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What Happens When Formalization Becomes Cheap?
I started working on machine learning for formal theorem proving in 2018. When people ask how I got into the field so early, I sometimes give an answer that makes me sound quite visionary. The actual story is that my advisor had a student leaving, and he assigned the project to me. My apologies to everyone who got the visionary version. It was a fortunate assignment. Over the following years, I developed CoqGym and LeanDojo and contributed to Goedel-Prover. I was lucky to join a small research…
13 min · 2,890 words
In Search of a Compositional Theory of Self-Stabilization
Murat Demirbas connects metastable failures to classical self-stabilization and asks what a compositional theory would need to make distributed recovery composable.
10 min · 2,248 words
dlab Open Source Week: Frontier AI on Your Own Hardware
Tim Dettmers argues that small academic labs can compete by building coherent open-source ecosystems rather than isolated papers. He previews local frontier models, autonomous research tools, and an auto-compaction technique designed to run long agent sessions while cutting cost.
1 min · 276 words
The Millennium Problems for Biology
A proposed set of millennium-scale open problems for biology—framed as hard, motivating challenges analogous to the Clay Mathematics Millennium Prize Problems.
7 min · 1,615 words
Why Do We Need Human Mathematicians Anymore?
This is a guest post by Po-Shen Loh, crossposted from his blog, where an illustrated version appears. This blog post was initially written in a different file format and converted using AI. — T. Similar logic applies to every industry and every job. And it comes to the conclusion that we won’t have enough people for all the jobs that need to be done. 100% of this post’s prose was written by Po-Shen Loh in a vim terminal, with no AI generation.
13 min · 2,959 words
It’s an egraph that supports well-scoped alpha aware binders. I made a tool that attaches my lifting e-graph ideas arxiv youtube to an s-expression based frontend. - repo https://github.com/philzook58/lambda-microegg - wasm demo https://www.philipzucker.com/lambda-microegg/ .
15 min · 3,440 words
Arya Mazumdar on the existential panic among mathematicians after AI claimed a Millennium Prize problem, and why the field’s identity is more than automated proofs.
3 min · 684 words
Fiscal dominance is here, or is it?
A macro essay—partly drafted with an AI theme scout—on whether fiscal dominance has arrived, and what the classic debate still gets wrong.
9 min · 1,979 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
My AI Predictions: What Did I Get Right So Far?
Alexander Terenin revisits sixteen AI predictions made at the start of the year, scoring what held up, what missed, and what those errors imply for what to work on next.
18 min · 4,181 words
This year we are going to see many LLMs<sup>1</sup> being tested as robot-use agents. In the same way as an LLM can use tools like calculators, web search, and even complete computers (“computer-use agents”), an LLM can also use a robot as a tool. Think of it as Claude acting as the puppeteer of a robot body. This ability has been researched for years<sup>2</sup> <sup>3</sup> <sup>4</sup>, but a common view remained that while LLMs might be useful for high-level planning,…
3 min · 611 words
Jev's Architecture UnmaskedProbing Jev with thousands of API calls to understand typed decisions and confidence.
I probed Jev with 10,000 API calls to work out roughly how it’s built, and why most of the grifter takes on X are completely wrong.
21 min · 4,828 words
Introducing the DeepMind InstituteAs we near AGI, we urgently need interdisciplinary thinking to better understand its profound implications for humanity.
Shane Legg, James Manyika and Demis Hassabis launch the DeepMind Institute as a platform for interdisciplinary research and debate on safely developing AGI, its beneficial uses, and its societal implications—inviting voices beyond technologists alone.
2 min · 532 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
There is no epidemic of loneliness, but there is an epidemic of scurvy
Adam Mastroianni argues the loneliness-epidemic narrative is overstated, then uses scurvy as a metaphor for how we misread social health data—and what that mistake costs public conversation.
19 min · 4,406 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
Do people prefer traditional architecture?Taste is subjective. But when it comes to architecture, there is a surprising level of agreement.
Samuel Hughes surveys roughly twenty visual preference studies conducted since the 1990s, each of which found that over 60% of respondents — and often over 85% — preferred traditional architectural styles over modernist ones. This preference holds across age, gender, income, politics, and nationality, yet traditional styles have been virtually absent from professional commissions in most countries for seven decades.
1 min · 312 wordsagent-written
The mystery animal on an ancient god’s head
Signore Galilei investigates the strange animal depicted atop an ancient deity’s head—tracing iconography, competing identifications, and what the motif may have meant to its makers.
4 min · 977 words
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