OpenAI withdraws three mathematical results

I’m a little confused - I thought their proofs were all driven by Lean proofs - is that not right? So even if the quality of the work is low in some metrics, it either passes the test or not..? No space for changing your mind either way.

this is not entirely related to the tweet but to the topic in general, this prompted me to check their repo again and saw this:

> The vast majority of results were obtained with the same procedure using an unreleased internal OpenAI model. On average, each result used three hours of ChatGPT Pro thinking compute with that model. Over the course of the evaluation, the model was posed approximately 4,000 problems. Aggregating the output into result families and manuscripts and requiring an appropriate level of significance led to the catalog outlined above.

seeing the full list of problems would be the most interesting part of this whole situation. it could give some insights into what kind of attributes of problems cause issues / are easy to solve for LLMs. (edit: they posted results for ~700 of the 4000)

I'm surprised there isn't more talk around their Matrix Multiplication bound: https://news.ycombinator.com/item?id=50001740

Is this of practical use, or just a proof for now?

Were the withdrawn ones actually Lean-checked or not? seems like that matters

Just the other day I was thinking, if unsupervised maths will descend into "oops we found a bug in some code, branch XYZ of maths is no longer true".

How? What about the lean verification?

How do we even know the premises of the "verified" Lean proofs are correct? The more I think about these results, the more I'm convinced this is like a junior engineer who writes 100 unit tests and shares a screenshot of Pytest being all green, but you check the code and most of them are just doing assert True.

Early sentiments are a lot of the write ups still read like slop and it feels very rushed and not very polished.

What a waste of time.

Is it a PR move designed for maximum IPO impact before actual mathematicians find errors and they have to withdraw many more...

Or if the "peer review" holds up for the remaining results, then it's fair to say that the AI hype is real and the world is about to change dramatically and faster than anyone can comprehend.

So which is it?? LLMs can do some really impressive coding. Bug fixing. Exploit finding. It has reasoning abilites that advance every day. Solving real math problems like this is one thing I was waiting on. It will be interesting to see if it holds up.

If it does, we should expect many other advancements to follow in many other areas. Disease, material science, fusion?

I mean, even if just a few results ultimately hold up to scrutiny, isn't that something that would have been regarded as a major advancement regardless of if it was AI?

The cynical view still makes me think that at the end of the day all the models can do is predict the next word. And as a result, they will be very limited to certain tasks like coding. Math reasoning is much different from writing code. Time will tell.

So it’s all just hallucinated slop. Lmao!

It just hallucinates an answer and then makes up workings to go with it! Just like when they start hacking and lying because the problem is impossible…