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What should open source AI mean?

The meaning of open source matters for AI. Our roundtable of experts discusses why, how, and for whom. There is general agreement in the open source community that open source is crucial for AI development, both to accelerate innovation and to make it safer and more...

Guardrailing large language models with TrustyAI Guardrails Orchestrator

As organizations push LLMs into more consequential domains, trust becomes the foundation for scale. Engineers in the open source TrustyAI project developed a guardrailing solution to ensure open source LLMs are both capable and safe for high-stakes deployments....

Bridging clusters: a comparative look at multicluster networking performance in Kubernetes

The EU Horizon project CODECO aims to provide smoother and more flexible support of services for distributed workloads across the edge-cloud continuum. Here’s what researchers discovered about multicluster networking solutions. The shift towards microservices has...

Breaking the silos

In this issue of RHRQ, we have a provocative discussion between Brian Stevens, AI CTO for Red Hat, and Ion Stoica, a professor at the University of California-Berkeley and director of Sky Lab. It’s a great conversation between two people who have had a...

From silos to startups: why universities must be part of industry’s AI growth

At the May 2025 Red Hat Summit, Senior Vice President and AI CTO Brian Stevens helped announce the launch of llm-d, an open source project aimed at meeting the need for distributed GenAI inference at scale. As readers may know, Brian had most recently been the CEO of...
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Red Hat Research connects Red Hat engineers with professors, researchers, and students to bring great research ideas into open source communities. Our activities around the world have produced grants from government and industry, papers at top conferences, and results that have landed in open source projects of all kinds. Red Hat Research welcomes participation from research-minded individuals around the world.

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