The RSI-Anything framework introduced by PhAI Labs extends the cross-domain predictive learning technology of JEPA-Anything. Centered around a world model, it establishes a cross-domain reusable recursive self-improvement process encompassing prediction, action, real feedback, and system updates. Through asynchronous updates of the policy and world model, along with component evaluation and compatibility checks, the framework ensures the stability of system iterations. RSI-Anything has achieved significant performance improvements in tasks such as code repair, computer graphical user interface interaction, laboratory planning, and chemical reaction optimization. Additionally, the framework has been expanded for application in immunological research, generating candidate combined intervention hypotheses for validation. This research provides a new path for AI to continuously self-evolve from digital tasks to complex physical and scientific worlds.