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Neuromorphic Computing for Future Breakthroughs in AI

오전 10:40 - 오전 11:10

Deep artificial neural networks have provided breakthroughs in AI in the form of near-human levels of data perception in many problem domains. Neuromorphic computing aims to take this a step further – chips directly inspired by the form and function of biological neural circuits so they can process new knowledge, adapt, behave, and learn in real time at extremely low power levels.  After several decades of research at the intersection of neuroscience and silicon engineering, this technology is now reaching maturity.  Progress in the field has advanced rapidly in recent years and, today, leading neuromorphic chips such as Intel’s Loihi research processor have a growing body of results showing quantitative gains compared to conventional architectures.  The results point to compelling performance trends over a diverse range of problems as these systems are scaled up to millions of neurons, providing a roadmap for continued breakthroughs in AI.

Speaker

Mike Davies

Mike Davies

Director, Neuromorphic Computing Lab, Intel

Mike Davies is Director of Intel’s Neuromorphic Computing Lab. Since joining Intel Labs in 2014, Mike has researched neuromorphic architectures, algorithms, software, and systems, and has fabricated several neromorphic chip prototypes to date. His group is responsible for Intel’s Loihi research chip. Previously, as a founding employee of Fulcrum Microsystems and its Director of Silicon Engineering, Mike pioneered high performance asynchronous design methodologies as applied to several generations of industry-leading Ethernet switch products. He joined Intel in 2011 by Intel’s acquisition of Fulcrum. Mike holds BS and MS degrees from Caltech in applied science, mathematics, and electrical engineering.