD SAT ROC Story ConvAI Images Context Episodic Induction Plans Intentions Summarization Values ImageNet VQA DSTC RALI General-AI Translation Narration Dynamic Abductive Goals Cultures Debate Negotiation WMT DeepVideo Alexa Prize ICCMA AT Learning from Labeled Training Data and Searching (Optimization) Learning by Watching and Reading (Education) Learning by Doing and being Responsible (Exploration) 2018 2021 2024 2027 2030 2033 2036 2039 6/12/2019 (c) IBM 2017, Cognitive Opentech Group 20 Which experts would be really surprised if it takes less time… and which experts really surprised if it takes longer? Approx. Year Human Level -> +3
- 21. Narrow AI Emerging Broad AI Disruptive and Pervasive General AI Revolutionary ▼ We are here 2050 and beyond 21IBM Research AI © 2018 IBM Corporation The evolution of AI Borrowed from David Cox, IBM-MIT Lead
- 22. Narrow AI Single task, single domain Superhuman accuracy and speed for certain tasks Broad AI Multi-task, multi-domain Multi-modal Distributed AI Explainable General AI Cross-domain learning and reasoning Broad autonomy 22IBM Research AI © 2018 IBM Corporation The evolution of AI
- 23. Karpathy and Li, 2015
- 24. “Teddy Bear” Meret Oppenheim, Le Déjeuner en fourrure
- 25. Gatys et al. 2015 Brock et al. 2018
- 26. Lake, Ullman, Tenenbaum & Gershman, 2016
- 27. Chen et al. 2018 Pin-yu Chen IBM
- 28. The path to Broad AI Explainability Security + Ethics restaurant cook Follow recipe person sweet cheesecake dessert satisfy hunger oven bake survive swallow eat cake Learn more from small data ReasonsLearns to transfer + Infrastructure Physics of AI
- 29. Who is winning 6/12/2019 (c) IBM 2017, Cognitive Opentech Group 29 https://www.technologyreview.com/s/608112/who-is-winning-the-ai-race/
- 30. Robots by Country • Industrial robots per 10,000 people by country 6/12/2019 IBM #OpenTechAI 30 34
- 31. Sweden 6/12/2019 (c) IBM MAP COG .| 31
- 32. Economic Growth Rates 2035: AI Projected Impact 6/12/2019 (c) IBM MAP COG .| 32
- 33. 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 6/12/2019 (c) IBM 2017, Cognitive Opentech Group 33
- 34. AI Risks • Job Loss • Shorter term bigger risk = de-skilling • Super-intelligence • Shorter term bigger risk = bad actors 6/12/2019 (c) IBM 2017, Cognitive Opentech Group 34
- 35. Other Technologies: Bigger impact? Yes. • 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.) 6/12/2019 (c) IBM 2017, Cognitive Opentech Group 35
- 36. Stakeholders = service system entities • Individuals • Families • Businesses and other Organizations • Industry Groups and Professional Associations • Regional Governments: • Cities • States • Nations 6/12/2019 (c) IBM 2017, Cognitive Opentech Group 36 “there is nothing as practical as a good abstraction” -> service science studies service system entities
- 37. “The best way to predict the future is to inspire the next generation of students to build it better” Digital Natives Transportation Water Manufacturing Energy Construction ICT Retail Finance Healthcare Education Government
- 38. Artificial Leaf • Daniel Nocera, a professor of energy science at Harvard who pioneered the use of artificial photosynthesis, says that he and his colleague Pamela Silver have devised a system that completes the process of making liquid fuel from sunlight, carbon dioxide, and water. And they’ve done it at an efficiency of 10 percent, using pure carbon dioxide—in other words, one-tenth of the energy in sunlight is captured and turned into fuel. That is much higher than natural photosynthesis, which converts about 1 percent of solar energy into the carbohydrates used by plants, and it could be a milestone in the shift away from fossil fuels. The new system is described in a new paper in Science. 6/12/2019 IBM Code #OpenTechAI 38
- 39. Food from Air • Although the technology is in its infancy, researchers hope the "protein reactor" could become a household item. • Juha-Pekka Pitkänen, a scientist at VTT, said: "In practice, all the raw materials are available from the air. In the future, the technology can be transported to, for instance, deserts and other areas facing famine. • "One possible alternative is a home reactor, a type of domestic appliance that the consumer can use to produce the needed protein." • According to the researchers, the process of creating food from electricity can be nearly 10 times as energy efficient as photosynthesis, the process used by plants. 6/12/2019 IBM Code #OpenTechAI 39
- 40. Exoskeletons for Elderly • A walker is a “very cost-effective” solution for people with limited mobility, but “it completely disempowers, removes dignity, removes freedom, and causes a whole host of other psychological problems,” SRI Ventures president Manish Kothari says. “Superflex’s goal is to remove all of those areas that cause psychological-type encumbrances and, ultimately, redignify the individual." 6/12/2019 IBM Code #OpenTechAI 40
- 41. Be Prepared: Master Better Building Blocks • Understand open AI code + data + models + stacks + communities • Leaderboards • 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 team’s skills of rapidly rebuilding from scratch • Build your open code eminence • Understand open innovation • Communities + Leaderboards 6/12/2019 (c) IBM 2017, Cognitive Opentech Group 41 1972 used Punch cards 2016 used IBM Watson Open APIs to win…
- 42. 6/12/2019 © IBM 2015, IBM Upward University Programs Worldwide accelerating regional development 42 I have… Have you noticed how the building blocks just keep getting better?
- 43. Learning to program: My first program 6/12/2019 © IBM 2015, IBM Upward University Programs Worldwide accelerating regional development 43 Early Computer Science Class: Watson Center at Columbia 1945 Jim Spohrer’s First Program 1972
- 44. 6/12/2019 © IBM UPWard 2016 44 Fast Forward 2016: Consider this…
- 45. Microsoft CaptionBot June 19, 2016 6/12/2019 © IBM UPWard 2016 45
- 46. Microsoft CaptionBot June 20, 2016 6/12/2019 © IBM UPWard 2016 46
- 47. IBM Image Tagging 6/12/2019 © IBM UPWard 2016 47
- 48. Today: November 10, 2017 6/12/2019 © IBM DBG COG 2017 48 IBM
- 49. 6/12/2019 49 1955 1975 1995 2015 2035 2055 Be Prepared: Master Better Building Blocks
- 50. 6/12/2019 © IBM UPWard 2016 50
- 51. Cupertino Teens • IBM Watson on Bluemix 6/12/2019 (c) IBM 2017, Cognitive Opentech Group 51 AI for NLP entity identification
- 52. 10 million minutes of experience 6/12/2019 Understanding Cognitive Systems 52
- 53. 2 million minutes of experience 6/12/2019 Understanding Cognitive Systems 53
- 54. Hardware < Software < Data < Experience < Transformation 6/12/2019 Understanding Cognitive Systems 54 Value migrates to transformation – becoming our future selves; people, businesses, nations = service system entities Pine & Gilmore (1999) Transformation Roy et al (2006) Data Osati (2014) Experience Life Log
- 55. Courses • 2015 • “How to build a cognitive system for Q&A task.” • 9 months to 40% question answering accuracy • 1-2 years for 90% accuracy, which questions to reject • 2025 • “How to use a cognitive system to be a better professional X.” • Tools to build a student level Q&A from textbook in 1 week • 2035 • “How to use your cognitive mediator to build a startup.” • Tools to build faculty level Q&A for textbook in one day • Cognitive mediator knows a person better than they know themselves • 2055 • “How to manage your workforce of digital workers.” • Most people have 100 digital workers. 6/12/2019 55 Take free online cognitive classes today at cognitiveclass.ai
- 56. 6/12/2019 © IBM 2015, IBM Upward University Programs Worldwide accelerating regional development 56 Cognitive Mediators for all people in all roles
- 57. Occupations = Many Tasks 6/12/2019 © IBM 2015, IBM Upward University Programs Worldwide accelerating regional development 57
- 58. Watson Discovery Advisor 6/12/2019 © IBM 2015, IBM Upward University Programs Worldwide accelerating regional development 58 Simonite, T. 2014. Software Mines Science Papers to Make New Discoveries. MIT. November 25, 2014. URL: http://m.technologyreview.com/news/520461/software-mines-science-papers-to-make-new-discoveries/
- 59. Types: Progression of models Models = instruction set of future 6/12/2019 Understanding Cognitive Systems 59 Task & World Model/ Planning & Decisions Self Model/ Capacity & Limits User Model/ Episodic Memory Institutions Model/ Trust & Social Acts Tool + - - - Assistant ++ + - - Collaborator +++ ++ + - Coach ++++ +++ ++ + Mediator +++++ ++++ +++ ++ Cognitive Tool Cognitive Assistant Cognitive Collaborator Cognitive Coach Cognitive Mediator
- 60. Prepare for AI Future • Do you have a GitHub account? Get it. • Yes: proceed • No: sign up • Do you program? Either OK, partnering is best. • Yes: Learn and do 3 R’s (read, redo, report) • Github master: Code, Content (Data), Community (IBM Code can help) • No: Learn to read and execute code with partner (T2T) • Do you have favorite AI leaderboards? • Yes: Learn and do 3 R’s (read, redo, report advances) • Kaggle master: Combine top decorrelated solution, new solution • No: Find a mentor with favorites, do together • Are you AI prepared? Do you know/do data, models, solutions? • Yes: Find favorite leaderboards you can do 3 R’s for today • Figure-Eight master: Labeled data that matters most • No: Wait until one model: one model that can do them all • Then rapidly rebuild in least time, energy (“zorch”), data, code 6/12/2019 © IBM Cognitive Opentech Group 2018 60 1. Where do we get labeled data? We create it: Figure Eight, Mechanical Turk, etc. 2. External/internal challenge? 10M minutes from birth to adult 2M minutes from novice to expert Not just external states, but internal states are data as well… The challenge of data for AI models 3. AI models as ”data” instruction set Computer’s have instruction sets Arithmetic, Logic, etc. Models are becoming instructions Models are data/experience
- 61. Resilience: Rapidly Rebuilding From Scratch • Dartnell L (2012) The Knowledge: How to Rebuild Civilization in the Aftermath of a Cataclysm. Westminster London: Penguin Books. 6/12/2019 IBM Code #OpenTechAI 61
- 62. Trust: Two Communities 6/12/2019 IBM Code #OpenTechAI 62 Service Science OpenTech AI Trust: Value Co-Creation, Transdisciplinary Trust: Ethical, Safe, Explainable, Open Communities Special Issue AI Magazine? Handbook of OpenTech AI?
- 63. 6/12/2019 (c) IBM MAP COG .| 63
- 64. Cognitive OpenTech & CODAIT / Future of AI / March 23, 2018 / © 2019 IBM Corporation 64 Linus Torvalds & Todd Moore
- 65. Join: Registrations Open 2019-03-25 - https://callforcode.org/ 65IBM Open Technologies / Future of AI / April 19, 2019 / © 2019 IBM Corporation This multi-year global initiative rallies developers to create practical, effective, and high-quality applications based on cloud, data, and artificial intelligence that can have an immediate and lasting impact on humanitarian issues. Call for Code brings startup, academic, and enterprise developers together and inspires them to solve the most pressing societal issues of our time - for example, faster and more resilient recovery from natural disasters.
- 66. 6/12/2019 (c) IBM MAP COG .| 66 Microsoft acquiring GitHub $7.5B 2018 John Marks on Open Source Models will run the world Why SW is eating the world IBM acquiring Red Hat for $34B
- 67. Linux Foundation Artificial Intelligence • LFAI 6/12/2019 (c) IBM MAP COG .| 67
- 68. 6/12/2019 IBM Code #OpenTechAI 68
- 69. IBM MAX • Model Asset Exchange 6/12/2019 (c) IBM MAP COG .| 69
- 70. AI Fairness 360 6/12/2019 (c) IBM MAP COG .| 70
- 71. “The best way to predict the future is to inspire the next generation of students to build it better” Digital Natives Transportation Water Manufacturing Energy Construction ICT Retail Finance Healthcare Education Government
- 72. Step Comment GitHub Get an account and read the guide MAX CODAIT’s Model Asset Exchange Learn 3 R's - Read, Redo, Report Read (Medium/arXiv), Redo (GitHub), Report (Jupyter Notebook) PapersWithCode Stay on top of recent advances; Do 3 R’s. Kaggle Compete in a Kaggle competition Leaderboards Compete to advance AI progress Linux Foundation AI Help end-to-end open source industry AI & Data infrastructure Mozilla Common Voice Donate your speech; Label and verify data; Recruit others. Figure Eight Generate a set of labeled data (also Mechanical Turk) Design New Challenges Build for Call for Code/Code and Response; Build your AI Helper; Build test-taker, that can switch to tutor-mode; Etc. Open Source Guide Establish open source culture in your organization 6/12/2019 IBM Code #OpenTechAI 72
- 73. Cognitive OpenTech & CODAIT / Future of AI / March 23, 2018 / © 2019 IBM Corporation 73 Call for papers: Advances in Cognitive Systems, Aug 2-5, MIT, Cambridge, MA http://www.cogsys.org/conference/2019/ … submission deadline: May 10th. @neurobongo https://twitter.com/JimSpohrer/status/1118180598583 947269
- 74. Cognitive OpenTech Cognitive OpenTech & CODAIT / Future of AI / March 23, 2018 / © 2019 IBM Corporation 74 Director, Jim Spohrer CODAIT (Center for Opensource Data and AI Technologies) - Vijay Bommireddipalli AI OpenTech & Systems Performance - Tom Truong Watson Developer Advocates - Josh Cheng Susan Malaika (STSM) Augustina Ragwitz Open AI Advocato, Computational Anthropology IBM Silicon Alley, NYC, NYIBM Silicon Valley, San Jose, CAIBM Watson West, San Francisco, CA IBM Almaden, San Jose, CA
Hinweis der Redaktion
- Susan’s references Internal https://w3.ibm.com/w3publisher/ibm-developer-marketing/code-and-response https://w3.ibm.com/w3publisher/cfc-finalists External https://developer.ibm.com/callforcode/ https://developer.ibm.com/code-and-response/
- Visit IBM Research – Almaden, San Jose, CA USA 05120 – instructions: http://service-science.info/archives/4679 Join ISSIP.org – it’s free for individuals to join and get monthly newsletter: http://service-science.info/archives/4901 Contribute a short book to our series – blog compilations welcomed - http://www.businessexpertpress.com/product-category/service-systems-and-innovations-in-business-and-society/ We are trying to make complex servce systems things simpler – but not too simple. Wise innovation increase resilience with abundant opportunities for all.
- URL: http://fasterthan20.com/ URL: https://xkcd.com/1232/
- URL: http://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html URL: https://en.wikipedia.org/wiki/Nathaniel_Rochester_(computer_scientist)
- URL: https://en.wikipedia.org/wiki/History_of_artificial_intelligence URL: http://www.businessinsider.com/infographic-ai-effect-on-economy-2017-8 Today’s infographic comes from the Extraordinary Future 2017, a new conference in Vancouver, BC that focuses on emerging technologies such as AI, autonomous vehicles, fintech, and block http://extraordinaryfuture.com/e/extraordinary-future-2017-71chain tech. Nathaniel Rochester: In 1948, Rochester moved to IBM where he designed the IBM 701, the first general purpose, mass-produced computer. He wrote the first symbolic assembler, which allowed programs to be written in short, readable commands rather than pure numbers or punch codes.
- URL: https://www.ted.com/talks/noriko_arai_can_a_robot_pass_a_university_entrance_exam
- URL: http://news.mit.edu/2017/ibm-mit-joint-research-watson-artificial-intelligence-lab-0907 URL: https://www.amazon.com/Master-Algorithm-Ultimate-Learning-Machine/dp/0465094279
- 1950 Nathaniel Rochester (IBM) 701 first commercial computer that did super-human levels of numeric calculations routinely. He worked at MIT on arithmetic unit of WhirlWind I programmable computer. Dota 2 is most recent August 11, 2017 as a super-human game player in Valve Dota 2 competition – Elon Musk’s OpenAI result. Miles Bundage tracks gaming progress: http://www.milesbrundage.com/blog-posts/my-ai-forecasts-past-present-and-future-main-post DOTA2: https://blog.openai.com/more-on-dota-2/
- What is beyond Exascale? Zetta (21), Yotta (24) Time dimension (x-axis) is plus or minus 10 years…. Daniel Pakkala (VTT) URL: https://aiimpacts.org/preliminary-prices-for-human-level-hardware/ Dan Gruhl: https://www.washingtonpost.com/archive/business/1983/11/06/in-pursuit-of-the-10-gigaflop-machine/012c995a-2b16-470b-96df-d823c245306e/?utm_term=.d4bde5652826  In 1983 10 GF was ~10 million.  That's 24.55 million in today's dollars.  or 2.4 billion for 1 TF in 1983  Today 1 TF is about $3k http://www.popsci.com/intel-teraflop-chip
- Source: http://service-science.info/archives/4741
- Modha’s Brain - Goal 1KW and 2 Litres…. Dharmendra Modha and his design for a brain chip playing pong: https://www.youtube.com/watch?v=gQ3HEVelBFY https://www.youtube.com/watch?v=tqeINGOzIZo https://twitter.com/dharmendramodha/status/545693986149511168
- URL: https://www.nature.com/articles/s41534-019-0130-6
- If Moore’s Law continues, by 2035 and by 2055, we are projected to have unimaginably large amounts of cheap computing…. 2035 one human brain level, and by 2055 all human brains level(10 billion people). Based on Kurweil’s graph of how much compute power $1000 will buy, it seems that by 2030, for $1000 you should be able to buy the compute power of one person’s brain, and that by 2060 for $1000 you should be able to buy the computer power of 10***10, or 10B people, the compute power of the world’s population for $1000. Source: http://waitbutwhy.com/2015/01/artificial-intelligence-revolution-1.html Was Moore’s Law inevitable? http://kk.org/thetechnium/was-moores-law/
- +3 from original estimates, getting video understanding (verbs and nouns and context) and episodic dynamic memory for learning events and expectation violations and importance is taking longer than expected… Expert predictions on HMLI: URL https://arxiv.org/pdf/1705.08807.pdf 2015 Pattern Recognition Speech: URL: http://spandh.dcs.shef.ac.uk/chime_challenge/chime2016/results.html 2015 Pattern Recognition Images: URL: http://www.image-net.org/ 2015 Patten Recognition Translation: URL: http://www.statmt.org/wmt17/ 2018 Video Understanding Actions: URL: http://www.thumos.info/home.html > Also UCF101 http://crcv.ucf.edu/data/UCF101.php 2018 Video Understanding Context: URL: http://visualqa.org/challenge.html 2018 Video Understanding DeepVideo: URL: http://cs.stanford.edu/people/karpathy/deepvideo/ 2021 Memory Declarative: URL: https://rajpurkar.github.io/SQuAD-explorer/ Also Allen AI Kaggle Science Challenge https://www.kaggle.com/c/the-allen-ai-science-challenge 2024 Reasoning Deduction: URL: http://www.satcompetition.org/ 2027: Social Interaction Scripts: URL: https://competitions.codalab.org/competitions/15333 2030: Fluent Conversation Speech Acts: URL: http://convai.io/ 2030: Fluent Conversation Intentions: URL: http://workshop.colips.org/dstc6/ 2030: Fluent Conversation Alexa Prize: URL: https://developer.amazon.com/alexaprize 2033: Assistant & Collaborator Summarization: URL: http://rali.iro.umontreal.ca/rali/?q=en/Automatic%20summarization 2033: Assistant & Collaborator Debate: URL: http://argumentationcompetition.org/2015/ 2036: Coach & Mediator General AI: URL: https://www.general-ai-challenge.org/ 2036: Coach & Mediator Negotiation: URL: https://easychair.org/cfp/AT2017
- it used to be that computers couldn’t understand images
- ROW – Rest of World Who is winning: https://www.technologyreview.com/s/608112/who-is-winning-the-ai-race/ Leaderboards and reproducibility: Hugo Larochelle (Google Brain) (@hugo_larochelle) 8/21/17, 7:36 AM My slides for my talk at ICML 2017 Reproducibility Workshop, on incentives for open source and on open research: https://drive.google.com/file/d/0B8lLzpxgRHNQZ0paZWQ0cTcxMlNYYnc0TnpHekMxMjVBckVR/view Slide 20: Conclusions: "Open source is the key to better reproducibility"
- URL: https://www.nytimes.com/2017/12/27/business/the-robots-are-coming-and-sweden-is-fine.html
- URL: https://www.slideshare.net/AccentureTechnology/ai-and-the-economy/1 URL: https://www.accenture.com/no-en/insight-artificial-intelligence-future-growth Plastino E, Purdy M (2018) Game changing value from Artificial Intelligence: eight strategies. Strategy & Leadership. 2018 Jan 15;46(1):16-22. URL: https://www.slideshare.net/AccentureTechnology/ai-and-the-economy/1 URL: https://www.accenture.com/no-en/insight-artificial-intelligence-future-growth URL: https://www.researchgate.net/profile/Eduardo_Plastino/publication/323126961_Strategy_Leadership_Game_changing_value_from_Artificial_Intelligence_eight_strategies_Article_information/links/5a81ae20a6fdcc6f3eacfe35/Strategy-Leadership-Game-changing-value-from-Artificial-Intelligence-eight-strategies-Article-information.pdf Someday we will have AI's that help write the first draft of our chapters - see Narrative Sciences: How the future gets written - https://narrativescience.com/ Alex when to grad school with Kris Hammond who founded Narrative Sciences...  and one of Alex's and my office mates Natalie Dehn was working on this topic for her dissertation at Yale - see: https://nil.cs.uno.edu/publications/papers/dehn1981story.pdf Circa 1984.... about 34 years ago...  Writing papers will get much easier....
- URL: https://www.wsj.com/articles/automation-makes-us-dumb-1416589342 URL: https://maliciousaireport.com/
- The nature of reality changes when there is more than one intelligent species, and we are not the smartest. The nature of reality also changes when the cost of exploring alternate experience pathways are made less risky – the notions of time and identity changes as a result. Mitigate risks and harvest benefits of existence, by learning to evermore efficiently and rapidly rebuild from scratch to higher states of value and capability of entities. The evolving ecology of service system entities their value co-creation and capability co-elevation mechanisms, as well as their capabilities, constraints, rights, and responsibilities at each stage in time. Human progress as well as the development of individuals, and the arc of institutions can be viewed in this way. Entities exist as individuals and populations. Generations of entities, generations of species (populations), generations of individuals (cohorts).
- By 2036, there will be an accumulation of knowledge as well as a distribution of knowledge in service systems globally. We need to ensure as there is knowledge accumulation that service systems at all scale become more resilient. Leading to the capability of rapid rebuilding of service systems across scales, by T-shaped people who understand how to rapidly rebuild – knowledge has been chunked, modularized, and put into networks that support rapid rebuilding.
- URL: https://www.technologyreview.com/s/601641/a-big-leap-for-an-artificial-leaf/
- URL: https://www.independent.co.uk/news/science/world-hunger-food-electricity-carbon-dioxide-ingredients-solve-climate-change-scientists-finland-a7869316.html
- URL: https://www.technologyreview.com/s/601420/the-elderly-may-toss-their-walkers-for-this-robotic-suit/
- IBM’s approach to open technologies: URL https://www.ibm.com/developerworks/cloud/library/cl-open-architecture-update/index.html
- Today’s talk will explore two questions What should we know how to make? What might programming education become? If we look at history we see a time when people could make only simple things, and often a single person could make them. Would it ever be possible for a single person to know and make complex things? And what role might programming education play? Will the cognitive era – the coming era of smart machines – make people more capable or less capable to know and make complex things?
- In the 1940’s IBM started teaching computer science at Columbia. My first program – punch cards 1972.
- Wendy Murphy’s dog – hard for AI to recognize in 2016, easy in 2018…
- The weakest link is what needs to be improved – according to system scientists. Accessing help, service, experts is the weakest link in most systems. By 2035 the phone may have the power of one human brain – by 2055 the phone may have the power of all human brains. Before trying to answer the question about which types of sciences are more important – the ones that try to explain the external world or the ones that try to explain the internal world – consider this, slide that shows the different telephones that I have used in my life. I grew up in rural Maine, where we had a party line telephone because we were somewhat remote on our farm in Newburgh, Maine. However, over the years phones got much better…. So in 2035 or 2055, who are you going to call when you need help?
- URL: http://www.mercurynews.com/2016/08/04/cupertino-teens-score-20000-for-24-hours-of-work/ Karan Mehta and Anish Krishnan
- Where is the variety? Hardware and even software standardizing into modules and algorithms…. Data will standardize next into categories and types…. Experience is where the uniqueness is, and variety and variability, and identity. Pine and Gilmore – Experience Economy Book – Chapter 10 – Transformation Economy - https://www.amazon.com/Experience-Economy-Theater-Every-Business/dp/0875848192#reader_0875848192 Pine II, B. J. & Gilmore, J. H. (1999). The experience economy: work is theatre & every business a stage. Harvard Business Press. pp: 186-189. (Chapter 10 is about the transformation economy) Osati, Sohrab (Dec 18, 2014) Sony Lifelog App Gains GPS Support for Android Wear. SonyRumors.net http://www.sonyrumors.net/2014/12/18/sony-lifelog-app-gains-gps-support-for-android-wear/ Roy, D., Patel, R., DeCamp, P., Kubat, R., Fleischman, M., Roy, B., ... & Levit, M. (2006). The human speechome project. In Symbol Grounding and Beyond (pp. 192-196). Springer, Berlin, Heidelberg.
- Free online cognitive classe URL: https://cognitiveclass.ai/ Here is what I tell students.... ... to try to provoke their thinking about the cognitive era:     (0) 2015 - about 9 months to build a formative Q&A system - 40% accuracy;         - another 1-2 years and a team of 10-20, can get it to 90% accuracy, by reducing the scope ("sorry that question is out of scope")         - today's systems can only answer questions, if the answers are already existing in the text explicitly         - debater is an example of where we would like to get to though in 5 years: https://www.youtube.com/watch?v=7g59PJxbGhY         - more about the ambitions at  http://cognitive-science.info     (1) 2025: Watson will be able to rapidly ingest just about any textbooks and produce a Q&A system         - the Q&A system will rival C-grade (average) student performance on questions     (2) 2035 - above, but rivals C-level (average) faculty performance on questions     (3) 2035 - an exascale of compute power costs about $1000         - an exascale is the equivalent compute of one person's brain power (at 20W power)     (4) 2035 - nearly everyone has a cognitive mediator that knows them in many ways better than they know themselves          - memory of all health information, memory of everyone you have ever interacted with, executive assistant, personal coach, process and memory aid, etc.     (5) 2055 - nearly everyone has 100 cognitive assistants that "work for them"         - better management of your cognitive assistant workforce is a course taught at university In 2015, we are at the beginning of the beginning or the cognitive era... In 2025, we will be middle of beginning... easy to generate average student level performance on questions in textbook.... In 2035, we will be end of beginning (one brain power equivalent)... easy to generate average faculty level performance on questions in textbook....     http://www.slideshare.net/spohrer/spohrer-ubi-learn-20151103-v2 By 2055, roughly 2x 20 year generations out, the cognitive era will be in full force. Cellphones will likely become body suits - with burst-mode super-strength and super-safety features: Suits - body suit cell phones Cognitive Mediators will read everything for us, and relate the information to  us - and what we know and our goals. Think combined personal coach, executive assistant, personal research team.... The key is knowing which problem to work on next - see this long video for the answer - energy, water, food, wellness -  and note especially the wellness suit at the end:     https://www.youtube.com/watch?v=YY7f1t9y9a0&index=10&list=WL Do not be put off by the beginning of the video - it is a bit over hyped and trivial, to say the leasat... but the projects are really good if you have the patience to watch.
- O*NET Online is the occupation network online, started by the US Dept of Labor in the 1990’s – it now represents one of the most comprehensive lists of occupations along with a great deal of information about each occupation, including skills, tasks, certifications, demand for these jobs, etc. O*NET lists about 1000 occupations from Accountants to Zoologists – and many job families in between. O*NET updates the descriptions of the occupations as well as adding new occupations over time. Source: http://www.onetonline.org/find/family?f=0
- Github registration URL: https://github.com/ Lukas Kaiser – one model that can do all leaderboard best - https://www.youtube.com/watch?v=8FpdEmySsuc T2T URL: https://github.com/tensorflow/tensor2tensor T2T iPython Notebook URL: https://colab.research.google.com/notebook#fileId=/v2/external/notebooks/t2t/hello_t2t.ipynb One favorite that can do them all: https://www.youtube.com/watch?v=8FpdEmySsuc URLs Github: code, content (data), community – http://github.com Kaggle: competition and leaderboards - http://Kaggle.com Figure-Eight: lots of labeled data – http://figure-eight.com Rapidly Rebuild: Danko Nicolic - AI Kindergarten (Practopoesis) - https://www.youtube.com/watch?v=aMQCi3Sn2mE Lukas Kaiser wants to get one model that can do all leaderboards – one model to do them all Danko Nicolic wants to rapidly rebuild from scratch intelligent agents (that behave well socially with people)– rapid rebuilding
- URL Amazon: https://www.amazon.com/Knowledge-Rebuild-Civilization-Aftermath-Cataclysm-ebook/dp/B00DMCV5YS/ URL TED Talk: https://www.youtube.com/watch?v=CdTzsbqQyhY Citation: Dartnell L (2012) The Knowledge: How to Rebuild Civilization in the Aftermath of a Cataclysm. Westminster London: Penguin Books. Jim Spohrer Blogs: Grand Challenge: http://service-science.info/archives/2189 Re-readings: http://service-science.info/archives/4416 Bad actors can cause collapse, but collapse can also happen from natural or accidental causes. When rapidly rebuilding from scratch, it is sometimgs possible to get to higher than previous level of performance, much faster.
- Visit IBM Research – Almaden, San Jose, CA USA 05120 – instructions: http://service-science.info/archives/4679 Join ISSIP.org – it’s free for individuals to join and get monthly newsletter: http://service-science.info/archives/4901 Contribute a short book to our series – blog compilations welcomed - http://www.businessexpertpress.com/product-category/service-systems-and-innovations-in-business-and-society/ We are trying to make complex servce systems things simpler – but not too simple. Wise innovation increase resilience with abundant opportunities for all.
- URL: Why software is eating the world – see https://www.wsj.com/articles/SB10001424053111903480904576512250915629460 URL: Microsoft acquiring GitHub – see https://blogs.microsoft.com/blog/2018/06/04/microsoft-github-empowering-developers/ URL: Models will run the world – see https://www.wsj.com/articles/models-will-run-the-world-1534716720 URL: John Marks, “Why Open Source Failed” https://medium.com/@johnmark/why-open-source-failed-6cae5d6a9f6 First, the good news, which is actually bad. In a 2016 survey from Blackduck, 96% of software products developed that year used open source software. That number is likely higher now. In the software world, particularly software that runs the computing infrastructure of the internet, open source is ubiquitous. One could claim, without any exaggeration, that our current world runs on open source software or that our modern world would not exist in its current form without open source software. I don’t know how to calculate the total value of open source software to the world, but I do know that if open source software suddenly went away, the results would be catastrophic, an existential crisis for humanity. So when I write that “open source has failed” I’m obviously not writing from a technology perspective, where it was been a clear-cut winner and the foundation of an endless supply of business models, products, and services. To say that open source contributed to the overall innovation of the world would be a shameful understatement. Better would be to say that the world’s computing innovations owe their existence to the triumph of open source development. If you think this all sounds pretty terrific, read on to find out what I left out. In the context of this essay, “failure” refers not to any technical achievements but rather to the lack of social ones. When we were but wee lads and lasses on the forefront of this thing we called free software and eventually open source, we knew that this was dangerous stuff. It was destined to set fire to an entire industry, undermining entrenched monopoly powers and establishing a more equitable approach to building wealth around the tools that would power humanity in the 21st century. It was about the democratization of software and would smash what we then called the “digital divide”. That premise was entirely false. The crux of this essay is thus: not only did open source not stem or stall the redistribution of wealth and power upwards, but rather it aided and abetted the redistribution of wealth and power upwards. To be an open source proponent at this time without acknowledging this very real and most unfortunate consequence is to be a cog in a much larger machine; a stooge; a very useful idiot. When considering the role of open source in redistributing wealth upwards, it’s instructive to consider the example of Microsoft. Not because I enjoy picking on them or think they’re evil — I don’t; Microsoft as a publicly traded company is no more or less evil than any other company. Rather, I like to single them out because their public stance towards open source has changed much over the years and is a useful measuring stick for the points I’m trying to make. Did you ever wonder *why* their public stance towards open source shifted so much over the years, from “Linux is a cancer” to “use our open source software”? Could it be because, unlike the company’s predecessors in 2000, current executives now understand that open source software forms the building blocks of modern capitalist behemoths?
- Source: Vijay Bommireddipally (CODAIT Director) and Fred Reiss (CODAIT Chief Architect)
- URL: https://www.siliconrepublic.com/machines/ibm-fairness-360-ai-bias URL: https://github.com/IBM/AIF360 (Sept 21 2018) 169 stars, 17 forks, 60 commits, 6 contributors Kush Varshney’s Sept 20, 2018 presentation - http://cognitive-science.info/community/weekly-update/ Presentation: http://cognitive-science.info/wp-content/uploads/2018/09/CSIG_krv-aif360-2018-09-20-1.pdf Individual fairness, group fairness, etc.
- By 2036, there will be an accumulation of knowledge as well as a distribution of knowledge in service systems globally. We need to ensure as there is knowledge accumulation that service systems at all scale become more resilient. Leading to the capability of rapid rebuilding of service systems across scales, by T-shaped people who understand how to rapidly rebuild – knowledge has been chunked, modularized, and put into networks that support rapid rebuilding.
- GitHub – open source code – http://github.com Kaggle – data and competitions – http://Kaggle.com Leaderboard – AI an competitions - https://www.slideshare.net/spohrer/leaderboards-80909263 Figure Eight – label data - https://en.wikipedia.org/wiki/Figure_Eight_Inc. Open Source Guides – reader, contributor, committer, governance - https://opensource.guide/ GitHub is to knowledge in action (writing code) as Wikidedia is to knowledge in text (writing text)