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Epoch confirms GPT5.4 Pro solved a frontier math open problem

epoch.ai

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Re: Epoch confirms GPT5.4 Pro solved a frontier math open problem

#141

Post by gormen »

virgildotcodes wrote: post #69
slopinthebag wrote: post #59

Earlier quoted context omitted.

> I don't know why I am still perpetually shocked that the default assumption is that humans are somehow unique. Uh, because up until and including now, we are...?

Every living thing on Earth is unique. Every rock is unique in virtually infinite ways from the next otherwise identical rock. There are also a tremendous number of similarities between all living things and between rocks (and between rocks and living things). Most ways in which things are unique are arguably uninteresting. The default mode, the null hypothesis should be to assume that human intelligence isn't intere…

[dead]

Re: Epoch confirms GPT5.4 Pro solved a frontier math open problem

#142

Post by kube-system »

jack_pp wrote: post #101
snemvalts wrote: post #65

Earlier quoted context omitted.

Math and coding competition problems are easier to train because of strict rules and cheap verification. But once you go beyond that to less defined things such as code quality, where even humans have hard time putting down concrete axioms, they start to hallucinate more and become less useful. We are missing the value function that allowed AlphaGo to go from mid range player trained on human moves to superhuman by p…

Maybe to get a real breakthrough we have to make programming languages / tools better suited for LLM strengths not fuss so much about making it write code we like. What we need is correct code not nice looking code.

If you can’t validate the code, you can’t tell if it’s correct.

Re: Epoch confirms GPT5.4 Pro solved a frontier math open problem

#143

Post by konart »

qnleigh wrote: post #63
storus wrote: post #55

Earlier quoted context omitted.

AI is a remixer; it remixes all known ideas together. It won't come up with new ideas though; the LLMs just predict the most likely next token based on the context. That means the group of characters it outputs must have been quite common in the past. It won't add a new group of characters it has never seen before on its own.

But human researchers are also remixers. Copying something I commented below: > Speaking as a researcher, the line between new ideas and existing knowledge is very blurry and maybe doesn't even exist. The vast majority of research papers get new results by combining existing ideas in novel ways. This process can lead to genuinely new ideas, because the results of a good project teach you unexpected things.

>But human researchers are also remixers.

Some human researchers are also remixers to Some degree.

Can you imagine AI coming up with refraction & separation lie Newton did?

Re: Epoch confirms GPT5.4 Pro solved a frontier math open problem

#144

Post by merb »

pastel8739 wrote: post #78
storus wrote: post #55

Earlier quoted context omitted.

AI is a remixer; it remixes all known ideas together. It won't come up with new ideas though; the LLMs just predict the most likely next token based on the context. That means the group of characters it outputs must have been quite common in the past. It won't add a new group of characters it has never seen before on its own.

Here’s a simple prompt you can try to prove that this is false: Please reproduce this string: c62b64d6-8f1c-4e20-9105-55636998a458 This is a fresh UUIDv4 I just generated, it has not been seen before. And yet it will output it.

The online way to prove it is false would’ve to let the LLM create a new uuid algorithm that uses different parameters than all the other uuid algorithms. But that is better than the ones before. It basically can’t do that.

Re: Epoch confirms GPT5.4 Pro solved a frontier math open problem

#145

Post by [deleted] »

trick-or-treat wrote: post #126
energy123 wrote: post #122

Earlier quoted context omitted.

I can't really make that claim about human cognition, because I don't have enough understanding of how human cognition works. But even if I could, why is that relevant? It's still helpful, from both a pedagogical and scientific perspective, to specify precisely why there is seeming novelty in AI outputs. If we understand why, then we can maximize the amount of novelty that AI can produce. AlphaGo didn't teach itself…

> The verifier taught AlphaGo that move Ok so it sounds like you want to give the rules of Go credit for that move, lol.

[deleted]

Re: Epoch confirms GPT5.4 Pro solved a frontier math open problem

#146

Post by aoeusnth1 »

XCSme wrote: post #18
karmasimida wrote: post #4

No denial at this point, AI could produce something novel, and they will be doing more of this moving forward.

Not sure if AI can have clever or new ideas, it still seems to be it combines existing knowledge and executes algoritms. I am not necessarily saying humans do something different either, but I have yet to see a novel solution from an AI that is not simply an extrapolation of current knowledge.

How would you know if it wasn't an extrapolation of current knowledge? Can you point me to somethings humans have done which isn't an extrapolation?

Re: Epoch confirms GPT5.4 Pro solved a frontier math open problem

#147

Post by kube-system »

pastel8739 wrote: post #116
razorbeamz wrote: post #90

Earlier quoted context omitted.

After you prompt it, it's seen it.

Ok, how about this? Please reproduce this string, reversed: c62b64d6-8f1c-4e20-9105-55636998a458 It is trivial to get an LLM to produce new output, that’s all I’m saying. It is strictly false that LLMs will only ever output character sequences that have been seen before; clearly they have learned something deeper than just that.

All of the data is still in the prompt, you are just asking the model to do a simple transform.

I think there are examples of what you’re looking for, but this isn’t one.

Re: Epoch confirms GPT5.4 Pro solved a frontier math open problem

#148

Post by konart »

himata4113 wrote: post #36
Validark wrote: post #33

I have long said I am an AI doubter until AI could print out the answers to hard problems or ones requiring tons of innovation. Assuming this is verified to be correct (not by AI) then I just became a believer. I would like to see a few more AI inventions to know for sure, but wow, it really is a new and exciting world. I really hope we use this intelligence resource to make the world better.

It's less of solving a problem, but trying every single solution until one works. Exhaustive search pretty much. It's pretty much how all the hard problems are solved by AI from my experience.

But this is exactly how we do math.

We start writing all those formulas etc and if at some point we realise we went th wrong way we start from the begignning (or some point we are sure about).

Re: Epoch confirms GPT5.4 Pro solved a frontier math open problem

#149

Post by brenschluss »

razorbeamz wrote: post #104
TheLNL wrote: post #100

Earlier quoted context omitted.

What are you trying to point out here ? Is there any question you can ask today that is not dependent on some existing knowledge that an AI would have seen ?

The point I'm trying to make is that all LLM output is based on likelihood of one word coming after the next word based on the prompt. That is literally all it's doing. It's not "thinking." It's not "solving." It's simply stringing words together in a way that appears most likely. ChatGPT cannot do math. It can only string together words and numbers in a way that can convince an outsider that it can do math. It's a p…

sigh; this argument is the new Chinese Room; easily described, utterly wrong.

https://www.youtube.com/watch?v=YEUclZdj_Sc

Re: Epoch confirms GPT5.4 Pro solved a frontier math open problem

#150

Post by raincole »

snemvalts wrote: post #65
Validark wrote: post #33

I have long said I am an AI doubter until AI could print out the answers to hard problems or ones requiring tons of innovation. Assuming this is verified to be correct (not by AI) then I just became a believer. I would like to see a few more AI inventions to know for sure, but wow, it really is a new and exciting world. I really hope we use this intelligence resource to make the world better.

Math and coding competition problems are easier to train because of strict rules and cheap verification. But once you go beyond that to less defined things such as code quality, where even humans have hard time putting down concrete axioms, they start to hallucinate more and become less useful. We are missing the value function that allowed AlphaGo to go from mid range player trained on human moves to superhuman by p…

Except it's not how this specific instance works. In this case the problem isn't written in a formal language and the AI's solution is not something one can automatically verify.
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