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BI 125 Doris Tsao, Tony Zador, Blake Richards: NAISys

BI 125 Doris Tsao, Tony Zador, Blake Richards: NAISys

FromBrain Inspired


BI 125 Doris Tsao, Tony Zador, Blake Richards: NAISys

FromBrain Inspired

ratings:
Length:
71 minutes
Released:
Jan 19, 2022
Format:
Podcast episode

Description

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Doris, Tony, and Blake are the organizers for this year's NAISys conference, From Neuroscience to Artificially Intelligent Systems (NAISys), at Cold Spring Harbor. We discuss the conference itself, some history of the neuroscience and AI interface, their current research interests, and a handful of topics around evolution, innateness, development, learning, and the current and future prospects for using neuroscience to inspire new ideas in artificial intelligence.





From Neuroscience to Artificially Intelligent Systems (NAISys).Doris:@doristsao.Tsao Lab.Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons.Tony:@TonyZador.Zador Lab.A Critique of Pure Learning: What Artificial Neural Networks can Learn from Animal Brains.Blake:@tyrell_turing.The Learning in Neural Circuits Lab.The functional specialization of visual cortex emerges from training parallel pathways with self-supervised predictive learning.





0:00 - Intro
4:16 - Tony Zador
5:38 - Doris Tsao
10:44 - Blake Richards
15:46 - Deductive, inductive, abductive inference
16:32 - NAISys
33:09 - Evolution, development, learning
38:23 - Learning: plasticity vs. dynamical structures
54:13 - Different kinds of understanding
1:03:05 - Do we understand evolution well enough?
1:04:03 - Neuro-AI fad?
1:06:26 - Are your problems bigger or smaller now?
Released:
Jan 19, 2022
Format:
Podcast episode

Titles in the series (99)

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.