by Josh Marshall · The Backchannel

A friend sent me this new Bain Capital study on the growth required to match the current levels of capital expenditure on AI, essentially breaking down the cost of the data center and other associated build outs. It’s an interesting document, not simply for the number-crunching and the predictions, but as a document in the more literary and analytic sense. Needless to say, Bain isn’t coming at this from any “boo capitalism!”/”this is insane lol” viewpoint. But the conclusions aren’t that far from the “this is insane lol” position. It’s very much, “hey! we can do this” but also, “um … wow, there’s quite a lot to do.”

The broad stroke numbers are these. The study says that to keep up with the current levels of capital expenditures AI will need to become a $6 trillion dollar market by 2031. (To give some perspective on that number, a recent Gartner study predicted that global IT spending will be just under $6.4 trillion this year. So devices, hardware, software, services, kind of everything.) It then posits that we can see the beginnings of, with some level of out-year predictability, something on the order of a $1.5 trillion market — which would be made up of a greatly expanded consumer market (Claude apps, ChatGPT, etc.) of between $200 and $400 billion and then an enterprise market (software, sales, marketing, business optimization) of between $1 and $1.4 trillion. So we’re left with about $4.5 trillion to go. That’s where the crash course in innovation comes in.

by Josh Marshall · The Backchannel

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In my recent writing about LLMs and AI, I’ve mainly focused on what it can do, what it is, what its potential dangers are. I haven’t focused as much on the pretty substantial evidence that we’re in the midst of an AI bubble. The entire U.S. economy is heavily dependent on the AI boom. Much of the rest of the economy is in a slump. That boom is based on cheap money and very high expectations for AI profits, just as the Fed is facing irresistible pressure to raise interest rates, which is to say, raise the cost of money. This whole question of an AI bubble gets talked about a lot. You probably know the basic outlines. What’s caught my attention is how just in the last week or so these questions, verging into assumptions about unsustainable spending, are bleeding into the tech and the Beltway political press.