Meet Ray, the Real-Time Machine-Learning Replacement for Spark

Researchers at UC Berkeley’s RISELab have developed a new distributed framework designed to enable Python-based machine learning and deep learning workloads to execute in real-time with MPI-like power and granularity. Called Ray, the framework is ostensibly a replacement for Spark, which is seen as too slow for some real-world AI applications, and should be ready … Continue reading Meet Ray, the Real-Time Machine-Learning Replacement for Spark