The Red Hat Blog: Expert insights for navigating tech complexity
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AI’s next inflection point: Transforming agents into enterprise superusers
Red Hat has introduced the Red Hat skills bundle alongside a dedicated skills repository, providing the company's best practices in enabling autonomous agents to effectively use and maximize Red Hat subscriptions.
Latest posts
Faster, cheaper, just as smart: Improving the economics of LLM inference with speculative decoding
Learn how Speculators, an open source library, brings speculative decoding from research into production, helping organizations reduce inference latency and cost for large language models (LLMs) without compromising on model quality.
Scaling enterprise AI: Delivering Models-as-a-Service with Red Hat OpenShift AI 3.4
Discover how Red Hat OpenShift AI 3.4 and Red Hat Connectivity Link deliver Models-as-a-Service (MaaS) to centrally govern, secure, and scale enterprise AI model serving.
Agentic AI demands a new infrastructure stack: AMD and Red Hat deliver
Learn how AMD Instinct MI355X GPU support, intelligent orchestration, and AMD EPYC virtual large language model (vLLM) CPU with ZenDNN backend are transforming enterprise AI with Red Hat AI 3.4. Discover the benefits of high-performance GPU and CPU infrastructure for agentic AI workloads.
Save the date: Red Hat Summit 2027 is coming to Boston
For 2027, Red Hat Summit is returning to its roots in the heart of the East Coast’s tech corridor—Boston, MA. We invite you to clear your schedule for Red Hat Summit 2027, taking place May 25-27, 2027.
Introducing AutoML and AutoRAG: Guided experience for AI engineers in Red Hat OpenShift AI
Learn how Auto ML and AutoRAG in Red Hat OpenShift AI 3.4 streamline model development and RAG optimization for enterprise-grade automated machine learning. Discover the benefits, use cases, and how they fit into the broader enterprise AI pipeline.
Featured stories
Platform engineering for AI agents ft. Tushar Katarki
Context And The True "Cost" Of AI
Red Hat AI Inference
Red Hat AI Inference optimizes model inference across the hybrid cloud, creating faster and more cost-effective model deployments
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