Tag: ray
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Why you should build your AI Applications with Ray
Compute-intensive applications that incorporate machine learning should be built on top of Ray. By Ben Lorica and Ion Stoica. [This post originally appeared on the Anyscale blog.] Introduction As machine learning and AI become prevalent in…
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The Emergence of Multi-cloud Native Applications and Platforms
As companies go multi-cloud, a new set of tools simplify IT management and application development. By Ben Lorica and Ion Stoica. [This post originally appeared on the Anyscale blog.] In a previous post we examined current…
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Towards an infinite laptop
The new Anyscale platform offers the ease of development on a laptop combined with the power of the cloud. During a series of short keynotes at the Ray Summit this morning, Anyscale1, the company formed by…
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Here’s what you need to look for in a model server to build ML-powered services
Ray Serve simplifies the integration of classic web serving and model serving. By Ben Lorica and Ion Stoica.
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Five Key Features for a Machine Learning Platform
ML platform designers need to meet current challenges and plan for future workloads. By Ben Lorica and Ion Stoica. [This post originally appeared on the Anyscale blog.] As machine learning gains a foothold in more and…
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Understanding the Ray ecosystem and community
Ray is both a general purpose distributed computing platform and a collection of libraries targeted at machine learning and other workloads. By Ben Lorica and Ion Stoica. [This post originally appeared on the Anyscale blog.] Ray…
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Introducing RLlib: A composable and scalable reinforcement learning library
[A version of this post appears on the O’Reilly Radar.] RISE Lab’s Ray platform adds libraries for reinforcement learning and hyperparameter tuning. In a previous post, I outlined emerging applications of reinforcement learning (RL) in industry.…