How Fast Does an AI Chip Depreciate, and Why Does It Matter for Nvidia Stock?

Artificial intelligence (AI) has become the defining technology race of this decade, and Nvidia (NVDA) sits squarely at its center. Its GPUs are the critical engines powering everything from large-language models (LLMs) to data center-scale AI training. But as the tech industry pours hundreds of billions of dollars into AI infrastructure, a surprisingly technical yet enormously consequential question has ignited one of the most intense debates on Wall Street: How fast does an AI chip actually depreciate, and why does it matter?

Michael Burry, the famed “Big Short” investor, has thrust this accounting issue into the spotlight, arguing that hyperscalers may be assuming unrealistically long useful lives for Nvidia’s GPUs. If he’s right, it could mean that major technology companies are understating expenses, overstating earnings, and setting themselves up for sizable write-downs in a few years. Others have joined the debate, scrutinizing everything from resale values to replacement cycles to how quickly new Nvidia AI chips make previous generations obsolete.