Python provides convenience and flexibility for scalable ML/AI

Anyscale develops Ray, an open-source suite that helps teams scale Python applications from a laptop to a cluster. Ray began at U.C. Berkeley as a toolset for machine learning and artificial intelligence researchers who needed flexible scaling for workloads such as reinforcement learning, hyperparameter tuning, and large neural network training.

Python remains a practical foundation for this work because it is widely used in ML/AI and can be instrumented without forcing users to rewrite large parts of their programs. Ray builds on that flexibility so developers can get distributed execution with less distributed systems expertise.