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GPT-5.2 derives a new result in theoretical physics

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

#151

Post by hellisad »

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…

Hmm feels a bit trivializing, we don't know exactly how difficult it was to come up with the generic set of equations mentioned from the human starting point.

I can claim some knowledge of physics from my degree, typically the easy part is coming up with complex dirty equations that work under special conditions, the hard part is the simplification into something elegant, 'natural' and general.

Also "LLM’s can make new things when they are some linear combination of existing things"

Doesn't really mean much, what is a linear combination of things you first have to define precisely what a thing is?

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

#152

Post by kylehotchkiss »

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…

> for people who know what they're doing.

I worry we're not producing as many of those as we used to

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

#153

Post by camdenreslink »

famouswaffles wrote: post #116
emil-lp wrote: post #100

Earlier quoted context omitted.

It's like saying: calculator drives new result in theoretical physics (In the hands of leading experts.)

No it's not like saying that at all, which is why Open AI have a credit on the paper.

Open AI have a credit on the paper because it is marketing.

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

#154

Post by blks »

kylehotchkiss wrote: post #152
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…

> for people who know what they're doing. I worry we're not producing as many of those as we used to

We will be producing them even less. I fear for the future graduates, hell even for school children, who are now uncontrollably using ChatGPT for their homework. Next level brainrot

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

#155

Post by torginus »

CGMthrowaway wrote: post #24
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…

This is the critical bit (paraphrasing): Humans have worked out the amplitudes for integer n up to n = 6 by hand, obtaining very complicated expressions, which correspond to a “Feynman diagram expansion” whose complexity grows superexponentially in n. But no one has been able to greatly reduce the complexity of these expressions, providing much simpler forms. And from these base cases, no one was then able to spot a…

I'm not sure if GPTs ability goes beyond a formal math package's in this regard or its just its just way more convienient to ask ChatGPT rather than using these software.

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

#156

Post by nextaccountic »

tjr wrote: post #104
randomtoast wrote: post #53

Earlier quoted context omitted.

> but I haven’t been to get them to do something totally out of distribution yet from first principles Can humans actually do that? Sometimes it appears as if we have made a completely new discovery. However, if you look more closely, you will find that many events and developments led up to this breakthrough, and that it is actually an improvement on something that already existed. We are always building on the shou…

Go enough shoulders down, and someone had to have been the first giant.

Probably not homo sapiens.. other hominids older than us developed a lot of technology

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

#157

Post by cpard »

jonahx wrote: post #140
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…

> The "AI replaces humans in X" narrative is primarily a tool for driving attention and funding. It's also a legitimate concern. We happen to be in a place where humans are needed for that "last critical 10%," or the first critical 10% of problem formulation, and so humans are still crucial to the overall system, at least for most complex tasks. But there's no logical reason that needs to be the case. Once it's not,…

The reason there is a marketing opportunity is because, to your point, there is a legitimate concern. Marketing builds and amplifies the concern to create awareness.

When the systems turn into something trivial to manage with the new tooling, humans build more complex or add more layers on the existing systems.

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

#158

Post by cpard »

elzbardico wrote: post #127
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…

Actually, the results were far worse and way less impressive than what the media said.

the c compiler results or the physics results this post is about?

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

#159

Post by [deleted] »

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…

[deleted]

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

#160

Post by NitpickLawyer »

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'…

> 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.

And the same practitioners said right after deep blue that go is NEVER gonna happen. Too large. The search space is just not computable. We'll never do it. And yeeeet...

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