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Apple: ‘Reasoning’ AIs fail hard if they actually have to think
(pivot-to-ai.com)
Big brain tech dude got yet another clueless take over at HackerNews etc? Here's the place to vent. Orange site, VC foolishness, all welcome.
This is not debate club. Unless it’s amusing debate.
For actually-good tech, you want our NotAwfulTech community
The promptfondlers on places like /r/singularity are trying so hard to spin this paper. "It's still doing reasoning, it just somehow mysteriously fails when you it's reasoning gets too long!" or "LRMs improved with an intermediate number of reasoning tokens" or some other excuse. They are missing the point that short and medium length "reasoning" traces are potentially the result of pattern memorization. If the LLMs are actually reasoning and aren't just pattern memorizing, then extending the number of reasoning tokens proportionately with the task length should let the LLMs maintain performance on the tasks instead of catastrophically failing. Because this isn't the case, apple's paper is evidence for what big names like Gary Marcus, Yann Lecun, and many pundits and analysts have been repeatedly saying: LLMs achieve their results through memorization, not generalization, especially not out-of-distribution generalization.
prompfondlers
Holy shit, I love it.
https://awful.systems/comment/7326260
I still prefer promptards
i prefer that you take your ableist vocabulary somewhere else, preferably stick it up your arse.