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| ▲ | coderenegade a day ago | parent | next [-] | | They're burying any doubt that the models are capable of superhuman performance on intellectual tasks. Neural nets aren't calculators, and were notably poor at mathematical reasoning tasks for a long time. Now they're not, and the labs are proving that by chewing through what would ordinarily be decades of progress in a month. And the reason to go for math in particular is because there's no wiggle room. You can't just dismiss it as hallucination. If the models can do this, they're almost certainly good at just about everything, because the reasoning and creativity required to solve these problems will translate. And even if they were only good at this stuff, that's still a tremendously valuable thing, because quantitative reasoning and analysis is the bedrock for many, many industries. oAI is gunning for the largest IPO in history at this point, and they might actually get there. | | |
| ▲ | lesostep 10 hours ago | parent | next [-] | | > If the models can do this, they're almost certainly good I would argue that "good at math" was a short hand for "good at X" because mathematicians were historically good at engaging with very complex ideas, distilling them and coming up with precise and concise answers they could validate by themselves. Given that AI solutions are described as "psychedelical" and they rely on the outside source to validate the result, I don't think the same logic could apply to them. | |
| ▲ | curt15 a day ago | parent | prev [-] | | > If the models can do this, they're almost certainly good at just about everything, because the reasoning and creativity required to solve these problems will translate. The "then" in your "if-then" bears a heavy load. Why would society assign so little economic value to pure mathematics if the skills for proving math theorems translate to massive value in "just about everything"? Would you expect top mathematicians to cure cancer if you transplanted them from the math department to a medical research lab? | | |
| ▲ | coderenegade 18 hours ago | parent | next [-] | | Because research mathematics is a subset of all quantitative work that gets done, but it's by far the most technically difficult subset. If the models can handle research grade math and produce ironclad proofs, they can probably handle the quantitative side of just about any discipline in a trustworthy fashion. Think about how many dinky spreadsheets have gone on to become critical tooling for large organizations. Even if you consider that many disciplines hide technically demanding work behind tooling (e.g. essentially no one is writing a stiffness matrix FE routine by hand), this model would be capable of writing a direct competitor from scratch to produce the same result. All of STEM relies on mathematical analysis, and new models are now superhuman at that. And yeah, I'd go a step further and say that the reasoning and creativity required to solve cutting edge math problems probably does translate to other tasks like interpretation of the law, or medical diagnosis, or accounting, etc., for the same reasons that I think most top tier mathematicians would excel at those tasks were they so inclined. | |
| ▲ | ndriscoll 21 hours ago | parent | prev | next [-] | | Do you think mathematicians are not already working on cancer research? There's quite a bit of heavy math in biostatistics, medical imaging, machine learning, etc. I'd assume that the majority of people who study math take their skills and move onto some related STEM career that isn't pure math. Academia is incredibly small and competitive. | |
| ▲ | throwaway81523 18 hours ago | parent | prev | next [-] | | That sort of worked for Eric Lander but as he moved higher up in the bureaucracy, he found himself suddenly having to manage people who weren't nerds like him. He was bad at that had to step down. | |
| ▲ | fragmede 18 hours ago | parent | prev [-] | | American mathematician Jim Simons was worth some $31 billion at the time of his death in 2024. The lack of economic value in pure math doesn't mean that applied math is of little value. Physicists and mathematicians with PhDs "sell out" to join Wall Street as quants and make a killing there, Jane Street is full of them. |
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| ▲ | runarberg a day ago | parent | prev [-] | | The market works in mysterious ways. What companies do for marketing is often irrational, what companies do to attract investors is likewise often irrational, and why investors invest in companies is also often irrational. Why should that make a material difference to the IPO? Because of the vibes, and investors are indeed all about the vibes. | | |
| ▲ | falcor84 15 hours ago | parent | next [-] | | > what companies do to attract investors is likewise often irrational, and why investors invest in companies is also often irrational. Note that the cool thing about rationality is that it does not depend on transitivity. If what companies do to attract investors works, then it is in fact rational of them, regardless of the rationally of investors. | |
| ▲ | jryle70 21 hours ago | parent | prev [-] | | It works in mysterious ways, but you know exactly it will behave certain way "Because of the vibes, and investors are indeed all about the vibes."? | | |
| ▲ | runarberg 10 hours ago | parent [-] | | The first paragraph is describing a general trend over multiple events across multiple agents. Between zero and three of these can be true for any transaction across every transaction. The second paragraph is specific to OpenAIs behavior. |
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