[antirez]

That's not the point, I think: you can implement the brain in BASIC, in theory, this does not means that the brain is per-se a BASIC program. I'll provide a more theoretical framework for reasoning about this: if the way to solve certain problems by an NN (the learned weights) can't be translated in some normal program that DOES NOT resemble the activation of an NN, then the NNs are not algorithms, but a different computational model.

[tsimionescu]

This may be what they were getting it, but it is still wrong. An NN is a computable function. So, NN inference is an algorithm for computing the function the NN represents. If we have an NN that represents a function f, with f(text) = most likely next character a human would write, then running the inference for that NN is an algorithm for finding out which character it's most likely a human would write next.

It's true that this is not an "enlightening" algorithm, it doesn't help us understand why or how that is the most likely next character. But this doesn't mean it's not an algorithm.