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Not saying anything about LLM But in CS in general many issues "cannot be solved" or "Cannot be solved in reasonable time (NP)" but approximations upper bound by some value are solvable in reasonable time (P).

And in the real world if the truck route of amazon is 20% off the mathematically optimal solution the traveling salesman is "Solved" in a good enough way.

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The claim of the paper is that computation is irreducible (assuming P!=NP), LLMs have limited computational capacity and will hallucinate on the irreducible problems.

I don’t know, the claim seems dubious to me. We usually are able to have algorithms that return a failure status, when the problem proved to be too large. Avoiding the “hallucination”. Don’t see why LLMs can’t have that embedded.

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