Features

Anyscale Emerges from Stealth with Plan to Scale Ray

Anyscale emerged from stealth today with a Series A round of venture capital worth $20.6 million from Andreessen Horowitz and the rough outlines of a plan to scale Ray, the RISELab technology that effectively turns every Read more…

Ray’s New Library Targets High Speed Reinforcement Learning

Data scientists looking to push the ball forward in the field of reinforcement learning may want to check out RLlib, a new library released as open source last month by researchers affiliated with RISELab. According to r Read more…

The Next Data Revolution: Intelligent Real-Time Decisions

Over the past decade, big data analysis and applications have revolutionized practices in business and science. They enabled new businesses (e.g., Facebook, Netflix), to disrupt existing industries (e.g., Airbnb, Uber), Read more…

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. Ca Read more…