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Paul Middlebrooks
Brain Inspired
Neuroscience and artificial intelligence work better together. Brain inspired is a celebration and exploration of the ideas driving our progress to understand intelligence. I interview experts about their work at the interface of neuroscience, artificial intelligence, cognitive science, philosophy, psychology, and more: the symbiosis of these overlapping fields, how they inform each other, where they differ, what the past brought us, and what the future brings. Topics include computational neuroscience, supervised machine learning, unsupervised learning, reinforcement learning, deep...
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Ratings & Reviews
4.9 stars from 150 ratings
Amazing insights
Wow the creativity episode was amazing!!! Thank you for sharing this valuable knowledge
Abder E via Apple Podcasts · United States of America · 05/12/21
The host really adds value to the discussions, while letting the guests shine.
neurocurious via Apple Podcasts · United States of America · 12/23/20
This podcast is excellent. Very informative conversations which goes into detail of concepts. Paul is well prepared for the discussion and I enjoyed almost all the episodes I heard so far. Keep the great work going plz.
BaharGh via Apple Podcasts · Germany · 10/28/20
Recent Episodes
Steve and I discuss many topics from his new book Know Thyself: The Science of Self-Awareness. The book covers the full range of what we know about metacognition and self-awareness, including how brains might underlie metacognitive behavior, computational models to explain mechanisms of...
Published 06/06/21
Jackie and Bob discuss their research and thinking about curiosity. We also discuss how one should go about their career (qua curiosity), how eye movements compare with other windows into cognition, and whether we can and should create curious AI agents (Bob is an emphatic yes, and Jackie is...
Published 05/27/21
Sanjeev and I discuss some of the progress toward understanding how deep learning works, specially under previous assumptions it wouldn't or shouldn't work as well as it does. Deep learning poses a challenge for mathematics, because its methods aren't rooted in mathematical theory and therefore...
Published 05/17/21
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