>The reason why they've failed is because we didn't understand the fundamentals. We still don't. That's the point. It's not backwards, that's where we should begin from.

Nope, they failed because there’s not enough data and the strategy is not computationally viable. They did however, have the “basic system down”, it’s just not very efficient from a practical standpoint. A infinite neural net is mathematically proven to be able to converge to any continuous function, it’s just that it does it in a very lengthy way and without providing much certainty on how accurate and close we are. But yes, they did have A basic system down, they just haven’t found the right system yet. All we have to do now is to find a way to cut corners and once enough corners are being cut, the machine will learn to cut by itself. So no, we do not need to structurally know the fundamentals of how a human mind works, we however, needs to know the fundamentals of how such mind might be created.

We are finding ways to make the “fetus”, NOT the “human”.

Also, “emotions”, depending on your definition certainly does come into play in the creation of AI, that’s the whole point of reinforcement learning. But the problems lies in what the “emotions” are specifically catering to. In humans, emotions serve as a directive for survival. In machines, it’s a device to deter the machine from pathways that results in a failure of a task and to nudge itself towards pathways that are promising. I think we both could agree that we can create a machine that solve complicated abstract math problems without needing it feeling horny first.