Google says self-improving AI isn't anywhere close
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An internal evaluation of Google DeepMind, included in Gemini 4 Argon's security report, did not find a structural acceleration of AI progress attributable to technology itself. Although tools write more than three-quarters of the production code, human revision remains routine and agents encounter complex tasks without intervention.
Google DeepMind has yet to find evidence that I.I. is accelerating the development of better I.I. models. Although neuronets already write most of the software code inside the company, complex research tasks still require people's involvement.
According to a post on X by Google researcher Haydn Belfield, we are still very far from self-improving AI at the moment. Belfield refers to the "Gemini 4 Argon Safety & Security Report", in which Google published the first holistic empirical assessment of the automation and acceleration of ML research and development at Google DeepMind.
Google says self-improving AI isn't anywhere close
Google engineer Haydn Belfield says there's no measurable acceleration of AI research driven by AI at Deepmind. AI now writes more than 75 percent of production code, but 88 percent of changes still need human oversight. The company's in-house General Capability Index shows steady growth with no sudden speedup. Self-improving AI isn't anywhere close, Belfield says. The article Google says self-improving AI isn't anywhere close appeared first on …
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