Scaling Vision-Language-Action (VLA) Pipelines for Robotics with Ray on Anyscale

Vision-Language-Action (VLA) models are transforming modern robotics and embodied AI by integrating perception, reasoning, and control into a cohesive system, demanding scalable data processing and training frameworks. As robotics teams transition from traditional vision models to fine-tuning VLA models tailored to proprietary data and hardware, they encounter challenges with single-node workflows and require robust frameworks like Ray to scale their operations. Ray offers a unified distributed execution framework that supports parallel processing across large GPU clusters, making it suitable for the complex demands of VLA pipelines, which include data preprocessing, training, simulation, and evaluation. This ensures that robotics teams can maintain experimentation velocity without incurring prohibitive compute costs. Ray on Anyscale further enhances this by providing a managed platform that automates cluster provisioning, offers multi-cloud orchestration, and ensures production-grade fault tolerance, allowing teams to focus on advancing models and algorithms rather than managing infrastructure.