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Reinforcement Learning at 65,000 Feet with Marlos C. Machado | Approximately Correct Podcast

This week’s episode of Approximately Correct looks at how the work of Marlos C. Machado is taking reinforcement learning to new heights.

Marlos sits down with hosts Alona Fyshe and Scott Lilwall to share the insights from his work using AI to control balloons in Earth's stratosphere, and what it teaches us about how reinforcement learning works in the real world.

"AI in the real world is hard; you'd be surprised how difficult some of the things we do day-to-day are when you try to get AI to do them."

- Amii Fellow and Canada CIFAR AI Chair Marlos C. Machado

Continual learning will be necessary for RL projects to deal with an unpredictable and ever-changing world, Marlos says. But that is easier said than done. The discussion goes deep into the challenges of continual learning, including the mystery of loss of plasticity, and the innovative ways Marlo's lab is trying to address it.


Tune in to hear this insightful discussion on Spotify, Apple Podcasts or your favorite podcast platform.
Approximately Correct: An AI Podcast from Amii is hosted by Alona Fyshe and Scott Lilwall. It is produced by Lynda Vang, with video production by Chris Onciul.

Tune in to hear this insightful discussion on Spotify, Apple Podcasts, Google Podcasts, or your favorite podcast platform.



You can hear episode three of Approximately Correct on Spotify, Apple Podcasts, Google Podcasts and other podcasting services.

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