Brain Inspired
Podcast autorstwa Paul Middlebrooks - Środy
155 Odcinki
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BI 214 Nicole Rust: How To Actually Fix Brains and Minds
Opublikowany: 18.06.2025 -
BI 213 Representations in Minds and Brains
Opublikowany: 4.06.2025 -
BI 212 John Beggs: Why Brains Seek the Edge of Chaos
Opublikowany: 21.05.2025 -
BI 211 COGITATE: Testing Theories of Consciousness
Opublikowany: 7.05.2025 -
BI 210 Dean Buonomano: Consciousness, Time, and Organotypic Dynamics
Opublikowany: 22.04.2025 -
BI 209 Aran Nayebi: The NeuroAI Turing Test
Opublikowany: 9.04.2025 -
BI 208 Gabriele Scheler: From Verbal Thought to Neuron Computation
Opublikowany: 26.03.2025 -
BI 207 Alison Preston: Schemas in our Brains and Minds
Opublikowany: 12.03.2025 -
Quick Announcement: Complexity Group
Opublikowany: 5.03.2025 -
BI 206 Ciara Greene: Memories Are Useful, Not Accurate
Opublikowany: 26.02.2025 -
BI 205 Dmitri Chklovskii: Neurons Are Smarter Than You Think
Opublikowany: 12.02.2025 -
BI 204 David Robbe: Your Brain Doesn’t Measure Time
Opublikowany: 29.01.2025 -
BI 203 David Krakauer: How To Think Like a Complexity Scientist
Opublikowany: 14.01.2025 -
BI 202 Eli Sennesh: Divide-and-Conquer to Predict
Opublikowany: 3.01.2025 -
BI 201 Rajesh Rao: From Predictive Coding to Brain Co-Processors
Opublikowany: 18.12.2024 -
BI 200 Grace Hwang and Joe Monaco: The Future of NeuroAI
Opublikowany: 4.12.2024 -
BI 199 Hessam Akhlaghpour: Natural Universal Computation
Opublikowany: 26.11.2024 -
BI 198 Tony Zador: Neuroscience Principles to Improve AI
Opublikowany: 11.11.2024 -
BI 197 Karen Adolph: How Babies Learn to Move and Think
Opublikowany: 25.10.2024 -
BI 196 Cristina Savin and Tim Vogels with Gaute Einevoll and Mikkel Lepperød
Opublikowany: 11.10.2024
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.
