That seems right, but also reminds me of the point that you need to randomly initialize your neural nets for gradient descent to work (because otherwise the gradients everywhere are the same). Like, in the randomly initialized net, each edge is going to be part of many subcircuits, both good and bad, and the gradient is basically “what’s your relative contribution to good subcircuits vs. bad subcircuits?”
That seems right, but also reminds me of the point that you need to randomly initialize your neural nets for gradient descent to work (because otherwise the gradients everywhere are the same). Like, in the randomly initialized net, each edge is going to be part of many subcircuits, both good and bad, and the gradient is basically “what’s your relative contribution to good subcircuits vs. bad subcircuits?”