Brain Inspired
En podkast av Paul Middlebrooks
Kategorier:
127 Episoder
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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 -
BI 115 Steve Grossberg: Conscious Mind, Resonant Brain
Publisert: 2.10.2021 -
BI 114 Mark Sprevak and Mazviita Chirimuuta: Computation and the Mind
Publisert: 22.9.2021 -
BI 113 David Barack and John Krakauer: Two Views On Cognition
Publisert: 12.9.2021 -
BI ViDA Panel Discussion: Deep RL and Dopamine
Publisert: 2.9.2021 -
BI 112 Ali Mohebi and Ben Engelhard: The Many Faces of Dopamine
Publisert: 26.8.2021 -
BI NMA 06: Advancing Neuro Deep Learning Panel
Publisert: 19.8.2021 -
BI NMA 05: NLP and Generative Models Panel
Publisert: 13.8.2021 -
BI NMA 04: Deep Learning Basics Panel
Publisert: 6.8.2021
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.
