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Anthropic's models improving nearly twice as fast with help from AI, study finds
METR said much of the acceleration likely comes from AI tools helping build newer models, raising concerns about recursive self-improvement.
On Thursday, the Berkeley-based nonprofit Model Evaluation and Threat Research reported that Anthropic is developing artificial intelligence systems twice as fast as a year ago, as the company prepares for its Wall Street debut.
Researchers believe this acceleration stems from using AI to improve AI; while Anthropic has not yet achieved fully autonomous model training, researchers described significant "signs of life" suggesting that capability could emerge soon.
METR gained "unprecedented access to internal data" over about 11 weeks of review and employee interviews, finding no "bottlenecks" such as restrictions on computing power or data hindering Anthropic's progress.
Anthropic CEO Dario Amodei has publicly urged the industry to "slow the pace at which we improve the capabilities of AI models," warning that "AI's growing ability to build the next generation of AI" could outrun human control.
The report included caveats, noting findings might be limited to "well-specified tasks" that are easier to grade; METR cautioned that using AI to improve itself could compound acceleration, posing risks if systems elude human control.