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Sugandha Sharma is a Ph.D. candidate at MIT advised by Prof. Ila Fiete and Prof. Josh Tenenbaum. She explores the computational and theoretical principles underlying higher cognition in the brain by constructing neuro-inspired models and mathematical tools to discover how the brain navigates the world, or how to construct memory mechanisms that don’t exhibit catastrophic forgetting. In this episode, we chat about biologically inspired neural architectures, how memory could be implemented, why control theory is underrated and much more.
By Kanjun Qiu4.8
1616 ratings
Sugandha Sharma is a Ph.D. candidate at MIT advised by Prof. Ila Fiete and Prof. Josh Tenenbaum. She explores the computational and theoretical principles underlying higher cognition in the brain by constructing neuro-inspired models and mathematical tools to discover how the brain navigates the world, or how to construct memory mechanisms that don’t exhibit catastrophic forgetting. In this episode, we chat about biologically inspired neural architectures, how memory could be implemented, why control theory is underrated and much more.

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