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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

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Update on Ray CVE-2023-48022: New Verification Tooling Available

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Comparing LLM performance: Introducing the Open Source Leaderboard for LLM APIs

Update on Ray CVEs CVE-2023-6019, CVE-2023-6020, CVE-2023-6021, CVE-2023-48022, CVE-2023-48023

Retrieval-augmented generation, or RAG applications are among the most popular applications built with LLMs. Embedding endpoints enables developers to use open-source embedding models. Today, we are starting with gte-large, and developers can access it at $0.05/MTokens. We plan to add more models in the future, and users can request newer embedding models by filling out this google form. For more info visit here.

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Anyscale Endpoints: Embedding endpoint, Llama-2 70B fine-tuning and improved sign-up experience

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Anyscale and Lambda - Addressing AI Scarcity with Engineering

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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