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The Geopolitics of AI Infrastructure - Dylan Patel, SemiAnalysis

Jun 19, 2025 · 18:29

Dylan Patel of SemiAnalysis argues that despite US sanctions, Huawei has engineered a 384-chip cluster (Cloud Matrix 384) that Nvidia failed to deploy, while accessing TSMC via Softgo and HBM from Samsung via shell companies — all legally. China's SMIC will soon produce 7nm AI chips in high volumes, debunking the notion that China lacks compute. Meanwhile, Middle East players like G42 (UAE) and Datavolt (Saudi Arabia) are building multi-gigawatt data centers, with G42's deal letting it keep 20% of 500,000 GPUs yearly for itself while 80% goes to US companies like OpenAI. Patel highlights the US's 63-gigawatt power shortfall vs. 100 GW of planned data centers, explaining why US companies rely on Middle East capacity and why China's superior power buildout gives it a geopolitical edge.

Accelerating Mixture of Experts Training With Rail Optimized InfiniBand Networking in Crusoe Cloud

Feb 12, 2025 · 17:45

Ievgen Bakulenko, product manager at Crusoe Cloud, explains how their rail-optimized InfiniBand networking accelerates training for sparse mixture of experts models. By leveraging NVIDIA's PXN feature, which allows GPUs to communicate across different rails using the internal NVSwitch in a single hop, Crusoe achieves a 50% improvement in synthetic benchmark latency and bandwidth for both small and large messages. In a real-world test fine-tuning the Mixtral model (8 feed-forward blocks, 7 billion parameters) on 240 H100 GPUs, this topology reduced training time by 14%, directly lowering cost and time-to-train. Bakulenko also outlines Crusoe's AI cloud platform, its climate-aligned mission using stranded energy, and its focus on easy-to-use infrastructure for AI engineers.