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18 September
Writer of kottke.org, one of the oldest blogs on the web, published since 1998 and supported by its members. He writes about art, technology, science, design and visual culture.
15 September
Artist and developer who makes esoteric software, games and tools aboard a sailboat as part of Hundred Rabbits with Rekka Bellum; creator of the Uxn virtual machine and the Orca livecoding environment.
I've been scratching my head trying to think how to package assets for my #lispGameJam project, I really REALLY wanted to be able to inline assets as raw hex code, like I normally do for uxn projects, not have to read binary files, so I added a special form with square brackets that lets me to just that! This is the first sprite(a little arrow) I was able to store in my source code. Related
13 September
Computer science professor who works on fast data processing; co-author of the simdjson parser and a weekly blogger about software performance since 2004.
I think that AI is helping us in ways that will only become clear in several years, as it is helping clarify knowledge, science and philosophy. In other words, I believe that it may usher in a new intellectual golden age, but not necessarily directly (by what “it” finds). Rather, it may force a reshaping of the current social hierarchies. Many people who have reigned over academia for decades are finding themselves on the defensive. Meanwhile, other models are slowly being valorized. If I am correct, we are in for quite a fight. It will get vicious. What I find interesting with OpenAI breakin… OpenAI Related
10 September
Creator of the Keras deep-learning library and the ARC-AGI benchmark.
"Symbolic learning" is simply "machine learning" (automatically learn function x -> y given examples of (x, y) pairs), but where the substrate is symbolic, i.e. the functions you learn are code-like, not curve-like. The term is in opposition to "parametric learning" or "curve-fitting". Symbolic learning does not mean that the system avoids numbers or probabilities. It means its learned representation are discrete, explicit, parsimonious, code-like. Related
4 September
Author of Shape Up; formerly head of strategy at Basecamp, where he worked on product design for seventeen years; now runs Felt Presence.
A friend turned me on to asking Fable to wireframe different options when I have a tricky UI problem with a lot of requirements and too many possible paths. Game changing. Gives me flashbacks to what @bmoesta taught me about using orthogonal arrays when an engineering problem has too many variables. It's not about one-shotting the answer. It's about getting enough contrast between options to clarify which variables (aka "factors") are most important. Not which solution is best -- which variables matter more. THEN I can use that knowledge to decide to fix certain variables and narrow the space… Related
2 September
Mathematical physicist at UC Riverside. Wrote This Week's Finds in Mathematical Physics and now the Azimuth blog on mathematics, physics and environmental science.
While you have 46 chromosomes, certain ferns carry huge numbers - the record is 1,400! Their genomes can be gigantic too: a little fern called Tmesipteris oblanceolata packs about 160 billion base pairs of DNA into each cell, the largest genome ever found in any living thing on Earth. People call these ferns 'chromosome hoarders'. But why all the hoarding? One classic idea from 1966 blames the ferns' sex lives. Many ferns can fertilize themselves. A single spore grows into a plant called a gametophyte that makes both egg and sperm. The egg from one plant can be fertilized by the sperm of anot… biorxiv.org
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21 August
Writer and climate campaigner; wrote The End of Nature in 1989, founded 350.org and Third Act, and writes The Crucial Years.
1 July
Self-taught home cook and food writer who has run the Smitten Kitchen recipe site since 2006; author of four cookbooks.
8 May
Geneticist at Harvard; reads ancient DNA to work out how populations moved and mixed, and wrote Who We Are and How We Got Here.
Their words
there's as populations become more apart, there begins to be biological incompatibilities rapidly developing, probably as the square of the distance separation, because you need pairs of interacting genes, and therefore it's the square of the separation.
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7 April
Software design writer and chief scientist at Thoughtworks; wrote Refactoring and Patterns of Enterprise Application Architecture.
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My bet is on the more effective two pizza teams. Um and it it's also some interesting, you know, feedback we're beginning to get in terms of pair programming. I mean, with pair programming, do you say pair programming is the human and the genie? Or is it two humans and and genies? Because if it's two of us, we can control the genies perhaps a little bit better.
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21 December 2025
Economist; Professor of the Practice of Economic Policy at Harvard, nonresident senior fellow at the Peterson Institute, and Chairman of the US Council of Economic Advisers from 2013 to 2017.
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This book manages to pull all of that together in a way that's genuinely readable and engaging, helped along by anecdotes from his own policymaking experience that both clarify the arguments and make them feel concrete and accessible to a much broader audience.
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fivebooks.com
4 May 2025
Mathematician and maker of the 3Blue1Brown YouTube channel, which explains mathematics through animation. Creator of the open-source Manim animation library and founder of the Summer of Math Exposition.
Bluesky In the most recent video about quantum computing, I saw many comments expressing a similar point of confusion regarding Grover's algorithm. I made a follow-up to (hopefully) clarify some of the issues and to address a few other under-emphasized points. youtu.be
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x.com In the most recent video about quantum computing, I saw many comments expressing a very similar point of confusion regarding Grover's algorithm. I made a follow-up to (hopefully) clarify some of the issues, which doubles as an excuse to talk a bit more about the central role of linearity in quantum computing. youtu.be
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17 April 2025
Member of technical staff at Anthropic. He has led ML/AI teams at Amazon, Alibaba and Lazada, and writes about LLMs, recommender systems and engineering at eugeneyan.com.
Had a session with very senior folks on how they build with AI and can’t help thinking there’s no better time to learn, clarify, brainstorm, write, debate, plan, design, code, debug, review, analyze, delegate, play, and in general do more more while doing less with AI—so psyched! Related
12 April 2024
Machine-learning researcher; has written the Lil'Log survey posts on how a model technique works since 2017, and worked at OpenAI from 2018 to 2024, latterly leading its safety systems team.
31 May 2021
Machine-learning researcher; has written the Lil'Log survey posts on how a model technique works since 2017, and worked at OpenAI from 2018 to 2024, latterly leading its safety systems team.
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