Soumith Chintala: PyTorch

Soumith Chintala: PyTorch

Author: Daniel Bashir March 30, 2023 Duration: 1:08:20

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.

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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) Outro

Links:

* 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



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Hosted by Daniel Bashir, The Gradient: Perspectives on AI moves beyond surface-level headlines to explore the intricate machinery and human ideas shaping artificial intelligence. Each episode is built on a foundation of deep research, leading to conversations that are both technically substantive and broadly accessible. You'll hear from researchers, engineers, and philosophers who are actively building and critiquing our technological future, discussing not just how AI systems work, but the larger implications of their integration into society. This isn't about speculative hype; it's a grounded examination of real progress, persistent challenges, and ethical considerations from those on the front lines. The discussions peel back layers on topics like model architecture, policy, and the fundamental science behind the algorithms becoming part of our daily lives. For anyone curious about the substance behind the buzz-whether you have a technical background or are simply keen to understand a defining technology of our age-this podcast offers a crucial and thoughtful resource. Tune in for a consistently detailed and nuanced take that treats artificial intelligence with the complexity it deserves.
Author: Language: English Episodes: 100

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