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And a simple PID controller built with op-amps looks an awful lot like a simple neural network.

http://www.ecircuitcenter.com/Circuits/op_pid/op_pid.htm

https://www.nutsvolts.com/magazine/article/the_perceptron_ci...



Isn't gradient descent basically PID over parameters? And tricks like momentum basically a low-pass filter integrated in the PID loop? It's quite weird how not that many concepts from analog electronics domain have gotten carried over to ML.




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