Brain Inspired
En podkast av Paul Middlebrooks - Onsdager
163 Episoder
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BI 222 Nikolay Kukushkin: Minds and Meaning from Nature’s Ideas
Publisert: 8.10.2025 -
BI 221 Ann Kennedy: Theory Beneath the Cortical Surface
Publisert: 24.9.2025 -
BI 220 Michael Breakspear and Mac Shine: Dynamic Systems from Neurons to Brains
Publisert: 10.9.2025 -
BI 219 Xaq Pitkow: Principles and Constraints of Cognition
Publisert: 27.8.2025 -
BI 218 Chris Rozell: Brain Stimulation and AI for Mental Disorders
Publisert: 13.8.2025 -
BI 217 Jennifer Prendki: Consciousness, Life, AI, and Quantum Physics
Publisert: 30.7.2025 -
BI 216 Woodrow Shew and Keith Hengen: The Nature of Brain Criticality
Publisert: 16.7.2025 -
BI 215 Xiao-Jing Wang: Theoretical Neuroscience Comes of Age
Publisert: 2.7.2025 -
BI 214 Nicole Rust: How To Actually Fix Brains and Minds
Publisert: 18.6.2025 -
BI 213 Representations in Minds and Brains
Publisert: 4.6.2025 -
BI 212 John Beggs: Why Brains Seek the Edge of Chaos
Publisert: 21.5.2025 -
BI 211 COGITATE: Testing Theories of Consciousness
Publisert: 7.5.2025 -
BI 210 Dean Buonomano: Consciousness, Time, and Organotypic Dynamics
Publisert: 22.4.2025 -
BI 209 Aran Nayebi: The NeuroAI Turing Test
Publisert: 9.4.2025 -
BI 208 Gabriele Scheler: From Verbal Thought to Neuron Computation
Publisert: 26.3.2025 -
BI 207 Alison Preston: Schemas in our Brains and Minds
Publisert: 12.3.2025 -
Quick Announcement: Complexity Group
Publisert: 5.3.2025 -
BI 206 Ciara Greene: Memories Are Useful, Not Accurate
Publisert: 26.2.2025 -
BI 205 Dmitri Chklovskii: Neurons Are Smarter Than You Think
Publisert: 12.2.2025 -
BI 204 David Robbe: Your Brain Doesn’t Measure Time
Publisert: 29.1.2025
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.
