GPU depreciation poses a significant risk for AI hyperscalers who have heavily invested in hardware. Unlike traditional servers that can remain functional for several years, modern GPUs are evolving rapidly, often becoming obsolete in just a couple of years. Companies now face a dilemma: falling behind even one generation in GPU technology can severely impact profitability. As Nvidia pushes for annual GPU releases, businesses may find it unsustainable to keep up, especially when their competitors can offer faster and cheaper services with newer hardware. The financial implications are dire. Companies like CoreWeave have spent billions on GPUs, expecting continued profitability to justify these investments. However, their business models rely on several assumptions, including the stability of the AI market and the continued effectiveness of existing hardware. Major players like Google and Amazon are somewhat insulated due to their diverse revenue streams, but they're not immune to the risks of rapid depreciation. Michael Burry highlighted that larger companies have extended the lifespan of their servers to show higher profits, but this strategy may miscalculate the pace at which AI hardware improves. The danger is that as GPUs lose value more quickly than anticipated, companies could find themselves needing new financing arrangements sooner than expected. With many players in the industry grappling with similar issues, this situation could lead to a significant financial crisis in the AI sector.