Industry Analysis
NVIDIA’s Blackwell and Rubin architectures are triggering a deep reconfiguration of the AI compute stack: upstream advanced packaging capacity (e.g., CoWoS) remains tight, with TSMC’s Taiwan, China fabs as the critical bottleneck, while downstream model training costs plummet, accelerating cloud providers’ in-house ASIC adoption. U.S. export controls on China have materially increased compliance overhead, squeezing margins on restricted SKUs like the H20 and forcing global customers to reassess supply chain resilience. AMD’s MI300 series gains share but can’t yet breach CUDA’s ecosystem moat; the real threat lies in scaled deployments of AWS Trainium and Google TPUs. Over the next 18 months, the industry will enter a ‘compute inflation’ phase—surging chip volumes amid pricing pressure—forcing NVIDIA to pivot from hardware vendor to full-stack AI platform before its architectural lead erodes.
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