"The AI stock boom has lost a lot of momentum in recent weeks due, in part, to worries that so-called hyperscalers aren't correctly accounting for the depreciation in the hoard of chips they've purchased to power chatbots. Michael Burry-the investor of Big Short fame who famously predicted the 2008 housing collapse-sounded the alarm last month when he warned AI-era profits are built on "one of the most common frauds in the modern era," namely stretching the depreciation schedule."
"For example, software can improve the performance of Nvidia's five-year-old A100 chip by two to three times compared to its initial version. Second, Alpine said the need for older chips remains strong amid rising demand for inference, meaning when a chatbot responds to queries. In fact, inference demand will significantly outpace demand for AI training in the coming years. "For inference, the latest hardware helps but is often not essential, so chip quantity can substitute for cutting-edge quality,""
New AI chips are entering the market rapidly as companies compete for greater computational power. Investors worry hyperscalers may understate depreciation on large chip purchases, with Michael Burry estimating Big Tech could understate depreciation by $176 billion from 2026–2028. Alpine Macro argues depreciation fears are overstated for three reasons. Software advances can materially improve older processors, sometimes doubling or tripling performance of chips like Nvidia's A100. Rising inference demand favors chip quantity over the latest quality and will outpace training demand. China’s persistent demand and supply gaps sustain long-term demand for older-generation chips.
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