"Red Hat AI 3 is designed to help organizations move AI workloads from proof-of-concept to production more efficiently. The platform focuses primarily on inference, the execution phase of enterprise AI. Research by the Massachusetts Institute of Technology shows that approximately 95 percent of organizations see no measurable financial return on the roughly $40 billion (€34.4 billion) spent on enterprise AI applications. For many companies, the step from AI experiments to actual production is a huge challenge."
"Red Hat AI 3, which includes Red Hat AI Inference Server, RHEL AI, and Red Hat OpenShift AI, aims to bridge this gap by providing a consistent, uniform experience. "With Red Hat AI 3, we are providing an enterprise-grade, open source platform that minimizes these hurdles," says Joe Fernandes, vice president and general manager of Red Hat's AI Business Unit. The platform builds on vLLM and llm-d community projects."
Red Hat AI 3 helps organizations move AI workloads from proof-of-concept to production by focusing on inference, the execution phase of enterprise AI. The platform includes Red Hat AI Inference Server, RHEL AI, and Red Hat OpenShift AI, and builds on vLLM and llm-d community projects. OpenShift AI 3.0 runs large language models natively on Kubernetes, combining distributed inference with Kubernetes orchestration. The platform leverages open-source components and accelerator libraries to maximize hardware acceleration, reduce costs, improve response times, and enable smart model scheduling and disaggregated serving. Prescribed 'Well-lit Paths' simplify large-scale model rollout and provide cross-platform hardware flexibility.
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