AT A GLANCE
Sergey Brin describes Google moving onto the recursive self-improvement treadmill: AI helping the research and engineering behind better AI. Google’s reported optimisation of one Gemma configuration is an example of infrastructure improvement, not proof that intelligence has tripled. Capability can develop quickly, so revisit useful business tasks regularly. Keep information protected, permissions controlled and results measured as the tools improve.
Just as businesses are getting used to AI assistants, the companies building them are using AI to help develop their successors, and now the trouble starts........
Google co-founder Sergey Brin describes the company as starting to get onto the “RSI treadmill”. RSI means Recursive Self-Improvement: AI helps build better AI, which can then become more capable of helping build the next generation. Researchers and models increasingly work together.
The principle is straightforward..... Today’s AI → research and code → tested improvements → better AI → repeat.
Each successful cycle could improve the tools doing the research, reduce development time and allow more ideas to be tested. Progress could therefore compound.
Yesterday’s assistant becomes tomorrow’s development tool..... and helps build the assistant after that!
There are already practical examples. Google reports that Gemini 4 Argon helped optimise the software running a Gemma model, making one particular configuration 2.85 times faster, while preserving its outputs. That is AI helping improve AI infrastructure..... although faster execution does NOT mean intelligence has tripled!
BUT..... an emerging feedback loop is not proof of unlimited acceleration.
Computing capacity, experiments, reliable evaluation and human judgement are critical. Further acceleration is a certainty, but its speed and extent remain uncertain.
For businesses, the implication is significant. A task that AI handles poorly today may deserve another look sooner than expected. Long-term plans based on today’s limitations could age rather quickly.
Start with useful business problems, measure the results and review capabilities regularly. Keep company information protected, permissions controlled and people trained as the technology improves.
An increasingly capable assistant still needs somebody deciding what it is allowed to do - this is what Microsoft is betting on - the Control Plane!
From the briefing.....
The briefing connected improving AI capability with governance. A more capable tool still needs controlled deployment, protected company information and clear authority. The published article distinguishes demonstrated optimisation from predictions about future acceleration.
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