Brain Inspired
Un podcast de Paul Middlebrooks - Les mercredis
166 Épisodes
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BI 206 Ciara Greene: Memories Are Useful, Not Accurate
Publié: 26/02/2025 -
BI 205 Dmitri Chklovskii: Neurons Are Smarter Than You Think
Publié: 12/02/2025 -
BI 204 David Robbe: Your Brain Doesn’t Measure Time
Publié: 29/01/2025 -
BI 203 David Krakauer: How To Think Like a Complexity Scientist
Publié: 14/01/2025 -
BI 202 Eli Sennesh: Divide-and-Conquer to Predict
Publié: 03/01/2025 -
BI 201 Rajesh Rao: From Predictive Coding to Brain Co-Processors
Publié: 18/12/2024 -
BI 200 Grace Hwang and Joe Monaco: The Future of NeuroAI
Publié: 04/12/2024 -
BI 199 Hessam Akhlaghpour: Natural Universal Computation
Publié: 26/11/2024 -
BI 198 Tony Zador: Neuroscience Principles to Improve AI
Publié: 11/11/2024 -
BI 197 Karen Adolph: How Babies Learn to Move and Think
Publié: 25/10/2024 -
BI 196 Cristina Savin and Tim Vogels with Gaute Einevoll and Mikkel Lepperød
Publié: 11/10/2024 -
BI 195 Ken Harris and Andreas Tolias with Gaute Einevoll and Mikkel Lepperød
Publié: 08/10/2024 -
BI 194 Vijay Namboodiri & Ali Mohebi: Dopamine Keeps Getting More Interesting
Publié: 27/09/2024 -
BI 193 Kim Stachenfeld: Enhancing Neuroscience and AI
Publié: 11/09/2024 -
BI 192 Àlex Gómez-Marín: The Edges of Consciousness
Publié: 28/08/2024 -
BI 191 Damian Kelty-Stephen: Fractal Turbulent Cascading Intelligence
Publié: 15/08/2024 -
BI 190 Luis Favela: The Ecological Brain
Publié: 31/07/2024 -
BI 189 Joshua Vogelstein: Connectomes and Prospective Learning
Publié: 29/06/2024 -
BI 188 Jolande Fooken: Coordinating Action and Perception
Publié: 27/05/2024 -
BI 187: COSYNE 2024 Neuro-AI Panel
Publié: 20/04/2024
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.
