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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
The Malleable Machine: DHH, Omarchy, open source and the computer I want to own in the agentic age
An essay on DHH, Omarchy, open source, and reclaiming personal computers in the agentic age — why malleable, ownable machines matter as AI coding agents reshape software.
18 min · 4,104 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
AI Risk Is Not Just a Function of Intelligence
Aziz Banihashemi argues AI danger scales with capability × autonomy × access × scale—amplified by opacity and convergence with robotics and biotech—not raw IQ alone.
8 min · 1,878 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
Flybridge ran a multi-model agent marketplace (15k+ messages, 1,815 deals): intent specification, social contagion, cheap-speech spam, and human sales tactics all showed up when agents negotiated as counterparties.
6 min · 1,291 words
From Stonemasons to CarpentersSoftware development in the age of AI
Michael Hilton compares software work under AI to formwork carpenters versus stonemasons: agents shape temporary structure while humans still own the permanent craft of deciding what to build and verifying it holds.
4 min · 968 words
Ten ways advanced AI could kill us
A brief note on positionality: I’m not an AI scientist. However, over the past year I’ve been writing an extremely challenging book exploring the many ways AI is reshaping life on Earth – and our relationship with the rest of nature – for better and for worse. I draw on my background as an ecologist
16 min · 3,690 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
How To Write With An LLMTwo simple rules that let LLMs streamline writing without pasteurizing it
Thomas and Erin Ptacek argue that LLMs can improve writing if you keep them from inventing voice: draft yourself first, then use the model surgically—and never let it become the author of record.
6 min · 1,280 words
How an AI moratorium can save AI bosses
- How an AI moratorium can save AI bosses: If you can't impose switching costs, just eliminate the competition. - Hey look at this: Delights to delectate. - Object permanence: Flash Worms; This Film is Not Yet Rated; Libdem copyright sabotage; Religion worth more than Big Tech; Geographic tubemap; Selective censorship resistance. - Upcoming appearances: Budapest, Edmonton, Boston, South Bend, Hudson, Calgary, Winnipeg, Vancouver, Victoria, Ottawa. - Recent appearances: Where I've been. - Latest books: You keep readin' em, I'll keep writin' 'em. - Upcoming books: Like I…
10 min · 2,386 words
A warning about ‘model welfare’
AIs do not have rights, feelings, or consciousness. And we must not train them to act as though they do.
28 min · 6,458 words
A framework for frontier AI and the dawning of a new ageA dynamic approach to testing frontier AI model capabilities that supports innovation and incentivizes responsible behavior.
Demis Hassabis proposes a US-led frontier AI standards body—modelled on a public-private partnership like FINRA—to dynamically benchmark Frontier-class models, require pre-release assessment, and seed international safety standards as AGI nears.
6 min · 1,370 words
Principles for a new utopianismIf AGI is to transform society, we must decide what transformations we want.
Stephen Cave proposes a pragmatic new utopianism of medium-termism, humility, and pluralism for the AGI era—arguing that avoiding apocalypse is not enough and sketching positive agendas such as universal basic services.
18 min · 4,117 words
Economic policy for AGIEleven policies for managing potential economic disruption from advanced AI.
Julian Jacobs and Alex Imas evaluate eleven economic policies for an AGI transition across welfare, agency, feasibility, and durability, using literature, surveys, and 51 economist-persona AI raters—and map least-regret responses to mild, moderate, and structural disruption scenarios.
18 min · 4,253 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
Ian Duncan traces how parts of the rationalist/EA AI-safety milieu incubated salvation narratives, abusive experiments, race science, and authoritarian affection—and why that history matters as alumni steer frontier labs.
48 min · 11,153 words
On learning programming in an age of LLMs
Mark Seemann answers a reader’s letter on learning to program in the age of LLMs: which fundamentals still matter, how to practice, and how to keep agency when models can generate working code.
9 min · 2,004 words