alt Hacker NewsWhen we say "think" in this context, do we just mean generalize? LLMs clearly generalize (you can give one a problem that is not exactly in it's training data and it can solve it), but perhaps not to the extent a human can. But then we're talking about degrees. If it was able to generalize at a higher level of abstraction maybe more people would regard it as "thinking".
I meant it in the same way the previous commenter did:
> Having seen LLMs so many times produce incoherent, nonsensical and invalid chains of reasoning... LLMs are little more than RNGs. They are the tea leaves and you read whatever you want into them.
Of course LLMs are capable of generating solutions that aren't in their training data sets but they don't arrive at those solutions through any sort of rigorous reasoning. This means that while their solutions can be impressive at times they're not reliable, they go down wrong paths that they can never get out of and they become less reliable the more autonomy they're given.