Industry Analysis
Burry’s bearish stance reflects deep skepticism about GPU architecture’s long-term dominance in AI training. If Google’s TPU v6 or Amazon’s Trainium II achieve >3x energy efficiency gains, it could trigger a heterogeneous computing inflection point, forcing cloud providers to overhaul their hardware stacks and reshaping TSMC’s EUV allocation below 7nm. U.S. export controls on advanced packaging may raise non-U.S. AI chip costs but accelerate custom silicon adoption by clients in Taiwan, China and Hong Kong, China. NVIDIA might respond by partially opening CUDA to retain lock-in, while rivals could license IP to form an anti-NVIDIA coalition. Within 18 months, the market will pivot from raw FLOPS to inference cost per dollar—exposing the weakest seam in NVIDIA’s moat.
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