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AnonTechie [soylentnews.org] writes:

An interesting article on the economics of AI Chips by Mihir Kshirsagar

This week, Open AI announced a multibillion-dollar deal [openai.com] with Broadcom to develop custom AI chips for data centers projected to consume 10 gigawatts of power. This investment is separate from another multibillion-dollar deal OpenAI struck with AMD last week. There is no question that we are in the midst of making one of the largest industrial infrastructure bets in United States history. Eight major companies—Microsoft, Amazon, Google, Meta, Oracle, OpenAI, and others—are expected to invest over $300 billion in AI infrastructure in 2025 alone. Spurred by news about the vendor-financed structure of the AMD investment and a conversation with my colleague Arvind Narayanan, I started to investigate the unit economics of the industry from a competition perspective.

What I have found so far is surprising. It appears that we’re making important decisions about who gets to compete in AI based on financial assumptions that may be systematically overstating the long-run sustainability of the industry by a factor of two. That said, I am open to being wrong in my analysis and welcome corrections as I write these thoughts up in an academic article with my colleague Felix Chen.

Here is the puzzle: the chips at the heart of the infrastructure buildout have a useful lifespan of one to three years due to rapid technological obsolescence and physical wear, but companies depreciate [investopedia.com] them over five to six years. In other words, they spread out the cost of their massive capital investments over a longer period than the facts warrant—what The Economist [economist.com] has referred to as the “$4trn accounting puzzle at the heart of the AI cloud.”

Center for Information Technology Policy [princeton.edu] (Princeton University)

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