catalog
Library
Cards and collections from my Semble library. Pages saved for later, grouped into shelves I return to. 780 cards, 25 shelfves.
Shelves
25 collections- Collection 575 cards
Skyreader Saves
- Collection 2 cards
toread
- Collection 1 card
To process
- Collection 2 cards
Building with agents
- Collection 3 cards
Protocol thinking
- Collection 4 cards
Cybernetics
- Collection 1 card
Cryptocurrency
It's bad
- Collection 2 cards
Thinking about thinking
- Collection 2 cards
ATproto development
Tools and resources for building on atproto
- Collection 19 cards
Cool Atmosphere apps
- Collection 9 cards
Internet sensemaking
- Collection 5 cards
The structure of social media
- Collection 9 cards
Books I've been reading
- Collection 3 cards
Tools for thought
- Collection 1 card
Cool tools
- Collection 2 cards
Awesome terminal
- Collection 8 cards
Local first
- Collection 5 cards
Tech right analysis
- Collection 9 cards
Security?
- Collection 1 card
Tech and Law
- Collection 105 cards
the AI of it all
- Collection 5 cards
understanding events
- Collection 1 card
vc stuff
- Collection 12 cards
development
- Collection 19 cards
atproto stuff
Recently filed
page 23 / 33-
Mathematics in the Library of Babel
Mathematics isn't only about saying true things. It's about asking the right questions, being confused, stumbling about, getting distracted, being wrong, recognizing when you're wrong, being stuck. Mostly being stuck. It's about clinging to a giant edifice and feeling it out until you understand some tiny piece of it. It's about finding meaning in and intuition for the texture of an object which, at first, can only be apprehended by bashing your skull into it until it imprints on your forehead. Then trying to convey some of that insight to someone else, and watching as they find their own way to it. I started trying to get LLMs to do math in July 2020, through the game "AI Dungeon," one of the earliest applications powered by GPT-3. I first got GPT-3 to produce a correct proof (of Fermat's Little Theorem) in April 2022. At the time I did not think they would become useful for math research in the near term. This changed when the first reasoning models were released: on February 1, 2025, I wrote that the model o3-mini-high “clearly has passed the threshold of genuine usefulness” for research, while still making many, many mistakes. Since then, the models have improved, and ChatGPT 5.2 Pro (released in December 2025) can regularly provide reasonable proofs of lemmas that I would characterize as “involved but routine for experts,” though it still makes many errors. And I have been using Codex, OpenAI's coding/computer use agent, for scientific computing tasks I would not have considered attempting a few months ago. In public comments, I've tried to credit successes while pushing back against hype. I've talked a lot about "slop" papers on arXiv. I have worried that we are polluting the scientific commons with incorrect mathematics whose errors are enormously difficult to detect. I've tried to focus on the present. In this essay I'll talk about the future.
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How will OpenAI compete?
OpenAI has some big questions. It doesn’t have unique tech. It has a big user base, but with limited engagement and stickiness and no network effect. The incumbents have matched the tech and are leveraging their product and distribution. And a lot of the value and leverage will come from new experiences that haven’t been invented yet, and it can’t invent all of those itself. What’s the plan?
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The Median Voter Theorem is a Clarity Trap
What the Democratic party needs - what it demands - is bold, persistent experimentation
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Ultima IX
This article tells part of the story of the Ultima series. Years ago, [Origin Systems] released Strike Commander, a high-concept flight sim that, while very entertaining from a purely theoretical point of view, was so resource-demanding that no one in the country actually owned a machine that could play it. Later, in Ultima VIII, the […]
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A.I. Isn't People
How many Reddit posts does it take to learn to read?