Photonic Chips Enable Optical Neural Learning
Researchers led by Shuiying Xiang at Xidian University built photonic computing chips that let neural networks learn using light, reported in the journal Optica. The programmable system pairs a 16-channel photonic processor (272 trainable parameters) with a laser array enabling nonlinear optical spiking, delivering 1.39 TOPS/W linear, 988 GOPS/W nonlinear, and 320 ps latency while solving CartPole and inverted-pendulum tasks. The prototype may enable low-latency, energy-efficient learning for autonomous vehicles and robots.
Scoring Rationale
Strong experimental demonstration with high efficiency metrics and clear training results; prototype scale and practical deployment remain limited in scope.
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