Rosanne Liu — Conducting Fundamental ML Research as a Nonprofit

How Rosanne is working to democratize AI research and improve diversity and fairness in the field through starting a non-profit after being a founding member of Uber AI Labs, doing lots of amazing research, and publishing papers at top conferences.

Rosanne is a machine learning researcher, and co-founder of ML Collective, a nonprofit organization for open collaboration and mentorship. Before that, she was a founding member of Uber AI. She has published research at NeurIPS, ICLR, ICML, Science, and other top venues. While at school she used neural networks to help discover novel materials and to optimize fuel efficiency in hybrid vehicles.

ML Collective: http://mlcollective.org/

Controlling Text Generation with Plug and Play Language Models: https://eng.uber.com/pplm/

LCA: Loss Change Allocation for Neural Network Training: https://eng.uber.com/research/lca-loss-change-allocation-for-neural-network-training/

Topics covered

0:00 Sneak peek, Intro

1:53 The origin of ML Collective

5:31 Why a non-profit and who is MLC for?

14:30 LCA, Loss Change Allocation

18:20 Running an org, research vs admin work

20:10 Advice for people trying to get published

24:15 on reading papers and Intrinsic Dimension paper

36:25 NeurIPS - Open Collaboration

40:20 What is your reward function?

44:44 Underrated aspect of ML

47:22 How to get involved with MLC

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