It seems to me we have only solved one part of the puzzle. Solved is possibly too strong a word, but the basic method seems to be to take a guess at what sort of network works best (flat / rrn / convolution / ltsm), throw a lot of data at it and with luck you get a good result. Sometimes as happened with AlphaZero a better result than the planet has seen to from man or machine to date. I suspect we have a fair bit to learn on the "best network design for a particular task" front, but it looks like that will happen over time.

I don't think that's too different to how nature does it in worms, as you say. However, our brains also have a different method of operation. We can see something just once, and learn from it. The small child scalds herself on the room heater, and never goes near it again.

So the child has learnt from a single example. We have no idea how to do that. At some level it's probably a complex mechanism that involves memorising it, replaying the memory over and over again till, as you put it, the brain hits a satisfactory p-level. As far as I know no one has built such a mechanism yet. However, that's probably because even if you did build it, the fact remains the brain has learnt from a single example and we have no idea how to learn near perfectly from a single example. Let alone do as the child did and learn the lesson in the space of seconds or at most minutes.