Faster Model Serving with Ray and Anyscale - Ray Summit 2024

Explore how Anyscale's platform extends Ray Serve to solve key challenges in serving large-scale AI models in this Ray Summit 2024 breakout session. Delve into the complexities of building AI applications in the era of large-scale generative AI, including the increased costs of initializing and running larger models and the need for specialized techniques like tensor or pipeline parallelism across multiple GPUs. Learn about Anyscale's Ray Serve as a solution that addresses production-readiness and developer productivity challenges associated with hosting ML models. Gain insights from Edward Oakes and Akshay Malik of Anyscale as they discuss the industry-leading ML platform for distributed model serving and deployment.

Faster Model Serving with Ray and Anyscale | Ray Summit 2024