An AI that develops more sample-efficient, continually learning systems for well-scoped machine-learning problems could produce more general learning abilities, provided there is sufficient transfer.

“But if you make an AI that is really good at making something that is more sample efficient,”

“that is capable of continual learning or these much more well scoped ML problems,”

“the thing that emerges out of that, assuming there's good enough transfer.”

“or from the direct problem you're solving and like this broader ability to learn can just be more general right so i think that's an important dynamic to keep in mind of why jaggedness can still lead to generality on the other end on this um question of i mean obviously experiments bottleneck you because if they didn't as you're saying”