Research team develops reconfigurable photonic computing architecture for lifelong learning

Artificial intelligence (AI) tasks have 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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