Ray is the most popular open source framework for scaling and productionizing AI workloads. From Generative AI and LLMs to computer vision, Ray powers the world’s most ambitious AI workloads.
From ChatGPT to Spotify recommendations to Uber ETA predictions, see how innovators are succeeding with Ray and Anyscale.
"At OpenAI, we are tackling some of the world’s most complex and demanding computational problems. Ray powers our solutions to the thorniest of these problems and allows us to iterate at scale much faster than we could before. As an example, we use Ray to train our largest models, including ChatGPT."
Co-founder and President
"We chose Ray as the unified compute backend for our machine learning and deep learning platform because it has allowed us to significantly improve performance and fault tolerance, while also reducing the complexity of our technology stack. Ray has brought significant value to our business, and has enabled us to rapidly pretrain, fine-tune and evaluate our LLMs."
"One of the biggest problems that Ray helped us resolve is improving scalability, latency, and cost-efficiency of very large workloads. We were able to improve the scalability by an order of magnitude, reduce the latency by over 90%, and improve the cost efficiency by over 90%. It was financially infeasible for us to approach that problem with any other distributed compute framework that we tried."
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The open source, scalable, and flexible framework for all of your AI workloads and Python applications.
The AI application managed platform by the Ray creators
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