← Research areas05 · Self-improvement

Making experience improve the next AI

An AI system can improve its own tools, models and ways of working. We study how those improvements last and build on one another.

Suppose a research team invents a better way to plan experiments. Keeping the paper that describes it helps. The bigger opportunity is to make the method part of what the team’s next generation can do, in its software, its models and its everyday practice.

The improvements that last are the ones that hold up on unfamiliar work, keep the abilities the system has earned and repay what they cost to find.

What a successor receives

A successor inherits tested methods and stronger models together with the evidence for them and the unfinished work. A harmful improvement can be rolled back.

The same discipline can improve the system’s own tools and the way its agents divide a project. Competing ideas stay open until the evidence settles them, and changes that cannot be reversed are held to a higher bar.

Our ambition is an institution that invents more capable successors through its own work. Durability keeps that cumulative, with each generation starting from what the last one earned.

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