From top to top and from afar? Companies expected to invest more than $500 billion in hyper-scalable artificial intelligence this year (including Magnificent 7 members such as Microsoft, Amazon, and Google) are still betting big on technology that follows this trajectory.
The least attractive alternative is up, up and popexpressing fears of bubbles that ignited when the Financial Times reported in December that Oracle had lost its “major backer” for a $10 billion data center in Michigan. Subsequently, shares of the cloud computing giant fell 5.4% and 32% over the past three months, weighing on other AI-related stocks including Nvidia, Broadcom and Advanced Micro Devices.
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Are AI opponents just pessimists? When Reuters asked technology leaders and investment analysts to review their Magic 8 Balls in October, the resounding response was “ask again later.”
What’s clearer is that the data centers that power AI globally will need $6.7 trillion in cumulative investment by 2030 to keep pace with computing demand, with another $1.3 trillion for power generation and transmission, according to McKinsey & Co. With about half a million skilled workers needed this year to fill the growing labor shortage in the IT sector construction, AI visionaries could see their investment plans stalled while the labor resources needed to build data centers catch up:
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“I don’t think there is a bubble, but we are seeing some constraints in terms of construction capacity that are not keeping up with all the new investments,” ABB CEO Morten Wierod told Reuters. “There aren’t enough people and resources to build all of this. »
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This reflects Wall Street’s fears of overvaluation, already heightened when Nvidia became the first company to reach a market capitalization of $4 trillion in July and then $5 trillion in October.
Yet even with billions of dollars earmarked for capital spending on AI, Magnificent 7 stocks, which focus heavily on AI and account for more than a third of the S&P 500’s market value, will most likely be isolated if the market crashes on profitability, said Andy Wu, an associate professor of business administration at Harvard Business School.
1 +1 = 1,000 billion: “While generative AI can do amazing things, it is also perhaps the most wasteful use of a computer ever,” Wu told the Harvard Gazette. “If you do 1+1 on a calculator, that does one calculation. If you do 1+1 in generative AI, that’s potentially a trillion calculations to get an answer. That consumes a huge amount of chip capacity and electricity.”
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