You say you want a revolution?

October 8, 2017

https://www.slideshare.net/spohrer/revolution-20171008-v23

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TED Arai Todai Robot

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… when will your smartphone be smart enough topass a university entrance exam?

“AI will change the world? Who will change AI?”

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“These amazing technologies must be able to help people like myself…”

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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?

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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

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2080204020001960

$1K

$1M

$1B

$1T

206020201980

+/- 10 years

$1

Person AverageAnnual Salary(Living Income)

Super ComputerCost

Mainframe Cost

Smartphone Cost

T

P

E

T P E

AI Progress on Open LeaderboardsBenchmark Roadmap to solve AI/IA

GPD/Employee

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(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 LeaderboardsBenchmark Roadmap to solve AI/IA

Leaderboards FrameworkAI Progress on Open Leaderboards - Benchmark Roadmap2015 2018 2021 2024 2027 2030 2033 2036

Perceive World Develop Cognition Build Relationships Fill Roles

Pattern recognition

Videounderstanding

Memory Reasoning Socialinteractions

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

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Which experts would be really surprised if it takes less time… and which experts really surprising if it takes longer?

Icons of AI Progress

• 1956: Dartmouth Conferenceorganized 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)

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AI Trends

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10

Dota 2

“Deep Learning” for“AI Pattern Recognition”depends on massiveamounts of “labeled data”and computing poweravailable since ~2012;

Labeled data is simplyinput and output pairs,such as a sound and word,or image and word, orEnglish sentence and Frenchsentence, or road sceneand car control settings –labeled data means havingboth input and output datain massive quantities.

For example, 100K imagesof skin, half with skincancer and half without tolearn to recognize presenceof skin cancer.

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

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AI to IA Timeline: Hard unsolved AI problems

• 2012-2017 AI Pattern Recognition andLearning 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 andMediator; Intelligence Augmentation (IA)

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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

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AI Risks

• Job Loss• Shorter term bigger risk

= de-skilling

• Super-intelligence• Shorter term bigger risk

= bad actors

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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.)

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Stakeholders

• Individuals

• Families

• Businesses and other Organizations

• Industry Groups

• Regional Governments:• Cities • States• Nations

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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

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1972 usedPunch cards

2016 usedIBM Watson

Open APIs to win…

Cupertino Teens

• IBM Watson on Bluemix

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AI for NLP entity identification

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.

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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.”

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IEEE 2017

IBM-MIT $240M over 10 year AI mission

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Future of Skills

Future-Ready T-Shapes

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In Summary

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“A service scienceperspective considersthe evolving ecology of service system entities, their value co-creation andcapability co-elevationinteractions, and their capabilities, constraints,rights, and responsibilities.”

Cognitive SystemsEntities

Service SystemsEntities With

CognitiveMediators

Add Rights &Responsibilities

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