Episode 34: Deep Learning Generalization, Representation, and Abstraction with Ari Morcos

Episode Summary

Ari Morcos is a Research Scientist at Facebook AI Research working on understanding the mechanisms underlying neural network computation and function and using these insights to build machine learning systems more intelligently. In particular, Ari has worked on a variety of topics, including understanding the lottery ticket hypothesis, the mechanisms underlying common regularizers, and the properties predictive of generalization, as well as methods to compare representations across networks, the role of single units in computation, and on strategies to measure abstraction in neural network representations. Previously, he worked at DeepMind in London, and earned his Ph.D. in Neurobiology at Harvard University, using machine learning to study the cortical dynamics underlying evidence accumulation for decision-making.

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