Brain Inspired
Podcast tekijän mukaan Paul Middlebrooks - Keskiviikkoisin
164 Jaksot
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BI 204 David Robbe: Your Brain Doesn’t Measure Time
Julkaistiin: 29.1.2025 -
BI 203 David Krakauer: How To Think Like a Complexity Scientist
Julkaistiin: 14.1.2025 -
BI 202 Eli Sennesh: Divide-and-Conquer to Predict
Julkaistiin: 3.1.2025 -
BI 201 Rajesh Rao: From Predictive Coding to Brain Co-Processors
Julkaistiin: 18.12.2024 -
BI 200 Grace Hwang and Joe Monaco: The Future of NeuroAI
Julkaistiin: 4.12.2024 -
BI 199 Hessam Akhlaghpour: Natural Universal Computation
Julkaistiin: 26.11.2024 -
BI 198 Tony Zador: Neuroscience Principles to Improve AI
Julkaistiin: 11.11.2024 -
BI 197 Karen Adolph: How Babies Learn to Move and Think
Julkaistiin: 25.10.2024 -
BI 196 Cristina Savin and Tim Vogels with Gaute Einevoll and Mikkel Lepperød
Julkaistiin: 11.10.2024 -
BI 195 Ken Harris and Andreas Tolias with Gaute Einevoll and Mikkel Lepperød
Julkaistiin: 8.10.2024 -
BI 194 Vijay Namboodiri & Ali Mohebi: Dopamine Keeps Getting More Interesting
Julkaistiin: 27.9.2024 -
BI 193 Kim Stachenfeld: Enhancing Neuroscience and AI
Julkaistiin: 11.9.2024 -
BI 192 Àlex Gómez-Marín: The Edges of Consciousness
Julkaistiin: 28.8.2024 -
BI 191 Damian Kelty-Stephen: Fractal Turbulent Cascading Intelligence
Julkaistiin: 15.8.2024 -
BI 190 Luis Favela: The Ecological Brain
Julkaistiin: 31.7.2024 -
BI 189 Joshua Vogelstein: Connectomes and Prospective Learning
Julkaistiin: 29.6.2024 -
BI 188 Jolande Fooken: Coordinating Action and Perception
Julkaistiin: 27.5.2024 -
BI 187: COSYNE 2024 Neuro-AI Panel
Julkaistiin: 20.4.2024 -
BI 186 Mazviita Chirimuuta: The Brain Abstracted
Julkaistiin: 25.3.2024 -
BI 185 Eric Yttri: Orchestrating Behavior
Julkaistiin: 6.3.2024
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.
