Recursive self-improvement
A process in which an AI system improves its own design, so each version can build a better one.
Recursive self-improvement is the idea of an AI system that helps make itself better, and whose improved version is then better still at making improvements. Each round of the loop could, in principle, feed into the next.
A rough comparison is a factory that builds better tools, which are then used to build a better factory. Today, AI is already used to help write software, and some of that software is used in AI development, so a weak form of the loop exists. The open question is whether it could become strong and fast enough to take people out of the process.
This is central to arguments about how quickly AI could advance. Those who expect a rapid jump point to the loop as the reason it could happen. Sceptics argue that progress depends on more than clever design: it also needs chips, data, energy and real-world testing, which do not speed up so easily. Others point out that improvements often get harder to find over time, so the loop might level off rather than run away. Nobody has yet observed a full example.