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Tag: Ray

The Future of Computing is Distributed

Feb 26, 2020 |

Distributed applications are not new. The first distributed applications were developed over 50 years ago with the arrival of computer networks, such as ARPANET. Since then, developers have leveraged distributed systems to scale out applications and services, including large-scale simulations, web serving, and big data processing. Read more…

Anyscale Emerges from Stealth with Plan to Scale Ray

Dec 17, 2019 |

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 everyday Python coders into parallel computing developers. Read more…

Why Every Python Developer Will Love Ray

Nov 5, 2019 |

There are many reasons why Python has emerged as the number one language for data science. It’s easy to get started and relatively forgiving for beginners, yet it’s also powerful and extensible enough for experts to take on complex tasks. Read more…

Ray’s New Library Targets High Speed Reinforcement Learning

Feb 1, 2018 |

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. Read more…

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

Mar 28, 2017 |

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. Read more…

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