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> The actual process of token generation works precisely the same I’d be wary of generalising it like that, it is like saying that all programs run on the same
by DougBTX 2y ago
> The actual process of token generation works precisely the same
I’d be wary of generalising it like that, it is like saying that all programs run on the same set of CPU instructions. NNs are function approximators, where the code is expressed in model weights rather than text, but that doesn’t make all functions the same.
- lukev 2y agoYou misunderstand. I mean that the model itself is doing exactly the same thing whether the output is a “hallucination “ or happens to be fact. There isn’t even a theoretical way to distinguish between the two cases based only on the information encoded in the model.
- skydhash 2y ago> it is like saying that all programs run on the same set of CPU instructions Turing machine is the embodiment of all computer programs. And then you come across the halting problem. LLMs can probably generate all books in existence, but it can't apply judgement to it. Just like you need programmers to actually write the program and verify that it correctly solves the problem. Natural languages are more flexible. There are no functions libraries, or paradigms to ease writing. And the problem space can't be specified and usually relies on shared context. Even if we could have snippets of prompts to guide text generations, the result is not that valuable.