Brain Inspired
Un pódcast de Paul Middlebrooks - Miercoles
155 Episodo
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BI 155 Luiz Pessoa: The Entangled Brain
Publicado: 10/12/2022 -
BI 154 Anne Collins: Learning with Working Memory
Publicado: 29/11/2022 -
BI 153 Carolyn Dicey-Jennings: Attention and the Self
Publicado: 18/11/2022 -
BI 152 Michael L. Anderson: After Phrenology: Neural Reuse
Publicado: 8/11/2022 -
BI 151 Steve Byrnes: Brain-like AGI Safety
Publicado: 30/10/2022 -
BI 150 Dan Nicholson: Machines, Organisms, Processes
Publicado: 15/10/2022 -
BI 149 William B. Miller: Cell Intelligence
Publicado: 5/10/2022 -
BI 148 Gaute Einevoll: Brain Simulations
Publicado: 25/9/2022 -
BI 147 Noah Hutton: In Silico
Publicado: 13/9/2022 -
BI 146 Lauren Ross: Causal and Non-Causal Explanation
Publicado: 7/9/2022 -
BI 145 James Woodward: Causation with a Human Face
Publicado: 28/8/2022 -
BI 144 Emily M. Bender and Ev Fedorenko: Large Language Models
Publicado: 17/8/2022 -
BI 143 Rodolphe Sepulchre: Mixed Feedback Control
Publicado: 5/8/2022 -
BI 142 Cameron Buckner: The New DoGMA
Publicado: 26/7/2022 -
BI 141 Carina Curto: From Structure to Dynamics
Publicado: 12/7/2022 -
BI 140 Jeff Schall: Decisions and Eye Movements
Publicado: 30/6/2022 -
BI 139 Marc Howard: Compressed Time and Memory
Publicado: 20/6/2022 -
BI 138 Matthew Larkum: The Dendrite Hypothesis
Publicado: 6/6/2022 -
BI 137 Brian Butterworth: Can Fish Count?
Publicado: 27/5/2022 -
BI 136 Michel Bitbol and Alex Gomez-Marin: Phenomenology
Publicado: 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.
