Brain Inspired
Ein Podcast von Paul Middlebrooks - Mittwochs
153 Folgen
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BI 212 John Beggs: Why Brains Seek the Edge of Chaos
Vom: 21.5.2025 -
BI 211 COGITATE: Testing Theories of Consciousness
Vom: 7.5.2025 -
BI 210 Dean Buonomano: Consciousness, Time, and Organotypic Dynamics
Vom: 22.4.2025 -
BI 209 Aran Nayebi: The NeuroAI Turing Test
Vom: 9.4.2025 -
BI 208 Gabriele Scheler: From Verbal Thought to Neuron Computation
Vom: 26.3.2025 -
BI 207 Alison Preston: Schemas in our Brains and Minds
Vom: 12.3.2025 -
Quick Announcement: Complexity Group
Vom: 5.3.2025 -
BI 206 Ciara Greene: Memories Are Useful, Not Accurate
Vom: 26.2.2025 -
BI 205 Dmitri Chklovskii: Neurons Are Smarter Than You Think
Vom: 12.2.2025 -
BI 204 David Robbe: Your Brain Doesn’t Measure Time
Vom: 29.1.2025 -
BI 203 David Krakauer: How To Think Like a Complexity Scientist
Vom: 14.1.2025 -
BI 202 Eli Sennesh: Divide-and-Conquer to Predict
Vom: 3.1.2025 -
BI 201 Rajesh Rao: From Predictive Coding to Brain Co-Processors
Vom: 18.12.2024 -
BI 200 Grace Hwang and Joe Monaco: The Future of NeuroAI
Vom: 4.12.2024 -
BI 199 Hessam Akhlaghpour: Natural Universal Computation
Vom: 26.11.2024 -
BI 198 Tony Zador: Neuroscience Principles to Improve AI
Vom: 11.11.2024 -
BI 197 Karen Adolph: How Babies Learn to Move and Think
Vom: 25.10.2024 -
BI 196 Cristina Savin and Tim Vogels with Gaute Einevoll and Mikkel Lepperød
Vom: 11.10.2024 -
BI 195 Ken Harris and Andreas Tolias with Gaute Einevoll and Mikkel Lepperød
Vom: 8.10.2024 -
BI 194 Vijay Namboodiri & Ali Mohebi: Dopamine Keeps Getting More Interesting
Vom: 27.9.2024
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.
