Feb. 14, 2024, 5:44 a.m. | Mustafa Yildirim Niyazi Ulas Dinc Ilker Oguz Demetri Psaltis Christophe Moser

cs.LG updates on arXiv.org arxiv.org

Deep neural networks have achieved remarkable breakthroughs by leveraging multiple layers of data processing to extract hidden representations, albeit at the cost of large electronic computing power. To enhance energy efficiency and speed, the optical implementation of neural networks aims to harness the advantages of optical bandwidth and the energy efficiency of optical interconnections. In the absence of low-power optical nonlinearities, the challenge in the implementation of multilayer optical networks lies in realizing multiple optical layers without resorting to electronic …

advantages bandwidth computing computing power cost cs.ai cs.et cs.lg data data processing efficiency electronic energy energy efficiency extract harness hidden implementation linear multiple networks neural networks optical optics physics.optics power processing speed

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