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Kunling Geng

Aydin Abiar

Philip Wang

Philip Wang picture

Goku Mohandas

Stephen Offer

Jason Ding

Ankur Khurana

Bryce Huang

Mickey Heynen

Anyscale Agent Skills brings production-grade Ray expertise directly into Claude Code and Cursor. Install via the Anyscale CLI and go from prompt to deployed, debugged workload without leaving your coding tool.

Introducing Anyscale Agent Skills

Introducing Anyscale Agent Skills: Build faster, debug smarter, and optimize AI workloads running on Ray

Ray Day: Seattle brought together ML engineers from Notion, Salesforce, Uber, and Apple to share how they scaled AI workloads with Ray.

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How Notion cut embedding costs by 80% and other stories on scaling AI with Ray from Salesforce, Uber, and more&hellip;

How Notion cuts embedding costs by 80% and other stories on scaling AI with Ray from Salesforce, Uber, and more&hellip;

Jeffrey Wang

Kourosh Hakhamaneshi

Abrar Sheikh

Seiji Eicher

See how Ray Serve LLM updates in Ray 2.55 enable DP group fault tolerance for vLLM Wide Expert Parallelism (WideEP)

DP Group Fault Tolerance for vLLM

Announcing DP Group Fault Tolerance for vLLM WideEP Deployments with Ray Serve LLM

Alex Yang

Akshay Malik

Spencer Peterson (Google)

Ray Serve upgrades deliver faster online inference with HAProxy and gRPC, enabling scalable LLM inference on Ray with lower latency and higher throughput.

Major upgrades to Ray Serve: Online Inference with 88% lower latency and 11.1x higher throughput

Ana Biazetti (RedHat)

Richard Liaw

Richard Liaw headshot

Cathal O&rsquo;Connor (RedHat)

Combine Ray Data + Docling to build scalable document parsing pipelines that process 10k+ complex files with heterogeneous (CPU+GPU) execution and high-accuracy document understanding.

Thumbnail for blog post Breaking the RAG Bottleneck: Scalable Document Processing with Ray Data and Docling

Breaking the RAG Bottleneck: Scalable Document Processing with Ray Data and Docling

Accelerate service debugging with new Ray Serve Grafana dashboard on Anyscale. Available with Ray v2.54+

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Ray Serve&rsquo;s New Grafana Dashboard: Debugging That Wasn&rsquo;t Possible Before

Robert Nishihara

Learn how Vision-Language-Action (VLA) models enable robotics and embodied AI, and how Ray on Anyscale helps teams scale VLA training and deployment.

VLA-LeRobot

Vision Language Action Models on Anyscale

Optimizing VLA Fine-Tuning Performance with LeRobot Datasets and Ray

Julian Forero

Ian Jordan, PhD

Distributed AI training with Ray on Anyscale: Run PyTorch, XGBoost and DeepSpeed across multi-node, multi-GPU clusters with high efficiency and reliability

Scalable Distributed Training: From Single-GPU Limits to Reliable Multi-Node Runs with Ray on Anyscale

David Wang

GPUs are often underutilized in production AI. Learn why CPU-centric architectures waste GPU capacity and how AI-native execution improves efficiency.

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GPU (In)efficiency in AI Workloads

KubeRay Team

KubeRay v1.5 introduces several enhancements for running Ray on Kubernetes, incorporating over 180 commits contributed by approximately 50 contributors.


Kuberay v1.5

Introducing KubeRay v1.5 

Masahiro Tanaka

Amjad Almahairi

Nithin Chalapathi

Matthew Deng

Praveen Gorthy

Stephanie Wang

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30% Faster Multimodal AI Training with Ray and Disaggregated Hybrid Parallelism

Rui Qiao

We are excited to announce new Ray Serve LLM APIs that make it easy to deploy state of the art serving patterns with vLLM

vLLM Ray Serve Anyscale - 3

Ray Serve LLM on Anyscale: Wide-EP and Disaggregated Serving with vLLM

Ray Serve LLM on Anyscale: APIs for Wide-EP and Disaggregated Serving with vLLM

Ray has become the engine for AI-native computing for thousands of AI- and digital-natives. Now Anyscale and Microsoft are partnering to bring the power of Ray to every enterprise.

Announcing first-party service - Anyscale on Azure

Announcing Anyscale on Azure: Build, Run and Scale AI-Native Workloads Securely on Azure Infrastructure

Ray, the open-source distributed compute framework for AI is joining the PyTorch Foundation, part of The Linux Foundation. 

Ray joins PyTorch Foundation

Ray is Joining The PyTorch Foundation

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Components of an Open Source AI Compute Tech Stack

An Open Source Stack for AI Compute: Kubernetes + Ray + PyTorch + vLLM

This section is used to order the "Types" and "Tags" that show up for filters on the Blog Index

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Products / Libraries

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Anyscale Agent Skills for Ray is now generally available:

Powered by Ray, Anyscale empowers AI builders to run and scale all ML and AI workloads on any cloud and on-prem.

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Anyscale

Sunbelt Computer Software

PL/B Language Development and Support