Brain Inspired
Un pódcast de Paul Middlebrooks - Miercoles
155 Episodo
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BI 135 Elena Galea: The Stars of the Brain
Publicado: 6/5/2022 -
BI 134 Mandyam Srinivasan: Bee Flight and Cognition
Publicado: 27/4/2022 -
BI 133 Ken Paller: Lucid Dreaming, Memory, and Sleep
Publicado: 15/4/2022 -
BI 132 Ila Fiete: A Grid Scaffold for Memory
Publicado: 3/4/2022 -
BI 131 Sri Ramaswamy and Jie Mei: Neuromodulation-aware DNNs
Publicado: 26/3/2022 -
BI 130 Eve Marder: Modulation of Networks
Publicado: 13/3/2022 -
BI 129 Patryk Laurent: Learning from the Real World
Publicado: 2/3/2022 -
BI 128 Hakwan Lau: In Consciousness We Trust
Publicado: 20/2/2022 -
BI 127 Tomás Ryan: Memory, Instinct, and Forgetting
Publicado: 10/2/2022 -
BI 126 Randy Gallistel: Where Is the Engram?
Publicado: 31/1/2022 -
BI 125 Doris Tsao, Tony Zador, Blake Richards: NAISys
Publicado: 19/1/2022 -
BI 124 Peter Robin Hiesinger: The Self-Assembling Brain
Publicado: 5/1/2022 -
BI 123 Irina Rish: Continual Learning
Publicado: 26/12/2021 -
BI 122 Kohitij Kar: Visual Intelligence
Publicado: 12/12/2021 -
BI 121 Mac Shine: Systems Neurobiology
Publicado: 2/12/2021 -
BI 120 James Fitzgerald, Andrew Saxe, Weinan Sun: Optimizing Memories
Publicado: 21/11/2021 -
BI 119 Henry Yin: The Crisis in Neuroscience
Publicado: 11/11/2021 -
BI 118 Johannes Jäger: Beyond Networks
Publicado: 1/11/2021 -
BI 117 Anil Seth: Being You
Publicado: 19/10/2021 -
BI 116 Michael W. Cole: Empirical Neural Networks
Publicado: 12/10/2021
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 learning, convolutional and recurrent neural networks, decision-making science, AI agents, backpropagation, credit assignment, neuroengineering, neuromorphics, emergence, philosophy of mind, consciousness, general AI, spiking neural networks, data science, and a lot more. The podcast is not produced for a general audience. Instead, it aims to educate, challenge, inspire, and hopefully entertain those interested in learning more about neuroscience and AI.
