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

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

#631

Post by hnfong »

scoofy wrote: post #600
qnleigh wrote: post #597

Earlier quoted context omitted.

I might as well answer my own question, because I do think there are some coherent arguments for fundamental LLM limitations: 1. LLMs are trained on human-quality data, so they will naturally learn to mimic our limitations. Their capabilities should saturate at human or maybe above-average human performance. 2. LLMs do not learn from experience. They might perform as well as most humans on certain tasks, but a human…

I studied philosophy focusing on the analytic school and proto-computer science. LLMs are going to force many people start getting a better understanding about what "Knowledge" and "Truth" are, especially the distinction between deductive and inductive knowledge. Math is a perfect field for machine learning to thrive because theoretically, all the information ever needed is tied up in the axioms. In the empirical wor…

> distinction between deductive and inductive knowledge

There's also intuitive knowledge btw.

Anyway, the recent developments of AI make a lot of very interesting things practically possible. For example, our society is going to want a way to reliably tell whether something is AI generated, and a failure to do so pretty much settles the empirical part of the Turing test issue. Or alternatively if we actually find something that AI can't reliably mimic in humans, that's going to be a huge finding. By having millions of people wonder whether posts on social media are AI generated, it is the largest scale Turing test we have inadvertently conducted.

The fact that AI seems to be able to (digitally) do anything we ask for is also very interesting. If humans are not bogged down by the small details or cost of implementation concerns, and we can just say what we want and get what we wished for (digitally), what level of creativity can we reach?

Also once we get the robots to do things in the physical space...

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

#633

Post by hnfong »

getnormality wrote: post #492
eru wrote: post #454

Earlier quoted context omitted.

"Truly novel" is fast becoming a True Scotsman.

No True Novelty, No True Understanding, etc. The problem with these bromides is not that they're wrong, it's that they're not even wrong. They're predictive nulls. What observable differences can we expect between an entity with True Understanding and an entity without True Understanding? It's a theological question, not a scientific one. I'm not an AI booster by any means, but I do strongly prefer we address the que…

There are already people dealing with AI intelligence scientifically. That's what benchmarks do.

It's the "it's just a stochastic parrot!" camp that's doing the theological work. (and maybe also those in the Singularity camp...)

That said, I do think there's value in having people understand what "Understanding" means, which is kinda a theological (philosophical :D) question. IMHO, in every-day language there's a functional part (that can be tested with benchmarks), and there's a subjective part (i.e. what does it feel like to understand something?). Most people without the appropriate training simply mix up these two things, and together with whatever insecurities they have with AI taking over the world (which IMHO is inevitable to some extent), they just express their strong opinions about it online...

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

#634

Post by nprateem »

Yizahi wrote: post #404
qnleigh wrote: post #288

I am kind of amazed at how many commenters respond to this result by confidently asserting that LLMs will never generate 'truly novel' ideas or problem solutions. > AI is a remixer; it remixes all known ideas together. It won't come up with new ideas > it's not because the model is figuring out something new > LLMs will NEVER be able to do that, because it doesn't exist It's not enough to say 'it will never be able t…

LLMs can generate anything by design. LLMs can't understand what they are generating so it may be true, it may be wrong, it may be novel or it may be known thing. It doesn't discern between them, just looks for the best statistical fit. The core of the issue lies in our human language and our human assumptions. We humans have implicitly assigned phrases "truly novel" and "solving unsolved math problem" a certain mean…

> Which a formally novel things, but we really never needed any of that

The history of science and maths is littered with seemingly useless discoveries being pivotal as people realised how they could be applied.

It's impossible to tell what we really "need"

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

#635

Post by hnfong »

eru wrote: post #599
mikkupikku wrote: post #554

Earlier quoted context omitted.

Agreed. We should be asking what the machines measurably can or can't do. If it can't be measured, then it doesn't matter from an engineering standpoint. Does it have a soul? Can't measure it, so it doesn't matter.

That's a bit too pessimistic. Often times you can productively find some measurable proxy for the thing you care about but can't measure. Turing's test is a famous example, of that. Sometimes you only have a one-sided proxy. Eg I can't tell you whether Claude has a soul, but I'm fairly sure my dishwasher ain't.

> Turing's test is a famous example

Ironically, the Turing test is the OG functionalist approach. The GP's comment basically sums up with the Turing test was designed for.

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

#636

Post by andrewflnr »

datsci_est_2015 wrote: post #336
NitpickLawyer wrote: post #167

Earlier quoted context omitted.

> I don't see this getting better. We went from 2 + 7 = 11 to "solved a frontier math problem" in 3 years, yet people don't think this will improve?

I’ve seen this style of take so much that I’m dying for someone to name a logical fallacy for it, like “appeal to progress” or something. Step away from LLMs for a second and recognize that “Yesterday it was X, so today it must be X+1” is such a naive take and obviously something that humans so easily fall into a trap of believing (see: flying cars).

Even more insane than assuming the trend will continue is assuming it will not continue. We don't know for sure (especially not by pure reason), but the weight of probability sure seems to lean one direction.

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

#637

Post by hnfong »

Validark wrote: post #205
keeda wrote: post #140

Earlier quoted context omitted.

I'm curious as to why you consider this as the benchmark for AI capabilities. Extremely few humans can solve hard problems or do much innovation. The vast majority of knowledge work requires neither of these, and AI has been excelling at that kind of work for a while now. If your definition of AI requires these things, I think -- despite the extreme fuzziness of all these terms -- that it's closer to what most people…

Fair point, however I am simply more interested in how AI can advance frontiers than in how it can transcribe a meeting and give a summary or even print out React code. I know the world is heavily in need of the menial labor and AI already has made that stuff way easier and cheaper. However I'm just very interested in innovation and pushing the boundaries as a more powerful force for change. One project I've been sup…

It's kind of interesting in your original comment you used the words "doubter" and "believer", as if AI was some kind of messianic event of some sort and you are deciding whether to "believe" in it.

I mean, if you step back and think about it, there's nothing that requires faith. As you said, current AI can do a lot of things pretty well (transcribe and summarize meetings, write boilerplate code, etc.) Nobody is doubting this.

And AI is definitely helping in innovation to some extent. Not necessarily drive it singlehandedly, but some people working on world-changing innovation find AI useful.

So yeah, I think some people are subconsciously not doubting whether AI works, but kinda having conflicted thoughts about AI being our new overlords or something.

If you think about it, is having AI that's capable of innovating better than humans really a good thing? Like, even if we manage to make benign AI who won't copy how humans are jerks to each other, it kinda takes away our fun of discovery.

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

#638

Post by int_19h »

aspenmartin wrote: post #521
Yizahi wrote: post #470

Earlier quoted context omitted.

We can't tell yet if that is true, partially true, or false for humans. We do know that LLM can't do anything else besides that (I mean as a fundamental operating principle).

Why is it important? “Statistical fit” is what you want…not understanding this is indicative of a limited understanding of what statistics is. What do you think it means to truly understand something? I don’t get it: read probability theory by Jaynes. It doesn’t really matter if the brain does Bayesian updates but that’s what’s optimal…

"Statistical fit" to environment is arguably what all life does.

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

#639

Post by int_19h »

storus wrote: post #563
tigershark wrote: post #544

Earlier quoted context omitted.

How many humans have been born until now and how many Einsteins have been born? And in how many hundreds of thousands of years?

The point is that humans do have some edge compared to current LLMs which are essentially next token predictors. If we all start relying on current AI and stop thinking, we would only be able to "exhaust the remix space" of existing ideas but won't be able to do any paradigm jumps. Moreover, it's quite likely that current training sets are self-contradictory, containing Dutch books, carrying some innate error in them…

It takes a lot of intelligence to "essentially predict" next token when you're doing a math proof. Or writing code.

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

#640

Post by int_19h »

sweezyjeezy wrote: post #253
famouswaffles wrote: post #109

Earlier quoted context omitted.

Last I checked humans didn't pop into existence doing that. It happened after billions of years of brute force, trial and error evolution. So well done for falling into the exact same trap the OP cautions. Intelligence from scratch requires a mind boggling amount of resources, and humans were no different.

To be fair, it is still pretty remarkable what the human brain does, especially in early years - there is no text embedded in the brain, just a crazily efficient mechanism to learn hierarchical systems. As far as I know, AI intelligence cannot do anything similar to this - it generally relies on giga-scaling, or finetuning tasks similar to those it already knows. Regardless of how this arose, or if it's relevant to A…

Human babies "train" their brain on literally gigabytes of multi-modal data dumped on them through all their sensory organs every second.

In a very real sense, our magic superpower is that we "giga-scale" with such low resource consumption, especially considering how large (in terms of parameters) the brain is compared to even the most advanced models we have running on those thousands of GPUs today. But that's where all those millions of years of evolution pay off. Don't diss the wetware!

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