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MLPatternsProduction
11 . 16 . 2021

Considerations for Deploying Machine Learning Models in Production

A common grumble among data science or machine learning researchers or practitioners is that putting a model in production is difficult. As a result, some claim that a large percentage, 87%, of models never see the light of the day in production.

“...

C++ + Ray
11 . 11 . 2021

Modern Distributed C++ with Ray

This blog showcases major enhancements that were made in Ray version 1.7 to the C++ API that make it much easier to build distributed C++ systems!

Ray Ecosystem
11 . 10 . 2021

What’s new in the Ray Distributed Library Ecosystem

Learn what is new in the Ray Distributed Library Ecosystem as the Ray community of users, contributors, libraries, and production use cases have grown substantially since we first described the Ray ecosystem over a year ago.

Identity Card Recognition
11 . 09 . 2021

Leveraging the Possibilities of Ray Serve in Implementing a Scalable, Fully Automated Digital Verification Service

This blog takes a closer look at digital identity verification, especially in the context of the cidaas ID validator and the modern Cloud Identity & Access Management solution – cidaas. You will get insight into what digital identity verification act...

Ray 1.8
11 . 04 . 2021

Ray version 1.8 has been released

Ray version 1.8 has been released! Release highlights include: Ray SGD has been renamed to Ray Train, Ray Datasets is now in beta, and experimental support for Ray on Apple Silicon (M1 Macs)

ChronosArchitecture
11 . 02 . 2021

From Ray to Chronos: Build end-to-end AI use cases using BigDL on top of Ray

Ray is a framework with simple and universal APIs for building innovative AI applications. BigDL, an open-source framework for building scalable end-to-end AI on distributed Big Data, has leveraged Ray and its native libraries to support advanced AI...

hutomRay
10 . 26 . 2021

How Hutom.io uses Ray and PyTorch to Scale Surgical Video Analysis and Review

Hutom is leading the new paradigm of surgery with its big data platform which helps hospitals and surgeons provide more optimized patient care. Its automated machine learning and computer vision system helps patients and doctors through better person...

naomi
10 . 25 . 2021

Why I joined Anyscale

I’m honored to join the world-class team at Anyscale for two reasons: I believe in the purpose-driven mission and I’m blown away by the team. Joining Anyscale felt like joining a movement to democratize machine learning; we’re providing equal access...

The live traffic pattern is variable and predictable. Serve’s replica autoscaling drives the cost down further during idle time.
10 . 19 . 2021

Cheaper and 3X Faster Parallel Model Inference with Ray Serve

Wildlife Studios’s ML team was deploying sets of ensemble models using Flask. It quickly became too hard and too expensive to scale. By using Ray Serve, Wildlife Studios was able to improve the latency and throughput while reducing the cost. Ray Serv...

DendraInferencePipeline
10 . 12 . 2021

How Ray and Anyscale make it easy to do massive-scale machine learning on aerial imagery

Dendra Systems’ mission is to enable faster, high-quality, transparent and scalable restoration. They do this using a variety of tools like drones for ultra-high resolution mapping at an unprecedented scale, machine learning algorithms that analyze i...