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.

> 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.

Terrence Tao can't decide to keep the money and pay himself more or something though. He _has_ to spend it

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.

You can't use mathematics without understanding it?

Let's say GPT-23 Astra grinds away for a full month one day and out pops a warp drive. Our best physicists ask it to explain. The resulting stream of text is essentially incomprehensible. But, they build a scale model at its direction to test and sure enough it does the Kessel run in 12 parsecs.

Are you saying we shouldn't hop aboard the USS Enterprise and check out Alpha Centauri because we don't understand the math?

I think what's really happening here is that there's an ivory-tower academic class that feels entitled to make their living at public expense thinking about and writing about their topic of interest, and along comes a new tool that's changing that dynamic up. Meanwhile, in the real world, the value remains with people who can take whatever the tool of the day is and do useful things with it. Which, I think, is why despite all the talk the only professional job losses blamed on AI appear to largely be companies that had a failed strategy of some sort or another and used AI as a boogeyman to do the layoff that they needed to do anyway. To people living in the private sector this isn't seen as a dangerous invader, LLM's are productivity multipliers.

That seems wrong unless you have an unusual definition of "understanding":

* Lots of people use math for calculations without having proven any theorems.

* You can understand a mathematical statement without understanding or even having a proof. There are proofs built on the axiom of choice and conjectured results.

I think you can understand* math in general. I think not understanding something it's a matter of presentation. Also I think the presentation can be improved. A good-quality AI can do both, hence it can get a presentation that you can understand.

Yet this has zero utility (other than your own satisfaction). Once you understand something, you will likely not even do a better job at explaining it to someone else, so the utility is strictly limited to yourself.

So even ignoring ability to understand the problem is the cost/efficiency of understanding (and applying it).

I agree with your other statements, but I feel you're suggesting the non-sense is scoped to just math. It's not it's almost everything that we do (exceptions are social interactions including care taking, etc.)

So in this frame your "nonsense" is (almost) everything that we do. Personally I'd like to keep doing things.

Yeah, the tangibility of benefits really need to be felt, especially for the so called "deplorables" who would like to swing for a politician that can demonstrate that they will get them housing, healthcare, prosperity in their communities. High paying jobs across the educational ladder and in rural areas also wouldn't hurt.

The yet compressing into now is the definition of singularity. I'd argue that it's "only of limited use" if you don't understand the problem well enough - so yes, it's limited for predicting anything for most people but that doesn't make it an irrelevant aspect at predicting in general.

That why our ancestors repurposed their pitchforks. History is marked by a drive towards inequality, punctuated by bouts of war and revolution that trigger a reset.

This is the society capitalists want tho, they don't care about the wellbeing of humans they just care about profit.

Once the citizens are made obsolete, there is no need for healthcare, housing, or (human) infrastructure. Just electricity, cooling water, and Internet connectivity.

Obsolete citizens don’t need healthcare, housing or infrastructure. They will just die of hunger and exposure and then the rich and powerful can frolic unencumbered in paradise.

We are miles away from that.

Math proofs are right in the sweet spot for training LLMs with RLVR. It isn't some general "LLMs are getting insanely smart!". Even most software development itself is miles away from being as well suited to training as math proofs are.

The majority of math research is akin to professional chess. Completely useless and the folks doing it are using their giant brains to play a game that no one outside themselves benefits from.