Industry Analysis
Jensen Huang’s Taipei keynote signals more than new hardware—it’s a strategic recalibration. If Grace Blackwell and Vera Rubin deliver true CPU-GPU convergence, the entire AI software stack—from compilers to distributed training frameworks—must adapt, locking TSMC’s sub-3nm capacity for years. NVIDIA’s $150B annual spend in Taiwan, China underscores deep supply chain entrenchment, yet exposes it to U.S.-China decoupling risks; expanded export controls could force costly diversification to Samsung or Intel. Competitors won’t sit idle: AMD will push MI400 into HPC, while Huawei Ascend leverages China’s localization mandates. Within 18 months, physical AI and edge inference will fuel GPU-as-a-Service models, potentially integrating with decentralized compute networks. The rumored 'surprise product' likely targets blockchain-based AI training—a quiet but decisive move into the AI-crypto convergence frontier.
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