Today’s foundation models excel at text and images—but they miss the relationships that define how the world works. In every enterprise, value emerges from connections: customers to products, suppliers to shipments, molecules to targets. This talk introduces Relational Foundation Models (RFMs)—a new class of models that reason over interactions, not just data points. Drawing on advances in graph neural networks and large-scale ML systems, I’ll show how RFMs capture structure, enable richer reasoning, and deliver measurable business impact. Audience will learn where relational modeling drives the biggest wins, how to build the data backbone for it, and how to operationalize these models responsibly and at scale.

In today’s data-driven IT landscape, managing ML lifecycles and operations is converging. On this podcast, we’ll explore how end-to-end ML lifecycle practices extend to proactive, automation-driven IT operations. We'll discuss key MLOps concepts—CI/CD pipelines, feature stores, model monitoring—and how they power anomaly detection, event correlation, and automated remediation.