You say you want a revolution? Benchmark Roadmap to solve AI/IA
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You say you want a revolution? questions and answers about preparing for the futuere of artificial intelligence (preparing for the future of AI)
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You say you want a revolution? Benchmark Roadmap to solve AI/IA
- 1. You say you want a revolution? October 8, 2017 https://www.slideshare.net/spohrer/revolution-20171008-v23 10/8/2017 (c) IBM 2017, Cognitive Opentech Group 1
- 2. TED Arai Todai Robot 10/8/2017 (c) IBM 2017, Cognitive Opentech Group 2 … when will your smartphone be smart enough to pass a university entrance exam?
- 3. “AI will change the world? Who will change AI?” 10/8/2017 (c) IBM 2017, Cognitive Opentech Group 3
- 4. “These amazing technologies must be able to help people like myself…” 10/8/2017 (c) IBM 2017, Cognitive Opentech Group 4
- 5. 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? 10/8/2017 (c) IBM 2017, Cognitive Opentech Group 5
- 6. 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 610/8/2017 (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 T P E T P E AI Progress on Open Leaderboards Benchmark Roadmap to solve AI/IA
- 7. GPD/Employee 10/8/2017 (c) IBM 2017, Cognitive Opentech Group 7 (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
- 8. Leaderboards Framework AI Progress on Open Leaderboards - Benchmark Roadmap 2015 2018 2021 2024 2027 2030 2033 2036 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) 2015 2018 2021 2024 2027 2030 2033 2036 10/8/2017 (c) IBM 2017, Cognitive Opentech Group 8 Which experts would be really surprised if it takes less time… and which experts really surprising if it takes longer?
- 9. 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) 10/8/2017 (c) IBM 2017, Cognitive Opentech Group 9
- 10. AI Trends 10/8/2017 © IBM Cognitive Opentech Group (COG) 10 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.
- 11. AI Leaders • Who is winning? • Regions China vs USA vs EU vs ROW • Companies Microsoft vs Google vs IBM • Leaderboards • SQuAD – Question Answering • EFF Measuring AI Progress 10/8/2017 (c) IBM 2017, Cognitive Opentech Group 11
- 12. AI to IA Timeline: Hard unsolved AI problems • 2012-2017 AI Pattern Recognition and Learning from Massive Labeled Data • Speech, image, translation, driverless, games • Chatbots as digital assistants • 2018 Video Understanding • 2021 Episodic Memory • 2022 Learning from Watching • 2024 Commonsense Reasoning • 2026 Learning from Reading • 2028 Learning from Doing • 2030 Fluent Conversation • 2031-2039 Cognitive Collaborator and Mediator; Intelligence Augmentation (IA) 10/8/2017 (c) IBM 2017, Cognitive Opentech Group 12
- 13. 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 10/8/2017 (c) IBM 2017, Cognitive Opentech Group 13
- 14. AI Risks • Job Loss • Shorter term bigger risk = de-skilling • Super-intelligence • Shorter term bigger risk = bad actors 10/8/2017 (c) IBM 2017, Cognitive Opentech Group 14
- 15. 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.) 10/8/2017 (c) IBM 2017, Cognitive Opentech Group 15
- 16. Stakeholders • Individuals • Families • Businesses and other Organizations • Industry Groups • Regional Governments: • Cities • States • Nations 10/8/2017 (c) IBM 2017, Cognitive Opentech Group 16
- 17. Be Prepared • 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 10/8/2017 (c) IBM 2017, Cognitive Opentech Group 17 1972 used Punch cards 2016 used IBM Watson Open APIs to win…
- 18. Cupertino Teens • IBM Watson on Bluemix 10/8/2017 (c) IBM 2017, Cognitive Opentech Group 18 AI for NLP entity identification
- 19. 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. 10/8/2017 19
- 20. Headlines • 2017 Popular • “AI vs People” • “X-Y team up to invest big in AI” • 2025 Commonplace • “People using AI to become better at their professions, serving others.” • “Teenagers using AI to solve challenges, and improve their communities.” • 2085 Resilience • “Teams competing to rapidly rebuild socio-economic-technical systems (wise service systems) from scratch” • “U.N. Pluto-base makes major discovery about nature of universe. U.F.P. established.” 10/8/2017 (c) IBM 2017, Cognitive Opentech Group 20 IEEE 2017
- 21. IBM-MIT $240M over 10 year AI mission 10/8/2017 (c) IBM 2017, Cognitive Opentech Group 21
- 22. 10/8/2017 © IBM 2015, IBM Upward University Programs Worldwide accelerating regional development 22
- 23. 10/8/2017 © IBM 2015, IBM Upward University Programs Worldwide accelerating regional development 23 Future of Skills
- 24. Future-Ready T-Shapes 10/8/2017 © IBM UPWard 2016 24
- 25. In Summary 10/8/2017 © IBM 2015, IBM Upward University Programs Worldwide accelerating regional development 25 “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
- 26. 10/8/2017 © IBM 2015, IBM Upward University Programs Worldwide accelerating regional development 26
Hinweis der Redaktion
- Please feel free to share and cite: Spohrer, JC (2017) You say you want a revolution? Presentation draft October 8, 2017 for AAAI Fall Symposium. https://www.slideshare.net/spohrer/smart-20171008-v23 Title slide video URL: https://www.youtube.com/watch?v=BGLGzRXY5Bw Opening ten seconds of the above Beatles video shows the self-astonishment of what a team of people can do with lots of practice and amazingly cool technologies. My brother Scott reminds me of John Lennon – not only in early long-hair look, but love of writing and singing songs about building a better world. Not utopia, he never believed in that – he knew life was hard by design, he just hoped for a world with more open minded people working together for the common good. Perhaps AI systems that know us better than we know are selves can help us all become more open minded. Thanks to IBM colleagues, and IBM visitors including Daniel Pakkala (VTT Finland)– see http://service-science.info/archives/4741 Thanks to “OECD 2016 – One year later group” as well: Elliot Stuart, Ken Forbus, Moshe Vardi, Frank Levy, Vijay Saraswat, Michael Witbrock, Alistair Nolan, Art Graesser, Charles Fadel, Ernest Davis, Jill Burstein, Michael Handel, Jerry Hobbs, Rebecca Passonneau, Mark Steedman
- URL: https://www.ted.com/talks/noriko_arai_can_a_robot_pass_a_university_entrance_exam
- URL: https://livestream.com/accounts/10060267/events/7701727/videos/163750822
- URL: https://www.ted.com/talks/chieko_asakawa_how_new_technology_helps_blind_people_explore_the_world
- 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
- 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
- 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.
- 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/
- 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"
- Chatbots: http://kasisto.com/ Learning by doing related The team has successfully applied the One Button Machine in various data science competitions where it outperformed most human teams and ranked among the top 16螄% of participants One Button Machine works by traversing the graph defined by the entities (tables) and relations (primary/foreign keys) of a relational database. The aggregation functions can be specified by the user, or chosen generically for certain data types. To deal with the combinatorial explosion of related entities, the One Button Machine deploys heuristics and sub-sampling strategies. Scalability to big databases is achieved by dynamic caching of intermediate results and a parallelisable implementation in Apache Spark, a distributed computing framework for analysing massive amounts of data. http://www.eetindia.co.in/news/article/ibm-develops-low-level-task-automation Learning by doing related.
- 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).
- URL: http://www.mercurynews.com/2016/08/04/cupertino-teens-score-20000-for-24-hours-of-work/ Karan Mehta and Anish Krishnan
- 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.
- URL: https://spectrum.ieee.org/static/ai-vs-doctors U.N. = United Nations U.F.P. = United Federation of Planets
- URL: http://news.mit.edu/2017/ibm-mit-joint-research-watson-artificial-intelligence-lab-0907