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Introducing AutoML and AutoRAG: Guided experience for AI engineers in Red Hat OpenShift AI
As organizations move from AI experimentation toward scalable production, the complexity of manually building high-performing AI models and retrieval systems often creates a significant bottleneck. Red Hat OpenShift AI 3.4 helps address this with the introduction of AutoML and AutoRAG, now available as technology previews. These tools are designed to automate the labor-intensive aspects of the AI lifecycle, allowing teams to focus on business impact rather than manual configuration.What is AutoML?AutoML in Red Hat OpenShift AI 3.4 brings enterprise-grade automated machine learning to your fing
Faster, cheaper, just as smart: Improving the economics of LLM inference with speculative decoding
Modern large language models (LLMs) are defined by their scale. GPT-3 introduced 175 billion parameters in 2020, and today, production-grade models routinely operate in the hundreds of billions, with some architectures exceeding one trillion. Each parameter represents a learned weight, collectively encoding the language, reasoning, and knowledge that make these systems capable.This scale is not incidental. Empirical research has consistently demonstrated that model capability scales predictably with size—larger models exhibit stronger reasoning, broader factual recall, and greater generaliza
Agentic AI demands a new infrastructure stack: AMD and Red Hat deliver
Agentic AI doesn’t just move AI forward, it flips the infrastructure built for traditional inference on its head. Agentic AI, systems that reason, plan, use tools, and execute multistep tasks autonomously, is rapidly moving from research into production. This shift is not just about more compute, it fundamentally changes how infrastructure must perform, scale, and be optimized for continuous, multistage reasoning workflows.But agents are fundamentally different workloads—they call models repeatedly, fan out across tools and data sources, and need to run continuously and cost-effectively. T
Linux Driver Posted For Intel Silicon Security Engine Interface "ISSEI"
Since Intel Meteor Lake has been the Intel Silicon Security Engine to serve as a silicon root-of-trust for secure firmware loading, boot measurements, and similar functionality. This Intel Silicon Security Engine has been built on with Lunar Lake and Panther Lake as well as set to take on more importance with future Intel hardware platforms. We are now seeing a Linux driver come for this silicon RoT with the Intel Silicon Security Engine Interface (ISSEI)...
Fragnesia Made Public As Latest Linux Local Privilege Escalation Vulnerability
Following last week's disclosure of the Dirty Frag vulnerability for the Linux kernel, which only finished being patched up in mainline on Monday, Fragnesia is now public as a similar local privilege escalation (LPE) vulnerability...
Rust stalks IBM mainframes, but only in nightly form - The Register
Rust stalks IBM mainframes, but only in nightly form The Register