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Akshay Malik

Edward Oakes

Phi Nguyen

Learn how Ray Serve & Anyscale solves common challenges of serving AI in production - improving time to market, reducing cost, and ensuring reliability.

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Tackling the Cost & Complexity of Serving AI in Production

Ray Serve: Tackling the cost and complexity of serving AI in production

Jiao Dong

Shreyas Krishnaswamy

Simon Mo

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Multi-model composition with Ray Serve deployment graphs

Archit Kulkarni

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Handling files and packages on your cluster with Ray runtime environments

Michael Galarnyk

In this post, we explore the 4 common patterns of ML in production and how to implement these patterns using Ray Serve.


Where Ray Serve Fits In

Serving ML Models in Production: Common Patterns

Ray Summit 2024, the annual Ray community conference, is back in San Francisco, CA this September 30th through October 2nd. It is a two-day event with a third day dedicated to training.

Call for Proposals is open Blog Post

Ray Summit 2024 Call for Proposals is now open

Intel and Anyscale have integrated Ray with Gaudi3. Gaudi3 is AI-optimized for efficient training and other machine learning workloads.

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Accelerating AI: Harnessing Intel(R) Gaudi(R) 3 with Ray 2.10

Anyscale is teaming with NVIDIA to combine the developer productivity of Ray Serve and RayLLM with the cutting-edge optimizations from NVIDIA Triton Inference Server software and the NVIDIA TensorRT-LLM library.

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Low-latency Generative AI Model Serving with Ray, NVIDIA Triton Inference Server, and NVIDIA TensorRT-LLM

Generating embeddings is a critical task for developing successful RAG applications, and Anyscalew with Pinecone is the most cost-efficient solution for this workflow.

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RAG at Scale: 10x Cheaper Embedding Computations with Anyscale and Pinecone

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Anyscale is the leading AI application platform. With Anyscale, developers can build, run and scale AI applications instantly.

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Posts by Edward Oakes

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