New paper with Josh Lam, about which I'm really excited! I want to try to briefly explain what the point is in this thread.

“If AI continues to bulldoze pure math, it’s going to crush the hopes of the young people who were dreaming of joining this tradition.”

With all due respect, AI ain’t bulldozing anything. This is an unnecessarily apocalyptic way to describe what is happening.

And as for crushing hopes, I suspect these apocalyptic narratives are doing more hope crushing than a collection of PDFs idly sitting in a repository.

It’s some mathematicians’ pride that got crushed.

Other mathematicians are simply engaging: reading, understanding, explaining, experimenting, developing new ideas, writing papers, and, yes, advancing mathematics.

Of course, our profession needs to adapt many of its practices and habits, and quickly. But unless the most pessimistic voices in mathematics, the math Cassandras so to say, eventually convince the world to defund mathematics, there will be jobs, because there will be a great deal to do.

What, exactly, is the proof of forced Navier–Stokes useful for until the ideas in it are extracted from the Lean proof and its confused, sloppy, natural-language translation, and integrated into scientific discourse?

A mathematical proof does not automatically become part of our mathematical understanding simply by existing. Someone has to understand it, explain it, connect it to what we already know, and determine what else can be done with its ideas. This is not a secondary activity that mathematicians perform after the real work has been done. It is a fundamental part of how mathematics advances. And it remains central to science, unless the plan is to delegate our entire intellectual life to machines and go live like brutes, mindlessly spending our (very hypothetical) universal basic incomes.

One further point: people are only focusing on LLM-generated proofs, but how many papers will humans write without using an LLM, simply in response to the new ideas and perspectives that enter the field? It is not even clear to me that the best results will necessarily come from LLMs.

Mathematicians have changed science in small and large ways, over and over again, through fifteen-page papers built around a single lateral insight or a powerful vision. Why should that stop now?

There will be a lot of work to do: Why should young mathematicians see this as the end of their intellectual ambitions?

The ongoing apocalypse is psychological rather than technological, and it is not being imposed on us by frontier labs. It’s more into how some of us have decided to think about this. I totally understand the initial emotional reaction, but maybe it’s time to move on.

Let’s get back to work. Advance mathematics, improve math education, demonstrate why our work deserves support. That is how we secure our future.

Young people will adapt faster than we do, and soon enough they will be leading the way.

just solved the trolley problem

Thanks to Daniel Litt from
@UofT for being a part of this year's #BottLectureSeries! He spoke about "The arithmetic of differential equations" and "Non-abelian motives" to an eager audience of mathematicians at Harvard's Science Center/Zimmer Hall.
#harvardmath

Gauss had a personal seal(!) emblazoned with the motto “Pauca sed Matura” ("Few, but Ripe"). Worth remembering as quantity becomes cheaper.

If someone asks you to write a reco letter and you plan to do it with AI, you should disclose it to them first.

It can come across as very lazy and low-effort and will harm the candidate.

If you want your people to succeed, don't do this.

some of you seem not to believe we want humans in the loop except as recipients of vertical video

my toddler just asked me to draw her a picture, and then when I was done she hanged it on the fridge

honestly it felt great

@hassanrahim they're trying to cut open the bird to find the song

Cope harder. Oh wait, AI will cope for you, better than you ever could.

they’re going to automate you. AI will do your job. it’ll be better than you at everything. when you want to smell a flower it’ll smell for you, better than you ever could. it’ll be the flower too.

I’m excited to announce that I will be working at the Mathematical AI Safety Institute (MAISI) full-time as its founding Scientific Director! This means I will not be joining OpenAI as an employee, though I will still be collaborating with them, and I’m happy to announce that OpenAI will be supporting MAISI. They have offered us $10MM in API credits, and access to their latest models for our research use. Moreover, they will be participating in a multi-lab AI safety workshop we are organizing for next year with other frontier AI labs.

As an independent research institute, we are also in conversations with other labs and AI safety orgs about how MAISI can collaborate with them and contribute quickly to AI safety research across the industry. As we’ve seen over the past few weeks, the need for action on AI safety is extremely urgent. Research is an important part of that, and mathematicians have an important role to play!

To the extent that mathematics is getting mogged by AI goodharting, it’s because mathematics goodharted itself into this position by rewarding the solving of conjectures over understanding, exposition, and pretty much everything else.

Q: how should we think about the OpenAI 372 math problem solutions?

A: research mathematics is an abelian sandpile exhibiting self-organized criticality. The OpenAI drop triggered a collapse to sub-criticality.

Q: WTF???

A: explanation here: blog.danromik.com/the-abelian-sa…

really sad how the invention of the telescope made astronomers obsolete

first proof third batch results are out! full report here: hexagonmath.org/2610.00244

The ideal outcome for science isn't a couple of labs using proprietary models and millions of dollars to crack trophy problems, it's to have millions of AI-aided human scientists who follow their curiosity and become way more ambitious

The academic hiring practices are changing fast and from what I have been hearing from folks @ Oxford, Cambridge, ETHZ, and NUS the weight of publication record will be far less in measuring competence;
"understanding" is now the rare commodity. Great!

@SchopenhauerOn Mathematicians have a wide range of opinions, and the reactions/letters making most of the news may give an incomplete and inaccurate picture of how mathematicians are actually reacting.