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Ray Spotlight

Ray Spotlight: How we delivered Ray weekly releases

Goku Mohandas

Execute end-to-end LLM workflows to develop & productionize LLMs at scale.

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End-to-end LLM Workflows Guide

Cindy Zhang

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Ray Spotlight Series: Multitenant Serve Applications with Runtime Envs as Containers

Marwan Sarieddine

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Natalia Czerep

Mateusz Kwasniak

Artur Zygadło

Cross-modal-Search-for-E-commerce

Cross-modal Search for E-commerce: Building and Scaling a Cross-Modal Image Retrieval App

Max Pumperla

Max Pumperla headshot

Figure 1. End-to-end Stable Diffusion training architecture diagram.

End-to-end Stable Diffusion training architecture diagram

We Pre-Trained Stable Diffusion Models on 2 billion Images and Didn't Break the Bank - Definitive Guides with Ray Series

The Anyscale Team

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Easily Debug Ray Applications with Ray Distributed Debugger

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Processing 2 Billion Images for Stable Diffusion Model Training - Definitive Guides with Ray Series

Yunxuan Xiao

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Hao Chen

In this blog post, we introduce an advanced pre-training solution for Stable Diffusion v2 models, leveraging the power of the Ray and Anyscale Platform to enhance scalability and cost efficiency.  

Scalable and Cost-Efficient Stable Diffusion Pre-training with Ray

Reducing the Cost of Pre-training Stable Diffusion by 3.7x with Anyscale

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

Christy Bergman

Cheng Su

Embedding Inference at Scale for RAG Applications with Ray Data and Milvus

Ramit Hora

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

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

Neelay Shah

Akshay Malik

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

Artur Niederfahrenhorst

Kourosh Hakhamaneshi

Based on the popular “Needle In a Haystack” benchmark and RAG, we share our process of creating a problem-specific fine-tuning dataset to extend the context of models to build better RAG systems.

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Fine-tuning LLMs for longer context and better RAG systems

Scott Lee

Kyle Huang

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

Anyscale + Astronomer

Scalable Machine Learning with Anyscale and Astronomer

Unlocking the Power of Scalable Machine Learning with Anyscale and Astronomer

At Ray Summit 2024, we brought together AI experts and practitioners to dive into the future of distributed AI and scalable machine learning.

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Ray Summit 2024: Breaking Through the AI Complexity Wall

Explore the new and improved Anyscale Workspaces. Get advanced observability features so you spend less time on busywork and more time building AI apps.

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Explore Anyscale’s New UX

Anyscale’s New User Experience: A Comprehensive Overview

With Anyscale on AWS Marketplace, you can build, scale, and optimize AI/ML and Generative AI—all within the trusted AWS cloud environment.

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Anyscale Available on AWS Marketplace

Anyscale Now Available on AWS Marketplace and Achieves Generative AI Competency

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