Deep Reinforcement Learning for Social Learning & Fun Chat | Natasha Jacques, @Google

Natasha Jaques is currently a Research Scientist at @Google Brain and post-doc fellow at @UC Berkeley, where her research interests are in designing multi-agent RL algorithms while focusing on social reinforcement learning, that can improve generalization, coordination between agents, and collaboration between human and AI agents. She received her PhD from @Massachusetts Institute of Technology (MIT) where she focused on Affective Computing and other techniques for deep/reinforcement learning. She has also received multiple awards for her research works submitted to venues like ICML and NeurIPS She has interned at@DeepMind, Google Brain, and is an @OpenAI Scholars mentor. 00:00 Introductions 01:25 Can you tell us a bit about what projects you are working on at Google currently? And what does the work routine look like as a Research Scientist? 06:25 You have worked as a researcher at many diverse backgrounds who are leading in the domain of machine learning: MIT, Google Brain, DeepMind - what are the key diff