Predictive world models can enable AI systems to self-improve without constant external feedback by learning which actions and data are most informative, opening a path toward more autonomous and efficient learning in real-world applications.
RSI-Anything is a framework that enables AI systems to improve themselves recursively by using predictive world models to guide learning and action selection. Rather than relying on expensive external feedback, the system learns from its own experiences and adapts both its policy and world model over time, with built-in checks to ensure updates are reliable.