The US is winning the AI race where it matters most: commercialization
Energy matters for AI, but the decisive layers are cloud infrastructure, data, and commercialization. On those layers the United States is ahead by a wide margin.
Energy matters for AI, but the decisive layers are cloud infrastructure, data, and commercialization. On those layers the United States is ahead by a wide margin.
The LISP curse is often quoted as the reason why so few libraries and reusable components exist for LISP dialects. According to the concept, LISP is so power...
OpenAI's GPT-6 Astra reaches state-of-the-art results on ARC-AGI-3
Sharing progress on a powerful type of cryptographic proof known as a zkSNARK, which is uniquely fit for provable inference.
We don’t need an extra reason to be anxious
Server deployment, parallel requests with continuous batching, new REST API endpoint, and refreshed application UI
A new analysis from OpenAI reveals issues in SWE-Bench Pro, a popular coding benchmark, raising concerns about reliability and accuracy in evaluating AI models.
Plus Fly’s new Sprites.dev addresses both developer sandboxes and API sandboxes at the same time
Exactly one year ago, Sam Altman made a bold prediction: “We believe that, in 2025, we may see the first AI agents ‘join the workforce’ ... Read more
AI can make implementation cheap while making review and judgment more expensive.
Karpathy's autoresearch runs one experiment at a time. We gave it access to our GPU infra and let it run experiments in parallel.
The balance of software copyright protection and openness has always been fraught with minutiae and detail that bores all but the most nerdy of pedants. Yet, through much effort and 40 years of debate we had reached an equilibrium. Now AI has thrown that out the window.
If you liked this piece, please subscribe to my premium newsletter. It’s $70 a year, or $7 a month, and in return you get a weekly newsletter that’s usually anywhere from 5,000 to 18,000 words, including vast, detailed analyses of NVIDIA, Anthropic and OpenAI’s finances,
The new era of tech seems to be built on superstitious behaviour
For thirty years I programmed with Phish on, every day. In 2026, the music is out of phase with the work.
In this post we look under the hood of BrightData's SDK and how it turns ordinary consumer TVs into exit nodes of an enormous commercial, residential proxy network leveraged by the AI industry to scrape web data and train language learning models.
Discover Gemini 4 Argon for robotics: leading the ERQA benchmark with physical reasoning, zero-shot control, Real2Sim, and agentic workflows.
How a community devoted to thinking clearly incubated salvation stories, abusive experiments, race science, and an affection for autocracy, and why that history matters now that its alumni are asking for public trust on AI.
Starting today, Claude Cowork and chat are one Claude, rolling out on Pro, Max, and Ultra plans. Hand over the task and Claude does the work. You keep the final say.
Reporting on 2B tokens of AI usage and what shapes model selection and cost
By Dr. Rachel Simmons, Postdoctoral Fellow, Stanford University
By Nihar B. Shah
Learn about Project Suncatcher, how we’re testing hardware survival for space, designing cooling systems for AI chips, and more.
The Cambridge Programme on AI Science & Policy (CASP) is an interdisciplinary research programme on frontier AI at the University of Cambridge.
Results and speed for other programs on enwik8 and enwik9 are available at the Large Text Compression Benchmark .
Four and a half years ago, Modular made a bet: AI would not run on one kind of silicon forever, and the software stack would need to be rearchitected for a world of heterogeneous hardware and increasingly complex AI workloads.
We gave our AI agent a SQL interface to billions of CI log lines in ClickHouse. How we ingest, store, and query 1.5 billion log lines a week.
A sampling of recent news