All Episodes

BI 011 Grace Lindsay: Visual Attention in CNNs

BI 011 Grace Lindsay: Visual Attention in CNNs

Brain Inspired
Brain Inspired
BI 011 Grace Lindsay: Visual Attention in CNNs
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Grace shares her recent work adding an attention signal to convolutional neural networks – ones that emulate the ventral visual stream in the brain – to test the “feature gain similarity” model of attention. Lots more, of course. Click the show to access the show notes.

BI 010 Adam Marblestone: Brain Cost Functions

BI 010 Adam Marblestone: Brain Cost Functions

Brain Inspired
Brain Inspired
BI 010 Adam Marblestone: Brain Cost Functions
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Adam and I discuss the possibility there are cost functions optimized in the brain, where and how it might work, Marvin Minsky’s Society of Mind, and lots more.

BI 009 Blake Richards: Deep Learning in the Brain

BI 009 Blake Richards: Deep Learning in the Brain

Brain Inspired
Brain Inspired
BI 009 Blake Richards: Deep Learning in the Brain
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Blake and I discuss his recent work exploring one way credit assignment could occur in the brain, using different regions within a single cortical neuron to encode the necessary signal.

BI 008 Joshua Glaser: Supervised ML for Neuroscience

BI 008 Joshua Glaser: Supervised ML for Neuroscience

Brain Inspired
Brain Inspired
BI 008 Joshua Glaser: Supervised ML for Neuroscience
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Josh and I talk about all the ways supervised machine learning can be used in neuroscience research, and we walk through how a variety of machine learning algorithms perform decoding on a few neural data sets.

BI 007 Daniel Yamins: Infant AI and CNNs

BI 007 Daniel Yamins: Infant AI and CNNs

Brain Inspired
Brain Inspired
BI 007 Daniel Yamins: Infant AI and CNNs
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In this episode, Dan Yamins and I talk about how he uses hierarchical convolutional neural networks to model the ventral visual stream, finding that the units in his model correspond to neurons in progressive layers of the brain. We also delve into the AI agents he develops that learn how to play through intrinsic motivation. Click the episode to get the show notes.

BI 006 Ryan Poplin: Deep Solutions

BI 006 Ryan Poplin: Deep Solutions

Brain Inspired
Brain Inspired
BI 006 Ryan Poplin: Deep Solutions
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Ryan and I go deep (pun intended) on convolutional neural networks and how he uses them to solve problems in medical risk factor discovery and improve genome sequencing, and more. Click the episode for the show notes

BI 005 David Sussillo: RNNs are Back!

BI 005 David Sussillo: RNNs are Back!

Brain Inspired
Brain Inspired
BI 005 David Sussillo: RNNs are Back!
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David and I cover recurrent neural networks (RNNs), his work using RNNs to study motor brain processes, how dynamical systems theory is a useful approach to brains and AI, and more. Click the episode for the show notes.

BI 004 Mark Humphries: Learning to Remember

BI 004 Mark Humphries: Learning to Remember

Brain Inspired
Brain Inspired
BI 004 Mark Humphries: Learning to Remember
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What does it mean to be a neural data scientist? Mark and I talk about that, his work discovering how rat prefrontal cortex learns to remember, and a bunch of AI topics he’s written about via his Medium blog. Click the episode for the show notes

BI 003 Blake Porter: Effortful Rats

BI 003 Blake Porter: Effortful Rats

Brain Inspired
Brain Inspired
BI 003 Blake Porter: Effortful Rats
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Blake and I talk about his work studying effort and decision making in the hippocampus of rats, how AI bots are taking over the gaming world, and more. Click the episode for the show notes

BI 002 Steven Potter Part 2: Brains in Dishes

BI 002 Steven Potter Part 2: Brains in Dishes

Brain Inspired
Brain Inspired
BI 002 Steven Potter Part 2: Brains in Dishes
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We talk about how he got the embodied cultured networks to actually work, the hurdles they had to jump through, the rise of citizen science, the Maker movement, and more. Click the episode for the show notes

BI 001 Steven Potter: Brains in Dishes

BI 001 Steven Potter: Brains in Dishes

Brain Inspired
Brain Inspired
BI 001 Steven Potter: Brains in Dishes
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We talk about his embodied cultured networks, the neuron-robot hybrid system, how brains work and learn and how that’s related to AI, and more. Click the episode for the show notes