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> the latter is falsified by the fact we can reason about code despite the Halting Problem.

I'm not talking in general terms, or describing 'what the code does' in a summary or bullet point high-level form. No one is arguing that it can't summarize and describe what code does. These models are very good at that.

I'm talking specifically about generating the output of the command, as the OP specifically mentioned.

It does generate the exact output for commands and scripts if you request it, sometimes even if you don't, just as an example; they're just, often, hallucinated rubbish.

Being impressed that GPT can invent from 'thin air' some creative writing (fiction) when you tell it `pretend you're a docker container and now run 'ls'` is I feel, missing the boat, in terms of understanding or being impressed by the capabilities of these LLMs.



And they're often not, even for quite complex functions that requires symbolically executing quite a few calculations to get to the pre-requisite output.

Nobody is impressed that it "can invent from 'thin air' some creative writing (fiction)", but that it often does not and in fact produces correct output. You're right we can't rely on it producing the correct output as it currently stands, but that it is capable of doing this at all is impressive.




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