Tag: Artificial Intelligence

Shazeer to openai, then John Jumper (the alphaFold nobel guy) to anthropic, plus Adler and Pritzler out the same door within a week. Every time one of these drops the framing is google is bleeding. I think people are reading it backwards. If the people who actually trained the thing can leave and instantly matter at a competitor, the weights were never the asset. The judgment about how to steer a model, what to eval it on, where it breaks, that stuff lives in heads not in checkpoints. Hardware you can buy. That you cannot. What it means for the rest of us is simpler than the talent drama. If capability is going to keep walking between labs every few months, betting your whole stack on one provider's model is a bet on that lab keeping its people, which is the one thing you cannot control. I...

Anthropic dropped their June 2026 Economic Index today and buried inside the survey data is something that should be making headlines: Over a third of respondents (9,700 actual Claude users, linked to real usage data) believe AI will be capable of handling most or nearly all of their work tasks within the next year. Not “some tasks.” Not “help me write emails.” MOST of their work. And here’s the part nobody wants to talk about: the people who delegate the most to AI are the MOST optimistic about their job prospects. Meanwhile entry-level workers are the ones most worried about displacement. Senior devs and managers? Thriving. Junior colleagues? Everyone in the survey is more worried about them than themselves. The data also shows AI autonomy is measurably higher on Claude Code than o...

Most of the open vs closed talk here is about whether you can run the thing on your own hardware. fair, that's the obvious draw. but the part i think gets slept on is that open weights mean you can actually post train on top of the base, not just run inference. With a closed api you're renting intelligence. you can prompt it, you can rag around it, but you can never make it yours. you cant fine tune the actual weights for your domain, you cant distill it down, you cant freeze a version and own it forever. You're permanently downstream of whatever the provider decides. I saw some post about people post training their own models on top of glm-5.2 now that its open weight, and that framing stuck with me more than the benchmark numbers did. a frontier-ish base you can legally build on changes ...