Red Hat introduces new AI platform

Red Hat has announced Red Hat AI 3 in what it says is a significant evolution of its enterprise AI platform. Bringing together the Red Hat AI Inference Server, Red Hat Enterprise Linux AI (RHEL AI) and Red Hat OpenShift AI, the platform is designed to help simplify the complexities of high-performance AI inference at scale, enabling organisations to more readily move workloads from proofs-of-concept to production and improve collaboration around AI-enabled applications.

As enterprises move beyond AI experimentation, they face significant hurdles, including data privacy, cost control and managing diverse models.

The company says Red Hat AI 3 focuses on directly addressing these challenges by providing a more consistent, unified experience for CIOs and IT leaders to maximise their investments in accelerated computing technologies. It makes it possible to rapidly scale and distribute AI workloads across hybrid, multi-vendor environments while simultaneously improving cross-team collaboration on next-generation AI workloads like agents, on the same common platform.

As organisations move AI initiatives into production, the emphasis shifts from training and tuning models to inference, the ‘doing’ phase of enterprise AI. Red Hat AI 3 emphasises scalable and cost-effective inference, by building on the vLLM and llm-d community projects and Red Hat’s model optimisation capabilities to deliver production-grade serving of large language models (LLMs).

Red Hat says that Red Hat AI 3 delivers a unified, flexible experience tailored to the collaborative demands of building production-ready generative AI solutions. It is designed to deliver tangible value by fostering collaboration and unifying workflows across teams through a single platform for both platform engineers and AI engineers to execute on their AI strategy. New capabilities include:

• Model as a Service (MaaS) capabilities that build on distributed inference and enable IT teams to act as their own MaaS providers, serving common models centrally and delivering on-demand access for both AI developers and AI applications.
• AI hub to empower platform engineers to explore, deploy and manage foundational AI assets. It provides a central hub with a curated catalogue of models, including validated and optimised gen AI models, a registry to manage the lifecycle of models and a deployment environment to configure and monitor all AI assets running on OpenShift AI.
• Gen AI studio, which provides a hands-on environment for AI engineers to interact with models and rapidly prototype new GenAI applications.
• New Red Hat validated and optimised models to simplify development.
   

“As enterprises scale AI from experimentation to production, they face a new wave of complexity, cost and control challenges,” said Joe Fernandes, vice president and general manager, AI Business Unit, Red Hat. “With Red Hat AI 3, we are providing an enterprise-grade, open source platform that minimises these hurdles. By bringing new capabilities like distributed inference with llm-d and a foundation for agentic AI, we are enabling IT teams to more confidently operationalise next-generation AI, on their own terms, across any infrastructure.”

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