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Breaking scaling limits of analog computing

Breaking scaling limits of analog computing
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Breaking the scaling limits of analog computing

A new technique greatly reduces the error in an optical neural network, which uses light to process data instead of electrical signals. With their technique, the larger an optical neural network becomes, the lower the error in its computations. This could enable them to scale these devices up so they would be large enough for commercial uses.

Deep learning with light

A new computing architecture enables advanced machine-learning computations to be performed on a low-power, memory-constrained edge device. The technique may enable self-driving cars to make decisions in real-time while only using a fraction of the energy that is currently demanded by their power-hungry on-board computers.

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