| 3 | Large-scale photonic natural language processing显示文摘Modern machine-learning applications require huge artificial networks demanding computational power and memory.Light-based platforms promise ultrafast and energy-efficient hardware,which may help realize nextgeneration data processing devices.However,current photonic networks are limited by the number of inputoutput nodes that can be processed in a single shot.This restricted network capacity prevents their application to relevant large-scale problems such as natural language processing.Here,we realize a photonic processor for supervised learning with a capacity exceeding 1.5×10^(10)optical nodes,more than one order of magnitude larger than any previous implementation,which enables photonic large-scale text encoding and classification.By exploiting the full three-dimensional structure of the optical field propagating in free space,we overcome the interpolation threshold and reach the over-parameterized region of machine learning,a condition that allows high-performance sentiment analysis with a minimal fraction of training points.Our results provide a novel solution to scale up light-driven computing and open the route to photonic natural language processing. | CARLO M.VALENSISE IVANA GRECCO DAVIDE PIERANGELI CLAUDIO C | 2022 | Photonics Research2022，10，12： | 0 |
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