United Kingdom, Nov. 10 -- Google Research has unveiled a machine learning framework called Nested Learning, a new paradigm designed to overcome one of AI's oldest problems: the inability to learn continuously without forgetting what it already knows.

Detailed in a new paper published for NeurIPS 2025, Nested Learning reimagines how neural networks update and organise information.

Instead of treating a model's architecture (its structure) and optimiser (its learning rule) as separate entities, Google's researchers propose viewing them as interconnected systems that operate across multiple levels - much like the layers of memory in the human brain.

The approach is designed to combat catastrophic forgetting, a phenomenon where AI models ...