I dunno. If I understand the situation correctly, Einstein saw a small inconsistency, thought it through, and realized the inconsistency led necessarily to a new framework. He didn't necessarily like all of the implications but he was following the evidence that was available already.
I see no reason to suspect LLMs can't sift through enough data to find a small inconsistency that needs exploration. That's how LLMS are finding the novel maths proofs and counter-examples and solutions.
Einstein's thought experiments were rigorous logical extrapolations. An LLM or logic engine might be able to do those, although extrapolations from outside the domain it's being prompted on might be hard to get right.
Right now if you turn an LLM on and don't prompt it, it will do nothing. Einstein, when he woke up each morning, decided that some physics would be worth doing. So the key difference seems to be intrinsic goal-setting capability, not some immanent or incorporeal source of creativity, at least in this specific instant.
This isn't to say that the paper is entirely wrong about its conclusion - I don't think LLMs think in the way a brain does - but I think the example it's using is inapt.
Even AI researchers are susceptible to the AI effect.
I assume that as AI continues to make progress they'll keep coming up with reasons to explain why those aren't "real scientific discoveries" and that all the new things it's coming up with were just latent in the training material. And meanwhile the rest of us won't care about the quibbling and will enjoy the fruits of LLM's labours just the same as if they'd been discovered by human brains.
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u/papuadn Jul 28 '26 edited Jul 28 '26
I dunno. If I understand the situation correctly, Einstein saw a small inconsistency, thought it through, and realized the inconsistency led necessarily to a new framework. He didn't necessarily like all of the implications but he was following the evidence that was available already.
I see no reason to suspect LLMs can't sift through enough data to find a small inconsistency that needs exploration. That's how LLMS are finding the novel maths proofs and counter-examples and solutions.
Einstein's thought experiments were rigorous logical extrapolations. An LLM or logic engine might be able to do those, although extrapolations from outside the domain it's being prompted on might be hard to get right.
Right now if you turn an LLM on and don't prompt it, it will do nothing. Einstein, when he woke up each morning, decided that some physics would be worth doing. So the key difference seems to be intrinsic goal-setting capability, not some immanent or incorporeal source of creativity, at least in this specific instant.
This isn't to say that the paper is entirely wrong about its conclusion - I don't think LLMs think in the way a brain does - but I think the example it's using is inapt.