A.I. and Machine Learning
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SLAC-Led Project Will Use Artificial Intelligence to Prevent or Minimize Electric Grid Failures
It's the first to employ AI to help the grid manage power fluctuations, resist damage and recover faster from storms, solar eclipses, cyberattacks and other disruptions.
Artificial Intelligence Analyzes Gravitational Lenses 10 Million Times Faster
Menlo Park, Calif. — Researchers from the Department of Energy’s SLAC National Accelerator Laboratory and Stanford University have for the first time shown that neural networks – a form of artificial intelligence – can accurately analyze the complex distortions in spacetime known as gravitational lenses 10 million times faster than traditional methods.
Franklin Fuller and Cornelius Gati Named 2017 Panofsky Fellows at SLAC
Over the next five years they’ll work on getting significantly more information about how catalysts work and improving biological imaging methods.
Machine Learning Dramatically Streamlines Search for More Efficient Chemical Reactions
An advance by SLAC and Stanford researchers greatly reduces the time needed to analyze complex catalytic reactions for making fuel, industrial chemicals and other products, and should improve computational analysis throughout chemistry.
