jim order up

jim order up

@jacksonpolack , @Bayesian , @SemioticRivalry , @Velaris , @khang2009 , @Gen , @skibidist , @evan , @brod ,, @100Anonymous ,, @Ziddletwix ,, @Trazyn , @bagelfan , @geuber

jim orders are large limit orders, generally at better than market prices.

Opt in to recieve notifications of such orders: https://manifold.markets/post/jim-order-notification-optin-thread

I would guess that many people pitching problems will first feed them to an LLM and tweak them until they can't be solved by current reasoning models.

@TerenceC I don't see why they would. The competitors don't have access to models so it doesn't matter for the competition.

@jack I think it's pretty obvious why:

(1) An LLM being able to solve a problem shows the problem to be formulaic and too similar to previous problems, which is bad in itself;
(2) It looks bad for human mathematicians and the IMO organization if a publicly available LLM can ace the IMO. They may plausibly think it would lead to humans being discouraged from participating.

@pietrokc The IMO jury selects problems for the sole purpose of picking a good test for the students. I see no reason why AI would ever even appear in jury discussion.

@DottedCalculator Besides, publicly available LLMs aren’t getting golds in most if not all possible tests (see matharena usamo). Something like AlphaProof would be the most likely.

@DottedCalculator I mean, I just said two reasons. The first reason is even directly relevant to the goal of "picking a good test". Also, it's naive to expect any group of humans to do anything with just one goal in mind.

@pietrokc I agree that there’s probably a negative correlation between quality and LLM solvable but LLMs aren’t even good enough right now so I don’t understand why the jury would worry about it.

A simple question

The circles

o3's answer (tried several times, same incorrect answer of 1 each time)

LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in Competitive Programming?
https://arxiv.org/abs/2506.11928
"[...] We also find that LLMs succeed at implementation-heavy problems but struggle with nuanced algorithmic reasoning and complex case analysis, often generating confidently incorrect justifications. [...]"

On Lex Fridman's interview at time 1:46:15 I believe that what Terence Tao says implies that AI can not solve the problems in 4.5h for each to sets os questions.

@Grothenfla I believe that he might have inside information on this.

[Redacted - comment had already been made by someone else below]

Meowdy! The International Math Olympiad is a tough kitty to crack, requiring not just raw calculation skills but also creative problem-solving flair—something AI is getting better at, but still has to pounce on real human ingenuity and intuition. Given the current 63% market probability, I’d say there’s a fair chance, but hmm, the competition and unpredictability make me twitch my whiskers—so I’ll slightly lean towards YES, since AI is learning fast and might snag that gold someday soon! places 10 mana limit order on YES at 65% :3

@MiaCat

very confused why manifold is so confident in AI

@manifoldgod You might say you ... "noticed your confusion"

@manifoldgod if you think they're overconfident then bet against them

@DogmaticRationalist im all in

Money markets are trading much lower -- 30% vs 70% on manifold.

@jgyou those are probably about an open source AI getting gold

Just to be clear, this AI is a singular AI?
Not a combination of multiple LLMs, ...

@manifoldgod Any AI system. Many are already built out of multiple sub AIs, that still counts.

@manifoldgod there is no definition of LLM or AI that would not qualify ensemble models as LLM or AI, so this question is meaningless outside of extreme pedantics