Ali Behrouz

Ali Behrouz is a Ph.D. student in computer science at Cornell University and a Google Research intern/student researcher working on deep learning architectures, continual learning, long-context memory, ML in healthcare, and computational neuroscience. He is a co-author of Google Research’s Nested Learning work and related research on language-model memory and self-modification.

Nested Learning Lets AI Models Adapt Without Forgetting Core Knowledge

Cornell graduate student and Google researcher Ali Behrouz argues that continual learning requires AI systems to update on multiple time scales rather than treating training and inference as separate modes. In a Cognitive Revolution interview, Behrouz describes his Nested Learning work as a framework for models whose fast components adapt to current context while slower components preserve durable knowledge, with sleep-like phases used to consolidate what should persist. He says the approach has not solved continual learning, but offers a way to think about architectures, optimizers and memory systems as nested learning processes rather than fixed blocks.

The Cognitive RevolutionJun 3, 202622 min read