// ai-demand

Source: Michael Burry

Michael Burry argues that NVIDIA's extraordinary growth depends on a finite cycle of model training rather than sustained operational workloads—a distinction most investors miss when extrapolating current GPU demand into perpetuity. Once foundational models mature and shift from training-intensive to inference-focused deployment, the concentrated buyer base (primarily cloud giants and labs) will need far fewer chips, potentially cratering both NVIDIA's growth rates and the valuations pricing in endless expansion. This framing rejects the "AI will require exponential compute forever" narrative and instead positions current demand as a bezzle-like phenomenon: real revenue now, but built on temporary distortions that will reverse.