Ray: Framework Universal para IA Distribuida y Aplicaciones Python

Fri, 01 May 2026 00:00:00 +0000

Distributed computing is the hidden tax on AI and data-intensive applications. The logic of your application — the training loop, the batch processor, the inference pipeline — is straightforward. But distributing that logic across multiple machines introduces a cascade of complexity: task scheduling, data serialization, fault tolerance, resource management, and cluster coordination.

Ray was created at UC Berkeley’s RISELab to eliminate this tax. It provides a minimal set of distributed computing primitives — tasks for stateless remote execution, actors for stateful remote computation, and a distributed object store for data sharing — that are powerful enough to build any distributed application and simple enough that a single developer can use them productively. The Ray ecosystem extends these primitives into specialized libraries for AI workloads that have become the de facto standard for production AI infrastructure.

Ray on SoloSoft

Ray: Framework Universal para IA Distribuida y Aplicaciones Python