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.
Our Commitment to Community-Driven AI Research
PyTorch was built with an open-source, community-first philosophy, and that won’t change with the transition to the Foundation. When researchers and developers open-source their code, others around the world can share their work, learn from each other’s advances and then contribute back to the AI community.
Going forward, the framework’s contributors will benefit from the robust governance, diverse leadership and additional investments provided by the new PyTorch Foundation partners. The Foundation will strive to adhere to four principles: remaining open, maintaining neutral branding, staying fair and forging a strong technical identity. One of its main priorities will be to keep a clear separation between the business and technical governance of PyTorch.
At Meta, we will continue to invest in PyTorch and use it as the primary framework for our AI research and production. The transition itself won’t mean any changes to PyTorch’s code, core project or developer operating models.
We’ve worked consistently to nurture the community-driven growth that has fueled PyTorch’s success, committing hundreds of engineers to the framework and supporting product development and community outreach.
Open science is at the core of our work in AI, whether it’s releasing code for large language models, self-supervised computer vision systems, innovative new datasets, embodied AI platforms and much more. We believe this approach enables the fastest progress in building and deploying new systems that will address real-world needs and answer fundamental questions about the nature of intelligence. With the creation of the PyTorch Foundation, the entire AI community is positioned to push the field forward in countless exciting new ways.