Anthropic's AI Models Are Now Improving Nearly Twice as Fast — With AI's Help

Anthropic's AI models are improving nearly twice as fast as before as the technology plays a bigger role in developing more powerful versions of itself, an independent study found, fanning concerns that advances could outpace efforts to assess risks.

The findings from AI safety nonprofit METR, published on Thursday, offer some of the clearest evidence yet that AI is accelerating its own development, potentially paving the way for recursive self-improvement — when AI systems can build more powerful versions of themselves without human intervention.

AI is behind most of the acceleration

METR estimated AI accounted for perhaps 80% of the current acceleration, though it cautioned that the figure was uncertain. The researchers found no convincing evidence of major bottlenecks that could slow progress over the next year.

"We are confident that the acceleration was not due to an acceleration in the scaling of training compute," METR, also known as Model Evaluation and Threat Research, said.

But it cautioned that AI was not yet capable of making highly significant, fully autonomous contributions to the most important stages of model training.

Why researchers are worried

The prospect of recursive self-improvement has fuelled warnings from AI researchers in recent months that such systems could become difficult to align with human goals, monitor and control, potentially posing an existential threat to humanity.

Such a shift could have far-reaching implications for an industry that has spent hundreds of billions of dollars building computing infrastructure to train advanced models, as AI itself could become an important driver of technological progress.

METR's 11-week assessment, which drew on confidential research, interviews and performance data from unreleased models, found Anthropic's benchmark capabilities had been improving 1.9 times faster since October 2025 than previously.

Sources

• Reuters — Anthropic's models improving nearly twice as fast with help from AI, study finds