

That’s not the only way to make meaningful change, getting people to give up on llms would also be meaningful change. This does very little for anyone who isn’t apple.
I’m an anarchocommunist, all states are evil.
Your local herpetology guy.
Feel free to AMA about picking a pet/reptiles in general, I have a lot of recommendations for that!
That’s not the only way to make meaningful change, getting people to give up on llms would also be meaningful change. This does very little for anyone who isn’t apple.
Meaningful change is not happening because of this paper, either, I don’t know why you’re playing semantic games with me though.
It does need to do that to meaningfully change anything, however.
that’s very true, I’m just saying this paper did not eliminate the possibility and is thus not as significant as it sounds. If they had accomplished that, the bubble would collapse, this will not meaningfully change anything, however.
also, it’s not as unreasonable as that because these are automatically assembled bundles of simulated neurons.
those particular models. It does not prove the architecture doesn’t allow it at all. It’s still possible that this is solvable with a different training technique, and none of those are using the right one. that’s what they need to prove wrong.
this proves the issue is widespread, not fundamental.
That indicates that this particular model does not follow instructions, not that it is architecturally fundamentally incapable.
I think it’s important to note (i’m not an llm I know that phrase triggers you to assume I am) that they haven’t proven this as an inherent architectural issue, which I think would be the next step to the assertion.
do we know that they don’t and are incapable of reasoning, or do we just know that for x problems they jump to memorized solutions, is it possible to create an arrangement of weights that can genuinely reason, even if the current models don’t? That’s the big question that needs answered. It’s still possible that we just haven’t properly incentivized reason over memorization during training.
if someone can objectively answer “no” to that, the bubble collapses.
It’s liquid ass