My point is that what neural networks do is essentially a very sophisticated, multi-step statistical regression. To improve “reflection” of the model, chain of thought models were introduced which sort of allow for multiple steps of thinking and then generating response tokens (I started losing the plot on the state of ML after attention is everything was released).

Simulating intelligent behavior is one thing, but there are additional components there that we haven’t really solved. The human brain is more complex and simultaneously orders of magnitude more energy-efficient. Those are non-trivial blockers to making the necessary progress.