
layout: blog_detail
title: "PyTorch & OpenXLA: The Path Forward"
author: Milad Mohammadi, Jack Cao, Shauheen Zahirazami, Joe Spisak, and Jiewen Tan 

As we celebrate the release of OpenXLA, PyTorch 2.0, and PyTorch/XLA 2.0, it’s worth taking a step back and sharing where we see it all going in the short to medium term. With PyTorch adoption leading in the AI space and XLA supporting best-in-class compiler features, PyTorch/XLA is well positioned to provide a cutting edge development stack for both model training and inference. To achieve this, we see investments in three main areas: