Researchers review scaling paths for diffractive optical AI

A published review of diffractive optical neural networks surveyed how layered optical elements can perform computation by transforming light as it propagates. Such designs promise parallel low-latency processing in suitable inference tasks.

The review also highlights practical limitations, including nonlinear activation, programmability, detector conversion and scale. It synthesizes prior research rather than demonstrating a new production processor.