GPT-5.2 derives a new result in theoretical physics • Hacker News Board

Re: GPT-5.2 derives a new result in theoretical physics

#211

Post by etraql » Fri, Feb 13, 2026, 10:41 PM UTC

lupsasca wrote: post #167

buttered_toast wrote: post #72

Earlier quoted context omitted.

I would interpret it as implying that the result was due to a lot more hand-holding that what is let on. Was the initial conjecture based on leading info from the other authors or was it simply the authors presenting all information and asking for a conjecture? Did the authors know that there was a simpler means of expressing the conjecture and lead GPT to its conclusion, or did it spontaneously do so on its own afte…

Hi I am an author of the paper. We believed that a simple formula should exist but had not been able to find it despite significant effort. It was a collaborative effort but GPT definitely solved the problem for us.

Do you also work at OpenAI? A comment pointing that out was flagged by the LLM marketers.

Re: GPT-5.2 derives a new result in theoretical physics

#212

Post by alansaber » Fri, Feb 13, 2026, 10:44 PM UTC

mym1990 wrote: post #149

Many innovations are built off cross pollination of domains and I think we are not too far off from having a loop where multiple agents grounded very well in specific domains can find intersections and optimizations by communicating with each other, especially if they are able to run for 12+ hours. The truth is that 99% of attempts at innovation will fail, but the 1% can yield something fantastic, the more attempts w…

I find it hard not to agree with this line of thinking (albeit will be less than 1%)

Re: GPT-5.2 derives a new result in theoretical physics

#213

Post by alansaber » Fri, Feb 13, 2026, 10:45 PM UTC

another_twist wrote: post #175

Thats great. I think we need to start researching how to get cheaper models to do math. I have a hunch it should be possible to get leaner models to achieve these results with the right sort of reinforcement learning.

Deepseek wrote a decent paper on this https://github.com/deepseek-ai/DeepSeek-Math-V2/blob/main/De...

Re: GPT-5.2 derives a new result in theoretical physics

#214

Post by DonHopkins » Fri, Feb 13, 2026, 10:46 PM UTC

layer8 wrote: post #197

rightbyte wrote: post #145

Earlier quoted context omitted.

> simplest nonzero amplitudes have two minus helicities while one-minus amplitudes vanish Sorry but I just have to point out how this field of maths read like Star Trek technobabble too me.

Where do you think Star Trek got its technobabble from?

Have I got a skill for you!

trekify/SKILL.md: https://github.com/SimHacker/moollm/blob/main/skills/trekify...

Re: GPT-5.2 derives a new result in theoretical physics

#215

Post by verdverm » Fri, Feb 13, 2026, 10:47 PM UTC

buttered_toast wrote: post #198

verdverm wrote: post #187

Earlier quoted context omitted.

I'm pretty sure it is widely known that the early 5.x series were built from 4.5 (unreleased). It seems more plausible the 5.x series is still in that continuation. For some extra context, pre-training is ~1/3 of the training, where it gains the basic concepts of how tokens go together. Mid & late training are where you instill the kinds of anthropic behaviors we see today. I expect pre-training to increasingly becom…

Okay I see what you mean, and yeah that sounds reasonable too. Do you have any context on that first part? I would like to know more about how/why they might not have been able to pursue more training runs.

I have not done it myself (don't have the dinero), but my understanding is that there are many runs, restarts, and adjustments at this phase. It's surprisingly more fragile than we know aiui

If you already have a good one, it's not likely much has changed since a year ago that would create meaningful differences at this phase (in data, arch is diff, I know less here). If it is indeed true, it's a datapoint to add to the others singling internal (everybody has some amount of this, not good when it makes the headlines)

Distillation is also a powerful training method. There are many ways to stay with the pack without having new pre-training runs. It's pretty much what we see from all of them with the minor versions. So coming back to it, the speculation is that OpenAi is still on their 4.x pre-train, but that doesn't impede all progress

Re: GPT-5.2 derives a new result in theoretical physics

#216

Post by blt » Fri, Feb 13, 2026, 10:50 PM UTC

TGower wrote: post #142

stouset wrote: post #120

Earlier quoted context omitted.

When chess engines were first developed, they were strictly worse than the best humans. After many years of development, they became helpful to even the best humans even though they were still beatable (1985–1997). Eventually they caught up and surpassed humans but the combination of human and computer was better than either alone (~1997–2007). Since then, humans have been more or less obsoleted in the game of chess.…

With a chess engine, you could ask any practitioner in the 90's what it would take to achieve "Stage 4" and they could estimate it quite accurately as a function of FLOPs and memory bandwidth. It's worth keeping in mind just how little we understand about LLM capability scaling. Ask 10 different AI researchers when we will get to Stage 4 for something like programming and you'll get wild guesses or an honest "we don'…

And their predictions about Go were wrong, because they thought the algorithm would forever be α-β pruning with a weak value heuristic

Re: GPT-5.2 derives a new result in theoretical physics

#217

Post by Toutouxc » Fri, Feb 13, 2026, 10:50 PM UTC

lovecg wrote: post #98

square_usual wrote: post #64

It's interesting to me that whenever a new breakthrough in AI use comes up, there's always a flood of people who come in to handwave away why this isn't actually a win for LLMs. Like with the novel solutions GPT 5.2 has been able to find for erdos problems - many users here (even in this very thread!) think they know more about this than Fields medalist Terence Tao, who maintains this list showing that, yes, LLMs hav…

Let’s have some compassion, a lot of people are freaking out about their careers now and defense mechanisms are kicking in. It’s hard for a lot of people to say “actually yeah this thing can do most of my work now, and barrier of entry dropped to the ground”.

I am constantly seeing this thing do most of my work (which is good actually, I don't enjoy typing code), but requiring my constant supervision and frequent intervention and always trying to sneak in subtle bugs or weird architectural decisions that, I feel with every bone in my body, would bite me in the ass later. I see JS developers with little experience and zero CS or SWE education rave about how LLMs are so much better than us in every way, when the hardest thing they've ever written was bubble sort. I'm not even freaking about my career, I'm freaking about how much today's "almost good" LLMs can empower incompetence and how much damage that could cause to systems that I either use or work on.

Re: GPT-5.2 derives a new result in theoretical physics

#218

Post by fsh » Fri, Feb 13, 2026, 10:52 PM UTC

computator wrote: post #204

I have a weird long-shot idea for GPT to make a new discovery in physics: Ask it to find a mathematical relationship between some combination of the fundamental physical constants[1]. If it finds (for example) a formula that relates electron mass, Bohr radius, and speed of light to a high degree of precision, that might indicate an area of physics to explore further if those constants were thought to be independent.…

The Bohr radius is the result of a simple classical physics calculation (a common exercise for undergraduates in their first year). It depends only on the electron mass and the fine structure constant which is the strength of the electromagnetic interaction. In the SI system, the speed of light has a fixed value which defines the unit of length.

Re: GPT-5.2 derives a new result in theoretical physics

#219

Post by singpolyma3 » Fri, Feb 13, 2026, 10:53 PM UTC

nyc_data_geek1 wrote: post #186

godelski wrote: post #123

Earlier quoted context omitted.

> I think this was all already figured out in 1986 though They cite that paper in the third paragraph... Naively, the n-gluon scattering amplitude involves order n! terms. Famously, for the special case of MHV (maximally helicity violating) tree amplitudes, Parke and Taylor [11] gave a simple and beautiful, closed-form, single-term expression for all n. It also seems to be a main talking point. I think this is a prim…

[flagged]

No

Re: GPT-5.2 derives a new result in theoretical physics

#220

Post by smj-edison » Fri, Feb 13, 2026, 10:58 PM UTC

Regardless of whether this means AGI has been achieved or not, I think this is really exciting since we could theoretically have agents look through papers and work on finding simpler solutions. The complexity of math is dizzying, so I think anything that can be done to simplify it would be amazing (I think of this essay[1]), especially if it frees up mathematicians' time to focus even more on the state of the art.

[1] https://distill.pub/2017/research-debt/