Improvement means being able to do more complicated things more reliably. Relatedly, it means being able to learn to do new things with fewer and fewer examples. We are running out of easily verifiable or simulation-friendly or data-rich domains for LLMs to conquer. (Note that I didn't say "simple" or "easy" domains.)
I suppose the next (and more risky) step is to let AI conduct its own real-world experiments, so that it can generate data to learn more physical and social properties.
Improvement means being able to do more complicated things more reliably. Relatedly, it means being able to learn to do new things with fewer and fewer examples. We are running out of easily verifiable or simulation-friendly or data-rich domains for LLMs to conquer. (Note that I didn't say "simple" or "easy" domains.)
I suppose the next (and more risky) step is to let AI conduct its own real-world experiments, so that it can generate data to learn more physical and social properties.
That sounds terrifying.
Which means someone is already working on it.
Models that are strong enough to improve themselves without a human (I.e. ai researcher) in the loop