Brain Inspired
Podcast autorstwa Paul Middlebrooks - Środy
164 Odcinki
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BI 223 Vicente Raja: Ecological Psychology Motifs in Neuroscience
Opublikowany: 22.10.2025 -
BI 222 Nikolay Kukushkin: Minds and Meaning from Nature’s Ideas
Opublikowany: 8.10.2025 -
BI 221 Ann Kennedy: Theory Beneath the Cortical Surface
Opublikowany: 24.09.2025 -
BI 220 Michael Breakspear and Mac Shine: Dynamic Systems from Neurons to Brains
Opublikowany: 10.09.2025 -
BI 219 Xaq Pitkow: Principles and Constraints of Cognition
Opublikowany: 27.08.2025 -
BI 218 Chris Rozell: Brain Stimulation and AI for Mental Disorders
Opublikowany: 13.08.2025 -
BI 217 Jennifer Prendki: Consciousness, Life, AI, and Quantum Physics
Opublikowany: 30.07.2025 -
BI 216 Woodrow Shew and Keith Hengen: The Nature of Brain Criticality
Opublikowany: 16.07.2025 -
BI 215 Xiao-Jing Wang: Theoretical Neuroscience Comes of Age
Opublikowany: 2.07.2025 -
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
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.
