The LF AI & Data Foundation continues to advance innovation in artificial intelligence (AI), machine learning, and data science. A hallmark of this progress lies in the collaborative integrations achieved by its projects, partnerships that strengthen individual solutions, and build a robust ecosystem of tools for developers and organizations.
One key requirement for a project to achieve graduation status within the foundation is to complete at least one integration with another Linux Foundation open-source initiative. This criterion emphasizes the importance of collaboration in creating interoperable, scalable, and impactful solutions. In this report, we celebrate the success stories of LF AI & Data projects that embody this spirit.
Collaboration in Action
- Egeria: Enhances metadata management and governance through integration with OpenLineage, boosting data visibility and lineage tracking for streamlined compliance.
- Elyra, Flyte, and Kedro: Simplify data science pipelines, offering seamless, reproducible workflows through partnerships with Linux Foundation tools.
- Horovod: Scales deep learning models with ONNX, ensuring compatibility across frameworks.
- ONNX: Centralizes model interoperability and integrates with tools like vLLM for efficient large language model inference.
- OpenLineage: Tracks data transformations with LF projects, ensuring integrity in AI/ML workflows.
- Pyro and vLLM: Push innovation in probabilistic programming and large language model inference, extending AI capabilities to broader audiences.
A Thriving Ecosystem
The success of these project integrations showcases LF AI & Data’s role as the foundation of a collaborative ecosystem where open-source projects address complex challenges. By driving deep learning scalability and enabling efficient, impactful workflows, these projects help shape the future of AI and data across industries.
Celebrating Contributions
The dedication of contributors and maintainers drives this progress, showcasing technical maturity and a commitment to community collaboration. These successes not only solve today’s challenges but also set the stage for tomorrow’s breakthroughs in AI and data.
Together, we are building tools that solve today’s problems and set the stage for tomorrow’s breakthroughs in AI and data.
