// Abstract

Over the past few years, PyTorch became the tool of choice for many AI developers ranging from academia to industry. With the fast evolution of state-of-the-art in many AI domains, the key desired property of the software toolchain is to enable the swift transition of the latest research advances to practical applications.

In this coffee session, Dmytro discusses some of the design principles that contributed to this popularity, how PyTorch navigates inherent tension between research and production requirements, and how AI developers can leverage PyTorch and PyTorch ecosystem projects for bringing AI models to their domain.

// Bio

Dmytro Dzhulgakov is a technical lead of PyTorch at Facebook where he focuses on the framework core development and building the toolchain for bringing AI from research to production.

Previously he was one of the creators of ONNX, a joint initiative aimed at making AI development more interoperable. Before that Dmytro built several generations of large-scale machine learning infrastructure that powered products like Ads or News Feed.

// Relevant Links

https://pytorch.org/

https://pytorch.org/blog/

https://ai.facebook.com/blog/pytorch-builds-the-future-of-ai-and-machine-learning-at-facebook/

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