Blog | Anyscale

Ray Summit 2025: Call for Proposals Closes on June 30th, 2025

05 . 30 . 2025

Ray Summit 2025: Call for Proposals Closes on June 30th, 2025

By Christina Zhu

04 . 09 . 2025

Simplifying AI Development at Scale: Google Cloud Integrates Anyscale's RayTurbo with GKE

By Gabe Monroy, VP & GM Cloud Runtimes and

By Keerti Melkote, CEO of Anyscale

10 . 03 . 2024

Ray Summit 2024: Breaking Through the AI Complexity Wall

By The Anyscale Team

Hash Shuffle / Joins blog header image

05 . 20 . 2025

New: Joins & Hash-Shuffle in Ray Data

By Alexey Kudinkin,

Praveen Gorthy and

Observability blog header image

05 . 20 . 2025

Streamline Distributed AI Monitoring and Debugging with New Ray Train & Ray Data Dashboards in Anyscale

Matthew Owen and

RayTurbo Data blog header image

05 . 20 . 2025

RayTurbo Data Improvements Deliver Up to 5x Faster Data Processing for AI Workloads

By Alexey Kudinkin,

Praveen Gorthy and

Group 464 (1)

10 . 01 . 2024

Ray Data GA

Richard Liaw and

Untitled design (43)

10 . 01 . 2024

Accelerated Metadata Fetching in Ray Data up to 4.5x Faster on Anyscale

By Balaji Veeramani,

Matthew Connor and

10 . 01 . 2024

Autoscaling Large AI Models up to 5.1x Faster on Anyscale

By Christopher Chou,

Edward Oakes and

Screenshot 2024-09-27 at 12.12.40 PM

10 . 01 . 2024

Announcing RayTurbo

By Akshay Malik,

Praveen Gorthy and

Untitled design (41)

10 . 01 . 2024

Batch LLM Inference on Anyscale slashes AWS Bedrock costs by up to 6x

By Cody Yu,

Praveen Gorthy and

Ray 2.8 blog post

11 . 07 . 2023

Ray 2.8 features Ray Data extensions, AWS Neuron cores support, and Dashboard improvements

By Jules S. Damji and

ray 2-7 annoucement

09 . 18 . 2023

Ray 2.7 features major stability improvements to Ray AI Libraries and KubeRay and introduces RayLLM

By Jules S. Damji and

2.6 animations

07 . 25 . 2023

Ray 2.6 features streaming for Serve and Train and new Multi-GPU Learner API

By Jules S. Damji and

Cover image for 23X batch blog

06 . 22 . 2023

How continuous batching enables 23x throughput in LLM inference while reducing p50 latency

By Cade Daniel,