PHYSICAL AI
Autonomy AI with Anyscale
Run sensor & video data processing, multimodal model training, and simulations on a scalable AI compute platform, powered by Ray.
Build, run and optimize data, train and inference pipelines at foundation model scale.
Deploy at scale on any cloud - AWS, Azure, GCP, CoreWeave & Nebius.
Process sensor and video data
Run end-to-end processing of LiDAR and camera streams with unified engine for CPU and GPU processing
Train perception models
Scale vision and sensor fusion model training runs from one GPU to thousands without complex ops
Run scenario sims in parallel
Coordinate thousands of simulator rollouts for safety validation, RL, and edge case synthesis
Curate driving datasets
Scale processing of raw fleet logs, sensor and camera data to structured tensors for model training
Generate scene embeddings
Power search, retrieval, and scenario curation with embeddings processing at PB-scale datasets
Run VLM batch inference
Run scene understanding, object detection, and labeling on PB-scale autonomy video with any VLM
Wayve uses Ray, and increasingly Anyscale on Azure to run distributed ML and data pipelines across large CPU and GPU fleets, supporting large-scale inference”
Wayve uses Ray, and increasingly Anyscale on Azure to run distributed ML and data pipelines across large CPU and GPU fleets, supporting large-scale inference”
1000s
Anyscale on Azure helps connect thousands of GPUs into a flexible supercomputer
Why autonomy companies unify their AI on Anyscale
Increase development velocity
Go from raw sensor files, to training a perception model to running sims and quickly turn the dev environment into a production-scale cluster.
Optimize compute costs
Intelligently orchestrate AI workloads across a shared CPU+GPU resource pool spanning reserved, on-demand, and spot instances.
Operate securely across clouds
Run the same code without cloud-specific rewrites to maximize GPU access. Manage security, governance and budgets in a single pane.
Built on Open Source
Autonomy AI workloads powered by Ray
Ray is the world’s most trusted AI compute engine. Anyscale turns this framework into a production-ready platform.
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Simple Python APIs
Execute Python functions and classes on a distributed cluster with a single decorator.
Agent-first experience
Build and iterate with scalable interfaces to Claude Code and Cursor, fast cluster startup time, instant autoscaling and deep workload observability.
Fine-grained hardware allocation
Compose workloads with distributed functions and classes each running on different CPUs, GPUs, TPUs, or accelerator racks like NVL72.
Multi-framework support
Ray offers support for MCAP data format and popular AI frameworks such as PyTorch, vLLM, Nvidia NeMo & more.
Build. Run. Scale. Repeat.
Deploy advanced AI applications without growing operational complexity with Ray on Anyscale.