Ray
ray.ioThe AI Compute Engine for any distributed workload at any scale
AI Toolsdistributed-computingmachine-learningopen-sourcepythonllmmlopsgpu-computing
About
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.
Problem
AI teams struggle with slow time to production, underutilized compute resources, and exploding costs due to increasingly complex AI workloads and fragmented infrastructure.
For
AI/ML engineers and platform teams building large-scale machine learning systems
How it works
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.
Business model
open-source
Status
launched
Company
Anyscale