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Pytorch: Fast Differentiable Dynamic Graphs in Python with Soumith Chintala - TWiML Talk #70

EPISODE · Nov 21, 2017 · 42 MIN

Pytorch: Fast Differentiable Dynamic Graphs in Python with Soumith Chintala - TWiML Talk #70

from The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) · host Sam Charrington

This week, we’ll be featuring a series of shows recorded from Strange Loop, a great developer-focused conference that takes place every year right in my backyard! The conference is a multi-disciplinary melting pot of developers and thinkers across a variety of fields, and we’re happy to be able to bring a bit of it to those of you who couldn’t make it in person! In this show I speak with Soumith Chintala, a Research Engineer in the Facebook AI Research Lab (FAIR). Soumith joined me at Strange Loop before his talk on Pytorch, the deep learning framework. In this talk we discuss the market evolution of deep learning frameworks and tools, different approaches to programming deep learning frameworks, Facebook’s motivation for investing in Pytorch, and much more. This was a fun interview, I hope you enjoy! The notes for this show can be found at twimlai.com/talk/70 For series information, visit twimlai.com/stloop

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Pytorch: Fast Differentiable Dynamic Graphs in Python with Soumith Chintala - TWiML Talk #70

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