Recursive self-improvement (RSI) refers to AI systems directly participating in improving the next generation of AI systems, so that each generation of models advances faster due to the help of the previous generation; the key difference from the traditional improvement model led by human researchers is that the proportion of human participation in the improvement loop declines, and the iteration cycle may compress from months to weeks or even shorter.