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Nested Learning: A new ML paradigm for continual learning


Introducing Nested Learning: A new ML paradigm for continual learning November 7, 2025 Ali Behrouz, Student Researcher, and Vahab Mirrokni, VP and Google Fellow, Google Research We introduce Nested Learning, a new approach to machine learning that views models as a set of smaller, nested optimization problems, each with its own internal workflow, in order to mitigate or even completely avoid the issue of “catastrophic forgetting”, where learning new tasks sacrifices proficiency on old tasks. The last decade has seen incredible progress in machine learning (ML), primarily driven by powerful neural network architectures and the algorithms used to train them.

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Google’s ‘Nested Learning’ paradigm could solve AI's memory and continual learning problem