Neil Jacobstein on the Latest in Artificial Intelligence

Tuesday, July 4, 2017

Neil Jacobstein on the Latest in Artificial Intelligence

Neil Jacobstein recently gave an information-packed talk at the Exponential Manufacturing conference on how artificial intelligence is redefining the future of work, production, supply chain, and design.

Singularity University recently held the Exponential Manufacturing Summit with some of the world's brightest executives, entrepreneurs and investors being led through an intensive three-day program in Boston to prepare them for the changes brought forth by unstoppable technological progress. See the full lecture below.

At the Summit, Neil Jacobstein chairs the Artificial Intelligence and Robotics Track at Singularity University, explored how exponential technologies including artificial intelligence, additive manufacturing, exponential energy, and bio manufacturing are continually redefining the future of work, production, supply chain, and design.

"What you'll see when you look behind the scenes of most AI startups and even research labs is an emerging symbiosis between human intelligence and machine intelligence."
"Hardware and software tend to get most of the attention in AI, but what you'll see when you look behind the scenes of most AI startups and even research labs is an emerging symbiosis between human intelligence and machine intelligence," states Jacobstein.

According to Jacobstein, systems like Libratus, a Texas Hold'em poker playing AI, represents the future of reseach, where humans and computer systems work together to achieve outstanding results.

Raven's Progressive Matrices
He lists a great number of such projects in the talk including, CogSketch from Ken Forbus and Andrew Lovett at Northwestern University, which is a computational model that performs at the same level as humans on Raven's Progressive Matrices standardized tests. "The Raven's test is the best existing predictor of what psychologists call 'fluid intelligence, or the general ability to think abstractly, reason, identify patterns, solve problems, and discern relationships,'"  Lovett has reported.

"Most artificial intelligence research today concerning vision focuses on recognition, or labeling what is in a scene rather than reasoning about it," Forbus said. "But recognition is only useful if it supports subsequent reasoning. Our research provides an important step toward understanding visual reasoning more broadly."

Such intelligence is now being built into our machines, continues Jacobstein. This includes our cars. For instance, Amazon's Alexa is now being incorporated into some Ford cars. Intel has also acquired Nervana Systems, a company that specializes in deep learning technology, and made Naveen Rao the head of an AI products group at the company. "They want to drive intelligence into every product and process that they have," suggests Jabobstein.

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Jacobstein suggests a framework for thinking about how AI will impact the world made up the drivers:

  • Capital
  • Algorithms
  • Hardware
  • Data
  • Talent
  • Applications 
  • Responsibility

AI Funding
Funding is accelerating as Jacobstein illustrates with the chart above.

Algorithms such as deep learning are making tremendous strides already in application, even as they continue to be engineered for performance and capability. Jacobstein shares the example of recent work done by Google DeepMind in helping to create models of grasping for potential uses in prosthetics and robotics.

The deep learning revolution is also accelerating with new open-source tools becoming available.

Hardware is a key component of the AI revolution, and Jacobstein introduces the Tensor Processing unit, that Google only recently introduced and deployed. 


Yann LeCun, Andrew Ng, and other personalities are mentioned as big-name talents in the field of AI.

All of these developments mean that the applications possible from AI are only just beginning to be realized. "I did a study of over 360 innovative applications of AI, and I was looking for patterns. These are the patterns I found [see image below], and it's not just better, faster, cheaper, it's different. Expanding the range of what's possible; doing things we never knew we could do before," emphasizes Jacobstein.

AIs Value Added

All of these factors mean that everyone must be involved in the responsibility of the impact of AI, suggests Jacbostein. From universal basic income, to business models, to education and security, we all need to be ready. "There is lots of uncertainty about this, and rather be uncertain and unprepared, I think it's better to be uncertain and well prepared and proactive," he states.

Jacobstein is a former President of Singularity University. He is a Distinguished Visiting Scholar in the Stanford University Media X Program, where his research focuses on augmented decision systems. He has served as a technical consultant on AI research and development projects for: DARPA, NSF, NASA, NIH, EPA, DOE, the U.S. Army and Air Force, GM, Ford, Boeing, Applied Materials, NIST, and other agencies. He was CEO of Teknowledge Corporation, a pioneering AI company, where he worked on AI applications systems for industry and government.

Jacobstein is deeply interdisciplinary, and has a keen sense of how the arts and sciences can integrate. Since 1992, he has served as Chairman of the Institute for Molecular Manufacturing, a 501c3 nanotechnology R&D organization. Jacobstein contributed to the 2005 National Academy of Sciences workshop on the feasibility of molecular manufacturing, and the 2007 Foresight Roadmap for Productive Nanosystems. He is the primary author of the Foresight Guidelines for the responsible development of nanotechnology.

SOURCE  Singularity University Summits

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