Brain Inspired
A podcast by Paul Middlebrooks - Wednesdays
164 Episodes
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BI 204 David Robbe: Your Brain Doesn’t Measure Time
Published: 29/01/2025 -
BI 203 David Krakauer: How To Think Like a Complexity Scientist
Published: 14/01/2025 -
BI 202 Eli Sennesh: Divide-and-Conquer to Predict
Published: 03/01/2025 -
BI 201 Rajesh Rao: From Predictive Coding to Brain Co-Processors
Published: 18/12/2024 -
BI 200 Grace Hwang and Joe Monaco: The Future of NeuroAI
Published: 04/12/2024 -
BI 199 Hessam Akhlaghpour: Natural Universal Computation
Published: 26/11/2024 -
BI 198 Tony Zador: Neuroscience Principles to Improve AI
Published: 11/11/2024 -
BI 197 Karen Adolph: How Babies Learn to Move and Think
Published: 25/10/2024 -
BI 196 Cristina Savin and Tim Vogels with Gaute Einevoll and Mikkel Lepperød
Published: 11/10/2024 -
BI 195 Ken Harris and Andreas Tolias with Gaute Einevoll and Mikkel Lepperød
Published: 08/10/2024 -
BI 194 Vijay Namboodiri & Ali Mohebi: Dopamine Keeps Getting More Interesting
Published: 27/09/2024 -
BI 193 Kim Stachenfeld: Enhancing Neuroscience and AI
Published: 11/09/2024 -
BI 192 Àlex Gómez-Marín: The Edges of Consciousness
Published: 28/08/2024 -
BI 191 Damian Kelty-Stephen: Fractal Turbulent Cascading Intelligence
Published: 15/08/2024 -
BI 190 Luis Favela: The Ecological Brain
Published: 31/07/2024 -
BI 189 Joshua Vogelstein: Connectomes and Prospective Learning
Published: 29/06/2024 -
BI 188 Jolande Fooken: Coordinating Action and Perception
Published: 27/05/2024 -
BI 187: COSYNE 2024 Neuro-AI Panel
Published: 20/04/2024 -
BI 186 Mazviita Chirimuuta: The Brain Abstracted
Published: 25/03/2024 -
BI 185 Eric Yttri: Orchestrating Behavior
Published: 06/03/2024
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.
