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More questions about whether researchers can trust OpenAI with unpublished math

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Re: More questions about whether researchers can trust OpenAI with unpublished math

#461

Earlier quoted context omitted.

Use a local model to produce thousands of pages worth of fake math that constantly states “I have solved the x conjecture” and methodically pump it into chat over months maybe?

That is a better idea. Ingesting your corpus with a lot of traces that have semantic patterns. Semantic steganography that suffixes well to real math and science (and any) topics. heh.

"Semantic steganography" is my new favorite search term – thank you for this rabbit hole.

Re: More questions about whether researchers can trust OpenAI with unpublished math

#462

Both things can be true: 1. OpenAI when using your chats in pretraining is improving its model’s intuition. The model parameter size is massive, and while the data is OOM larger it is plausible that model remembers stuff about chats that improves its latent representation. 2. During RL on verifiable math and massive compute, the model discovers techniques and connections to solve math problems that are superhuman and…

> The rumor I’ve heard from multiple employees at OAI and Ant is that the model has solved hundreds of open problems in maths

Obviously these are unbiased and trustworthy sources.

Re: More questions about whether researchers can trust OpenAI with unpublished math

#465
Silicon Valley is flying head first into a FAFO train wreck on trust with everyone else.

OpenAI is firmly earning a reputation as a company where people just assume they’re up to no good. Rightly or wrongly that’s a terrible place to be.

The AI industrial complex in general is finding out hard what happens on the data center side when you get arrogant with local communities. Politicians have seen the polling numbers and folks you wouldn’t expect are running to the front of the crowd with pitch forks in hand.

Silicon Valley has totally lost the narrative here, but also lacks the self awareness to grasp how bad things are and will get and what that means for their own business viability.

Re: More questions about whether researchers can trust OpenAI with unpublished math

#467
post #398

Earlier quoted context omitted.

I think people are focusing on the training data issue too much. If the data was contaminated, I can still blame that on negligence. But, at least with the Navier-Stokes solution, it's clear [^1] that they learned that Alpöge and Buckmaster were getting close to a solution and learned of the general approach they were taking. Only after learning the secret to cracking the problem did they send the first prompt. What…

> They intentionally threw $15 million in compute at the problem what? really?

Yes. Maybe much more:

> Such intensive use of AI doesn't come cheap. In a post on X, LisanBench, an LLM benchmark evaluator, estimated that the output tokens alone would cost about $6.5 million at OpenAI's average consumer price. Including the far larger volume of input tokens, the post estimated the total could reach $10 million to $40 million.

https://www.businessinsider.com/openai-math-problem-solved-t...

Re: More questions about whether researchers can trust OpenAI with unpublished math

#468

Earlier quoted context omitted.

Both can be true: 1. OpenAI couldn't have solved the problem without the researchers' private data for training. 2. OpenAI models can solve math problems

You forgot possibility 3: OpenAI solved the problem without using any private training data from the two researchers. Everyone in this thread seems to have made up their mind about OpenAI's guilt though.

Extraordinary claims require extraordinary evidence.

An article post that wouldn't even amount to a white paper + the LEAN proof is not evidence of how they got to produce it.

Re: More questions about whether researchers can trust OpenAI with unpublished math

#469
post #434
post #412

I think it's a useful analogy to compare OpenAI to a human collaborator. These researchers willingly collaborated with an OpenAI model, giving it ideas, and OpenAI provided useful replies. Then, OpenAI goes ahead and publishes work along the lines of this collaboration, without attributing the researchers. If OpenAI was in fact a human researcher, this would be highly unethical. Now, OpenAI is claiming that the model…

> I think it's a useful analogy to compare OpenAI to a human collaborator. Frankly I don’t buy this. It’s not a human or a collaborator. It’s a tool. This is like saying it’s not Microsoft’s fault if they extract a bunch of data from people’s Excel sheets because they willingly put it into the program. Anthropomorphizing software is ignorant and foolhardy

Tools don’t turn around and scoop you. What OpenAI did here was use the same tool that the researcher did which might have coupled their work together.

Re: More questions about whether researchers can trust OpenAI with unpublished math

#470
post #412

I think it's a useful analogy to compare OpenAI to a human collaborator. These researchers willingly collaborated with an OpenAI model, giving it ideas, and OpenAI provided useful replies. Then, OpenAI goes ahead and publishes work along the lines of this collaboration, without attributing the researchers. If OpenAI was in fact a human researcher, this would be highly unethical. Now, OpenAI is claiming that the model…

The irony is that OpenAI got into this trouble only because they tried to play "nice". They told Buckmaster that he could publish the final result as the author as long as he removed Alpöge from the author list. They wanted to give Buckmaster a chance to be the one solved N-S problem. While this behavior is highly questionable, if OpenAI just published the final result without notifying Buckmaster first and simply ci…

> if OpenAI just published the final result without notifying Buckmaster first and simply cited his previous researched, there would be no ground for anyone to accuse OpenAI for anything

Yes, there would? They would have left off Buckmaster as a precedent whose work they potentially relied on.

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