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BI 044 Talia Konkle: Turning Vision On Its Side

BI 044 Talia Konkle: Turning Vision On Its Side

FromBrain Inspired


BI 044 Talia Konkle: Turning Vision On Its Side

FromBrain Inspired

ratings:
Length:
76 minutes
Released:
Aug 18, 2019
Format:
Podcast episode

Description

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:



Talia’s lab website. Follow her on twitter: @talia_konkle. Check out the Cognitive Computational Neuroscience conference, where she'll give a keynote address.Papers we discuss/reference: Early work on the tripartite organization. Tripartite Organization of the Ventral Stream by Animacy and Object Size. A more recent update, with the texforms we discuss and comparision too deep learning CNN networks used to model the ventral visual stream. Mid-level visual features underlie the high-level categorical organization of the ventral stream.The article Talia references about an elegant solution to an old problem in computer science.
Released:
Aug 18, 2019
Format:
Podcast episode

Titles in the series (100)

Neuroscience and artificial intelligence work better together. Brain inspired is a celebration and exploration of the ideas driving our progress to understand intelligence. I interview experts about their work at the interface of neuroscience, artificial intelligence, cognitive science, philosophy, psychology, and more: the symbiosis of these overlapping fields, how they inform each other, where they differ, what the past brought us, and what the future brings. Topics include computational neuroscience, supervised machine learning, unsupervised learning, reinforcement learning, deep learning, convolutional and recurrent neural networks, decision-making science, AI agents, backpropagation, credit assignment, neuroengineering, neuromorphics, emergence, philosophy of mind, consciousness, general AI, spiking neural networks, data science, and a lot more. The podcast is not produced for a general audience. Instead, it aims to educate, challenge, inspire, and hopefully entertain those interested in learning more about neuroscience and AI.