Comment by famouswaffles
14 hours ago
Claude and GPT both ask for clarification
https://claude.ai/share/3e14f169-c35a-4eda-b933-e352661c92c2
https://chatgpt.com/share/6919021c-9ef0-800e-b127-a6c1aa8d9f...
>Of course if you know anything about LLMs you should realize that they are just input continuers, and any conversational skills comes from post training.
No, they don't. Post-training makes things easier, more accessible and consistent but conversation skills are in pre-trained LLMs just fine. Append a small transcript to the start of the prompt and you would have the same effect.
>I'm not sure why you regard this as a "gotcha" question. If you're expressing opinions on LLMs, then table stakes should be to have a basic understanding of LLMs - what they are internally, how they work, and how they are trained, etc.
You proposed a distinction and explained a situation which would make that distinction falsifiable. And I simply told you LLMs don't respond the way you claim they would. Even when models respond mat (Now I think your original point had a typo?), it is clearly not due to a lack of understanding of what normal sentences are like.
>If you find a description of LLMs as input-continuers in the least bit contentious then I'm sorry to say you completely fail to understand them - this is literally what they are trained to do. The only thing they are trained to do.
They are predictors. If the training data is solely text then the output will be more text, but that need not be the case. Words can go in while Images or actions or audio may come out. In that sense, humans are also 'input continuers'.
> Claude and GPT both ask for clarification
Yeah - you might want to check what you actually typed there.
Not sure what you're trying to prove by doing it yourself though. Have you heard of random sampling? Never mind ...
>Yeah - you might want to check what you actually typed there.
That's what you typed in your comment. Go check. I just figured it was intentional since surprise is the first thing you expect humans to show in response to it.
>Not sure what you're trying to prove by doing it yourself though. Have you heard of random sampling? Never mind ...
I guess you fancy yourself a genius who knows all about LLMs now, but sampling wouldn't matter here. Your whole point was that it happens because of a fundamental limitation on the part of LLMs that causes them unable to do it. Even one contrary response, never mind multiple would be enough. After all, some humans would simply say 'mat'.
Anyway, it doesn't really matter. Completing 'mat' doesn't have anything to do with a lack of understanding. It's just the default 'assumption' that it's a completion that is being sought.