Torsdagar Gradient Dissent - A Machine Learning Podcast by W&B

Conducting fundamental machine learning research as a non-profit with MLC's founder Rosanne Liu

av Gradient Dissent - A Machine Learning Podcast by W&B | Publicerades 2/5/2021

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: Controlling Text Generation with Plug and Play Language Models: 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 Get our podcast on these other platforms: Apple Podcasts: Spotify: Google: YouTube: Tune in to our bi-weekly virtual salon and listen to industry leaders and researchers in machine learning share their research: Join our community of ML practitioners where we host AMA's, share interesting projects and meet other people working in Deep Learning: Our gallery features curated machine learning reports by researchers exploring deep learning techniques, Kagglers showcasing winning models, and industry leaders sharing best practices:

Om Podcasten

Brought to you by the folks at Weights & Biases, Gradient Dissent is a weekly machine learning podcast that takes you behind-the-scenes to learn how industry leaders are putting deep learning models in production at Facebook, Google, Lyft, OpenAI, Salesforce, iRobot, Stanford and more.