This podcast was created entirely by AI and based on the following research paper:<ul><li>Title: Scaling Limits of Wide Neural Networks with Weight Sharing: Gaussian Process Behavior, Gradient Independence, and Neural Tangent Kernel Derivation</li><li>Source: arXiv</li><li>Authors: Greg Yang</li><li>Published Date: 2020-04-04</li></ul>Visit www.paper2podcast.com to download the full paper and learn more. Thanks for listening!

This podcast was created entirely by AI and based on the following research paper:Title: Scaling Limits of Wide Neural Networks with Weight Sharing: Gaussian Process Behavior, Gradient Independence, and Neural Tangent Kernel DerivationSource: arXivAuthors: Greg YangPublished Date: 2020-04-04Visit www.paper2podcast.com to download the full paper and learn more. Thanks for listening!

Making Super-wide AI Networks Understandable

Embark on an exhilarating knowledge quest with "Paper-to-Podcast," where our ingenious AI effortlessly transforms complex research papers into captivating audio adventures! Everything you hear is produced using AI systems, so expect plenty of wonderful weirdness along the way. Visit https://www.paper2podcast.com for more information and fascinating papers.

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Embark on an exhilarating knowledge quest with "Paper-to-Podcast," where our ingenious AI effortlessly transforms complex research papers into captivating audio adventures! Everything you hear is produced using AI systems, so expect plenty of wonderful weirdness along the way. Visit https://www.paper2podcast.com for more information and fascinating papers.

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Making Super-wide AI Networks Understandable

Making Super-wide AI Networks Understandable