Video by PyTorch via YouTube
Joseph Groenenboom of Red will give two talks at PyTorch Conference North America:
Ecosystem Working Group: Unlocking Community Impact Through the PyTorch Landscape
Created by the PyTorch Foundation in early 2025, the PyTorch Ecosystem Working Group spotlights, through inclusion in the PyTorch Landscape, projects that demonstrate technical excellence and active community engagement in their respective domains. The Landscape includes projects that are both Foundation-hosted and community-hosted. With more than 70 active Landscape projects, including Helion, SGLang, and vLLM, membership creates opportunities for broader impact and recognition within the PyTorch community. In this session, led by the Ecosystem Working Group, you will learn:
– What the Ecosystem Landscape is and why it matters: how membership drives visibility and community engagement for independent projects
– How to apply: a lightweight, GitHub-based process that makes it straightforward for projects to apply for ecosystem status
– How lifecycle management works: what ongoing membership looks like and how the Working Group supports active projects
Attendees will leave with a clear understanding of the benefits of joining the Landscape, the minimum governance standards to qualify for inclusion, and will have the opportunity to meet working group members.
Making Enterprise Agentic Inference Production-Ready with PyTorch and vLLM
While serving AI models for research and pilot use cases is a well solved problem, moving it to 24/7 Enterprise ready systems is the next important phase in AI maturity. The reliability, observability, KV cache management, and concurrency requirements for Enterprise readiness are non-trivial problems. Rising to this challenge, PyTorch, vLLM, and the other foundation projects and broader ecosystem have begun adding Enterprise level features and enhancements.
In this session we will cover the various upstream work committed to helping PyTorch and its ecosystem support Enterprise workloads. This talk will cover a sampling of some of the project work; from core PyTorch project build infrastructure up to model serving improvements to account for tool calling support and long context multi-turn chat.
You will leave this session not only with a deeper understanding of what Enterprise ready” actually entails but also understanding how those changes can be created in a large, diverse, open source ecosystem. There will be code shown and tales shared from the engine room.
Join us in San Jose, October 20-21: https://hubs.la/Q04v4SL60