It would be nice to have more mathematicians, but we don't need more. Once AI math goes so far beyond human abilities, any human involvement is like an ant trying to understand quantum physics

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dgacmu 5 hours ago | parent | next [-]

We've been those ants for a million years, and only in the last 100 did we start to wrap our heads around quantum physics. We are the purpose behind creating LLMs. There's plenty in the universe we don't understand, and it's very human to keep striving to do so.

If you believe that math is discovering, it's natural to think that all of that AI math already exists and is just waiting for us to find ways to discover and understand it.

Don't write us out quite yet. :)

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aesbetic 3 hours ago | parent | prev | next [-]

I think a better analogy would be comparing to an ancient human instead of an ant. An ancient human would have none of the basic abstractions that we take for granted today like literacy and arithmetic, so it would be very difficult for them to even attempt trying to understand quantum mechanics. But I don't think it's impossible because our ability to learn by stacking abstractions is basically endless——so far as our health permits at least.

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jahbrewski 6 hours ago | parent | prev | next [-]

Even if that happens, what’s the point if there’s no human involvement? AI doing math for math’s sake? And doing what with it?

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tappingdance 2 hours ago | parent | next [-]

I think it is like saying what is the point of playing chess when you can never beat stockfish?

What is Magnus Carlsen going to do when he can't beat the computer?

It seems like a category error between humans using tools and humans building tools.

There is not much point in trying to figure out a better chess engine. There has never been a better time though to want to learn chess.

I find the idea that the computer will discover mathematics and humans call it a day rather ridiculous. As if humans will not then spend their time understanding and incorporating the ideas from the computer.

Alphafold is a better example. Alphafold is only bad if you spent your life trying to solve protein folding. But even if you did, that is the same person who is the most setup to reap the benefits of the unlock in the pragmatic application of protein folding.

We don't figure out how to get machines to harvest corn and then spend all day sitting around eating corn in between naps.

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itishappy 5 hours ago | parent | prev | next [-]

> AI doing math for math’s sake? And doing what with it?

Stuff! Inscrutable stuff, maybe, but that's not "doing math for math's sake."

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rudy6912 6 hours ago | parent | prev | next [-]

> AI doing math for math's sake?

Yes, why not? And, of course, AI doing math for AI.

We may not be needed forever...

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alex_sf 6 hours ago | parent | prev [-]

I don't understand how to make a modern CPU. I'm not involved in the manufacturing of it. From my perspective, there may as well not be any human involvement. I can still use the resulting chip (in an larger system of other things I can't make and wasn't involved in) to argue with you on the internet.

It becomes another abstraction, really. As long as we can use it for something useful, it's still valuable.

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awepofiwaop 6 hours ago | parent | next [-]

At some level of abstraction it's all built around allowing you to do some work/play/etc that you understand. Some of that work allows you to make money and eat food.

If the LLM is operating at such a high level that it never actually constructs a useful product for humans to use, then how will that be good for humanity?

	▲	itishappy 5 hours ago \| parent [-]
		> If the LLM is operating at such a high level that it never actually constructs a useful product for humans to use, then how will that be good for humanity? If you replace "LLM" with "mathematician" than this is the state of the world today. Stuff like Galois theory is beautiful mathematically, but what has it constructed or enabled for you and me?

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altmanaltman 5 hours ago | parent | prev [-]

There is a difference between manufacturing and design. Yes manufacturing is largely done by machines because of the nature involved but to look at a cpu and think 'no human was involved in creating this', you're wrong and also insulting to the humans who actually worked on things that led to the cpu and the manufacturing process.

A cpu (the physical thing that sits in your mother) is not an abstraction, what are you talking about

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joshmoody24 4 hours ago | parent | prev | next [-]

Or maybe ants and humans are qualitatively different. Maybe there's a critical mass of intelligence where you can pretty much understand anything, and maybe humans are past that threshold. I don't know that for sure, but I don't think we're anywhere close to hitting fundamental limits to our ability to understand the universe.

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6 hours ago | parent | prev | next [-]

[deleted]

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gaigalas 6 hours ago | parent | prev | next [-]

Need? We don't need lots of things, including computers. We did well without them for hundreds of thousands of years.

We want to understand. Quantum physics, mathematics, how stuff works. Ants don't.

That want is not a given, not all of us have that drive. In fact, very few of us have it. So far though, it seems multiple disconnected civilizations learned to keep that trait going instead of suppressing it and focusing only on practical ant-like activities.

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rvz 6 hours ago | parent | prev [-]

> Once AI math goes so far beyond human abilities, any human involvement is like an ant trying to understand quantum physics

This makes no sense whatsoever.

We need more, because there will always be far more difficult problems yet to be discovered and solved, and that means, we certainly need expert humans to define and verify them.

If you cannot even explain the problem you are facing, not only you don't understand it, but you certainly would not be able to know if the AI solved your problem correctly.

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WarmWash 6 hours ago | parent [-]

>and that means we need expert humans to define and verify them.

And this will be true for how long? 3-4 months?

	▲	rvz 6 hours ago \| parent [-]
		As long as there are problems to discover and solve, which is forever. The risk of liability is a social problem that is far more difficult to be solved with technical solutions even with AI.