Open source ML framework Ray release version 2.0
Machine learning technology Ray by Anyscale has advanced to Ray 2.0, becoming one of the most popular solutions for organisations to manage complicated artificial intelligence (AI) workloads. With Ray 2.0, the platform marked the next significant milestone at the Ray Summit-2022 held in San Francisco on Wednesday. With the addition of the Ray AI Runtime (AIR), a runtime layer for ML service execution, Ray 2.0 has features that make it easier to create and manage AI workloads. “We’re using Ray to train our largest models. So, it has been very helpful for us in terms of just being able to scale up to a pretty unprecedented scale,” said Greg Brockman, CTO and co-founder of OpenAI, at the summit. Thanks to Ray, machine learning models may now scale across hardware resources, supporting MLops workflows. Ray 1.0 was released in September 2020 after undergoing multiple revisions over the past two years. Besides the new release, Anyscale, the lead commercial backer of Ray, has also announced a new enterprise platform for running Ray, raising $99M to push commercial adoption. The open-source Ray framework has been utilised by various businesses like Shopify and Instacart. It is a foundational element for leading AI innovators OpenAI and the team behind the GPT-3 Large Language Model and DALL-E image generation technology.
The new version has features that make it easier to create and manage AI workloads
The new version has features that make it easier to create and manage AI workloads
["AI (Artificial Intelligence)", "Machine Learning", "ML models"]
["Go", "artificial intelligence", "machine learning", "OpenAI", "AI", "ML", "ML models", "Machine Learning", "MLOps", "Anyscale", "Ray", "R", "AI (Artificial Intelligence)"]
["AI", "artificial intelligence", "machine learning", "ML", "OpenAI", "MLOps", "Ray", "Anyscale", "R", "Go"]
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