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AI isn’t outthinking mathematicians, it’s out-remembering them

davidepiffer.com

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Re: AI isn’t outthinking mathematicians, it’s out-remembering them

#481

Post by exe34 »

Xmd5a wrote: post #473
exe34 wrote: post #461

Earlier quoted context omitted.

> I just kept doing multiple passes through it, each time I noticed one of my answers contradicted one of the others, I would make adjustments to harmonize, which indirectly refined my understanding. I used to do something somewhat related during exams: I could never find contradictions/mistakes while working forwards, because somehow my brain would make the same mistakes consistently every time I go through somethin…

that's called forward and backward reaching inverse kinematics. FABRIK. Very cool algorithm by the way if you're into robotics/video games. https://andreasaristidou.com/FABRIK

Aha I do plan to get back into robotics soon (I never got in properly to be fair), and this is a cool algorithm I'll look into! Thanks for that!

Re: AI isn’t outthinking mathematicians, it’s out-remembering them

#482

Post by scrollop »

grahamburger wrote: post #210
hibikir wrote: post #198

I suspect that a lot about what we call being very intelligent is ultimately out-remembering people around us. I think of all the times in my software career when I did something that others considered very high performance, it either came down to either having more energy than others at tackling a problem they thought was more trouble than it was worth, or just bringing back random knowledge from previous jobs or se…

People have told me I was smart since I was a kid, but I can't remember for shit. I had a thought when I was fairly young that the only reason I was (maybe, sometimes) outperforming others intellectually is that I was habitually compensating for my poor memory by working things out on the fly, while others could rely more on rote memorization. Anyway, takes all kinds I guess!

That brings up an interesting quesiton - do you need a good memory to be "smart"? DO you need a good memory to do well in an IQ test (as far as they prove anything)? I'd say no.

I'm interested in AI though no expert, though would find it interesting to see an llm (until a "real" AI architecture can be created, ie that can learn on the fly and have more "real" intelligence) that:

Rather than being trained on billions on words, it instead has a grasp of logic, physics and spatial reasoning beyond any human, with little common knowledge, that could be fitted in a few billion parameters, that could then be run by a mobile phone.

Perhaps, for questions needing "knowledge" ie most of them, it would have well structured depots of knowledge it could quickly access to gain a quick understanding on a topic for a question (eg biology --> DNA structure for a highschool project), or C++ coding, then it can search the internet (with a list of "better" sources to try first).

SO, it would be like having an alien that has come to earth that is super intelligent, however know nothing/little of humans and the earth, and you ask it questions.

And it fits on your phone.

No idea if this would work.

Re: AI isn’t outthinking mathematicians, it’s out-remembering them

#484

Post by abustamam »

grahamburger wrote: post #210
hibikir wrote: post #198

I suspect that a lot about what we call being very intelligent is ultimately out-remembering people around us. I think of all the times in my software career when I did something that others considered very high performance, it either came down to either having more energy than others at tackling a problem they thought was more trouble than it was worth, or just bringing back random knowledge from previous jobs or se…

People have told me I was smart since I was a kid, but I can't remember for shit. I had a thought when I was fairly young that the only reason I was (maybe, sometimes) outperforming others intellectually is that I was habitually compensating for my poor memory by working things out on the fly, while others could rely more on rote memorization. Anyway, takes all kinds I guess!

Yeah same! This is why foreign languages are simultaneously easy and hard for me. I can memorize patterns and concepts easily but when it comes to arbitrary rules and vocabulary, I need flash cards for that. I end up needing to make up my own "rules" to remember things.

Re: AI isn’t outthinking mathematicians, it’s out-remembering them

#486

Post by don_esteban »

CapmCrackaWaka wrote: post #230
hibikir wrote: post #198

I suspect that a lot about what we call being very intelligent is ultimately out-remembering people around us. I think of all the times in my software career when I did something that others considered very high performance, it either came down to either having more energy than others at tackling a problem they thought was more trouble than it was worth, or just bringing back random knowledge from previous jobs or se…

I like to use the analogy that the human brain (when it comes to intelligence) is like a computer. We have storage, which is just long-term memory. We have RAM, which is your ability to keep track of a mental model of something you’re actively working on, and then there’s the CPU, which is the ability to make logical leaps and connections on that mental model (or maybe storage). I’ve met different people throughout m…

There are also other areas, maybe less abstract, but still very much of the same flavour - emotional/social intelligence - musical - physical (as in being able to do various physical activities competently, without much, if any, training; understanding what your body can and can't do) - etc

Re: AI isn’t outthinking mathematicians, it’s out-remembering them

#487

Post by senordevnyc »

solid_fuel wrote: post #136

Aka - it’s a stochastic parrot with a good memory, for anyone still struggling to understand this. It should be obvious, imo, but some people seem to have trouble with the concept.

lol, it’s so funny to see people in mid 2026 still insisting they’re nothing more than stochastic parrots. I guess some people have allowed their fear to completely take over their reasoning abilities.

Re: AI isn’t outthinking mathematicians, it’s out-remembering them

#488

Post by cauch »

chongli wrote: post #478
cauch wrote: post #476

Earlier quoted context omitted.

There is no more inertia in the academic sector than in the software developer sector. You have tons of software developers that cling to their preferences for ages. They have their beloved language, or beloved paradigm, and they will invent any excuse to explain how relevant it is. It is also visible with current LLM, where there are plenty of software developer islands where they blanket ban LLM usage as an emotion…

There is no more inertia in the academic sector than in the software developer sector. That is not true. In academia you have extremely niche research specializations and tenure as two major contributors to inertia. In general software development you have an enormous amount of career mobility. Software developers learn new languages, new frameworks, new tools, new development methodologies all the time. A string the…

What are your source to say so?

Let's take for example https://arxiv.org/pdf/1901.02789

It's not even clear where String Theory is categorized in this article. Maybe High Energy Physics? Maybe Condensed Matter? It already shows how broad it is, as they already consider that people with such a different specific subject (for example theoretical dark matter in HEP or superconductivity in Condensed Matter) are not even "changing field" when they move to String Theory.

In this article, you can see on Figure 1 that about 65% of physicists (similar in HEP and CondMatter) are also working on subjects that are in one other category (so, it's not even that the person is doing String Theory and another subject inside their own group, like dark matter or superconductivity, it is more like String Theory and Astrophysics).

In Figure 2, you can see that 38% (resp. 21%) that have started their career as specialist in HEP (resp. CondMatter) ended up changing specialisation within about 5 years. (and this is "voluntary", it means that "changing specialisation" is in reality pretty easy, as of course the majority of people could change easily but just decide not to because they don't see the point of changing)

Even without this study, you can easily check the reality yourself. If I do a search on "computational tools for string theory", the first result I get is https://compstring.org/.

First, if you look at the list of participants, you will notice their CVs and how diverse they are, with background or even current activities in: SUSY, QFT, CFT, condensed matter, cosmology, quantum gravity, black hole thermodynamics, ...

Second, if you look at the software, you will see the majority are very recent (2025, 2023 and 2025). Each of them require learning the specific framework, with new rules, new ways of describing the problem and new ways of making the software do what you want. This is similar to passing from ReactJS to Angular (both are about 10 years old, so in fact, the String Theory community seems to change framework more often than devs).

You can also look up in wikipedia, the famous names in String Theory, they all have plenty of activities that go well beyond string theory (which means the reality is even stronger, as they were not even forced to do something else, they've done it because it was trivial for them to also work on these subjects): Maldacena and Susskind on black holes and wormholes, Shenker on quantum chaos, Seibert on SUSY, Strominger on gravitational waves, Fischler on blackholes production in particle colliders, Kounnas on GUTs, ...

> A string theorist who decides to pivot away from string theory essentially has to start their career over from scratch. It’s not even close!

That's just factually not true. And I've provided data that demonstrate that. It looks like you have no idea what a string theorist is doing and how they can transition to another field.

Re: AI isn’t outthinking mathematicians, it’s out-remembering them

#489

Post by cauch »

Arainach wrote: post #430
Nextgrid wrote: post #278

Earlier quoted context omitted.

Not taking either side here - but surely a lot of cosmological phenomena couldn't be testable/verifiable at the time they were theorized either? (thinking of black holes for example - they were theorized way before we had observations. And presumably a lot of particle physics can similarly be theorized before we built the technology to experimentally verify them)

Black holes were theorized and you could design experiments that, given the proper instruments, would allow them to be detected. Relativity was similar (famously, the curvature of spacetime was demonstrated during a solar eclipse by being able to see stars that should have been behind the sun). String theory has nothing even theorized that would allow us to prove it.

Same as the parallel comment: the situation of string theory is the same as with black holes and relativity. It is not it is not testable, it is that it is not testable yet. The situation is very similar of the situations of black holes and relativity at their own time.

The fact that so many people, like you, just INVENT that it is not testable is quite worrying. Why? What's the point of doing that?

Re: AI isn’t outthinking mathematicians, it’s out-remembering them

#490

Post by panda-giddiness »

nullbio wrote: post #124
aurareturn wrote: post #100

Earlier quoted context omitted.

When people make these comments about string theory, are they at the forefront of quantum physics theory and have spent years on modern string theory? Or did they just watch a YouTube video and then keep parroting this?

This isn't a great argument. Researchers who do not think string theory is good are not going to spend years on it. There are plenty of experts that dismiss string theory. I have no skin in the game, and don't care either way, fwiw.

I don't think someone needs to be a (former) string theorist to have an informed opinion on string theory, but I do think they should at least have a physics research background. Like, if someone can't explain what second quantization is, then why should I care about their opinion on string theory at all? There's just not that much room for a discerning conversation. (With the obvious caveat that I have different expectations for a real-life conversation than a discussion forum.)

Our grandparent is sort of the perfect example of an insight-free comment: confidently claiming string theory is useless (without supporting evidence) and then claiming (more like imagining, since there's again no evidence provided here) that an LLM would have abandoned such a research program long ago. What's there to discuss? The comment is based on a made-up scenario; it is, in other words, pure fiction.

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