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Comment Re:Why? (Score 1) 149

Yeah, there's two main problems:

1) People entering the wrong fields. For example, medicine really needs workers, at all levels, but not enough people are going into it.

2) Certain manual labour fields, like field work and home construction, because... well, I think we all know why there's a shortage of workers in those fields.

Comment Re: That's stucking fupid. (Score 1) 231

Most US population centers are in places east of the point in their time zones where the sun is overhead (or due south) at noon, and being a bit west is better than being a bit (or very, for New England) east. This means that DST is mostly the right UTC offset for the wrong reason: Boston should be on Atlantic Standard Time year-round, but Eastern Daylight Time is a name for the same clock setting that is already used there sometimes, so that's easier to legislate. Of course, the people who live west of their true noon line don't think permanent DST would be good, but the fact that we should have no DST and a different map is too nuanced for the position that there's got to be a single simple answer as to how to fix everything, regardless of the situation.

Comment Ha. Old hat... (Score 1) 82

More than 35 years ago, well before the Internet, BBSes ruled.

One I was a pillar of was nothing but a wall where you would post anonymously (or not).
The software was written to verify the typing rate to make sure that no text was uploaded

CHALLENGE ACCEPTED!

I wrote a special terminal program that would randomize the time between characters to foil that BBS's rejection of uploads...

(Oh, it worked, and the dude running the show never found out).

Comment Re:LLM output is Grey Goo and Ecophagy. (Score 2) 149

Or let's put this another way. Show of hands - how many of you "spicy autocorrect" / "stochastic parrot" people had "AI will start mass-solving Erdos problems" on your forecast list a couple years back? Huh, none of you? Fascinating!

Take some time to reassess your priors. And while you do so, understand that, yes, they are doing logic / reasoning.

Comment Re:LLM output is Grey Goo and Ecophagy. (Score 4, Interesting) 149

They weren't discovered by an LLM. They were known conjectures that were proven by an automated solving language that was linked to an LLM.

I'll take "Things That Didn't Happen For $200", Alex.

Only a handful of meaningful proofs have ever been done by automated formal theorem solvers (the Four Colour Theorem being the most noteworthy example - but its proof is so long that humans can't verify it). By contrast, AI tools have been solving Erdos problems en masse. The majority of them just bog-standard commercial models. In case you need help, the only ones on that list that were hybrid (AI / non-AI) in the actual solving phase are:

1) AlphaProof / DeepMind Prover Agent / AlphaProof Nexus
2) Aristotle (Harmonic)
3) Seed Prover / Seed Prover 1.5 (ByteDance)
4) AxiomProver (Axiom Math)

In each of the above, LLMs come up with the lemmas / strategies but then use Monte Carlo search ("brute force") or likewise to investigate what they came up with. These are a minority. In the "AI Standalone" category, these "hybrid" tools made up only ~20% of attempts and successful proofs. Hybrid tools actually made more of a contribution in the "AI Alongside Literature" (related literature found afterward) and even more of the "AI Building On Literature" (related literature known beforehand) categories, which is the opposite of what people like you expect.

And even with the hybrid tools, it's still the AI doing the heavy lifting when it comes to strategy. Non-AI theorem solvers, again, don't have a spectacular record for churning out novel proofs to unsolved problems. Tools like Lean are more about mathematical rigour - a passive environment that requires a driver (a human or AI) to feed it actual strategies, lemmas, and proof steps. And no, you cannot brute force "strategy" in the vast majority of cases, which is, again, why automated theorem solvers don't have much of a track record with unsolved mathematical problems.

Let's take a random example: the disproof of the unit distance conjecture. It was solved purely by a general purpose commercial GPT model, not custom-trained to mathematics, with no external tools. Read what the various mathematicians reviewing / commenting on it have to say (sections #3 and onward). Seriously, don't skip reading them, actually read them. This was one of Erdos's favourite problems. He mentioned it commonly in his lectures. Essentially every mathematician working in complex geometry has thought about this problem. The approach that the model came up with was highly novel approach, based on CM-fields and class field towers.

I know you don't want to accept this reality, but it is the reality, so you better improve your ability to accept it,. The field of mathematics is already doing so.

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