Brain Inspired
En podkast av Paul Middlebrooks - Onsdager
155 Episoder
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BI 155 Luiz Pessoa: The Entangled Brain
Publisert: 10.12.2022 -
BI 154 Anne Collins: Learning with Working Memory
Publisert: 29.11.2022 -
BI 153 Carolyn Dicey-Jennings: Attention and the Self
Publisert: 18.11.2022 -
BI 152 Michael L. Anderson: After Phrenology: Neural Reuse
Publisert: 8.11.2022 -
BI 151 Steve Byrnes: Brain-like AGI Safety
Publisert: 30.10.2022 -
BI 150 Dan Nicholson: Machines, Organisms, Processes
Publisert: 15.10.2022 -
BI 149 William B. Miller: Cell Intelligence
Publisert: 5.10.2022 -
BI 148 Gaute Einevoll: Brain Simulations
Publisert: 25.9.2022 -
BI 147 Noah Hutton: In Silico
Publisert: 13.9.2022 -
BI 146 Lauren Ross: Causal and Non-Causal Explanation
Publisert: 7.9.2022 -
BI 145 James Woodward: Causation with a Human Face
Publisert: 28.8.2022 -
BI 144 Emily M. Bender and Ev Fedorenko: Large Language Models
Publisert: 17.8.2022 -
BI 143 Rodolphe Sepulchre: Mixed Feedback Control
Publisert: 5.8.2022 -
BI 142 Cameron Buckner: The New DoGMA
Publisert: 26.7.2022 -
BI 141 Carina Curto: From Structure to Dynamics
Publisert: 12.7.2022 -
BI 140 Jeff Schall: Decisions and Eye Movements
Publisert: 30.6.2022 -
BI 139 Marc Howard: Compressed Time and Memory
Publisert: 20.6.2022 -
BI 138 Matthew Larkum: The Dendrite Hypothesis
Publisert: 6.6.2022 -
BI 137 Brian Butterworth: Can Fish Count?
Publisert: 27.5.2022 -
BI 136 Michel Bitbol and Alex Gomez-Marin: Phenomenology
Publisert: 17.5.2022
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.
