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Building AI Data Commons and AI Data Meshes: Collaborative Approaches for Scalable, Responsible, Distributed, and Federated AI

DescriptionThis BoF is a collaborative discussion on architecting and deploying AI data commons and AI data meshes to support scalable, responsible, and federated AI. Focusing on minimal, interoperable architectures, it aims to empower approaches building small to midscale AI models, highlight challenges and opportunities in federating public and private data commons, and accelerate community adoption of best practices. Key topics include core services, embedding architectures, secure federation, and agentic orchestration. The session seeks to foster a roadmap for the community, exchange best practices, and explore the potential for establishing a working group to advance AI data infrastructure standards.

Session Leader