And if that revenue was coming from end users, it would be great. But it isn't---most of it is coming from the very same debt that is the subject of the article. There's a huge difference in my financial outlook if my biggest customer is borrowing all the money they are spending with me vs earning it in the marketplace. In the latter scenario, my business is tied into the success of the my customer in the market (harder to grow), in the former it's just a question of how much money they can borrow (much easier to grow, especially if I'm Nvidia and I can guarantee their debt).
I see the business press make this fundamental mistake all the time, starting off by drawing a boundary around the AI industry as a whole and correctly assessing the staggering levels of debt, but then switching perspective to individual sectors and completely forgetting about where the revenue actually originates, and treating it the same as organic growth.
From a financial standpoint this is all looking like early 2008. The risk assessment bits of the market seem to have concluded this is all totally f*ked. But money keeps getting pumped into things that the market has decided will fail because the only thing that stops it from imploding is pumping more money in.
Like 2008 once key players get their armor on, expect things to suddenly unleash in a way that gets real ugly real quick. This is essentially what the article is saying. This all only hasn’t collapsed because money lenders haven’t pulled the plug yet. When that happens, and with every day this looks like a question of when not if, it will be a $hitstorm the likes of which we’ve not seen in a while.
I bought a gaming GPU six months ago for running local LLMs, at outrageous price (2x MSRP), and in 6 months it's price doubled again.
AWS already sold all the compute it has planned for 2026, 2027 and 2028.
If we’re in a gas shortage, all that matters is who has the gas, true. But the issue is that we’re burning 50% of the gas that’s made every day, mean while the other 50% is being stockpiled based on the idea that everyone is going to drive 10x farther next year.
Gasoline in a car is one analogy, but another one is data on the Internet. When the Internet first broke out of universities, there was dial-up. In the late 70's the 300 baud modem was being sold to consumers. It would take roughly three hours to download a novel of 350 pages. It would take roughly two hours to download a single poor quality 256 kilobyte raw 8bpp image file. Jpeg hadn't been invented yet. Now, that image file will take less than ten milliseconds. Roughly a million times faster.
The things we transferred changed too. Today, we stream multiple 4k video with audio streams up and down, so a regular home connection won't suffice for more than a few users. Wirth's law; what Intel giveth, Microsoft taketh away; also applies.
Sometimes digital trends do tend to 10x, or in the case of ISP speeds, we went from 300 baud to gigabit in ~40 years; 3.3 million times faster.
I have no idea what the future holds, but analogies only go so far.
Sure, those things too. I was meaning “inference” as a shorthand for any ai workloads.
Whatever analogy you want to use: gas, data transfer, it doesn’t matter. My point is that all the capacity is being hoarded for future use making it feel like a scarce resource now.
If the demand grows like they say it will, then hoarding was a smart choice and the people who own the GPUs will make lots of money. If the demand doesn’t grow as fast and as much as they say, then hoarding was a bad call and the house of cards collapses and a lot of people will lose a lot of money.
To use your data transfer analog - during the dotcom bubble a ton of fiber was built. But after the bubble popped most of it went unused for years. Some of that “dark fiber” is still unused today, 25+ years later. Afaik it would have been a lot cheaper and more stable for the economy to lay that fiber more incrementally.
1. GPUs are reportedly increasingly just getting put on shelves because there aren’t data centers to host them, which is creating a setup for a financial mess (rapidly depreciating assets purchased, paid for, but not utilized),
2. And massive chunk of the compute “demand” is coming from circular financing (ie AWS is “sold out” in large part because it gave startups like Anthropic money to buy the thing it’s now telling the market is “sold out” so there’s some shenanigans behind those headlines.)
I do agree though that compute is really the only place to make money in AI in the long run. Models are an increasingly a commodity with little value above the cost of compute to run them. However selling compute will be with razor thin margins, not the fat AWS margins the market got used to in cloud, so AWS and others will have to deal with that uncomfortable reality.
Unfortunately, "paid for, but not utilized" doesn't result in rapid depreciation in the case of coordinated market scalping. In that case, dark (unused) hardware is kept on storage to actually cause higher prices until them chips can be sold for profit, in the form of services, after eventual deployment.
I suspect, digging a bit deeper would find some shady financial practices that may lead to a taxpayer funded bailout via the insurance loophole.
I don’t understand the scenario that destroying the chips would guard against. Amazon could just leave these chips in a warehouse indefinitely.
Depends on how they're stored. Computer chips aren't potato chips, they don't rot, properly stored they can last a really long time, a multitude of storage technologies are available for that purpose.
> Doesnt take long for chips to go out of date.
That used to be the case but it's no longer true. Advanced chips are made by 3 companies total and competition is nowhere to be seen. Then, with every generation of chips, their production costs and prices are rising more than the benefits that generation provides i.e. the benefits curve is flattening faster than cost curve.
Theoretically, China can bring the prices down but they are sanctioned, tariffed and have a huge market of their own to satisfy first.
GPU's produced in 2020, with a supposedly "3 year life before depreciating to zero" are now sold at twice their price from 2020.