Nathan Lambert: Lossy self-improvement is real but won't cause fast takeoff
natolambert · x · 2026-09-10
Nathan Lambert (Interconnects) argues AI models are accelerating AI research, but not toward rapid recursive self-improvement or near-term takeoff. Key points: two or three labs are consolidating into an oligopoly with the best models and resources; superhuman coding assistants are making formerly intractable training problems approachable, setting up a year of rapid frontier progress; yet models are already good enough for valuable knowledge work, and it's unclear which tasks they'll master beyond code and CLI computer-use. Self-improvement is 'lossy'—real, but not an explosive loop.
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