https://x.com/doomslide/status/2108121379660832930

here's a paper in their dump that is very similar to what humans uploaded a month ago

same poster goes on to say that the scale of the intellectual fraud is unbelievable

The whole threatening careers thing happened with navier stokes too.

These people are completely rotten to the core.

OpenAI then threatened his career if he tried to tell people what had happened.

and thus ended academic collaborations with OpenAI.

it might not even be the last step in a way. A person may have it solved but worries about publishing until they check and double check and run it down a few times to be sure and then of course there is the writing. So really it might just be acting as a technical writer for the researcher at best.

All it did was steal human work and rush publication

Ok, but literally all it does is steal human work and provide an output.

I wonder how the mathematician expected it to go. Was he expecting to be directly provided the AI output so he could publish it? Was he going to care if the AI used a novel approach he hadn't employed and was unable to identify where it got it from? We have seen since the beginning that AI has an attribution problem, so it seems like his actual concern was that HE wasn't credited.

I'm not an AI supporter, but this whole "it did just a small part" complaint is weird to me. I believe I read that most were solved in 3 hours of compute. I'm sure the mathematician wasn't just 3 hours from solving the problem. It did it faster than humans did. Isn't that the point? Does it matter how little the step was if it hadn't been taken yet? It could've taken mathematics years to make that last step. Shouldn't we be excited to see this development? If we're going to have AI, isn't the point that it accelerates problem solving. If AI sped up life saving medical research by years or even just months by doing one last step, would people be having the same reaction?

I've seen the same people complaining about this regularly talk about using AI for coding. Why is it ok that so many companies have put programmers in this position, but all the sudden it's bad for mathematicians?

Throwing 700 papers out there is intentional to generate buzz, “hey look how great we are”, and to slow attempts at proving or disproving their results.

The Gish gallop is a rhetorical technique in which a person in a debate attempts to overwhelm an opponent by presenting an excessive number of arguments, without regard for their accuracy or strength, with a rapidity that makes it impossible for the opponent to address them in the time available. Gish galloping prioritizes the quantity of the galloper's arguments at the expense of their quality.

The term "Gish gallop" was coined in 1994 by the anthropologist Eugenie Scott, who named it after the creationist Duane Gish, described by Scott as the technique's "most avid practitioner".[1][2]

Someone should just say they are all wrong. Then tell OpenAI to prove which one is right.

It will discourage generating new inputs, which it completely relies on, and thus, will quickly kill itself.

There are two issues really - one is a perception that they're not vetting any of this output, just dumping it out on the internet and expecting real mathematicians to actually check it all, so yes if a human was doing the same thing it'd probably still be suspect.

The other is the widely held suspicion that much of the "breakthrough" mathematics here has been stolen from real researchers who've been using chatgpt to develop their theories by talking to it

It is a lot of stuff from an unreliable source that basically vomits out stuff that looks correct but is often not and that is a ton of human work to verify that humans were already in the process of doing.

It is most likely just the stuff humans were close to finishing being scooped up and spit out and not reliably correct.

I think there are three main issues (though I might be overlooking something):

1. AI taking over peoples work is as much an issue for mathematicians here, as it is for programers, artists, writers, etc. elsewhere.
2. We still need to check if these 700 papers are correct (AI makes mistakes at least as often as humans, usually more often). This involves a huge amount of effort. And if it turns out that they contain a bunch of mistakes, OpenAI is unlikely to care. To them, these papers have already served their purpose (generating headlines).
3. Solving a problem in mathematics means being able to (formally) convince other people that your opinion is correct (massively simplified, but imo that is what mathematics boils down to), by getting them to understand why your opinion is correct. Having a pile of linear algebra spit out 700 texts about certain math problems removes the whole "human understanding" part of that.

However, it's not entirely unprecedented for a computer to provide a proof that we don't completely understand. I forgot the details (and I'll edit them in if I can find it), but there was at least one problem that was solved using a computer and brute force trying millions of cases. That produces a proof much longer than any human could read in a lifetime, and iirc there where quite a few mathematicians unhappy about it at the time too.

There's an onus now on those that care about math to check the proofs. If errors are found in one their might be similar errors in another. A serial release would have been cleaner and allowed commentary that might help improve the accuracy or perhaps even the way the model conveyed the data to make it more understandable / digestable.

Openai dug the problems up from somewhere. They could have collaborated with some of the people that defined the problems in the first place. This is just perpetuation of their culture of theft.

We all want the problems solved, right? Is there a wrong way to solve them?

Science is not mainly about solving problems (that would be engineering for example).

But more specifically to your question:

There are many wrong ways of doing scientific work, and what current AI does is one of them: reading it all, rephrasing it all a little and then already declare everything as done & good, even when it isn't.

A scientist needs proof, and peer reviews, etc. before the work can be called good.

Never forget AI isn't creating really new things, it can only chew up and spit out what has been there before. This is especially true in science.

Solving a problem has no value if no one understands the solution.

Why would you work if someone else gets the salary?