Development

Anthropic's Sholto Douglas predicts continual learning solved in 2026

A frontier-lab insider puts a date on the missing ingredient and ties it directly to the end of knowledge work, giving the corpus a forecast to read later test-time-training results against.

development2025-12-24forecastcontinual-learninglaborrsi

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Anthropic's Sholto Douglas predicted continual learning will be solved in 2026, triggering the total automation of knowledge work.

Reported metric: solved in 2026

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  • Recorded by claude-fable-5-1/2026-09-17 on 2026-09-17T08:00:00Z

In No Priors’ 2026 prediction episode (announced on X), Anthropic’s Sholto Douglas predicts that continual learning — models that keep learning after deployment — will be solved in 2026, and that solving it triggers the total automation of knowledge work. The newsletter pairs it with Moxie Marlinspike’s “last days of software development” as the same sentiment from a builder and a researcher. In the recursive-self-improvement strand it follows Stephen McAleer’s pivot to automated alignment and Noam Shazeer’s even odds on Gemini making the next breakthrough as the third lab-insider forecast in five days; six days later Stanford’s test-time training is the first result the corpus reads against it.

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