Neil indicates the Dota 2 announcement was a problem. 50 people beat the Dota 2 bot after the announcement.
AlphaGo beat the top world champion at Go.
Libratus beat human pros at Texas holdem poker.
AI optimized hardware exist today.
Neil reviewed the exponential growth in the skills capability for Amazaon Alexa.
Neil is editing ScienceRobotics a new journal.
There was no work to overcome catastrophic forgetting in neural networks.
XAI (Darpa project) to provide an explanation model and explanation interface.
Talks about the latest chips
Human Longevity Inc released 10,000 genomes as Open source
Intraspection is an AI that searches your corporate email to identify future potential litigation.
High-throughput materials discovery involves the rapid synthesis, measurement, and characterization of many different but structurally related materials. A central problem in materials discovery, the phase map identification problem, involves the determination of the crystal structure of materials from materials composition and structural characterization data. We present Phase-Mapper, a novel solution platform that allows humans to interact with both the data and products of AI algorithms, including the incorporation of human feedback to constrain or initialize solutions. Phase-Mapper is compatible with any spectral demixing algorithm, including our novel solver, AgileFD, which is based on convolutive non-negative matrix factorization. AgileFD allows materials scientists to rapidly interpret XRD patterns, and can incorporate constraints to capture the physics of the materials as well as human feedback. We compare three solver variants with previously proposed methods in a large-scale experiment involving 20 synthetic systems, demonstrating the efficacy of imposing physical constraints using AgileFD. Since the deployment of Phase-Mapper at the Department of Energy’s Joint Center for Artificial Photosynthesis (JCAP), thousands of X-ray diffraction patterns have been processed and the results are yielding discovery of new materials for energy applications, as exemplified by the discovery of a new family of metal oxide solar light absorbers, among the previously unsolved Nb-Mn-V oxide system, which is provided here as an illustrative example. Phase-Mapper is also being deployed at the Stanford Synchrotron Radiation Lightsource (SSRL) to enable phase mapping on datasets in real time.
Artificial Intelligence & Robotics Chair
Neil Jacobstein chairs the Artificial Intelligence and Robotics Track at Singularity University on the NASA Research Park campus in Mountain View California. Neil is a former President of Singularity University. Jacobstein is a Distinguished Visiting Scholar in the Stanford University Media X Program, where his research focuses on augmented decision systems. He Chaired AAAI’s 17th Innovative Applications of Artificial Intelligence Conference, and continues to review technical papers for IAAI.Â In 2016, he became a founding member of the editorial board of AAAS Science Robotics. Neil 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. He worked as a graduate research intern in Alan Kay’s Learning Research Group at Xerox’s Palo Alto Research Center (PARC), and was a consultant in PARC’s Software Concepts Group. Jacobstein is a Henry Crown Fellow at the Aspen Institute. He has moderated Aspen Institute Socrates Programs on the technical and ethical implications of advanced technologies, and he coaches Socrates moderators. Neil 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. Neil is in demand as an engaging speaker who can make complex topics clear to diverse audiences. He has given invited talks worldwide on the technical, business, and ethical implications of exponential technologies, such as AI, robotics, and atomically precise manufacturing. He is a member of AAAS, AAAI, IEEE, and ACM. Neil has served in a variety of executive and technical advisory roles for industry, nonprofit, and government organizations.