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BI 186 Mazviita Chirimuuta: The Brain Abstracted

BI 186 Mazviita Chirimuuta: The Brain Abstracted

FromBrain Inspired


BI 186 Mazviita Chirimuuta: The Brain Abstracted

FromBrain Inspired

ratings:
Length:
104 minutes
Released:
Mar 25, 2024
Format:
Podcast episode

Description

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Mazviita Chirimuuta is a philosopher at the University of Edinburgh. Today we discuss topics from her new book, The Brain Abstracted: Simplification in the History and Philosophy of Neuroscience.



She largely argues that when we try to understand something complex, like the brain, using models, and math, and analogies, for example - we should keep in mind these are all ways of simplifying and abstracting away details to give us something we actually can understand. And, when we do science, every tool we use and perspective we bring, every way we try to attack a problem, these are all both necessary to do the science and limit the interpretation we can claim from our results. She does all this and more by exploring many topics in neuroscience and philosophy throughout the book, many of which we discuss today.






Mazviita's University of Edinburgh page.



The Brain Abstracted: Simplification in the History and Philosophy of Neuroscience.



Previous Brain Inspired episodes:

BI 072 Mazviita Chirimuuta: Understanding, Prediction, and Reality



BI 114 Mark Sprevak and Mazviita Chirimuuta: Computation and the Mind






0:00 - Intro
5:28 - Neuroscience to philosophy
13:39 - Big themes of the book
27:44 - Simplifying by mathematics
32:19 - Simplifying by reduction
42:55 - Simplification by analogy
46:33 - Technology precedes science
55:04 - Theory, technology, and understanding
58:04 - Cross-disciplinary progress
58:45 - Complex vs. simple(r) systems
1:08:07 - Is science bound to study stability?
1:13:20 - 4E for philosophy but not neuroscience?
1:28:50 - ANNs as models
1:38:38 - Study of mind
Released:
Mar 25, 2024
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.