Ray
The AI Compute Engine for any distributed workload at any scale
Ray is an open-source Python-native framework for building, scaling, and distributing AI and machine learning workloads across any infrastructure. It provides primitives for distributed computing along with high-level libraries for data processing, model training, serving, and reinforcement learning. Ray is developed and maintained by Anyscale, which also offers a fully managed cloud platform built on top of Ray.
Ray provides a unified Python-native framework with core primitives (tasks, actors, objects) and high-level ML libraries that distribute and orchestrate workloads across clusters of CPUs and GPUs at any scale.
AI/ML engineers and platform teams building large-scale machine learning systems
Background.
- Status
- launched
- Business model
- open-source
- Company
- Anyscale
Similar projects.
Editorial take on the space this project sits in — momentum signals, adjacent moves, our call on whether the wedge is real. Get pinged when we publish a new read or when the landscape shifts.
Have a take on this space?
Tell us what you’d build differently, where you think the incumbents miss, or what we’ve gotten wrong about this project. Comments + reactions are coming soon.