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Today I'm in conversation with Rajesh Rao, a distinguished professor of computer science and engineering at the University of Washington, where he also co-directs the Center for Neurotechnology. Back in 1999, Raj and Dana Ballard published what became quite a famous paper, which proposed how predictive coding might be implemented in brains. What is predictive coding, you may be wondering? It's roughly the idea that your brain is constantly predicting incoming sensory signals, and it generates that prediction as a top-down signal that meets the bottom-up sensory signals. Then the brain computes a difference between the prediction and the actual sensory input, and that difference is sent back up to the "top" where the brain then updates its internal model to make better future predictions.
So that was 25 years ago, and it was focused on how the brain handles sensory information. But Raj just recently published an update to the predictive coding framework, one that incorporates actions and perception, suggests how it might be implemented in the cortex - specifically which cortical layers do what - something he calls "Active predictive coding." So we discuss that new proposal, we also talk about his engineering work on brain-computer interface technologies, like BrainNet, which basically connects two brains together, and like neural co-processors, which use an artificial neural network as a prosthetic that can do things like enhance memories, optimize learning, and help restore brain function after strokes, for example. Finally, we discuss Raj's interest and work on deciphering an ancient Indian text, the mysterious Indus script.
Read the transcript.
0:00 - Intro
By Paul Middlebrooks4.8
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Support the show to get full episodes, full archive, and join the Discord community.
Today I'm in conversation with Rajesh Rao, a distinguished professor of computer science and engineering at the University of Washington, where he also co-directs the Center for Neurotechnology. Back in 1999, Raj and Dana Ballard published what became quite a famous paper, which proposed how predictive coding might be implemented in brains. What is predictive coding, you may be wondering? It's roughly the idea that your brain is constantly predicting incoming sensory signals, and it generates that prediction as a top-down signal that meets the bottom-up sensory signals. Then the brain computes a difference between the prediction and the actual sensory input, and that difference is sent back up to the "top" where the brain then updates its internal model to make better future predictions.
So that was 25 years ago, and it was focused on how the brain handles sensory information. But Raj just recently published an update to the predictive coding framework, one that incorporates actions and perception, suggests how it might be implemented in the cortex - specifically which cortical layers do what - something he calls "Active predictive coding." So we discuss that new proposal, we also talk about his engineering work on brain-computer interface technologies, like BrainNet, which basically connects two brains together, and like neural co-processors, which use an artificial neural network as a prosthetic that can do things like enhance memories, optimize learning, and help restore brain function after strokes, for example. Finally, we discuss Raj's interest and work on deciphering an ancient Indian text, the mysterious Indus script.
Read the transcript.
0:00 - Intro

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