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Brain InspiredWhere Neuroscience and AI Converge Author: Paul Middlebrooks
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. Language: en-us Genres: Natural Sciences, Science, Technology Contact email: Get it Feed URL: Get it iTunes ID: Get it |
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BI 224 Dan Nicholson: Schrödinger’s What is Life? Revisited
Wednesday, 5 November, 2025
Support the show to get full episodes, full archive, and join the Discord community. The Transmitter is an online publication that aims to deliver useful information, insights and tools to build bridges across neuroscience and advance research. Visit thetransmitter.org to explore the latest neuroscience news and perspectives, written by journalists and scientists. Read more about our partnership. Sign up for Brain Inspired email alerts to be notified every time a new Brain Inspired episode is released. To explore more neuroscience news and perspectives, visit thetransmitter.org. My guest today is Dan Nicholson, Assistant Professor of Philosophy at George Mason University, here to talk about his little book, What Is Life? Revisited. Erwin Schrödinger's What Is Life is a famous book that people point to as having predicted DNA and influenced and inspired many well-known biologists ushering in the molecular biology revolution. But Schrödinger was a physicist, not a biologist, and he spent very little time and effort toward understanding biology. What was he up to, why did he write this "famous little book"? Schrödinger had an agenda, a physics agenda. He wanted to save the older deterministic version of quantum physics from the new indeterministic version. When Dan was on the podcast a few years ago, we talked about the machine view of biological systems, how everything has become a "mechanism", and how that view fails to capture what modern science is actually telling us, that organisms are unlike machines in important ways. That work of Dan's led him down this path to Schrödinger's What Is Life, which he argues was a major contributor to that machine metaphor so ubiquitous today in biology. One of the reasons I'm interested in this kind of work is because the cognitive sciences, including neuroscience and artificial intelligence, inherited this mechanistic perspective, and swallowed it so hard that if you don't include the word "mechanism" in your research paper, you're vastly decreasing your chances of getting your work published, when in fact the mechanistic perspective is one super useful perspective among many. Dan’s website. Google Scholar. Social: @NicholsonHPBio; @djnicholson.bsky.social What Is Life? Revisited Previous episode: BI 150 Dan Nicholson: Machines, Organisms, Processes Read the transcript. 0:00 - Intro 7:27 - Why Schrodinger wrote What is Life 15:13 - Aperiodic crystal and the meaning of code 21:39 - Order-from-order, order-from-disorder 28:32 - Appeal to authority 37:48 - Cell as machine 39:33 - Relation between DNA and organism (development) 44:44 - Negentropy 53:54 - Original contributions 58:54 - Mechanistic metaphor in neuroscience 1:16:05 - What's the lesson? 1:28:06 - Historical sleuthing 1:39:49 - Modern philosophy of biology
