Industry Analysis
Google and Amazon’s aggressive in-house AI chip push is fundamentally an assault on NVIDIA’s vertically integrated GPU-software hegemony. Technically, TPU v5e and Trainium3—built on 3nm EUV—force upgrades across the stack: EDA tools, advanced packaging, and thermal solutions, especially benefiting CoWoS alternatives. On compliance, tightening U.S. export controls on AI chips to China accelerate cloud providers’ shift to proprietary silicon to sidestep licensing hurdles and cut BOM costs. Strategically, NVIDIA may counter with an early Blackwell Ultra launch and partial CUDA compatibility layers, while Microsoft could fast-track Maia to form a third pole. Over the next 12–24 months, the market will pivot from GPU monoculture to heterogeneous multi-chip architectures, with training/inference specialization becoming standard—small-to-mid model vendors will lead adoption of non-NVIDIA solutions, redefining data center procurement.
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