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Optical Transformers
We conclude that with well-engineered, large-scale optical hardware, it may be possible to achieve a $100 \times$ energy-efficiency advantage for running some of the largest current Transformer models, and that if both the models and the optical hardware are scaled to the quadrillion-parameter regime, optical computers could have a $>8, 000\times$ energy-efficiency advantage over state-of-the-art digital-electronic processors that achieve 300 fJ/MAC.
Image sensing with multilayer, nonlinear optical neural networks
In image sensing, a measurement, such as of an object's position, is performed by computational analysis of a digitized image.
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