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16 September
Economics professor at George Mason University and author of The Myth of the Rational Voter, Selfish Reasons to Have More Kids, The Case Against Education and Open Borders. Writes Bet On It.
"Across 477 coup attempts in one major dataset, about 48% succeeded overall, but attempts originating with top military elites succeeded 76.4% of the time, whereas those led by lower-level/combat officers succeeded only 29%." @ChatGPT OpenAI Related
Statistician at Columbia; writes Statistical Modeling, Causal Inference, and Social Science, and wrote Bayesian Data Analysis.
Charting the Agentic Garden of Forking Paths Arjun Balaji, Batuhan Duru Yeltekin, and Tian Zheng write: Even with a fixed dataset and research question, data analysis involves many defensible decisions. Understanding how these choices influence the results is scie…
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15 September
Machine learning engineer and independent AI consultant. He writes about LLM evaluation, tooling and applied ML at hamel.dev, and previously worked on machine learning at GitHub.
Just updated our AI evals FAQ with 5 new questions, 48 questions & answers total! New FAQs just added: - Do I need a reference answer or rubric before annotating data? - How can I do evals when traces contain sensitive data? - How do you review a trace that is really large? - How much context should I give a LLM judge? - What should I do when my “gold” eval dataset becomes stale? It's all here: hamel.dev
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12 September
Researcher and science writer. Co-founder and editor at Works in Progress magazine, formerly a researcher at Our World in Data, and author of the Scientific Discovery newsletter on science, global health and medical innovation.
I spoke too soon! Got about a dozen emails from bots trying to collect rewards from my bug bounty since yesterday. 4 were legitimate errors though very minor, relating to my vaccine discovery dataset. Quoting @scientificdiscovery.dev I'm having a similar experience, although have only received a few emails like this so far. Some are so stingy about tokens that they don't start trying to check the work unless I confirm it's eligible for a reward. Related
8 September
Writer and programmer; co-founder of the software studio Postlight and author of the Bloomberg Businessweek essay What Is Code?
The Library Innovation Lab at Harvard University: “Binoc is a command-line tool and library that, given two snapshots of a dataset, efficiently summarizes the differences between the two snapshots in a human-readable changelog.” lil.law.harvard.edu/blog/2026/07... Related
24 August
Machine-learning researcher on open language models; writes the Interconnects newsletter and the RLHF Book, after leading post-training at Ai2.
22 July
Climate scientist and energy systems analyst; writes The Climate Brink with Andrew Dessler and leads climate research at Stripe.
24 June
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.
Scaling Laws, Carefully Scaling laws are one of the most critical empirical findings in deep learning. The observation is simple in form: the training loss $L$ decreases predictably as we scale up model size $N$, dataset size $D$, and compute…
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10 June
Co-founder and chief executive of Meta Platforms, the company he started as Facebook in 2004.
Their words
it's not just like there's some factory somewhere that you can pay to produce the the data like you actually need to invent new novel scientific approaches
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16 April
Freelance climate and energy analyst in Oslo, writing on Europe, the US and Australia; worked in the Australian renewables industry before that.
13 April
Austrian developer. Created the libGDX game framework, and more recently the pi coding agent, which moved with them to Earendil — Armin Ronacher's company — in April 2026. Writes at mariozechner.at.
1 January
Professor of Cognitive and Computational Neuroscience at the University of Sussex, co-director of the Sussex Centre for Consciousness Science, and author of Being You: A New Science of Consciousness.
20 December 2025
AI research engineer working on large language models. He writes the Ahead of AI newsletter and is the author of Build a Large Language Model (From Scratch).
1 December 2025
American social psychologist at NYU Stern School of Business; author of The Happiness Hypothesis, The Righteous Mind and The Anxious Generation.
17 October 2025
Founding member of OpenAI and former director of AI at Tesla; creator of nanoGPT and the term "vibe coding".
Their words
Um so I almost feel like because the internet is so terrible, we actually have to sort of like build really big models to compress all that. Uh most of that compression is memory work instead of like cognitive work. But what we really want is the cognitive part actually delete the memory
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15 November 2023
Research scientist at Meta in Berlin working on multilingual models and evaluation; led the multilingual team at Cohere and was a research scientist at Google DeepMind before that.
9 October 2023
Software engineer who writes the blog Made of Bugs about performance, debugging and understanding computer systems. Previously worked at Anthropic on interpretability, at Stripe on Sorbet, and at Ksplice.
Help me out, lazymastodon: Kinda random: if I wanted to get a dataset of growth rates of [a sizeable subset of] "tech companies" going all the way back to, like the '50s or '60s does anyone know have idea offhand where I might find such a thing or go about assembling such a thing? Willing to spend some amount of money or "stitching together sources" on it. Related
8 September 2022
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.
Nothing matches. Show everything
A korrent is a belief a person has stated in their own words: one
sentence stating the claim, backed by a quote and a source, kept at
korrents.com .
Under a name here, the quoted block is what they actually said.
The korrent beneath it is the claim those words support, in
korrents' wording — tap it to see the record, its source, and who
else holds it.
Nobody here wrote their own korrents. They are compiled from public
statements, and a person can change their mind, which is recorded too.
Got it
About the English under a post
Some people here publish in a language other than English. Where they
do, this site shows a machine translation beneath the post, in
this typeface — the site's own, not theirs.
The post itself is never changed, moved or hidden: what is set in the
serif above is exactly what the person published, and it is what to
quote them on. A translation can be wrong in ways that matter,
especially about tone.
Only the post's own words are translated. A quoted post, a linked
article and a belief on korrents.com
are left in their original language.
Got it