Download - Smart 20171006 v20
When will smartphones become smart?
October 6, 2017
https://www.slideshare.net/spohrer/smart-20171006-v20
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TED Arai Todai Robot
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… when will your smartphone be smart enough topass a university entrance exam?
“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 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?
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Costs go down…
• Cost of Digital Workers• Moore’s Law can be thought of
as lowering costs by a factor of…• Thousand times lower
in 20 years• Millions times lower
in 40 years• Billion times lower
in 60 years
• 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
GPD/Employee
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(Source)
Leaderboards FrameworkAI Progress on Open Leaderboards - Benchmark Roadmap
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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The Past
• The Dartmouth Conference of 1956[39] was organized by Marvin Minsky, John McCarthy and two senior scientists: Claude Shannon and Nathan Rochester of IBM
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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
• 2012-2019 AI Pattern Recognition andLearning 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 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?
• 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
• Businesses and other Organizations
• Industries
• Regions: Cities, States, Nations
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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/orleaderboards
• Improve your skills of rapidly rebuilding from scratch• Build your open code eminence
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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”
• 2025 Commonplace• “People using AI to
become better at their profession.”
• “Teenagers solve challenge to improve their community.”
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10/6/2017© IBM 2015, IBM Upward University Programs Worldwide
accelerating regional development 22
Future of Skills
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