Distributed deep learning with Ray Train is now in Beta
Introducing Ray Train, an easy-to-use library for distributed deep learning. In this post, we show how Ray Train improves developer velocity, is production-ready, and comes with batteries included.
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Machine intelligence at Google scale, vision / speech APIs, Tensorflow, and Cloud Machine Learning
With my colleague Martin Görner , at the Devoxx conference in Belgium last month, we gave a talk on Machine Learning, on the various APIs pr
Building a Deep Learning Library from Scratch with NumPy
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Parallax by Gradient: Distributed AI Platform for Running LLMs Across Multiple Devices
Your local AI just leveled up to multiplayer. Parallax is the easiest way to build your own AI cluster to run the best large language models

From Training to Inference: How AI Workloads Are Reshaping Next-Gen Data Centers
The explosive growth of generative AI models at GPT-scale continues to redefine enterprise infrastructure in 2026. With models now featuring
GPEmu: A GPU Emulator for Rapid, Low-Cost Deep Learning Prototyping [pdf]
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Anyscale Review: The Managed Ray Platform for Serious AI Workloads
Anyscale built the Ray open-source framework, transferred it to the PyTorch Foundation in 2025, and now sells a managed platform that runs o

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