Large-scale photonic natural language processing

作     者：CARLO M.VALENSISE IVANA GRECCO DAVIDE PIERANGELI CLAUDIO C CARLO M.VALENSISE;IVANA GRECCO;DAVIDE PIERANGELI;CLAUDIO CONTI

作者机构：Enrico Fermi Research Center(CREF)00184 RomeItaly Physics DepartmentSapienza University of Rome00185 RomeItaly Institute for Complex SystemsNational Research Council(ISC-CNR)00185 RomeItaly 

出 版 物：《Photonics Research》 (光子学研究（英文版）)

年 卷 期：2022年第10卷第12期

页      面：2846-2853页

核心收录：

学科分类：070207[理学-光学] 07[理学] 08[工学] 081203[工学-计算机应用技术] 0835[工学-软件工程] 0803[工学-光学工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 0702[理学-物理学] 

基　　金：Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi Ministero dell’Universitàe della Ricerca(PRIN No.20177PSCKT) 

主　　题：demanding overcome exceeding 

摘      要：Modern machine-learning applications require huge artificial networks demanding computational power and ***-based platforms promise ultrafast and energy-efficient hardware,which may help realize nextgeneration data processing ***,current photonic networks are limited by the number of inputoutput nodes that can be processed in a single *** restricted network capacity prevents their application to relevant large-scale problems such as natural language ***,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 *** 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 *** results provide a novel solution to scale up light-driven computing and open the route to photonic natural language processing.