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

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

#191

Post by BrouteMinou » Fri, Feb 13, 2026, 10:08 PM UTC

cpard wrote: post #162

decidu0us9034 wrote: post #139

Earlier quoted context omitted.

I'm not sure you can call something an optimizing C compiler if it doesn't optimize or enforce C semantics (well, it compiles C but also a lot of things that aren't syntactically valid C). It seemed to generate a lot of code (wow!) that wasn't well-integrated and didn't do what it promised to, and the human didn't have the requisite expertise to understand that. I'm not a theoretical physicist but I will hold to my s…

sure, I won't argue on this, although it did manage to deliver the marketing value they were looking for, at the end their goal was not to replace gcc but to make people talk about AI and Anthropic. What I said in my original comment is that AI delivers when it's used by experts, in this case there was someone who was definitely not a C compiler expert, what would happen if there was a real expert doing this?

Deliver what exactly? False hope and lies?

https://github.com/anthropics/claudes-c-compiler/issues/228

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

#192

Post by throwuxiytayq » Fri, Feb 13, 2026, 10:14 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…

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

#193

Post by tedd4u » Fri, Feb 13, 2026, 10:15 PM UTC

outlace wrote: post #11

The headline may make it seem like AI just discovered some new result in physics all on its own, but reading the post, humans started off trying to solve some problem, it got complex, GPT simplified it and found a solution with the simpler representation. It took 12 hours for GPT pro to do this. In my experience LLM’s can make new things when they are some linear combination of existing things but I haven’t been to g…

What does a 12-hour solution cost an OpenAI customer?

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

#194

Post by dakolli » Fri, Feb 13, 2026, 10:16 PM UTC

loire280 wrote: post #105

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…

It's easy to fall into a negative mindset when there are legions of pointy haired bosses and bandwagoning CEOs who (wrongly) point at breakthroughs like this as justification for AI mandates or layoffs.

Yes, all of these stories, and frequent model releases are just intended to psyop "decision makers" into validating their longstanding belief that the labour shouldn't be as big of a line item in a companies expenses, and perhaps can be removed altogether.. They can finally go back to the good old days of having slaves (in the form of "agentic" bots), they yearn to own slaves again.

CEOs/decision makers would rather give all their labour budget to tokens if they could just to validate this belief. They are bitter that anyone from a lower class could hold any bargaining chips, and thus any influence over them. It has nothing to do with saving money, they would gladly pay the exact same engineering budget to Anthropic for tokens (just like the ruling class in times past would gladly pay for slaves) if it can patch that bitterness they have for the working class's influence over them.

The inference companies (who are also from this same class of people) know this, and are exploiting this desire. They know if they create the idea that AI progress is at an unstoppable velocity decision makers will begin handing them their engineering budgets. These things don't even have to work well, they just need to be perceived as effective, or soon to be for decision makers to start laying people off.

I suspect this is going to backfire on them in one of two ways.

1. French Revolution V2, they all get their heads cutoff in 15 years, or an early retirement on a concrete floor.

2. Many decisions makers will make fools of themselves, destroy their businesses and come begging to the working class for our labor, giving the working class more bargaining chips in the process.

Either outcome is going to be painful for everyone, lets hope people wake up before we push this dumb experiment too far.

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

#195

Post by bagacrap » Fri, Feb 13, 2026, 10:16 PM UTC

supern0va wrote: post #165

cpard wrote: post #126

AI can be an amazing productivity multiplier for people who know what they're doing. This result reminded me of the C compiler case that Anthropic posted recently. Sure, agents wrote the code for hours but there was a human there giving them directions, scoping the problem, finding the test suites needed for the agentic loops to actually work etc etc. In general making sure the output actually works and that it's a s…

>AI can be an amazing productivity multiplier for people who know what they're doing. >[...] >The "AI replaces humans in X" narrative is primarily a tool for driving attention and funding. You're sort of acting like it's all or nothing. What about the the humans that used to be that "force multiplier" on a team with the person guiding the research? If a piece of software required a team of ten to people, and instead…

Well those Uber drivers are usually pretty quick to note that Uber is not their job, just a side hustle. It's too bad I won't know what they think by then since we won't be interacting any more.

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

#196

Post by [deleted] » Fri, Feb 13, 2026, 10:18 PM UTC

fragmede wrote: post #134

cpard wrote: post #126

AI can be an amazing productivity multiplier for people who know what they're doing. This result reminded me of the C compiler case that Anthropic posted recently. Sure, agents wrote the code for hours but there was a human there giving them directions, scoping the problem, finding the test suites needed for the agentic loops to actually work etc etc. In general making sure the output actually works and that it's a s…

Right. If it hadn't been Nicholas Carlini driving Claude, with his decades of experience, there wouldn't be a Claude c compiler. It still required his expertise and knowledge for it to get there.

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

#197

Post by layer8 » Fri, Feb 13, 2026, 10:19 PM UTC

rightbyte wrote: post #145

CGMthrowaway wrote: post #132

Earlier quoted context omitted.

You're right. Parke & Taylor showed the simplest nonzero amplitudes have two minus helicities while one-minus amplitudes vanish (generically). This paper claims that vanishing theorem has a loophole - a new hidden sector exists and one-minus amplitudes are secretly there, but distributional

> 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?

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

#198

Post by buttered_toast » Fri, Feb 13, 2026, 10:19 PM UTC

verdverm wrote: post #187

buttered_toast wrote: post #77

Earlier quoted context omitted.

Can't say, just seems implausible, but I am a nobody anyways ¯\_(ツ)_/¯

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.

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

#199

Post by Davidzheng » Fri, Feb 13, 2026, 10:20 PM UTC

compass_copium wrote: post #188

Davidzheng wrote: post #13

Earlier quoted context omitted.

My understanding is there's been around 10 erdos problems solved by GPT by now. Most of them have been found to be either in literature or a very similar problem was solved in literature. But one or two solutions are quite novel. https://github.com/teorth/erdosproblems/wiki/AI-contribution... may be useful

...am I wrong in thinking that 1(a) is the relevant section here, and shows a lot of red?

I honestly don't see the point of the red data points. By now all the erdos problems have been attempted by AIs--so every unsolved one can be a red data point.

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

#200

Post by drdeca » Fri, Feb 13, 2026, 10:26 PM UTC

fpgaminer wrote: post #68

bottlepalm wrote: post #26

Earlier quoted context omitted.

Is every new thing not just combinations of existing things? What does out of distribution even mean? What advancement has ever made that there wasn’t a lead up of prior work to it? Is there some fundamental thing that prevents AI from recombining ideas and testing theories?

> Is every new thing not just combinations of existing things? If all ideas are recombinations of old ideas, where did the first ideas come from? And wouldn't the complexity of ideas be thus limited to the combined complexity of the "seed" ideas? I think it's more fair to say that recombining ideas is an efficient way to quickly explore a very complex, hyperdimensional space. In some cases that's enough to land on ne…

Well, what exactly an “idea” is might be a little unclear, but I don’t think it clear that the complexity of ideas that result from combining previously obtained ideas would be bounded by the complexity of the ideas they are combinations of.

Any countable group is a quotient of a subgroup of the free group on two elements, iirc.

There’s also the concept of “semantic primes”. Here is a not-quite correct oversimplification of the idea: Suppose you go through the dictionary and one word at a time pick a word whose definition includes only other words that are still in the dictionary, and removing them. You can also rephrase definitions before doing this, as long as it keeps the same meaning. Suppose you do this with the goal of leaving as few words in it as you can. In the end, you should have a small cluster of a bit over 100 words, in terms of which all the other words you removed can be indirectly defined. (The idea of semantic primes also says that there is such a minimal set which translates essentially directly* between different natural languages.)

I don’t think that says that words for complicated ideas aren’t like, more complicated?