
Talia and I discuss her work on how our visual system is organized topographically, and divides into three main categories: big inanimate things, small inanimate things, and animals. Her work is unique in that it focuses not on the classic hierarchical processing of vision (though she does that, too), but what kinds of things are represented along that hierarchy. She also uses deep networks to learn more about the visual system. We also talk about her keynote talk at the Cognitive Computational Neuroscience conference and plenty more.
Show notes:
Show notes: DeepMind. The papers we discuss: Neuroscience-Inspired Artificial Intelligence. A nice summary of the meta-reinforcement learning work. Learning to reinforcement learn. Prefrontal cortex...
[bctt tweet="Check out episode 6 of the Brain Inspired podcast: Deep learning, eyeballs, and brains" username="pgmid"] Mentioned in the show Ryan Poplin What is...