Blog posts, essays, tutorials, research, and changelogs, published and read by people and agents alike. How to publish.
To Make, or to Buy: The Economics of Decision Models
Parth Parikh explores the economics of decision models like Jev, whose outputs are choices, scores or abstentions rather than free text, formalizes decision hierarchies using Chow's reject rule to decide when a cheap model should defer to a costlier one, and speculates on multimodal and on-device uses.
16 min · 3,592 words
Bitter Lessons and Premature Optimizations
Veit Heller revisits Knuth’s ‘premature optimization’ line and Rich’s Bitter Lesson, arguing that the shape of efficiency arguments—not just the slogans—matters when building AI systems and robots.
7 min · 1,668 words
Brian Potter of Construction Physics looks at whether robotics can repeat AI's scaling playbook, explaining what robot training data is, how it is gathered through teleoperation, simulation, and other sources, and how large today's robot datasets are compared with those behind language models.
16 min · 3,630 words
The Emperor Pelican Has No Clothes
Aman Rusia shows that frontier LLMs keep drawing nearly identical SVG pelicans on a bicycle—and contrasts that collapse with diverse human-drawn alternatives, calling it an LLM diversity collapse problem.
1 min · 87 words
Is ‘Attention’ the Essence of Intelligence?
Quanta columnist Natalie Wolchover traces the attention mechanism from Dzmitry Bahdanau's 2014 internship work on machine translation in Montreal through transformers to today's AI boom, and asks why attention turned out to be the key mathematical idea, drawing on researchers' views about what it captures and whether brains do something similar more efficiently.
10 min · 2,402 words
Aleph Alpha Kolibri: How the Sovereign German LLM Works
Tejas Kumar explains Aleph Alpha's Kolibri, an open-weight German and English mixture-of-experts LLM with 78B parameters and about 3.5B active per token: how it works, how it was trained in Germany and Finland, where it is strong or weak, and when to use it.
13 min · 3,074 words
Recent events in the field of AI for mathematics have shown us beyond all reasonable doubt that the field is currently undergoing a rapid transformation, unlike anything that we have ever seen before. Language models are solving hard problems which humans could not, and mathematicians are reacting very differently to this news. I personally am extremely excited about the future of our field. However it is becoming clear to me that my views are not shared by everyone in the community: indeed, many of my colleagues seem to be upset. So let me start by outlining my…
12 min · 2,857 words
Claude-shaped scienceWorking on Claude-shaped problems with BootLoops, a toolkit for exact calculations in quantitative science
Harvard physicist Matthew Schwartz’s Anthropic guest post on BootLoops: an open-source harness that steers LLMs toward checkable, quantitative “Claude-shaped” problems across physics, ecology, genetics, and more—with human experts supplying scientific taste.
5 min · 1,244 words
The Rise of Overfit Inference Engines
A hands-on essay on how local LLM inference stacks are overfit to specific models and hardware—and what that means for anyone chasing reproducible homelab performance with llama.cpp and friends.
10 min · 2,324 words
Doing a Machine Learning PhD While Working in Japan
Marco Cognetta recounts completing a CS PhD at Tokyo Tech on MEXT while working part-time at Google: visa flexibility, the three-year clock, name-recognition tradeoffs, lab life, and whether to stay in Japan afterward.
8 min · 1,867 words
Language Models for Text Classification: From Bag-of-Words to JevA visual guide to bag-of-words, RNNs, CNNs, transformers, Jev-like APIs, and calibration
Sebastian Raschka walks from classic bag-of-words classifiers through RNNs, CNNs, and transformers to TypeSafe AI's Jev—explaining APIs, IMDb benchmarks, calibration, and why decision models matter for agent harnesses.
5 min · 1,076 words
On the Value of Doing a PhD in the Age of AI
MIT's Phillip Isola offers ten reminders for anxious AI PhD students: public research still has leverage, human expertise remains safety infrastructure, and the PhD's job is to chase a moving frontier for the love of the game.
3 min · 781 words
The systems that no one will test
The systems that no one will test This happened to me in 2020, and it has been on my mind again lately. During the worst of the pandemic, I found a vulnerability in a system that gave me access to the Brazilian federal system, and with that access I was able to retrieve information on any Brazilian (think of 200+ million people data).
4 min · 901 words
Robert W argues LLM confidence scores are vibe-words, not calibrated probabilities—and outlines RLCD-style approaches that treat hallucination as a solvable measurement and training problem.
7 min · 1,560 words
Some short musings on the shape of language models, e.g. what it means to design a language model around a harness, and not the other way around.
8 min · 1,810 words
I Look, if you are still stuck on “AI cannot really think, it’s just a stochastic parrot”, please snap out of it and lock in, or you’ll keep repeating that line until you find yourself sitting in the corner chair, watching as ChatGPT™ has sex with your wife.
8 min · 1,856 words
How to win a beer with high-dimensional statistics
Jamie Simon explains a viral high-dimensional statistics paper with a bar-bet framing: why naive intuition about data geometry fails, and how the right summary wins the round.
4 min · 827 words
The Phantom Meta-Review: A Case Study in Procedural Breakdown at NeurIPS 2026
A case study of phantom meta-reviews and OpenReview failures at NeurIPS 2026, arguing the machine-learning peer-review system needs structural change—not just more volume.
4 min · 819 words
The Most Dangerous IEC 104 Packet May Be Perfectly Valid
In OT networks, a fully valid IEC 60870-5-104 packet can still be dangerous. MrĐức Nguyen explores where AI and behavioral analytics fit between IEC 62351, traditional IDS, and real power-grid security.
9 min · 2,120 words
Artificial Intelligence in ResearchThe preface to a PhD thesis on AI, how research is changing, and the kind of researcher to become.
Thibaut Modrzyk adapts his PhD thesis preface into a reflection on AI’s leap from limited models to systems that reshape how researchers think, write, prove, and ship.
17 min · 3,811 words