Deploying Many Models Efficiently with Ray Serve
Explore efficient deployment and management of multiple models using Ray Serve in this 26-minute conference talk. Gain comprehensive insights into serving numerous models while optimizing resource utilization and maintaining ease of use. Learn about three key features of Ray Serve: model composition, multi-application, and model multiplexing. Discover common industry patterns for serving many models and how Ray Serve simplifies management and enhances performance. Dive into case studies of Ray Serve users running many-model applications in production. Access the slide deck for additional information and visual aids. Understand how Ray, an open-source framework, powers ambitious AI workloads, including Generative AI, LLMs, and computer vision. Consider Anyscale's managed Ray service for developing, running, and scaling AI applications.