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Deep learning with coherent nanophotonic circuits [pdf]
- corndoge 10y agoI wonder if this is what Intel is playing at with their comments about beating NVidia in the ML space within a few years without using GPUs?
- deepnotderp 10y agoNo it wasn't, they were talking about ASICs.
- hengheng 10y agoBingo!
- kovek 10y agoWhat do you mean? I've had a short discussion with a professor at my university about the practical efficiency of circuits. It seems like some tasks are better solved with algorithms and others with circuits. I think that a proper mix between turing machines and circuits will be important in the future of AI.
- johncolanduoni 10y agoUnfortunately they didn't implement the non-linear part in optical form as of yet, though they do at least model a fairly realistic saturable absorber.
- danieldrehmer 10y agoIt would be cool if they implemented a way of generating true random numbers by measuring a quantum events as part of the system
- amelius 10y agoIs this addressing the learning phase of the neural network, or just the feed-forward phase?
- graphene 10y agoThey trained on a computer model of the optical circuit, and only did the feed-forward step on the real thing. The rationale for that is that real-life models spend much more time (and energy) in inference mode, so that is the step you'd most want to optimize. I can't help but think it would be really cool to automatically produce a circuit that would output the gradient of the error of the actual NN, so you could optimize that directly.
- vivekchandsrc 10y agoVery interesting paper, optical circuits have always been interesting option for computing whether it is in the form of plasmonics (surface plasmon + electronics) or linear quantum computing (with similar circuits reported in the manuscript). However, the challenge to translate this into any practical application involves solving a lot of engineering challenges....