Very good, thank you for well-articulating this distinction, the crucial question around it, and a decent initial stab at some implications and consequences.
Provisionally, I think ‘mostly crystallised’ is right. Among the things that crystallise (especially from diverse agentic training) are something like crystallised heuristics for runtime exploration and in-context updating. I note that it’d be great to have readier evidence and trends on this!
Very good, thank you for well-articulating this distinction, the crucial question around it, and a decent initial stab at some implications and consequences.
Provisionally, I think ‘mostly crystallised’ is right. Among the things that crystallise (especially from diverse agentic training) are something like crystallised heuristics for runtime exploration and in-context updating. I note that it’d be great to have readier evidence and trends on this!
This is why I think exploration capability and its complement, sample-efficient learning, are totally central to any question of the impacts of AI on R&D (of AI and of other things).