Google DeepMind finds no acceleration in AI research progress

Google DeepMind published its first comprehensive internal assessment of AI-driven machine learning research on October 14, 2026. The audit found no measurable acceleration in AI progress that can be credited to AI itself. What the audit actually measured The assessment appears inside the Gemini 4 Argon Safety & Security Report. Researcher Haydn Belfield led the work. The team tracked frontier Gemini capabilities with a metric it calls the General Capability Index, or GCI. Across 123 models and 92 benchmarks, that score has climbed by approximately 0.1 GCI points each month. The report says thorough statistical analysis shows no significant structural speedup after April 2026. For public models, the monthly change before April 2026 was 0.091 points. After that date, it was 0.118 points. The report found no substantial difference between the two. Gemini 4 Argon itself landed marginally above the expected trend line. DeepMind’s report suggests that bump mainly comes from more compute and organizational investment, not from the model accelerating its own development. AI writes the code, humans still sign off AI tools contribute to writing over 75% of production code at DeepMind. S...