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. Head to braininspired.co for the show notes.

BI 005 David Sussillo: RNNs are Back!

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. To hear the whole episode, go to https://braininspired.co/podcast/bi-001-steven-potter-brains-in-dishes/

BI 001 Steven Potter: Brains in Dishes

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. To hear the whole episode, go to:

https://braininspired.co/podcast/bi-003-blake-porter-effortful-rats/

BI 003 Blake Porter: Effortful Rats

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. To hear the whole episode, go to:

https://braininspired.co/podcast/bi-004-mark-humphries-learning-to-remember/

BI 004 Mark Humphries: Learning to Remember

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. To hear the whole episode, go to:

https://braininspired.co/podcast/bi-006-ryan-poplin-deep-solutions/

BI 006 Ryan Poplin: Deep Solutions

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. To hear the whole episode, go to:

https://braininspired.co/podcast/7/

BI 007: Infant AI and Visual Cortex

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. To hear the whole episode, go to:

https://braininspired.co/podcast/8/

BI 008 Josh Glaser: ML for Neuroscience

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. To hear the whole episode, go to:

https://braininspired.co/podcast/9/

BI 009 Blake Richards: Deep Learning in the Brain

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. To hear the whole episode, go to:

https://braininspired.co/podcast/10/

BI 010 Adam Marblestone: Brain Cost Functions

Neuroscience and artificial intelligence work better together. I interview experts about their thoughts and discoveries at the interface of neuroscience and artificial intelligence. The symbiosis of the two fields, how they overlap, how machine learning informs neuroscience, how neuroscience informs machine learning and other AI tools, how they differ, what the past brought us, and what the future holds.

Brain Inspired