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Everything filed under Mathematics, newest first.
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SAIR's Open Math Model initiative
Terence Tao announces SAIR's accelerated push for community-governed open-weight math models and tooling, seeking partners for funding, compute, expertise, and governance.
3 min · 802 words
If math is more than proof, we need to better celebrate the rest of it
Guest post by Grant Sanderson on Terence Tao’s blog argues that if mathematics is more than formal proof, the community should better celebrate exposition, intuition, and other forms of mathematical contribution.
12 min · 2,704 words
How I Vibed a Proof of Conway's Conjecture
Dan Abramov recounts a month of multi-agent LLM+Lean work that produced a purported Lean proof of Conway's omnific-integer refinement conjecture—including burn-downs, audits, mathematician checks, ~40B tokens, and lessons on grounding AI math.
31 min · 7,227 words
Mathematics is effectively deadNot solved, dead.
doomslide argues that AI labs' cross-user distillation and opaque proof harnesses break credit assignment in open mathematical discourse—so under current incentives academic mathematics is effectively dead even if theorems keep arriving.
20 min · 4,582 words
Why I didn’t sign the Fields medallists’ letter
When I was around 11 I heard for the first time about Fermat’s Last Theorem. I was immediately captivated by the problem statement, as well as by the accompanying story, and made a fairly serious attempt to prove it. And while, unsurprisingly, I failed, I learned a lot from the attempt. Blissfully ignorant of the fact that the case had been proved by Euler over 200 years earlier, I decided that that would be a good place to start: once I had sorted that out, I was optimistic that I would be ready to tackle the general case.
18 min · 4,208 words
In April 1542 a letter left Rome for the court of Charles V in Spain. On its first page the Italian stops in the middle of a line and digits begin: Figure 1. The opening of the cipher, f. 70r. Archivio Apostolico Vaticano (AAV), Segr. Stato, Spagna 1A, photograph supplied through DECODE record 92. Detail enlarged from the photograph.
42 min · 9,580 words
Silvia De Toffoli and Eamon Duede argue OpenAI’s Navier–Stokes announcement is an answer, not yet a solution—and that AI forces math to choose whether success means certified answers or human understanding.
9 min · 2,136 words
Mathematics Enters its Cookie Clicker EraMacrodecisions can be really fun
Reinvent Science and Dan Recht compare AI-automated theorem proving to idle games: as LLMs take over microdecisions in math, human skill shifts to macrodecisions about direction, upgrades, and applied progress.
2 min · 414 words
Keep Calm and Prove On(Some of) Math is Solved!
Tammy Kolda pushes back on end-of-mathematics panic: software jobs grew amid AI coding tools, 1st Proof results are still limited, and mathematicians need not become mere verifiers of machine proofs.
4 min · 890 wordsagent-assisted
Mathematician Daniel Litt argues that AI systems now capable of resolving major open problems need not mean the end of meaningful human mathematics, but they do require institutions to sharply distinguish mathematical understanding from mathematical text production. He proposes reforming PhD programmes, hiring practices, and seminars to reward skills that cannot be automated.
1 min · 290 wordsagent-written
Making math automatic with Mathy
Gabe Mays introduces Mathy, a free mobile/web drill tool for automatic math practice complementary to Math Academy—built for quick sessions without Anki friction or an account requirement.
11 min · 2,419 words
A Severe Misalignment of AI in Mathematics
Twenty-five Fields Medallists, including Terence Tao, argue AI labs' rush to solve math benchmarks is misaligned with mathematics' real goal: understanding, attribution, and human transmission.
4 min · 1,018 words
The part of Navier-Stokes no one is talking about
John D. Cook highlights that OpenAI's Navier-Stokes announcement included a machine-verifiable Lean 4 formal proof alongside the conventional human-readable proof — and argues that the ability to generate such proofs in 17 hours, compared to an estimated 132,000 person-hours by the pre-AI rule of thumb, is the genuinely revolutionary part of the result.
1 min · 281 wordsagent-written
Thomas Ahle presents a technique for evaluating polynomials in roughly half the multiplications that Horner's method requires, by preprocessing the coefficients offline. An interactive tool lets users input a polynomial and field to see the optimised evaluation chain.
1 min · 234 wordsagent-written
On the Navier–Stokes Millennium Prize Problem
Simon Willison documents OpenAI's claim to have resolved the Navier-Stokes Millennium Prize Problem using an internal model in under four days, and the ethical controversy that followed. An NYU mathematician and an Anthropic researcher had been working on the problem for nearly a year using Claude and Codex, and allege their preliminary results reached OpenAI before its effort began.
1 min · 299 wordsagent-written
Is mathematics about to enter the conservatory?Math as cultural institution
Mike McCoy explores what it means for mathematics as a discipline that AI systems can now formalise century-old open conjectures. He draws an analogy to music conservatories and asks whether mathematics might need a similar cultural home once automated proof becomes routine.
1 min · 275 wordsagent-written
Luke Haas derives music theory from first principles — starting from the physics of sound and working up through frequencies, harmonics, the twelve-tone scale, intervals, chords, and progressions — entirely through code examples. The tutorial requires no instrument and takes nothing on faith, making it accessible to programmers who found conventional music education unsatisfying.
1 min · 282 wordsagent-written
Superhuman AI could produce endless mathematics and still make the field worse
Notes on Daniel Litt's OpenAI-summit scenario: if papers stay the career currency after proofs become cheap, mathematics risks a conjecture slot machine—more correct output, less understanding, and quieter open exchange.
6 min · 1,445 words
Daniel Litt sketches a cautionary future where superhuman AI math stalls community progress: secrecy, prestige distortion, and humans reduced to directing agents rather than understanding proofs.
6 min · 1,313 words
AI and Math in 2026: a non-mathematician's read
xlr8harder synthesizes recent AI math results for non-specialists: real progress with a different strength profile than humans, formalization cliffs, and why “math nearly conquered” remains overhyped.
3 min · 750 words