Overview
Explore the innovative approach to optimizing batch inference using Ray Data and Anyscale's infrastructure stack in this 32-minute conference talk from Ray Summit 2024. Discover how Richard Liaw and Scott Lee from Anyscale address the critical challenge of large-scale batch inference for enterprises with increasingly complex machine learning models. Learn about the limitations of legacy systems and online serving endpoints for handling large-scale, latency-insensitive workloads. Gain valuable insights into Anyscale's proprietary advancements in Ray Data, infrastructure design, and model optimization, and understand how these innovations combine to create a cost-efficient batch inference stack that outperforms alternatives. Benefit from this presentation if you're looking to enhance your organization's batch inference capabilities and reduce operational costs in machine learning deployments.
Syllabus
Anyscale's Ray Data: Revolutionizing Batch Inference | Ray Summit 2024
Taught by
Anyscale