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Tengwei Cai, Yang Liu, Chengxi Luo, Xiaofeng Yang, Simon Mo

Calling Python Actor from Java Deployment

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Flexible, cross-language, distributed model inference framework: Ray Serve with Java API

Tengwei Cai, Yang Liu, Chengxi Luo, Xiaofeng Yang

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How Ant Group uses Ray to build a Large-Scale Online Serverless Platform

 Abhishek Malvankar (IBM Research) and Dmitri Gekhtman (Anyscale)

Unblock your ML workload using KubeRay with the Multi-Cluster-App-Dispatcher (MCAD) Kubernetes controller.

mcad_ray_diagram

Gang Scheduling Ray Clusters on Kubernetes with MCAD

Gang Scheduling Ray Clusters on Kubernetes with Multi-Cluster-App-Dispatcher (MCAD)

Jake Carter

Phi Nguyen

BlogBiolexis on Anyscale (4)

Biolexis Boosts Their New AI/ML Drug Discovery Platform Using Anyscale’s Fully-Managed Ray Platform

Houssem Eddine Gharbi

Tim Kreienkamp

Blog Adtriba on Anyscale (4)

Adtriba Accelerates and Advances Media Mix Modeling Using the Anyscale Fully-Managed Ray Platform

Richard Decal

Dendra Systems need speed & efficiency at an unprecedented scale. Learn how Ray & Anyscale have helped execute on their ML platform vision.

Blog Dendra on Anyscale (2)

How Massive-Scale ML is Made Easy With Ray & Anyscale

How Ray and Anyscale Make it Easy to Do Massive-Scale Machine Learning on Aerial Imagery 

SangBin Cho, Alan Guo, Ricky Xu, Eric Liang

Explore how you can view native time series metrics to garner insights into the scheduling and performance of your Ray workloads.

ray_integration_with_prometheus_and_graphana

Monitoring & Debugging Ray Workloads: Ray Metrics | Anyscale

Monitoring and Debugging Ray workloads: Ray Metrics

Eric Liang, Jules S. Damji, Zhe Zhang

This blog covers four methods of [batch inference](https://docs.ray.io/en/latest/ray-overview/use-cases.html#batch-inference) (distributed model evaluation) in Ray: from low-level using Ray Actors, to high-level using Ray AIR libraries. 

We'll see how low-level Ray APIs allow you to control exactly "How" Ray is executing computations, while Ray's libraries enable you to specify just the "What" --- for a more out-of-the-box scalable experience.

Four ways of model batch inference in Ray.

Model Batch Inference in Ray: Actors, ActorPool & Datasets

Model Batch Inference in Ray: Actors, ActorPool, and Datasets

Zhe Zhang

Ion Stoica

Ion Stoica headshot

Ben Lorica

Ray For Success

Four Reasons Why Leading Companies Are Betting On Ray

Anyscale logo (webinar thumbnail)

Ray Summit, the Industry Event for Scalable AI, Unveils New Innovations in Ray and the Anyscale Platform; Features Speakers from Uber, IBM, OpenAI, Shopify, Dow and Numerous Global Organizations

Anyscale Unveils Ray 2.0 and Anyscale Innovations at Ray Summit 2022; Adds an Additional $99M Funding from Existing Investors Addition, Intel Capital, and Foundation Capital

Anyscale Ray Team

Ray 2.0

Announcing Ray 2.0

Dat Ngo

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Ray + Arize

Ray + Arize, Productionize ML for Scale and Usability

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Ray Forward 2022

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Ray Serve + FastAPI: The best of both worlds

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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