From my experience, you have to be good at math to trust an LLM to do the math.
This is why laypeople have not used Ai to make math breakthroughs . it has all been ppl with lots of knowledge already.
What sort of maths are LLMs good at?
101–110 of 189 posts
Re: What sort of maths are LLMs good at?
#102Earlier quoted context omitted.
You can easily test this yourself with the SOTA models....or read the corroborating literature... "General365: Benchmarking General Reasoning in Large Language Models Across Diverse and Challenging Tasks" https://arxiv.org/abs/2604.11778 "...General365, a benchmark specifically designed to assess general reasoning in LLMs. By restricting background knowledge to a K-12 level, General365 explicitly decouples reasoning…
What proportion of the human population could answer the example from that paper? Question: Strangers A, B, C, D, and E line up from youngest on the left to oldest on the right. Their clothing colors and shoe colors all differ, and they come from five different regions. Known facts: 1. A is from Morocco. 2. D is five years older than B. 3. E is older than A. 4. C stands next to D. 5. A stands next to B. 6. The person…
No offense to you, but we had to do these kind of exercises in grade school on days when a sub was in. You'd get together in a group and work through the logic puzzle on a structured form (i.e., it let you represent what you know about the person wearing green shoes, or the person from Morocco, etc.)
Re: What sort of maths are LLMs good at?
#103Earlier quoted context omitted.
for somebody who's out of the loop: what's the fuss over the ABC conjecture?
This is a reference to Inter-Universal Teichmüller Theory. Its Wikipedia article gives a good overview ( https://en.wikipedia.org/wiki/Inter-universal_Teichm%C3%BCll... ). In maths lasting disagreements over a published "proof" are rare, but IUTT is an example of it. What the article misses: There is a more recent, ongoing effort to formalize the published proof in Lean under the name of "LANA" (e.g. see https://zen.…
> Peter Scholze and Jakob Stix pointed out 8 years ago
Interesting read!
https://ncatlab.org/nlab/files/why_abc_is_still_a_conjecture...
Re: What sort of maths are LLMs good at?
#104> If they were, then their big speed advantage over us would mean that there would be much more of a flood of results. Is this true right now? Just recently Jarred Sumner tweeted [1] that he managed to make some progress on the Riemann hypothesis while on a jog. Managed to get somewhere by encouraging the llm to “keep going” and “believe in yourself”. This raised a few questions for me. Had no one at Anthropic though…
The result in [1] is not progress on the Riemann Hypothesis. It's another fine result, but it's not progress on the Riemann Hypothesis. You could prove 100% of zeros are on the line and it wouldn't show the Riemann Hypothesis. 100% of natural numbers are composite in this same asymptotic density sense, and yet that doesn't prove that all natural numbers are composite.
Re: What sort of maths are LLMs good at?
#105Earlier quoted context omitted.
Would you trust a bridge built by a single human? In reality, we have lots of guardrails to ensure that we don't screw up and kill a lot of people by deploying defective bridges (or cars to drive on them). Those guardrails often are written in blood, and still occasionally fail.
Why not have AGI check other AGI? Peer review by fellow humans is what gives humans assurance, to the degree in which review was done by peers of equal or greater intelligence. AGI checking other AGI should give you that same trust, no? Deepseek says my ChatGPT bridge is stable, you should trust it. Claude says it's stable. The humans say it isn't, but they aren't AGI. You can trust this bridge because it's been vett…
One step further, our current generative AI is not discrete. “AGI checking other AGI” doesn’t really make technical sense. Currently, every interaction between two generative AI units is treated as agglomerative. We talk about “Claude”, not the 70 subagents that Claude spun up to achieve a task.
In other words, as soon as two generative AIs interact, they become one. Our current definition of AI (generative AI operating in feedback loops) is dependent on that.
Edit: this is somewhat an epiphany to me. Our current generation of “AI” isn’t an “entity”, it’s a “process”. I guess it’s hard to define formally, but I would compare it to how law and the pursuit of justice is a process, not an entity.
And I think that’s a fundamental limitation to achieving artificial general intelligence.
Re: What sort of maths are LLMs good at?
#106Earlier quoted context omitted.
Based on the rest of your writing I’m going to assume that the prompt was the problem.
Keep deluding yourself, unless you work for an LLM provider... "Frontier LLMs Still Struggle with Simple Reasoning Tasks" https://arxiv.org/abs/2507.07313 "General365: Benchmarking General Reasoning in Large Language Models Across Diverse and Challenging Tasks" https://arxiv.org/abs/2604.11778 "...General365, a benchmark specifically designed to assess general reasoning in LLMs. By restricting background knowledge to…
Keep deluding yourself, unless you work for an LLM provider
You're clearly operating in bad faith, but just for the record: the General365 problems are very difficult as you can see from the examples at https://arxiv.org/html/2604.11778v1#A1. It's actually impressive that Gemini 3 Pro got 62%, and the strongest OpenAI and Anthropic models they tried were GPT-5.1 and Sonnet 4.5.
Re: What sort of maths are LLMs good at?
#107Since no one has mentioned it yet - just want to point out that Timothy Gowers is a Fields medalist.
That means the post was good, even though the blurry math images are illegible. But yes, as a Fields medalist he is an expert on LLMs.
> But yes, as a Fields medalist he is an expert on LLMs.
Not what I was claiming, but since you are, feel free to expand on this.
Re: What sort of maths are LLMs good at?
#108Re: What sort of maths are LLMs good at?
#109Earlier quoted context omitted.
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> You get better at modeling the trajectory because the neurons physically move closer together as you learn I think "modeling the trajectory" is not necessarily what we are doing either. It's more likely we are using much simpler heuristics. If you are trying to catch a ball flying through the air, you can just look at the ball and modulate your running speed to keep your eyes at a fixed angle until you catch the ba…
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Re: What sort of maths are LLMs good at?
#110It seems intuitive that finding a counter-example might be easier than proving a generality, since you're starting from a concrete goal ("build a foo that has properties X, Y & Z") that you can branch out from, identify sub-problems, etc. Proving a generality seems much more difficult since you don't know what you are trying to build, although I suppose in some cases you can prove it by proving that it's impossible t…
One hesitation I have with this idea is that proofs themselves can be modeled as mathematical objects. So if you have a machine which can construct examples then we just view the proof as an example, and it should be good at constructing them.
Maybe this is naive.