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BI 159 Chris Summerfield: Natural General Intelligence

BI 159 Chris Summerfield: Natural General Intelligence

FromBrain Inspired


BI 159 Chris Summerfield: Natural General Intelligence

FromBrain Inspired

ratings:
Length:
89 minutes
Released:
Jan 26, 2023
Format:
Podcast episode

Description

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Chris Summerfield runs the Human Information Processing Lab at University of Oxford, and he's a research scientist at Deepmind. You may remember him from episode 95 with Sam Gershman, when we discussed ideas around the usefulness of neuroscience and psychology for AI. Since then, Chris has released his book, Natural General Intelligence: How understanding the brain can help us build AI. In the book, Chris makes the case that inspiration and communication between the cognitive sciences and AI is hindered by the different languages each field speaks. But in reality, there has always been and still is a lot of overlap and convergence about ideas of computation and intelligence, and he illustrates this using tons of historical and modern examples.






Human Information Processing Lab.



Twitter: @summerfieldlab.



Book: Natural General Intelligence: How understanding the brain can help us build AI.



Other books mentioned:

Are We Smart Enough to Know How Smart Animals Are? by Frans de Waal



The Mind is Flat by Nick Chater.






0:00 - Intro
2:20 - Natural General Intelligence
8:05 - AI and Neuro interaction
21:42 - How to build AI
25:54 - Umwelts and affordances
32:07 - Different kind of intelligence
39:16 - Ecological validity and AI
48:30 - Is reward enough?
1:05:14 - Beyond brains
1:15:10 - Large language models and brains
Released:
Jan 26, 2023
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.