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> As the recently released Apple study demonstrates, LLMs don't reason Where is everyone getting this misconception? I have seen it several times. First off, t
by throwaway314155 1y ago
> As the recently released Apple study demonstrates, LLMs don't reason
Where is everyone getting this misconception? I have seen it several times. First off, the study doesn't even try to qualify whether or not these models use "actual reasoning" - that's outside of the scope. They merely examine how effective thinking/reasoning _is_ at producing better results. They found that - indeed - reasoning improves performance. But the crucial result is that it only improves performance up to a certain difficulty-cliff - at which point thinking makes no discernable difference due to a model collapse of sorts.
It's important to read the papers you're using to champion your personal biases.
- miltonlost 1y agoAn LLM was given the algorithm to Towers of Hanoi and was unable to solve it. There is no "reasoning".
- throwaway314155 1y agoYou're conflating two definitions of reasoning. LLM's have struggled with visual reasoning since their inception because guess what!? they're trained on language mostly, not a 3d environment. LLM's aren't magic - those who claim they are are hyping for some reason or another. Ignore them. View AI objectively. Ignore your bias.
- tsimionescu 1y agoVisual reasoning is not required to follow an algorithm that was laid out. The fact that the model can't execute an algorithm it was provided proves that it is not able to do deductive synbolic reasoning in general, since that is all that would have been required required. I would agree with you if this were about inventing the algorithm for itself - it may well be that you'd need some amount of visual reasoning to come up with it. But that's not what the GP (or the paper) were talking about.
- deleted 1y ago[deleted]
- tsimionescu 1y ago> They found that - indeed - reasoning improves performance. You're oversimplifying the results a bit here. They show that reasoning decreases performance for simple problems, improves performance for more complex ones, and does nothing for very complex problems.
- throwaway314155 1y agoThanks good catch!
- gamblor956 1y agoI think you need to re-read the paper. The LLMs don't "reason" by any definition of the term. If they did, then the Tower of Hanoi and the river problem would have been trivial for them to handle at any level because ultimately the solutions are just highly recursive. What the LLMs do is attempt to pattern match to existing solved problems in their training set and just copy those solutions. But this results in overthinking for very simple problems (because they're copying too much of the solutions from their training set), works well for the somewhat complex problems like a basic Tower of Hanoi, and not at all for the problems that would require actual reasoning because...they're just copying solutions. The point of the paper is that what LLMs do is not reasoning, however much the AI industry may want to redefine the word to suit their commercial interests.