PyTorch Foundation Expands as Umbrella Organization for Open Source AI
The PyTorch Foundation has officially expanded into an umbrella foundation, marking a new phase in its mission to support open source AI development. As part of this move, two high-impact projects—vLLM and DeepSpeed—have been accepted under its governance, approved by the foundation’s Technical Advisory Council. This structure enables the foundation to host a broader portfolio of AI tools spanning the full AI lifecycle, including model training, inference, and domain-specific applications.
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A Strategic Move Amid Growing Demand for Open Source AI
With global generative AI spending projected to reach $644 billion in 2025, enterprises are increasingly turning to scalable, interoperable solutions. The PyTorch Foundation aims to meet this demand by serving as a vendor-neutral hub for trusted AI tooling. Its expanded role will reduce vendor lock-in, accelerate enterprise adoption of AI, and foster responsible innovation through open governance and transparent development.
Projects will now be categorized into two types:
- Platform Projects supporting broad stages of the AI lifecycle (e.g., model training and deployment)
- Vertical Projects tailored for specific use cases, such as protein folding or geospatial analysis
vLLM and DeepSpeed Join as Inaugural Hosted Projects
The first hosted projects under the expanded framework include:
- vLLM, a high-performance inference engine for large language models, built to support low-latency, high-throughput deployments using techniques like PagedAttention.
- DeepSpeed, a distributed training library known for enabling efficient scaling of massive AI models, featuring tools like ZeRO and 3D parallelism.
Both projects will benefit from the foundation’s open governance model, community support, and increased visibility. The PyTorch Foundation now supports over 120 projects with backing from more than 30 member companies and continues to serve as a preferred platform for AI research and deployment.
