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Comment by schrototo

4 days ago

But it's not like those guys will just pocket that money. They will use it like all academic grant money is used: to hire PhD students and postdocs.

> The foundation will manage and award the funding, including through an open call for proposals, to support workshops and initiatives that help researchers evaluate recent AI-assisted results, learn and use new tools, share perspectives and shape collective standards for AI use.

A non-zero amount of it is probably going directly to the AI companies through tokens...

  • Why not use some of the money to develop open-weight, open-training-pipeline, fully introspectable and hackable LLM-based theorem proving assistants? Make them a commodity in every mathematician's office like other computational tools. Such a project would itself yield research topics.

    • I do seeing this becoming a trend more and more. A lot of open models are fairly strong and fine-tuning and other post-training techniques could easily make bespoke domain-specific inference considerably cheaper (in token usage and energy consumption) and allow for more data sovereignty.

  • > A non-zero amount of it is probably going directly to the AI companies through tokens...

    Much the same way that VC money has been funnelled to Google and Meta through advertising budgets.

  • Isn’t the very pitch ai bros have to their investors: “we’ll replace ppl by tokens.”

    If it doesn’t pay for non-permanent staff salary that would be sad for the maths ppl indeed.

    OTOH I have a phd in th physics, 15+ y of academic senior researcher experience, now working 60+ h /w on an unpaid internship and using lunch money to pay for tokens.

    And I’m by far not most unlucky

    Edit: just to put things in perspective, my phd field (string theory) has 15-30M€ annual funding in Europe (per google)

  • While the contributing AI companies certainly have a lingering conflict of interest, the relevant point is the effort find a constructive way to live with the reality of AI?

    Mathematicians are in the same boat as Silicon Valley programmers in the end: AI is doing their job better than them and cheaper. Other professions will join shortly.

    The question then becomes, what do humans do? Resigning to die quietly is hardly the most favorable option?

    Just because somebody else can do something better than you ever could doesn't make doing it superfluous. There is more to mathematics and software engineering than finding proofs and algorithms.

    • "Better than them" is just barely in the realm where it's not incredible to discuss, and still quite debatable.

      Cheaper than them? That's dramatically unproven and unlikely just on power efficiency alone, even if we accept the suspect assumption the only efficiency anyone should care about is currency marked per line of code or theorem proved.

      We're not just going to have to become better existential philosophers, we're going to have to become better examiners of assumptions and claims.

> to hire PhD students and postdocs

Why? I thought we already established* that most professional mathematicians are not necessary (in the near future, then maybe "any"), so why would they doom these students with pity grants to basically create unnecessary jobs for them? More practically, wouldn't that money be best served (i.e., raw ROI) by purchasing more tokens on the frontier models?

(*) The existence of this effort itself is a good heuristic.

  • Do you consider yourself to be necessary? Like, for mankind? Probably not: you're just one of eight billion nearly-identical people, and if you vanish off the surface of the planet, the economic loss will be basically zero. Heck, if you're of retirement age, you're probably a net burden for the society.

    But that doesn't sound like a good argument to ride off into the sunset, right? You probably enjoy living and it does make a difference in the lives of some close friends and relatives?

    We don't organize societies around ruthless efficiency optimization, we organize them to be at least somewhat hospitable to humans and human enterprise.