Expert takes Oct 11, 2026

Today · post, October 11

Wildeford says no lab fully automates R&D; he shows no data

AI policy researcher Peter Wildeford splits the claim that "some lab has cracked AI self-improvement" into two meanings: AI doing all of R&D, which no company has achieved, and AI speeding R&D up, which all the major labs are doing. He writes: "If you mean AI can fully automate all R&D, I call BS - no company has cracked that yet. If you mean AI is accelerating development, then yes obviously the major companies are doing that." (Peter Wildeford, 2026-10-11). Wildeford's statement is opinion; he attaches no internal lab data. He was responding to an anonymous rumor with no source, which we don't use. Our September 27 issue reported that the automated training loop for Alibaba's flagship model Qwen3.8-Max ran 33 iterations over more than a month of fully automated operation; the press release doesn't say what each round did. The same release says that in a chip-design experiment the model kept improving itself for more than 60 hours and called chip-design software more than 10,000 times; that was a chip-design task, not model training (Alibaba Cloud, 2026-09-22). Our October 9 issue reported that the research group Epoch AI gave two models, Anthropic's Fable 5 and OpenAI's GPT-5.6 Sol, 3,000 GPU hours each, and neither produced a comparable innovation in training methods. Applying Wildeford's split is our move; he didn't comment on either case. Alibaba's 33 rounds count as speeding R&D up. Alibaba doesn't say who set the goals or who chose which round's results went into the production model, and while people still do those two steps, it isn't AI doing the R&D. Epoch's experiment found that, given compute to do research on their own, neither model came up with a comparable innovation; that one test shows no sign of the fully automated end, though it doesn't rule out labs with more compute or internal tooling. That supports our September 27 reading: the big labs already run automated training pipelines, but that doesn't mean models will get better by themselves.