A weekend at the Curve conference—an AI insider gathering in Berkeley revealed how people think about AGI timelines, China, creativity, and writing
Notes from inside China's AI labs
Lessons from my trip to talk to most of the leading AI labs in China.
No. 021: AI peer review ensembles, Riemann zeta bound, VibeMathed registry - The Hallway Track
The Hallway Track No. 021 - How AI is affecting the practice of science
More Than a Tool
What We Learned from a Year of Conversations About AI
The Era of Experience & The Age of Design: Richard S. Sutton, Upper Bound 2025
The Scaling Era: An Oral History of AI, 2019–2025
An inside view of the AI revolution, from the people an…
My Thoughts on AI, Part 1: Fears, Opinions, and Mental Journey
My own personal thoughts and opinions on AI effects and usage, and how those have evolved over time
What the hell happened with AGI timelines in 2026?
Is there something it is like to be an AI?
Posted on Wednesday 2 Jul 2025. 1,593 words, 6 links. By Matt Webb.
Large AI models are cultural and social technologies
Implications draw on the history of transformative information systems from the past , Debates about artificial intelligence (AI) tend to revolve around whether large models are intelligent, autonomous agents. Some AI researchers and commentators speculate that we are on the cusp of creating agents with artificial general intelligence (AGI), a prospect anticipated with both elation and anxiety. There have also been extensive conversations about cultural and social consequences of large models, orbiting around two foci: immediate effects of these systems as they are currently used, and hypothetical futures when these systems turn into AGI agents—perhaps even superintelligent AGI agents. But this discourse about large models as intelligent agents is fundamentally misconceived. Combining ideas from social and behavioral sciences with computer science can help us to understand AI systems more accurately. Large models should not be viewed primarily as intelligent agents but as a new kind of cultural and social technology, allowing humans to take advantage of information other humans have accumulated.
No. 026: AI use in science study, astronomy disclosure gap, Paper2Agent, SAIR initiative - The Hallway Track
The Hallway Track No. 026 - How AI is affecting the practice of science
AI Isn't as Powerful as We Think | Hannah Fry
The only reason you’ll ever need not to write with AI — The Carlson Lab
Over the last year, our lab has been developing a policy on AI use. To do this, we did three main things: We read a lot of academic publications and tech news. We set up an #ai channel on our lab Slack to share news, experiences, and memes. We had several long and grueling lab meetings talk
AI Index | Stanford HAI
The mission of the AI Index is to provide unbiased, rigorously vetted, and globally sourced data for policymakers, researchers, journalists, executives, and the general public to develop a deeper understanding of the complex field of AI. To achieve this, we track, collate, distill, and visualize dat
“The task that generative A.I. has been most successful at is lowering our expectations, both of the things we read and of ourselves when we write anything for others to read.” — Ted Chiang
Why A.I. Isn’t Going to Make Art
www.newyorker.com