Rosanne Liu — Conducting Fundamental ML Research as a Nonprofit
Rosanne Liu — Conducting Fundamental ML Research as a Nonprofit  
Podcast: Gradient Dissent: Conversations on AI
Published On: Fri Feb 05 2021
Description: 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 covered0:00 Sneak peek, Intro1:53 The origin of ML Collective5:31 Why a non-profit and who is MLC for?14:30 LCA, Loss Change Allocation18:20 Running an org, research vs admin work20:10 Advice for people trying to get published24:15 on reading papers and Intrinsic Dimension paper36:25 NeurIPS - Open Collaboration40:20 What is your reward function?44:44 Underrated aspect of ML47:22 How to get involved with MLCGet our podcast on these other platforms:Apple Podcasts: http://wandb.me/apple-podcastsSpotify: http://wandb.me/spotifyGoogle: http://wandb.me/google-podcastsYouTube: http://wandb.me/youtubeTune in to our bi-weekly virtual salon and listen to industry leaders and researchers in machine learning share their research:http://wandb.me/salonJoin our community of ML practitioners where we host AMA's, share interesting projects and meet other people working in Deep Learning:http://wandb.me/slackOur gallery features curated machine learning reports by researchers exploring deep learning techniques, Kagglers showcasing winning models, and industry leaders sharing best practices:https://wandb.ai/gallery