Brain Inspired
Ein Podcast von Paul Middlebrooks - Mittwochs
154 Folgen
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BI 154 Anne Collins: Learning with Working Memory
Vom: 29.11.2022 -
BI 153 Carolyn Dicey-Jennings: Attention and the Self
Vom: 18.11.2022 -
BI 152 Michael L. Anderson: After Phrenology: Neural Reuse
Vom: 8.11.2022 -
BI 151 Steve Byrnes: Brain-like AGI Safety
Vom: 30.10.2022 -
BI 150 Dan Nicholson: Machines, Organisms, Processes
Vom: 15.10.2022 -
BI 149 William B. Miller: Cell Intelligence
Vom: 5.10.2022 -
BI 148 Gaute Einevoll: Brain Simulations
Vom: 25.9.2022 -
BI 147 Noah Hutton: In Silico
Vom: 13.9.2022 -
BI 146 Lauren Ross: Causal and Non-Causal Explanation
Vom: 7.9.2022 -
BI 145 James Woodward: Causation with a Human Face
Vom: 28.8.2022 -
BI 144 Emily M. Bender and Ev Fedorenko: Large Language Models
Vom: 17.8.2022 -
BI 143 Rodolphe Sepulchre: Mixed Feedback Control
Vom: 5.8.2022 -
BI 142 Cameron Buckner: The New DoGMA
Vom: 26.7.2022 -
BI 141 Carina Curto: From Structure to Dynamics
Vom: 12.7.2022 -
BI 140 Jeff Schall: Decisions and Eye Movements
Vom: 30.6.2022 -
BI 139 Marc Howard: Compressed Time and Memory
Vom: 20.6.2022 -
BI 138 Matthew Larkum: The Dendrite Hypothesis
Vom: 6.6.2022 -
BI 137 Brian Butterworth: Can Fish Count?
Vom: 27.5.2022 -
BI 136 Michel Bitbol and Alex Gomez-Marin: Phenomenology
Vom: 17.5.2022 -
BI 135 Elena Galea: The Stars of the Brain
Vom: 6.5.2022
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.
