Brain Inspired
Un pódcast de Paul Middlebrooks - Miercoles
155 Episodo
-
BI 214 Nicole Rust: How To Actually Fix Brains and Minds
Publicado: 18/6/2025 -
BI 213 Representations in Minds and Brains
Publicado: 4/6/2025 -
BI 212 John Beggs: Why Brains Seek the Edge of Chaos
Publicado: 21/5/2025 -
BI 211 COGITATE: Testing Theories of Consciousness
Publicado: 7/5/2025 -
BI 210 Dean Buonomano: Consciousness, Time, and Organotypic Dynamics
Publicado: 22/4/2025 -
BI 209 Aran Nayebi: The NeuroAI Turing Test
Publicado: 9/4/2025 -
BI 208 Gabriele Scheler: From Verbal Thought to Neuron Computation
Publicado: 26/3/2025 -
BI 207 Alison Preston: Schemas in our Brains and Minds
Publicado: 12/3/2025 -
Quick Announcement: Complexity Group
Publicado: 5/3/2025 -
BI 206 Ciara Greene: Memories Are Useful, Not Accurate
Publicado: 26/2/2025 -
BI 205 Dmitri Chklovskii: Neurons Are Smarter Than You Think
Publicado: 12/2/2025 -
BI 204 David Robbe: Your Brain Doesn’t Measure Time
Publicado: 29/1/2025 -
BI 203 David Krakauer: How To Think Like a Complexity Scientist
Publicado: 14/1/2025 -
BI 202 Eli Sennesh: Divide-and-Conquer to Predict
Publicado: 3/1/2025 -
BI 201 Rajesh Rao: From Predictive Coding to Brain Co-Processors
Publicado: 18/12/2024 -
BI 200 Grace Hwang and Joe Monaco: The Future of NeuroAI
Publicado: 4/12/2024 -
BI 199 Hessam Akhlaghpour: Natural Universal Computation
Publicado: 26/11/2024 -
BI 198 Tony Zador: Neuroscience Principles to Improve AI
Publicado: 11/11/2024 -
BI 197 Karen Adolph: How Babies Learn to Move and Think
Publicado: 25/10/2024 -
BI 196 Cristina Savin and Tim Vogels with Gaute Einevoll and Mikkel Lepperød
Publicado: 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.
