After months in preview, PyTorch 2.0 has been made generally available by the PyTorch Foundation. The open source PyTorch project is among the most widely used technologies for machine learning (ML) training. Originally started by Facebook (now Meta), PyTorch 1.0 came out in 2018 and benefitted from years of incremental improvements. Don't miss our special issue: The quest for Nirvana: Applying AI at scale. In September 2022, the PyTorch Foundation was created in a bid to enable more open governance and encourage more collaboration and contributions.

Meta AI announced today that the governance of PyTorch, a popular open source deep-learning framework, has moved to an independent organization called the PyTorch Foundation. It will operate as part of the nonprofit Linux Foundation, and its governing board includes representatives from Nvidia, Meta, Google, Microsoft, Amazon, and AMD. The move comes as the PyTorch framework becomes more widely used across the deep-learning industry to power many natural-language and computer-vision projects, including Tesla Autopilot. Meta cites more than 2,400 contributors and 150,000 projects built on the framework. Spinning PyTorch off into its own foundation avoids potential conflicts of interest that might come if PyTorch were only controlled by Meta, which created the framework.

To accelerate progress in AI, PyTorch is moving to a new, independent PyTorch Foundation, under the Linux Foundation umbrella. The project will join the Linux Foundation with a diverse governing board composed of representatives from AMD, Amazon Web Services, Google Cloud, Meta, Microsoft Azure, and Nvidia, with the intention to expand over time. The PyTorch Foundation will act as a responsible steward for the technology and support PyTorch through conferences, training courses, and other initiatives. The foundation's mission is to drive adoption of AI tooling by fostering and sustaining an ecosystem of open source, vendor-neutral projects with PyTorch. It will democratize state-of-the-art tools, libraries, and other components to make these innovations accessible to everyone.

Since 2016, when we partnered with the AI community to create the PyTorch framework for AI research, open collaboration has been essential to its success. With thousands of contributors who have built more than 150,000 projects on it, PyTorch has become one of the leading platforms for research and production across the AI community. Today, Mark Zuckerberg announced that the project will transition to a newly launched PyTorch Foundation, which will be part of the nonprofit Linux Foundation, a technology consortium whose core mission is the collaborative development of open-source software. The creation of the PyTorch Foundation ensures that decisions will be made in a transparent and open manner by a diverse group of board members for many years to come. The governing body will be composed of representatives from AMD, Amazon Web Services, Google Cloud, Meta, Microsoft Azure and Nvidia, with the intention to expand further over time.

As you have heard, Meta has finally announced the PyTorch Foundation. It took us almost a year to get to this place where we finally can release it (if you even can say "release" about things like the foundation). In this article, I want to outline why this is done and what this means. Let's start with the problem. For quite some time, Meta was a gatekeeper for PyTorch.

In 2016, Meta (then but a simple country Facebook) launched its open-source AI research library, the Pytorch framework. Six years and 150,000 projects from 2,400 contributors later, Meta announced on Monday that the Pytorch project will soon spin out from the company's direct control to become its own entity, the Pytorch Foundation, a subsidiary within the larger Linux Foundation nonprofit hegemony. Over the last half decade, Pytorch has grown to become a leading standard for the AI research community with Meta CEO Mark Zuckerberg noting in Monday's press release that some 80 percent of "researchers who submit their work at major ML conferences, such as NeurIPS or ICML, harness the framework." "We have built libraries that support some of the principal domains of the AI field, such as torchvision, which powers most of the world's modern computer vision research," Zuckerberg continued. "The framework will continue to be a part of Meta's AI research and engineering work."