August 28, 2016

Neil Jacobstein - AI 101 at Global Singularity Summit #gsummit

Neil Jacobstein Chairs the AI and Robotics Track at Singularity University headquartered at the NASA Ames Research Park. He is a former President of Singularity University. Jacobstein is a Distinguished Visiting Scholar in Stanford’s Media X Program. He was a Senior Research Fellow in the Reuters Digital Vision Program at Stanford University. He has served as an AI technical consultant on projects for leading business, government, and defense organizations including Deloitte, XPrize, GM, Ford, Boeing, ING, Wells Fargo, FMC, P&G, Hershey, Coca Cola, Loews, Harman, GE, Wipro, Dow, Genentech, Boeing, Lockheed Martin, Applied Materials, NSF, DARPA, NASA, NIH, EPA, DOE, the U.S. Army, Navy, and Air Force. Jacobstein was CEO at Teknowledge Corporation, an early AI company. He chaired the 17th Association for the Advancement of Artificial Intelligence’s (AAAI) Innovative Applications of Artificial Intelligence (IAAI) Conference. Jacobstein is a Henry Crown Fellow at the Aspen Institute. He was a Graduate Research Intern in Alan Kay’s Learning Research Group at Xerox Palo Alto Research Center, and a consultant in PARC’s Software Concepts Group. Jacobstein was appointed by the United States National Academy of Sciences, Engineering and Medicine to their Division on Earth and Life Sciences Committee for the period 2015-2018. He became a founding Editorial Board Member of AAAS Science Robotics in 2016. Neil advises corporations, governments, and startups, and speaks internationally on AI, Robotics, and the Implications of Exponential Technologies.


Seven factors driving the AI revolution

Summary of 7 factors driving AI

1. Money and funding of AI - 1st quarter 2016 deal activity is up seven times from 2011
2. Algorithms driving the AI revolution [he suggests downloading RStudio]
3. Hardware
4. DATA - used for training AI
5. Talent
Data science competition at kaggle [website], to offer prizes for AI problems (but requires posting data publicly)

Experfy [website] lets you have AI people bid to solve your AI problems (Neil is an investor in this company)

6. Applications

Apple Siri 
Google Assistant
Microsoft Cortana
Hound app for iOS and android
More than 1000 people are working on Amazon Echo and Alexa
Alphabet home 
VIV Global brain

7. Responsibility

Seven factors in more detail

1. 1st quarter 2016 deal activity is up seven times from 2011

$2.4 billion invested in 2015

The race of AI

What is AI ?

A. Pattern recognition techniques
B. Software agents
C. a vision of superhuman intelligence that has not happened yet
D. A computer science that accelerates other exponential technologies

Synthesis of AI and human intelligence



2. Algorithms is the next big factor driving the AI revolution

Deep learning is making huge gains
850 stage deep learning image recognition at Microsoft

Download RStudio

RToolkit


3. Hardware

Alphabet Google TPU Tensor Processing Unit



Used in search and streetview

Qualcomm Zeroth NPU - 4K and DSP signal processing

Nvidia- deep learning chip

IBM truenorth neuromorphic computing platform, 16 million neurons, 4 biilion synpases, 2.5 watts

4. DATA

All kinds of data, big data, genomic data, market price data, wikipedia, 500 million tweets per day, webfeeds,
patient data, relational data

a lot publicly available

Tensorflow integrate algorithms and data







5. Talent

Companies are acquiring companies for talent and targeting key people

Facebook new deeptext and deepface programs

Google acquired Deepmind for more than $500 million

South Korea promised $3 billion for AI R and D after the Alphago shock

Data science competition at kaggle, to offer prizes for AI problems (but requires posting data publicly)

Experfy lets you have AI people bid to solve your AI problems (Neil is an investor in this company)

6. Applications

AI applications

AI value adds
Augments human skills
etc...

Machine learning applications - AII website

IBM Watson

Watson is moving into different domains with any credible partners

IBM investing $1 billion in 2014 and setup $100 million venture fund

We will extend our capability with assistance systems

Apple Siri
Google Assistant
Microsoft Cortana
Hound app for iOS and android

More than 1000 people are working on Amazon Echo and Alexa

Alphabet home

VIV Global brain (architects of SIRI came out of stealth mode) want to create intelligence as a utility

VIV allows you to delegate work to your computer



7. Responsibility

AI impacts human resources

AI is here now with practical problem solving

AI will blow the lid on education and will enable powerful one on one tutoring

Ai comes with tradeoffs

Trust will be important

AIRBnb is using AI to reduce risk to customers and hosts

AI Open Letter

The signatories ask: How can engineers create AI systems that are beneficial to society, and that are robust? Humans need to remain in control of AI; our AI systems must "do what we want them to do".[1] The required research is interdisciplinary, drawing from areas ranging from economics and law to various branches of computer science, such as computer security and formal verification. Challenges that arise are divided into
verification ("Did I build the system right?"),
validity ("Did I build the right system?"),
security, and
control ("OK, I built the system wrong, can I fix it?"

OpenAI $1 billion

Reverse engineer the brain eventually

Eureqa = virtual data scientist

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