> I guess we're just learning to make better and better AIs.

The way I understand it, most of the recent successes in AI and ML are because we finally have the computing power to implement the models we made in the decades before. There have obviously been incremental improvement in these models, but I am under the impression that there has not been a fundamental new insight in quite a while.

It depends on what you'd consider fundamental. It's true that most of our advances since the mid-80s have been about improving the robustness, data- and compute-efficiency of the training process through optimized architectures and learning algorithms, and in principle in the limit of infinite data and compute you could have taken a model from 1986 and scaled it up to do everything that our current models do. In that sense there have been no "fundamental" advances.

On the other hand, in the limit of infinite size and complexity most mathematical functions can be represented by hash maps, yet to say that there have been no fundamental advances in programming since the invention of hash maps in the fifties would seem like an odd claim to make.

> I guess most learning starts with and happens through mimicry. I guess we're just learning to make better and better AIs.

For all the actual "intelligence" these mimics are displaying so far, the question is what exactly they're mimicking. If, as seems palusible to me, they aren't on the path of, say, a human baby -- i.e. beginning to form a mental model of physical facts, logical connections, and causal relations -- but just regurgitating input, then maybe what "we" are just to make is better and better earthworms, not primates.