Researchers introduce Nested Learning a new ML paradigm treating models as nested optimization problems to solve catastrophic forgetting The approach unifies model architecture and training algorithms enabling continual learning Proof of concept architecture Hope demonstrates superior language modeling and long context memory management outperforming existing models