Check out episode 6 of the Brain Inspired podcast: Deep learning, eyeballs, and brainsClick To Tweet


Mentioned in the show

Ryan Poplin
What is a convolutional neural network?

Here’s a good summary. Here’s another good summary.


Deep learning on eye images: CV risk factors can be predicted from retinal fundus images
DeepVariant: Deep learning on genomics

The paper: Creating a universal SNP and small indel variant caller with deep neural networks
A nice, less technical summary of the work
The code on Github



 

Check out episode 6 of the Brain Inspired podcast: Deep learning, eyeballs, and brainsClick To Tweet Mentioned in the show Ryan Poplin What is a convolutional neural network? Here’s a good summary. Here’s another good summary. Deep learning on eye images: CV risk factors can be predicted from retinal fundus images DeepVariant: Deep learning on genomics The paper: Creating a universal SNP and small indel variant caller with deep neural networks A nice, less technical summary of the work The code on Github

Check out episode 6 of the Brain Inspired podcast: Deep learning, eyeballs, and brainsClick To Tweet


Mentioned in the show

Ryan Poplin
What is a convolutional neural network?

Here’s a good summary. Here’s another good summary.


Deep learning on eye images: CV risk factors can be predicted from retinal fundus images
DeepVariant: Deep learning on genomics

The paper:&nbsp;Creating a universal SNP and small indel variant caller with deep neural networks
A nice, less technical summary of the work
The code on Github



&nbsp;

BI 006 Ryan Poplin: Deep Solutions

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.

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BI 006 Ryan Poplin: Deep Solutions

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