How Notion cuts embedding costs by 80% and other stories on scaling AI with Ray from Salesforce, Uber, and more…
Anyscale hosted Ray Day Seattle, showcasing how companies like Notion and Salesforce are using the Ray framework to scale AI workloads. Notion significantly reduced embedding costs by 80% and improved query latency by migrating their AI pipeline to Ray, consolidating multiple steps into a single engine. Salesforce leveraged Ray to build a distributed system for summarizing lengthy documents, achieving low latency with a 20B parameter model. Uber also presented improvements in GPU utilization and training time using Ray for their ML platform. AI
IMPACT Demonstrates practical scaling solutions for AI workloads, reducing costs and improving performance for major tech companies.