Galit and I discuss the independent roles of prediction and explanation in scientific models, their history and eventual separation in the philosophy of science, how they can inform each other, and how statisticians like Galit view the current deep learning explosion.
Mentioned in the show: Dan’s Stanford Neuroscience and Artificial Intelligence Laboratory: The 2 papers we discuss Performance-optimized hierarchical models predict neural responses in higher...
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Support the Podcast David and I talk about his work to understand how sound waves floating in the air get transformed into meaningful concepts...
