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Learn how Snowflake has integrated Ray as the backbone of its AI and ML stack to scale thousands of models across terabytes of data within the Snowflake AI Data Cloud in this 15-minute conference talk from Ray Summit 2025. Discover the industry-wide trend of Ray becoming the de facto distributed computing platform for large-scale ML, DL, and RL workloads as Vinay Sridhar from Snowflake explains how his company adopted Ray to power end-to-end training pipelines operating seamlessly inside its unified data environment. Explore the architectural decisions and platform enhancements required to bring Ray into the Snowflake ecosystem, including the critical work of enabling users to pull data directly from Snowflake tables, Apache Icebergâ„¢, and other cloud storage sources into Ray with minimal friction. Understand how Snowflake removes data silo boundaries and simplifies the path from data to model training while gaining insights into how Ray scales machine learning across massive datasets and fits naturally into the AI Data Cloud vision. See how Snowflake customers can leverage this integration to build performant, scalable, and unified ML workflows that operate at enterprise scale.
