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In this interview from The CEO Summit 2026 (CASPA), Sunghyun Park, co-founder and chief executive officer of Rebellions Inc., joins theCUBE's John Furrier and Dave Vellante to discuss how workload-aware system design and tokenomics are reshaping the economics of AI inference infrastructure. Park explains that the industry is moving beyond rack-scale deployments toward systems tailored to specific workload demands, whether latency-critical, throughput-hungry or power-constrained. He details how the shift from training to inference has made tokenomics, measuring performance per dollar per watt, the critical metric for the agent era, where machines rather than humans drive token consumption around the clock. Park notes that AI infrastructure buildout remains less than 10% complete, underscoring why semiconductor leaders must collaborate across the ecosystem. The conversation also explores how memory bandwidth and data movement, rather than raw logic density, have become the industry's central bottleneck, pushing designers toward 3D-stacked memory and faster interconnects such as Ethernet and NVLink Fusion. Park details why sovereign AI deployments demand low-power, air-cooled systems that avoid costly liquid-cooling retrofits, along with chip-level security and heterogeneous compute that reduces reliance on any single supplier. He argues flexibility, not raw performance, will determine which neoclouds survive an anticipated wave of consolidation in the coming years. From kernel-level chip optimization to scale-up and scale-out network architectures, Park outlines a practical path for building AI factories that can adapt as fast as the models running on them. Find more SiliconANGLE news and analysis https://siliconangle.com/ Follow theCUBE's wall-to-wall event coverage https://siliconangle.com/events/ Learn about the latest theCUBE events https://www.thecube.net/ 00:00 - Semiconductor Collaboration for AI Infrastructure 02:44 - Workload-Aware AI Infrastructure and Inference Performance 05:37 - Profitable Scaling for AI Agent Workloads 07:53 - AI Memory Bandwidth and Interconnect Bottlenecks 10:14 - Flexible AI Hardware for Secure Sovereign Deployment 13:13 - Scaling AI Infrastructure Through Flexibility #theCUBE #CASPA #theCUBEresearch #Rebellions #Semiconductors #AI

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