Inference has emerged as the new frontier of complexity in AI. Modern models are evolving into agentic systems capable of multi-step reasoning, persistent memory, and long-horizon context—enabling them to tackle complex tasks across domains such as software development, video generation, and deep research. These workloads place unprecedented demands on infrastructure, introducing new challenges in compute, memory, and networking that require a fundamental rethinking of how inference is scaled and optimized. This blog explores the next evolution in disaggregated inference infrastructure and introduces NVIDIA Rubin CPX—a purpose-built GPU designed to meet the demands of long-context AI workloads with greater efficiency and ROI.
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