Cathy Wu's guest appearances

Cathy Wu

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

The Robot Brains Podcast

Sergey Levine

Flora Tasse

Shakir Mohamed

Eric Horvitz

Charles Isbell

Alison Gopnik

Ayanna Howard

Chelsea Finn

Dario Amodei

Jianxiong Xiao

Kate Darling

Jason Holmberg

Lotte Bransen

Christopher Berner

David Spiegelhalter

OwlTail

Previous guests on our podcasts - from Tesla, Aurora, Waymo - are building the brains of the cars and trucks of our future. This episode's guest, Professor Cathy Wu, is building the roadways of our future. She is building machine-learning to predict the ideal infrastructure for the world's future mobility, the cost of building this infrastructure, and most importantly, what's the solution that eliminates traffic jams and gridlock forever.Currently at MIT's Institute for Data, Systems, and Society (IDSS), Professor Cathy Wu (and previous student of Pieter Abbeel's) gives listeners an overview of the type of potential scenarios being modeled with machine-learning such as scenarios in which the road is filled with mixed-autonomy vehicles. What emergent behaviors might happen? Are there infrastructure solutions or software solutions that can help ensure smooth travel and safe roadways as our mode for transportation and delivery evolve? What are the policy considerations?Throughout the talk, Wu cites building reinforcement learning for her work and why it's the right fit her research, "Reinforcement learning is essentially this paradigm at the intersection of machine learning and also control, and it is essentially about how agents learn from experience and in particular through trial and error." Her past and current research can be found here and you can watch her recent TedXMIT talk here.SUBSCRIBE TO THE ROBOT BRAINS PODCAST TODAY | Visit therobotbrains.ai and follow us on YouTube at TheRobotBrainsPodcast, Twitter @therobotbrains, and Instagram @therobotbrains.| Host: Pieter Abbeel | Executive Producers: Alice Patel &amp; Henry Tobias Jones | Production: Fresh Air Production Hosted on Acast. See acast.com/privacy for more information.

Previous guests on our podcasts - from Tesla, Aurora, Waymo - are building the brains of the cars and trucks of our future. This episode's guest, <a href="http://www.wucathy.com/blog/" rel="noopener noreferrer nofollow" target="_blank">Professor Cathy Wu</a>, is building the roadways of our future. She is building machine-learning to predict the ideal infrastructure for the world's future mobility, the cost of building this infrastructure, and most importantly, what's the solution that eliminates traffic jams and gridlock forever.Currently at <a href="https://idss.mit.edu/" rel="noopener noreferrer nofollow" target="_blank">MIT's Institute for Data, Systems, and Society (IDSS)</a>, Professor Cathy Wu (and <a href="https://news.mit.edu/2021/qa-cathy-wu-developing-algorithms-safely-integrate-robots-our-world-1216" rel="noopener noreferrer nofollow" target="_blank">previous student of Pieter Abbeel's</a>) gives listeners an overview of the type of potential scenarios being modeled with machine-learning such as scenarios in which the road is filled with mixed-autonomy vehicles. What emergent behaviors might happen? Are there infrastructure solutions or software solutions that can help ensure smooth travel and safe roadways as our mode for transportation and delivery evolve? What are the policy considerations?Throughout the talk, Wu cites building reinforcement learning for her work and why it's the right fit her research, "Reinforcement learning is essentially this paradigm at the intersection of machine learning and also control, and it is essentially about how agents learn from experience and in particular through trial and error." Her<a href="https://scholar.google.com/scholar?hl=en&amp;as_sdt=0%2C5&amp;as_vis=1&amp;q=cathy+wu+transportation+AI+systems&amp;oq=" rel="noopener noreferrer nofollow" target="_blank"> past and current research can be found here</a> and you can watch her recent<a href="https://www.youtube.com/watch?v=mrk8I-9iLs4" rel="noopener noreferrer nofollow" target="_blank"> TedXMIT talk here</a>.SUBSCRIBE TO THE ROBOT BRAINS PODCAST TODAY | Visit <a href="http://therobotbrains.ai" rel="nofollow" target="_blank">therobotbrains.ai</a> and follow us on YouTube at <a href="https://www.youtube.com/c/TheRobotBrainsPodcast" rel="noopener noreferrer nofollow" target="_blank">TheRobotBrainsPodcast</a>, Twitter <a href="https://twitter.com/therobotbrains" rel="noopener noreferrer nofollow" target="_blank">@therobotbrains</a>, and Instagram @therobotbrains.| Host: Pieter Abbeel | Executive Producers: Alice Patel &amp; Henry Tobias Jones | Production: Fresh Air Production Hosted on Acast. See <a href="https://acast.com/privacy" rel="noopener noreferrer nofollow" target="_blank">acast.com/privacy</a> for more information.

Cathy Wu of MIT on the future of our highways and roads 

Today we’re joined by Cathy Wu, Assistant Professor at MIT. We had the pleasure of catching up with Cathy to discuss her work applying RL to mixed autonomy traffic, specifically, understanding the potential impact autonomous vehicles would have on various mixed-autonomy scenarios. To better understand this, Cathy built multiple RL simulations, including a track, intersection, and merge scenarios. We talk through how each scenario is set up, how human drivers are modeled, the results, and much more.

Simulating the Future of Traffic with RL w/ Cathy Wu - #362