I think the author has a point. LLMs struggle with what you might call epistemically constructive novelty. It's the ability not just to synthesize existing knowledge, but to identify what's missing and conjecture something to fill the gap and demonstrate it to satisfaction. Out-of-distribution knowledge gaps are typically where LLMs "hallucinate." Unlike highly skilled human researchers, they don't pause and construct the bridge that will get them from known to unknown, they just immediately rush to fill in the blank with whatever sounds most plausible. They need to ask questions that haven't been asked before, or answer ones that haven't been answered.
Is this just some missing subroutine that we'll eventually figure out? Or is this conjecture-proving process much more elaborate than whatever existing models, no matter how scaled, can manage? I'm not sure. But the answer starts with a question.
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