Soumith Chintala's guest appearances

Soumith Chintala

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Voices in AI

Gradient Dissent: Exploring Machine Learning, AI, Deep Learning, Computer Vision

The Gradient: Perspectives on AI

Meredith Broussard

Ilias Diakonikolas

Scott Clark

Celeste Kidd

Dennis Mortensen

Rob Walker

Sanmi Koyejo

Chelsea Finn

Dario Amodei

Jianxiong Xiao

Kate Darling

Jason Holmberg

Lotte Bransen

Christopher Berner

David Spiegelhalter

OwlTail

On this episode, we’re joined by Soumith Chintala, VP/Fellow of Meta and Co-Creator of PyTorch. Soumith and his colleagues’ open-source framework impacted both the development process and the end-user experience of what would become PyTorch.We discuss:- The history of PyTorch’s development and TensorFlow’s impact on development decisions.- How a symbolic execution model affects the implementation speed of an ML compiler.- The strengths of different programming languages in various development stages.- The importance of customer engagement as a measure of success instead of hard metrics.- Why community-guided innovation offers an effective development roadmap.- How PyTorch’s open-source nature cultivates an efficient development ecosystem.- The role of community building in consolidating assets for more creative innovation.- How to protect community values in an open-source development environment.- The value of an intrinsic organizational motivation structure.- The ongoing debate between open-source and closed-source products, especially as it relates to AI and machine learning.Resources:- Soumith Chintalahttps://www.linkedin.com/in/soumith/- Meta | LinkedInhttps://www.linkedin.com/company/meta/- Meta | Websitehttps://about.meta.com/- Pytorchhttps://pytorch.org/Thanks for listening to the Gradient Dissent podcast, brought to you by Weights &amp; Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation.#OCR #DeepLearning #AI #Modeling #ML

On this episode, we’re joined by <a href="https://www.linkedin.com/in/soumith/" rel="noopener noreferrer nofollow" target="_blank">Soumith Chintala</a>, VP/Fellow of <a href="https://www.linkedin.com/company/meta/" rel="noopener noreferrer nofollow" target="_blank">Meta</a> and Co-Creator of PyTorch. Soumith and his colleagues’ open-source framework impacted both the development process and the end-user experience of what would become PyTorch.We discuss:- The history of PyTorch’s development and TensorFlow’s impact on development decisions.- How a symbolic execution model affects the implementation speed of an ML compiler.- The strengths of different programming languages in various development stages.- The importance of customer engagement as a measure of success instead of hard metrics.- Why community-guided innovation offers an effective development roadmap.- How PyTorch’s open-source nature cultivates an efficient development ecosystem.- The role of community building in consolidating assets for more creative innovation.- How to protect community values in an open-source development environment.- The value of an intrinsic organizational motivation structure.- The ongoing debate between open-source and closed-source products, especially as it relates to AI and machine learning. Resources:- Soumith Chintala<a href="https://www.linkedin.com/in/soumith/" rel="nofollow" target="_blank">https://www.linkedin.com/in/soumith/</a>- Meta | LinkedIn<a href="https://www.linkedin.com/company/meta/" rel="nofollow" target="_blank">https://www.linkedin.com/company/meta/</a>- Meta | Website<a href="https://about.meta.com/" rel="nofollow" target="_blank">https://about.meta.com/</a>- Pytorch<a href="https://pytorch.org/" rel="nofollow" target="_blank">https://pytorch.org/</a> Thanks for listening to the Gradient Dissent podcast, brought to you by Weights &amp; Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation. #OCR #DeepLearning #AI #Modeling #ML

Exploring PyTorch and Open-Source Communities with Soumith Chintala, VP/Fellow of Meta, Co-Creator of PyTorch

In episode 66 of The Gradient Podcast, Daniel Bashir speaks to Soumith Chintala.Soumith is a Research Engineer at Meta AI Research in NYC. He is the co-creator and lead of Pytorch, and maintains a number of other open-source ML projects including Torch-7 and EBLearn. Soumith has previously worked on robotics, object and human detection, generative modeling, AI for video games, and ML systems research.Have suggestions for future podcast guests (or other feedback)? Let us know here!Subscribe to The Gradient Podcast:  Apple Podcasts  | Spotify | Pocket Casts | RSSFollow The Gradient on TwitterOutline:* (00:00) Intro* (01:30) Soumith’s intro to AI journey to Pytorch* (05:00) State of computer vision early in Soumith’s career* (09:15) Institutional inertia and sunk costs in academia, identifying fads* (12:45) How Soumith started working on GANs, frustrations* (17:45) State of ML frameworks early in the deep learning era, differentiators* (23:50) Frameworks and leveling the playing field, exceptions* (25:00) Contributing to Torch and evolution into Pytorch* (29:15) Soumith’s product vision for ML frameworks* (32:30) From product vision to concrete features in Pytorch* (39:15) Progressive disclosure of complexity (Chollet) in Pytorch* (41:35) Building an open source community* (43:25) The different players in today’s ML framework ecosystem* (49:35) ML frameworks pioneered by Yann LeCun and Léon Bottou, their influences on Pytorch* (54:37) Pytorch 2.0 and looking to the future* (58:00) Soumith’s adventures in household robotics* (1:03:25) Advice for aspiring ML practitioners* (1:07:10) Be cool like Soumith and subscribe :)* (1:07:33) OutroLinks:* Soumith’s Twitter and homepage* Papers* Convolutional Neural Networks Applied to House Numbers Digit Classification* GANs: LAPGAN, DCGAN, Wasserstein GAN* Automatic differentiation in PyTorch* PyTorch: An Imperative Style, High-Performance Deep Learning Library Get full access to The Gradient at thegradientpub.substack.com/subscribe

In episode 66 of The Gradient Podcast, <a href="https://twitter.com/spaniel_bashir" rel="nofollow" target="_blank">Daniel Bashir</a> speaks to <a href="https://twitter.com/soumithchintala?s=20" rel="nofollow" target="_blank">Soumith Chintala</a>.Soumith is a Research Engineer at Meta AI Research in NYC. He is the co-creator and lead of Pytorch, and maintains a number of other open-source ML projects including Torch-7 and EBLearn. Soumith has previously worked on robotics, object and human detection, generative modeling, AI for video games, and ML systems research.Have suggestions for future podcast guests (or other feedback)? Let us know here!Subscribe to The Gradient Podcast:  <a href="https://podcasts.apple.com/us/podcast/the-gradient-podcast/id1569777340" rel="nofollow" target="_blank">Apple Podcasts</a>  | <a href="https://open.spotify.com/show/6onNcSqsP6hEEqmZ6TU2g8" rel="nofollow" target="_blank">Spotify</a> | <a href="https://pca.st/itunes/1569777340" rel="nofollow" target="_blank">Pocket Casts</a> | <a href="https://api.substack.com/feed/podcast/265424/s/1354/private/3bbc085c-7aa9-4037-8784-1575653a0438.rss" rel="nofollow" target="_blank">RSS</a>Follow The Gradient on <a href="https://twitter.com/gradientpub" rel="nofollow" target="_blank">Twitter</a>Outline:* (00:00) Intro* (01:30) Soumith’s intro to AI journey to Pytorch* (05:00) State of computer vision early in Soumith’s career* (09:15) Institutional inertia and sunk costs in academia, identifying fads* (12:45) How Soumith started working on GANs, frustrations* (17:45) State of ML frameworks early in the deep learning era, differentiators* (23:50) Frameworks and leveling the playing field, exceptions* (25:00) Contributing to Torch and evolution into Pytorch* (29:15) Soumith’s product vision for ML frameworks* (32:30) From product vision to concrete features in Pytorch* (39:15) Progressive disclosure of complexity (Chollet) in Pytorch* (41:35) Building an open source community* (43:25) The different players in today’s ML framework ecosystem* (49:35) ML frameworks pioneered by Yann LeCun and Léon Bottou, their influences on Pytorch* (54:37) Pytorch 2.0 and looking to the future* (58:00) Soumith’s adventures in household robotics* (1:03:25) Advice for aspiring ML practitioners* (1:07:10) Be cool like Soumith and subscribe :)* (1:07:33) OutroLinks:* Soumith’s <a href="https://twitter.com/soumithchintala?s=20" rel="nofollow" target="_blank">Twitter</a> and <a href="https://soumith.ch/" rel="nofollow" target="_blank">homepage</a>* Papers* <a href="https://arxiv.org/pdf/1204.3968.pdf" rel="nofollow" target="_blank">Convolutional Neural Networks Applied to House Numbers Digit Classification</a>* GANs: <a href="https://proceedings.neurips.cc/paper/2015/file/aa169b49b583a2b5af89203c2b78c67c-Paper.pdf" rel="nofollow" target="_blank">LAPGAN</a>, <a href="https://arxiv.org/abs/1511.06434" rel="nofollow" target="_blank">DCGAN</a>, <a href="https://arxiv.org/abs/1701.07875" rel="nofollow" target="_blank">Wasserstein GAN</a>* <a href="https://openreview.net/pdf?id=BJJsrmfCZ" rel="nofollow" target="_blank">Automatic differentiation in PyTorch</a>* <a href="https://proceedings.neurips.cc/paper/2019/file/bdbca288fee7f92f2bfa9f7012727740-Paper.pdf" rel="nofollow" target="_blank">PyTorch: An Imperative Style, High-Performance Deep Learning Library</a> Get full access to The Gradient at <a href="https://thegradientpub.substack.com/subscribe?utm_medium=podcast&amp;utm_campaign=CTA_4" rel="nofollow" target="_blank">thegradientpub.substack.com/subscribe</a>

Soumith Chintala: PyTorch

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

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 <a href="http://twimlai.com/talk/70" rel="nofollow" target="_blank">twimlai.com/talk/70</a> For series information, visit <a href="http://twimlai.com/stloop" rel="nofollow" target="_blank">twimlai.com/stloop</a>

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