I will note for all concerned - in the history of technology, increased efficiency does not generally drive reduction in expenditure. It drives increased use. When corporations found that fluorescent lights were cheaper than incandescent lights, they didn't reduce their electricity use - they increased how much space was lit, and how long they left the lights on! When we increase the efficiency of algorithms or decrease the cost per flop of hardware... they'll just do EVEN MORE COMPUTUING.
True. The demand in lighting that couldn't be met earlier because it was too costly was met through the technological progress. There is no reason to think that more efficient computing will lead to less computing being used overall. The point that more efficient computing can reach the same goal with less investment is totally unrelated to the total use: if we get cars that run 100km on one liter of gasoline, we'll probably see people use their car more often rather than just save on gasoline. There are some goods for which there is a plateau (you don't eat twice as much when food becomes available more readily after some point...) but computing is probably not reached.
While the idea that efficiency upgrades will somehow save the situation, the history suggests otherwise. If nothing else - the current cost is over an order of magnitude higher than the current revenue. You aren't getting a 10x decrease in cost in short order, even considering Moore's Law. And nobody understands who is going to spend a trillion dollars on AI output.
Well, Bain does, apparently, since they estimate that revenue could be up to 1.2 trillion out of the 2 trillion investment they forecast to be needed.
The actual risk is the economic upheaval should the AI business collapse for any reason. Collapsing because they can't get enough machoflops to be an actual product is one possible reason for collapse. Not being able to get enough people to pay for the result is another possible reason. Either one leaves us with massive debt incurred that cannot be repaid, and the economic impacts therefrom.
I wouldn't use the term upheaval. While it can have localized effect, stock bubble busts do not greatly impact global growth.
The Internet bubble only caused a temporary slowdown in global growth, while the 2009 crisis triggered by the subprime collapse reduced growth by about 1% before a rapid recovery. The monetary scale of those events is also very different from today’s AI investments, especially outside infrastructure, which, as you correctly point out, are the main source of capital need.
Major infrastructure providers like Amazon, Google, and Microsoft are highly profitable and can afford to run their data centers below capacity if AI startups fail. They aren’t overleveraged or indebted beyond their means. At worst, they may end up with underused infrastructure and see lower profits compared to recent years, but their debt levels are not a concern given their tremendous profitability. Even a trillion dollars in losses would represent only about three years of combined net profit for the GAFAM group.
As for AI companies themselves, they carry almost no debt. Their growth is financed mainly through venture capital rather than borrowing. Firms like OpenAI, Mistral, and Anthropic, for instance, have minimal debt and rely on burning investor capital instead of taking on credit.
The most significant dent in growth came in 2020, with a lot of developped countries shuting down their economies out of sanitary concern, and not economic concerns.
Even at the epicenter of the phenomenon, results were quite tame when stock valuation bubbles aren't connected to debt bubbles:
The Internet bubble crash didn't severely impede even the US economy:
(annual growth rate, measured quarterly, in 2000-2003)
It could have had localized effects (in area with strong employment in the same sector and ineffective social safety nets), or at the individual level of course but that's far from an economic upheaval. It wasn't even technically a recession.
