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Tag: Ray

Anyscale Nabs $100M, Unleashes Parallel, Serverless Computing in the Cloud

With a fresh $100 million in the bank and $1 billion valuation, UC Berkeley’s RISELab alum Anyscale is now set to scale up its business as the latest data unicorn. The company also announced the general availability of Read more…

From Amazon to Uber, Companies Are Adopting Ray

What if you could use your favorite machine learning library to code an AI program on your laptop, and have it automatically transferred to run in a massive, distributed fashion on the cloud? That’s the general idea be Read more…

Scaling to Great Heights at the Ray Summit

If you haven’t yet heard about Ray, the open source Python framework for building distributed applications, then next week’s Ray Summit will provide a compelling introduction to what might be one of the cornerstone t Read more…

The Future of Computing is Distributed

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 Read more…

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…

Why Every Python Developer Will Love Ray

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 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…

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…

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