I think the current architecture is limited.

To quote Einstein directly:

-----

Viereck (Interviewer): How do you account for your discoveries? Through intuition or inspiration?

Einstein: Discussing intuition and his confidence in relativity, noting he was convinced the 1919 eclipse would confirm his hypothesis.

Viereck: Then you trust more to your imagination than to your knowledge?

Einstein: I am enough of the artist to draw freely upon my imagination. Imagination is more important than knowledge. Knowledge is limited. Imagination encircles the world.

-----

I think we need more breakthroughs to build AI that can "draw freely upon imagination" to quote Einstein describing his process.

That is just my guess.

David Hilbert presented the field equations of general relativity within a few weeks of Einstein, so if anything GR was more sure to appear than SR, which took years for others to even notice (Einstein became famous only after the 1919 experiment that confirmed GR). Pertinently to the recent Navier-Stokes drama, there was very little controversy between the two and they both admitted that the other got some aspect better.

https://en.wikipedia.org/wiki/General_relativity_priority_di...

They also have custom brain bits evolved to aid in this task

I was defining novelty somewhat more narrowly. The 'program' a child must learn concerns the coordination of its sensory-motor system. It has no prior experience of similar programs in the program-class Walking (ie., the internal sensory-motor actions needed to walk) . So we could call the problem of learning to walk a novel one for that child.

I'd be surprised if direct observation of parents etc. played much of a direct role in learning to walk. I would guess it more furnishes the child's imagination so it can simulate itself walking -- rather than the statistical AI approach of 'learning the distribution of walking patterns in visual sensation'.

The ability to simulate possible programs is one of the capacities which enable coping with novel circumstances. My guess is the child learns to walk by updating its simulation of what it needs to do in order to walk, by its attempts to walk.

This simulation<->sensory-motor-update loop is missing in LLMs, for example.

Some animals walk within minutes of being born. Of course on four legs it's probably easier.

just because humans couldn't solve does not mean the necessary technique were not already discovered...we have agents that don't get tired and has access to all humanity knowledge, the building blocks could be there already..

this is not moving the goalposts, this is try to understand what this tech truly able and not able to do.

He needed his friend and math genius, Marcel Grossman, to turn his imagination into a workable theory. AI may be our own personal Marcel Grossman at this point.

Here is his quote:

"Imagination is more important than knowledge. For knowledge is limited, whereas imagination encircles the world,” means that facts alone only describe what currently exists, while imagination allows us to discover what is yet unproven or unbuilt"

This probably sums up the current AI limitation nicely.