# Google DeepMind Finds No AI Acceleration in ML R&D

> DeepMind's AI research shows no significant speedup in machine learning development despite heavy code automation.
- Title: Google DeepMind Finds No AI Acceleration in ML R&D · TokenPost
- Summary: DeepMind's AI research shows no significant speedup in machine learning development despite heavy code automation. Google DeepMind's internal analysis found…
- Keywords: google deepmind, machine learning, ai research, ml r&d, deepmind, production code, gci index, crypto, finance, Google, Finds, Acceleration
- Source: TokenPost — https://tokenpost.com/news/technology/32936
- Published: 2026-10-16T01:48:41+00:00
- Read time: 1 min
- Topics: google deepmind, machine learning, ai research, ml r&d, deepmind, production code, gci index, crypto, finance
## DeepMind's R&D Assessment
Google DeepMind's internal analysis found no significant end-to-end acceleration in machine learning research and development despite AI writing more than 75% of the lab's production code.

> There is currently no significant end-to-end acceleration of ML R&D, AI-driven or otherwise.
## GCI Index Trend
The GCI v1 index shows frontier Gemini capabilities rose by 0.1 points per month with no significant change after April 1, 2026.
## Code Automation Levels
Fully delegated pull requests rose from 7.5% in April 2026 to 11.9% in September 2026, but 88% still needed human steering.
## Automation Effectiveness
Automation works best on clearly specified tasks with verifiable outcomes but struggles with open-ended scientific ideas and long-range research.
## Key takeaway

Google DeepMind's internal analysis found no end-to-end acceleration in machine learning R&D despite AI writing 75% of production code.