L2ONN: Reconfigurable Photonic Computing Architecture for Li

L2ONN: Reconfigurable Photonic Computing Architecture for Lifelong Learning

Artificial intelligence (AI) tasks become increasingly abundant and complex fueled by large-scale datasets. With the plateau of Moore's law and end of Dennard scaling, energy consumption becomes a major barrier to more widespread applications of today's heavy electronic deep neural models, especially in terminal/edge systems.

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Lu Fang , Jiangxi , China , Beijing , Laura Thomsonapr , Department Of Electronic Engineering , Sigma Laboratory , Tsinghua University , Light Science , Professor Lu Fang , Electronic Engineering ,

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