Brain Inspired
En podkast av Paul Middlebrooks - Onsdager
155 Episoder
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BI 135 Elena Galea: The Stars of the Brain
Publisert: 6.5.2022 -
BI 134 Mandyam Srinivasan: Bee Flight and Cognition
Publisert: 27.4.2022 -
BI 133 Ken Paller: Lucid Dreaming, Memory, and Sleep
Publisert: 15.4.2022 -
BI 132 Ila Fiete: A Grid Scaffold for Memory
Publisert: 3.4.2022 -
BI 131 Sri Ramaswamy and Jie Mei: Neuromodulation-aware DNNs
Publisert: 26.3.2022 -
BI 130 Eve Marder: Modulation of Networks
Publisert: 13.3.2022 -
BI 129 Patryk Laurent: Learning from the Real World
Publisert: 2.3.2022 -
BI 128 Hakwan Lau: In Consciousness We Trust
Publisert: 20.2.2022 -
BI 127 Tomás Ryan: Memory, Instinct, and Forgetting
Publisert: 10.2.2022 -
BI 126 Randy Gallistel: Where Is the Engram?
Publisert: 31.1.2022 -
BI 125 Doris Tsao, Tony Zador, Blake Richards: NAISys
Publisert: 19.1.2022 -
BI 124 Peter Robin Hiesinger: The Self-Assembling Brain
Publisert: 5.1.2022 -
BI 123 Irina Rish: Continual Learning
Publisert: 26.12.2021 -
BI 122 Kohitij Kar: Visual Intelligence
Publisert: 12.12.2021 -
BI 121 Mac Shine: Systems Neurobiology
Publisert: 2.12.2021 -
BI 120 James Fitzgerald, Andrew Saxe, Weinan Sun: Optimizing Memories
Publisert: 21.11.2021 -
BI 119 Henry Yin: The Crisis in Neuroscience
Publisert: 11.11.2021 -
BI 118 Johannes Jäger: Beyond Networks
Publisert: 1.11.2021 -
BI 117 Anil Seth: Being You
Publisert: 19.10.2021 -
BI 116 Michael W. Cole: Empirical Neural Networks
Publisert: 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.
