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from Barrons, not my take
”Historically, these cycles have followed enough of a pattern to consider where artificial intelligence falls in the cycle. One could be dubbed the rule of 25, for the amount of total spending the U.S. has been able to digest during transformational booms as a percentage of the overall economy. At the start of the railroad boom in the 1860s, for instance, U.S. gross domestic product was about $10 billion a year, according to the National Bureau of Economic Research, while rail spending eventually totaled $2.5 billion before the 1873 panic arrived. Similarly, about $1.5 trillion was spent building internet infrastructure in the late 1990s, while the U.S. economy was only $6 trillion at the time. The same holds true for the industrial and electrification buildout of the 1920s.”
“Using that standard, it’s possible to generate a top-down estimate of how much can be spent on AI before the economy is ready to collapse under its own weight. With U.S. GDP at roughly $30 trillion, the danger zone sits at about $7.5 trillion, or an additional $5 trillion to $6 trillion in domestic AI spending. Hyperscalers are projected to spend $3.7 trillion globally through 2029, and they aren’t the only ones, with Oracle, SpaceX, Anthropic, and OpenAI, among others, building, too. At this rate, AI spending won’t trip the rule of 25 until the early 2030s, six or seven years into the boom.“