[CamperBob2]

You could think of a lens as a "Fourier transformer," not in the LLM sense directly but in the sense of something that executes a Fourier transform. See the excellent videos by Huygens Optics including this one: https://www.youtube.com/watch?v=Y9FZ4igNxNA entitled "Fourier optics used for optical pattern recognition."

Having established that, well, it's not hard to imagine that something that's good at running Fourier transforms is probably good for other situations where you need to run a lot of dot products in parallel. That, in turn, should sound like an awfully familiar problem...

[amelius]

Ok, but dot products and Fourier transforms are both linear operations. Maxwell's equations are linear (light also obeys them).

Neural nets, on the other hand, generally require nonlinear operations. As do most computer programs.

So the explanation here is either not complete, or perhaps applies to a very restricted type of neural network only.

[CamperBob2]

Good point. I know there are people working on optical NNs, but I have no idea how they handle nonlinear activation functions.

[Q6T46nT668w6i3m]

There’re a handful of ways to introduce electro-optical and all-optical non-linearities into optical neural networks. Here’s a fair survey of the field: https://dl.acm.org/doi/full/10.1145/3607533