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I've always said this but AI will win a fields medal before being able to manage a McDonald's. Math seems difficult to us because it's like using a hammer (the
by vatsachak 7mo ago
I've always said this but AI will win a fields medal before being able to manage a McDonald's.
Math seems difficult to us because it's like using a hammer (the brain) to twist in a screw (math).
LLMs are discovering a lot of new math because they are great at low depth high breadth situations.
I predict that in the future people will ditch LLMs in favor of AlphaGo style RL done on Lean syntax trees. These should be able to think on much larger timescales.
Any professional mathematician will tell you that their arsenal is ~ 10 tricks. If we can codify those tricks as latent vectors it's GG
- smokel 7mo agoI think this is mostly about existing legislature, not about technology. In any other context than when your paycheck depends on it, you would probably not be following orders from a random manager. If your paycheck depended on following the instructions of an AI robot, the world might start to look pretty scary real soon.
- vatsachak 7mo agoThere's a lot to being a manager - Coherent customer interaction - Common sense judgements - Scheduling - Quality control All which are baked into humans but not so much into LLMs Even if it were legal to have an LLM as a GM, I think it would fair poorly
- throw3747488 7mo agoAI actually has to follow all rules, even the bad rules. Like when autonomous car drives super carefully. Imagine mcdonald management would enforce dog related rules. No more filthy muppets! If dog harasses customers, AI would call cops, and sue for restraining order! If dog defecates in middle of restaurant, everything would get desinfected, not just smeared with towels! Nutters would crucify AI management!
- jfim 7mo ago> If your paycheck depended on following the instructions of an AI robot, the world might start to look pretty scary real soon. That's already the case, minus AI, for gig workers. Their only agency is to accept or decline a ride/delivery, the rest is follow instructions.
- vatsachak 7mo agoTricks are nothing but patterns in the logical formulae we reduce. Ergo these are latent vectors in our brain. We use analogies like geometry in order to use Algebraic Geometry to solve problems in Number Theory. An AI trained on Lean Syntax trees might develop it's own weird versions of intuition that might actually properly contain ours. If this sounds far fetched, look at Chess. I wonder if anyone has dug into StockFish using mechanistic interpretability
- slopinthebag 7mo agoStockfish's power comes from mostly search, and the ML techniques it uses are mainly about better search, i.e. pruning branches more efficiently.
- vatsachak 7mo agoThe weights must still have some understanding of the chess board. Though there is always the chance that it makes no sense to us
- slopinthebag 7mo agoEven that is probably too much. It has no understanding of what "chess" is, or what a chess board is, or even what a game is. And yet it crushes every human with ease. It's pretty nuts haha.
- anematode 7mo agoActually, the neural net itself is fairly imprecise. Search is required for it to achieve good play. Here's an example of me beating Stockfish 18 at depth 1: https://lichess.org/XmITiqmi https://lichess.org/XmITiqmi
- Sopel 7mo agochess is just a simple mathematical construct so that's not surprising
- 7mo ago
- slopinthebag 7mo ago> AI will win a fields medal before being able to manage a McDonald's Of course, because it takes multi-modal intelligence to manage a McDonalds. I.e. it requires human intelligence. > I predict that in the future people will ditch LLMs in favor of AlphaGo style RL Same for coding as well. LLM's might be the interface we use with other forms of AI though.
- vatsachak 7mo agoSomething like building Linux is more akin to managing a McDonald's than it is to a 10 page technical proof in Algebraic Groups. Programming is more multimodal than math. Something like performance engineering might be free lunch though
- slopinthebag 7mo agoYeah, it's hard to compare management and programming but they're both multimodal in very different ways. But there's gonna be entire domains in which AI dominates much like stockfish, but stockfish isn't managing franchises and there is no reason to expect that anytime soon. I feel like something people miss when they talk about intelligence is that humans have incredible breadth. This is really what differentiates us from artificial forms of intelligence as well as other animals. Plus we have agency, the ability to learn, the ability to critically think, from first principles, etc.
- vatsachak 7mo agoExactly. It's what the execs are missing. Also animals thrive in underspecified environments, while AIs like very specific environments. Math is the most specified field there is lol
- slopinthebag 7mo agoOooh yeah that's really good framing. Humans have been building machines that outperform humans for hundreds of years at this point, but all in problems which are extremely well specified. It's not surprising LLM's are also great in these well specified domains. One difference between intelligence and artificial intelligence is that humans can thrive with extremely limited training data, whereas AI requires a massive amount of it. I think if anybody is worried about being replaced by AI, they should look at maximising their economic utility in areas which are not well specified.
- NamlchakKhandro 7mo agoI've never seen you say that
- vatsachak 7mo agoYou will have to take my word that I started saying this in Dec 2024 lol
- madrox 7mo ago> I've always said this but AI will win a fields medal before being able to manage a McDonald's. I love this and have a corollary saying: the last job to be automated will be QA. This wave of technology has triggered more discussion about the types of knowledge work that exist than any other, and I think we will be sharper for it.
- bitwize 7mo agoThe ownership class will be sharper. They will know how to exploit capital and turn it into more capital with vastly increased efficiency. Everybody else will be hosed.
- DoctorOetker 7mo agobut what if we succeed in gamifying the latent knowledge in LLM's to upload it to our human brains, by some kind of speed / reaction game?
- madrox 7mo agoI'm not sure if people will be more hosed than before. Historically, what makes people with capital able to turn things into more capital is its ability to buy someone's time and labor. Knowledge labor is becoming cheaper, easier, and more accessible. That changes the calculus for what is valuable, but not the mechanisms.
- tmoertel 7mo ago> Historically, what makes people with capital able to turn things into more capital is its ability to buy someone's time and labor. You forgot to include resources: What makes people with capital able to turn things into more capital is their ability to buy labor and resources. If people with more capital can generate capital faster than people with less capital, then (unless they are constrained, for example, by law or conscious) the people with the most capital will eventually own effectively all scarce resources, such as land. And that's likely to be a problem for everyone else.
- ryanar 7mo agoAre they actually producing new math? In the most recent ACM issue there was an article about testing AI against a math bench that was privately built by mathematicians, and what they found is that even though AI can solve some problems, it never truly has come up with something novel and new in mathematics, it is just good at drawing connections between existing research and putting a spin on it.
- hodgehog11 7mo agoIt's finding constructions and counterexamples. That's different from finding new proof techniques, but still extremely useful, and still gives way to novel findings.
- in-silico 7mo agoI'm not accusing you in particular, but I feel like there's a lot of circular reasoning around this point. Something like: AI can't discover "new math" -> AI discovers something -> since it was discovered by AI it must not be "new math" -> AI can't discover "new math" For example, there was a recent post here about GPT-5.4 (and later some other models) solving a FrontierMath open problem: https://news.ycombinator.com/item?id=47497757 https://news.ycombinator.com/item?id=47497757 That would definitely be considered "new math" if a human did it, but since it was AI people aren't so sure.
- parineum 7mo agoThere is a kind of rubrik I use on stuff like this. If LLMs are discovering new math, why have I only read one or two articles where it's happening? Wouldn't it be happening with regularity? The most obvious example of this thinking is, if LLMs are replacing developers, why us open ai still hiring?
- specvsimpl 7mo agoI can only say that at family meetings, I hear people talk about contracting with a shop that used to have 4 web designers, but now it's 1 guy, delivering 4x faster than before. So devs are being replaced.
- hodgehog11 7mo agoAs a professional mathematician, I would say that a good proof requires a very good representation of the problem, and then pulling out the tricks. The latter part is easy to get operating using LLMs, they can do it already. It's the former part that still needs humans, and I'm perfectly fine with that.
- threethirtytwo 7mo agoBut are you ok with the trendline of ai improvement? The speed of improvement indicates humans will only get further and further removed from the loop. I see posts like your all the time comforting themselves that humans still matter, and every-time people like you are describing a human owning an ever shrinking section of the problem space.
- tartoran 7mo agoHumans needing to ask new question due to curiosity push the boundaries further, find new directions, ways or motivations to explore, maybe invent new spaces to explore. LLMs are just tools that people use. When people are no longer needed AI serves no purpose at all.
- threethirtytwo 7mo agoWho said LLMs can’t push boundaries either? People can use other people as tools. An LLM being a tool does not preclude it from replacing people. Ultimately it’s a volume problem. You need at least one person to initialize the LLM. But after that, in theory, a future LLM can replace all people with the exception of the person who initializes the LLM.
- tossandthrow 7mo agoThe initialization problem is solved - maybe the next Nobel price will be given to a Mac mini.
- hodgehog11 7mo ago
- 3abiton 7mo agoIt will be heavily still reliant onexpert human input and interactions. Knuth is an expert, and know how to guide.
- kelseyfrog 7mo agoAs of now, no models have solved a Millennium Prize Problem[1]. 1. https://mppbench.com/ https://mppbench.com/
- deleted 7mo ago[deleted]
- Yoric 7mo ago> I predict that in the future people will ditch LLMs in favor of AlphaGo style RL done on Lean syntax trees. These should be able to think on much larger timescales. This is certainly my hope. In my spare time, I'm slowly, very slowly, inching towards a prototype of something that could work like that.
- pfdietz 7mo ago> Any professional mathematician will tell you that their arsenal is ~ 10 tricks. If we can codify those tricks as latent vectors it's GG And if we can train the systems to discover new tricks, whoa Nelly.