https://www.tomshardware.com/tech-industry/data-centers-in-n...
It’s not the same as dark fiber capacity being overbuilt for demand that wasn’t there yet.
Is this really true? Other than the occasional outages, the frontier labs don't seem to be getting overloaded by API pricing customers at peak times, and with Opus 5.5 using even less tokens (which translates into less GPU time and less money spent on the same tasks), it seems actual capacity isn't literally strained right now. If current needs are met by currently available capacity, where is this demand going to come from?
Maybe somebody will use them, but not the original owners.
I can directly confirm this fact, and I'm just some random dude out here in suburbia, who can only imagine what the Indiana Jones warehouse of glowing GPUs looks like in a data center.
We're all salivating over this imagined future where an AI toilet seat greets us every morning.
Who here has already asked AI how to make your own DRAM ? I know you have. Thats a sign of peak interest in a subject or market.
I'm not, but I can certainly believe the surveillance industry vectoralists are salivating over a future where their AI toilet seats greet each of their data subjects every morning.
Today, the "old" corporations like google, meta, amazon are also spending a lot of money.
Not according to this article[1], which says:
"I believe we are now in an inevitable overbuild situation, one with no neat, tidy Dot-Com Bubble-style exit story. Demand for NVIDIA GPUs — and those from Broadcom, AMD and other semiconductor companies — is driven by speculative capital believing that the AI industry will become magnitudes larger than it is today, largely driven by the fact that everybody believes there’s far more demand for compute capacity than actually exists. ... NVIDIA has created a remarkable illusion perpetuated by the media — that GPU sales are a direct measurement of the actual demand for AI compute, rather than a measurement of how a few companies are willing to invest in an idea two years in advance, using circular financing as a means of creating the sense that you must buy these GPUs now, or you’ll miss out on the future. ... At the very least, hyperscalers are going to be burdened with brutal depreciation charges or onerous write-offs for years to come, whether their capacity turns into revenue or not. ... I don’t see how 90%+ of NVIDIA’s sales ever end up generating a single dollar of revenue, and considering the amount of project financing-backed data center debt deals, there’s very little that exists to protect investors if AI compute demand never arrives."
The man saw the market demand for saying "AI bubble is going to pop and AI tech is going to wither away and die", and went to meet it on the supply side - truth be damned.
So far, AI companies still keep getting bottlenecked on compute, AI utilization increases - driven by, among other things, increased price-performance of AI making it viable in more and more roles. And the demand for both AI inference and AI hardware in general shows no signs of stopping.
HN discussion: https://news.ycombinator.com/item?id=49526069
The other hyperscalers are even further delayed. CoreWeave has some VeraRubin, but not in volume (as I understand).
After the crash no one will need to build a new data center for 20 years, and there will be plentiful power connections
A lot of its current use is just basic questions that could be handled by local llms just as well, yet they are being processed on GB200s on the other side of the world.