Why you should care about AI inference

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A platform of products and services for the development and deployment of AI across the hybrid cloud.
Red Hat AI Enterprise
Build, develop, and deploy AI-powered applications across the hybrid cloud.
Red Hat AI Inference
Optimize model performance with an integrated stack for fast, consistent, and cost-effective inference at scale.
Red Hat OpenShift AI
Build and deploy AI-enabled applications and models at scale across hybrid environments.
Current Red Hat AI customers
Hardware & infrastructure
Simply put, there’s no AI without inference. It’s at the core of generative AI.
The good news is, we know how successful it can be. The challenge is: how do we scale it?
Let’s break down how to scale AI inference with open source tools like vLLM and llm-d.
Inference is the final step, when a model delivers the desired output. It’s a necessary function for AI to be successful.
That’s why the hardware and software that support inference can make or break your AI strategy.
The architecture with the most options for scaling is built on open source technology.
The enterprise inference playbook
Inside open source AI strategy
Getting started with AI inference
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Why vLLM is the most advanced AI inference engine. Video Duration 2:44.
Preview a sample of the upcoming O’Reilly technical guide: AI Inference at Scale. Take a closer look at AI inference and aligning the input of work with the output of results.
The full guide will be available in February 2027.