Why I'm Short the AI Buildout Even Though I'm Long Computers

ternaryoperator

A good read and a more reasoned version of the arguments Ed Zitron has been making.

PunchTornado

They keep talking about gpu depreciation and I pay a fortune to rent A100. We have a policy at our company to never close them because demand is so high that we can't find resources to spin them back up when we need them. So msft doesn't even spend money cooling them.

colingauvin

Good article. >I do think there is a real but moderate Jevons effect here: because inference is so cheap now, I’m much more likely to implement marginal automations than I would have been before. But it isn’t unbounded. In practice, it’s maybe 2x or 3x as much code as I would have wanted at the old price, because I still have to specify what to build, review the output, and maintain it. When the price per task drops 20x, and my usage only goes up 2x to 3x, total dollar revenue into the ecosystem (and net GPU demand per user) still collapses by 70% to 85%. I don't think this checks out. Jevon's paradox doesn't say when electricity becomes 20x cheaper, someone already using electricity will use 20x more on the same thing they already do, or even 20x more at all. It means a combination of more people and more enterprises will use it, and use more of it. Concretely - at Claude API prices I'm not going to have AI run a bunch of things that I can do without it. But at DeepSeek API prices, I might. Fundamentally, I think that we aren't even imagining a number of the use cases for AI, in large part because they don't exist yet. But I do think they will eventually exist in the next 20+ years. Right now we are strapping AI to everything, not reimagining life with coherent artificial intelligence. Similarly I couldn't have predicted something like Walmart+ or Amazon Prime back in 1995.

torginus

I think if you use common sense reasoning you can see why the failure mode of AI financing predicted by AI skeptics is unlikely - that is, companies will be swimming in debt and are unable to pay for hardware. The thing is, these AI GPUs are sold at insane markups - a 5090 was like $1700 MSRP, and a datacenter GPU can't cost like more than triple to make - its just that there's so much demand, that people are paying these markups; thast means these companies are flush with cash, and its in their best interest that their customers don't become insolvent, because then its back to selling GPUs to us rubes, who get sticker shock at 'even' a $1000 price tag. Therefore they both have the ability and willingness to maintain this forever. Demand also seems to be there in droves, so the only scenario I can imagine is if datacenter or power infra buildout becomes impossible - plausible, but not what people are worrying about right now.

godzillafarts

> For the tech industry, writing code is the main bottleneck of the business. This couldn’t be further from my experience; producing code has never been the bottleneck.