“1/9 In the Gemini 4 Argon Safety & Security Report, we published our first holistic…”

1/9 In the Gemini 4 Argon Safety & Security Report, we published our first holistic empirical assessment of ML R&D automation and acceleration inside Google DeepMind — combining capability benchmarks, a macro capability index, data on AI-written code and trajectory outcomes, and a survey of senior frontier researchers.

Our main findings are that:

1. There is currently no significant end-to-end acceleration of ML R&D, AI-driven or otherwise.
2. While some components of ML R&D are being automated and there have been many examples of AI-driven breakthroughs and optimizations, we are far from full end-to-end automation.
3. We therefore conclude that the risk from AI-driven ML R&D is currently low.

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