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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
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"
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.
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....
Preparing for the Future
of Artificial Intelligence (AI)
October 6, 2017
10/6/2017 (c) IBM 2017, Cognitive Opentech Group 1
TED Arai Todai Robot
10/6/2017 (c) IBM 2017, Cognitive Opentech Group 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)
• AI Reasoning
• Broad AI (Slow)
310/6/2017 (c) IBM 2017, Cognitive Opentech Group
+/- 10 years
10/6/2017 (c) IBM 2017, Cognitive Opentech Group 4
AI Progress Leaderboards - Benchmark Framework
Perceive World Develop Self Build Relationships Fill Roles
Memory Reasoning Social
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
10/6/2017 (c) IBM 2017, Cognitive Opentech Group 5
• 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?
10/6/2017 (c) IBM 2017, Cognitive Opentech Group 6
• The Dartmouth
organized by Marvin
McCarthy and two
Claude Shannon and
Nathan Rochester of
10/6/2017 (c) IBM 2017, Cognitive Opentech Group 7
• Who is winning?
• Regions China vs USA vs EU vs ROW
• Companies Microsoft vs Google vs IBM
• SQuAD – Question Answering
• EFF Measuring AI Progress
10/6/2017 (c) IBM 2017, Cognitive Opentech Group 9
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)
10/6/2017 (c) IBM 2017, Cognitive Opentech Group 10
• 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
10/6/2017 (c) IBM 2017, Cognitive Opentech Group 11
• Job Loss
• Shorter term bigger risk
• Shorter term bigger risk
= bad actors
10/6/2017 (c) IBM 2017, Cognitive Opentech Group 12
Other Technologies: Bigger impact?
• Augmented Reality (AR)/
Virtual Reality (VR)
• Game worlds
• Trust and security
• Advanced Materials/
• Manufacturing as cheap,
local recycling service
(utility fog, artificial leaf, etc.)
10/6/2017 (c) IBM 2017, Cognitive Opentech Group 13
• Businesses and
10/6/2017 (c) IBM 2017, Cognitive Opentech Group 14
• 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
• Improve your skills of rapidly
rebuilding from scratch
• Build your open code eminence
10/6/2017 (c) IBM 2017, Cognitive Opentech Group 15
Open APIs to win…
• IBM Watson on Bluemix
10/6/2017 (c) IBM 2017, Cognitive Opentech Group 16
AI for NLP
• “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
• “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
• “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
• “How to manage your workforce of digital workers.”
• Most people have 100 digital workers.