Noah Hutton writes, directs, and scores documentary and narrative films. On this episode, we discuss his documentary In Silico. In 2009, Noah watched a TED talk by Henry Markram, in which Henry claimed it would take 10 years to fully simulate a human brain. This claim inspired Noah to chronicle the project, visiting Henry and his team periodically throughout. The result was In Silico, which tells the science, human, and social story of Henry’s massively funded projects – the Blue Brain Project and the Human Brain Project.
Lauren Ross is an Associate Professor at the University of California, Irvine. She studies and writes about causal and non-causal explanations in philosophy of science, including distinctions among causal structures. Throughout her work, Lauren employs Jame’s Woodward’s interventionist approach to causation, which Jim and I discussed in episode 145. In this episode, we discuss Jim’s lasting impact on the philosophy of causation, the current dominance of mechanistic explanation and its relation to causation, and various causal structures of explanation, including pathways, cascades, topology, and constraints.
James Woodward is a recently retired Professor from the Department of History and Philosophy of Science at the University of Pittsburgh. Jim has tremendously influenced the field of causal explanation in the philosophy of science. His account of causation centers around intervention – intervening on a cause should alter its effect. From this minimal notion, Jim has described many facets and varieties of causal structures. In this episode, we discuss topics from his recent book, Causation with a Human Face: Normative Theory and Descriptive Psychology. In the book, Jim advocates that how we should think about causality – the normative – needs to be studied together with how we actually do think about causal relations in the world – the descriptive. We discuss many topics around this central notion, epistemology versus metaphysics, the the nature and varieties of causal structures.
Large language models, often now called “foundation models”, are the model de jour in AI, based on the transformer architecture. In this episode, I bring together Evelina Fedorenko and Emily M. Bender to discuss how language models stack up to our own language processing and generation (models and brains both excel at next-word prediction), whether language evolved in humans for complex thoughts or for communication (communication, says Ev), whether language models grasp the meaning of the text they produce (Emily says no), and much more.
Rodolphe Sepulchre is a control engineer and theorist at Cambridge University. He focuses on applying feedback control engineering principles to build circuits that model neurons and neuronal circuits. We discuss his work on mixed feedback control – positive and negative – as an underlying principle of the mixed digital and analog brain signals,, the role of neuromodulation as a controller, applying these principles to Eve Marder’s lobster/crab neural circuits, building mixed-feedback neuromorphics, some feedback control history, and how “If you wish to contribute original work, be prepared to face loneliness,” among other topics
