In episode 29 of The Gradient Podcast, we chat with Rosanne Liu. Rosanne is a research scientist in Google Brain, and co-founder and executive director of ML Collective, a nonprofit organization for open collaboration and accessible mentorship. Before that she was a founding member of Uber AI. Outside of research, she supports underrepresented communities, and organizes symposiums, workshops, and a weekly reading group “Deep Learning: Classics and Trends” since 2018. She is currently thinking deeply how to democratize AI research even further, and improve the diversity and fairness of the field, while working on multiple fronts of machine learning research including understanding training dynamics, rethinking model capacity and scaling.
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Outline:
(01:30) How did you go into AI / research
(6:45) AI research: the unreasonably narrow path and how not to be miserable
(16:30) ML Collective Overview
(21:45) Deep Learning: Classics and Trends Reading Group
(26:25) More details about ML Collective
(48:00) Narrowness vs Variety in research
(57:20) Favorite Papers
(58:50) Measuring the Intrinsic Dimension of Objective Landscapes
(01:01:40) Natural Adversarial Objects
(01:03:00) Interests outside of AI - Writing
(01:08:05) Interests outside of AI - Narrating Travels with Charley
(01:13:22) Outro
Rosanne Liu: Paths in AI Research and ML Collective