[rdlecler1]

To demystify NNs further we need to stop graphically representing spurious interactions. If you can perturb or remove a link win between any two neurons i & j, then that interaction is spurious and shouldn't be represented by in the graphical network representation. Doing this iteratively you can start to better appreciate that neural networks are computational circuits that use thereshold functions instead of logic gates.

[soared]

To me 'demystifying' really means making simpler to understand. Yours sounds like technical pedantry, that while true (idk?) is meaningless to anyone who actual needs a neural net demystified.

[rdlecler1]

Um, no. Show an electrical engineer the circuit diagram of an 8-bit added and they'll know the function right away. The function of the NN is similarly determined by the topological circuitry--in fact the function can often be preserved when you represent these networks as Boolean network, but all that's concealed when we don't remove spurious connections and it starts to feel like weird voodoo mathemagic. This is not an opinion, I've published on this and have seen scientist get confused because of it.