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Re:30% Drop In o1-Preview Accuracy When Putnam Problems Are ... by Panzer04 on Wednesday January 01, 2025 @08:02AM (#42565760)
Seems a bit picky. If the bot has seen the exact problem before it's not really doing anything more than recall to solve it.
Re:30% Drop In o1-Preview Accuracy When Putnam Problems Are ... by bandrami on Wednesday January 01, 2025 @08:21AM (#42565853)
20 years ago in grad school we were doing a very early iteration of this where we built Markov chains with Shakespeare's plays and wanted to produce a plausibly "Shakespearian" clause given a single word to start and a bearish professor said "the more plausible it gets the more I worry people might forget plausibility is all that it promises".

(There was also a much earlier piece of software that would generate semi-intelligible Kant or Hegel one sentence at a time, though that was through a series of a priori generation rules and a large at the time dictionary of stock phrases. I wonder what ever happened to that.)

Re:30% Drop In o1-Preview Accuracy When Putnam Problems Are ... by sickblastoise on Wednesday January 01, 2025 @09:29AM (#42566201)
I think your prof’s worries came true on a massive scale
Re:30% Drop In o1-Preview Accuracy When Putnam Problems Are ... by jeffreygoesto on Wednesday January 01, 2025 @08:27AM (#42565885)
It became a successful consultant...
Re:30% Drop In o1-Preview Accuracy When Putnam Problems Are ... by marcosdumay on Wednesday January 01, 2025 @09:58AM (#42566357)
That said, a bot with contextual recall can be very useful.

The problem is just that people keep insisting that those things are intelligent.