Every time a new open-weight AI model is released, people say that local models are the future. Why spend billions of dollars building out datacenters when everyone will just be able to run AI models on their laptops or phones? I think this idea is doomed. No matter how strong open-weight models get, most inference will always happen in AI datacenters.
AI GPUs probably live longer than three years
People who think current AI use is unsustainable often rely on the claim that inference GPUs only last “three years at the most” under load1. The idea here is that once the AI bubble money drains away, current infrastructure will rapidly become obsolete, and there won’t be enough money floating around to buy a whole slate of brand-new GPUs. Inference costs would thus rapidly become way too expensive for current AI products to make any financial sense.
OpenAI ‘in early talks to give 5% stake to US government’
CEO Sam Altman argued move would share benefits of AI and it would involve other firms doing similar, report says
co/core — an AI cooperative
co/core is a cooperative for AI inference — people pooling the Macs they already own to run open models for each other, instead of renting from the big clouds. An experiment in AI infrastructure we build, share, and own together. Bring your existing OpenAI-compatible code, or share a Mac and help run it.
Import AI 446: Nuclear LLMs; China's big AI benchmark; measurement and AI policy
Will AIs be jealous of one another?
Dark Cloud Gathers as Bill Comes Due for AI Industry
AI companies are finding they can no longer sustain footing the bill of their heavily vibe coding customers.
Something Big Is Happening
A personal note for non-tech friends and family on what AI is starting to change.
AI demands more engineering discipline. Not less
If you lived through the shift from handcrafted server pets to immutable infrastructure, you should sense something oddly familiar about what's happening now.
The Arguments Against Open Source AI are Very Bad | Tom Bedor's Blog
The release of Kimi K3 has opened a fresh round of angst and confused discourse. There's a loud cohort of journalists, business leaders, and politicians arguing that open source AI is a dangerous threat. OpenAI's Dean Ball:
Running local models is good now
Local agentic coding has gotten great over the past few months
How StrongDM’s AI team build serious software without even looking at the code
Last week I hinted at a demo I had seen from a team implementing what Dan Shapiro called the Dark Factory level of AI adoption, where no human even looks …
✨🙌 AI that helps communities thrive on their own terms
Open protocols + AI-enabled coding = building what we need for ourselves
Coasts — Containerized Hosts for AI Agents
Free, open source parallel runtimes for AI agents. Run multiple isolated environments on your machine — no cloud, no conflicts.
The machines are fine. I'm worried about us.
On AI agents, grunt work, and the part of science that isn't replaceable.
Training AI models doesn't emit that much
If we just make reasonable comparisons instead of crazy ones
The AI Industry Has a Major Problem: Most People Aren’t Freaks Who Want an AI Agent Running Their Whole Life
There's a problem for AI agents like Meta's Muse: ordinary people don't seem very interested in what they're offering.
Andrew Ng: The Biggest Opportunities in AI Aren't Where You Think