How Roblox Scaled Machine Learning by Leveraging Ray for Efficient Batch Inference

Explore a conference talk from Ray Summit 2024 where Roblox engineers Steve Han, Wei Zeng, and Yiqing Wang demonstrate how they scaled machine learning operations through Ray's batch inference capabilities. Gain insights into Roblox's strategic approach to expanding their ML infrastructure, with particular emphasis on recent developments in multimodal language models. Learn about the technical implementation of multimodal models within vLLM, an open-source initiative that has attracted substantial community attention. Discover practical solutions to scaling challenges encountered during integration, and understand how these lessons can be applied to large-scale ML deployments in gaming platforms. Examine real-world examples of implementing advanced ML technologies at scale, complete with detailed technical insights and best practices for similar infrastructure scaling initiatives.