Comment by jerf | Hacker News Reader

Comment by jerf | Hacker News Reader

I'm at a loss as to how some of these projects got funded in the first place. Anyone funding these should have had the perspective to see that there isn't enough power for them. Anyone funding them should have had the perspective to see that by the time power could come online for even a significant fraction of them, the depreciation and interest costs should have murdered the company trying to do it, especially if their solution to that problem is the oh-so-21st century solution of "solving" the problem of losing money by levering up. It does no good to go out of business entirely in 2027 to make the phat buxx in 2030, which seems to be the best case scenario for this space as a whole.

The other question I have is... who exactly is doing all of 1. Using AI right now 2. Making substantial money on it or getting real value and 3. Capacity constrained? Who is actually going to productively soak up all this capacity? It seems to me that bringing all this stuff online can't really make things much cheaper than they are now because the fixed costs aren't going anywhere, and if anything, trying to jam so many projects through all at once just raises those fixed costs even higher. It's not like they triple data center capacity (and increasing AI capacity by, what, 10x? 20x?), stick them full of AI systems, and into that 10x+ greater AI capacity they can sell it at the prices they are now. Higher capacity would crash the selling price but the costs would be as high or higher than now.

I am at a complete loss as to how the numbers are supposed to work here. You can't build a company in 2026 on the economy and tech infrastructure of 2036 anymore than it worked to build a company in 1999 on the economy and tech infrastructure of 2019, no matter how rosy the numbers look on the projections based on conveniently ignoring the fact the company passes through "death" in a year and half. Everything promised in 1999 happened, but trying to artificially accelerate it onto Wall Street's time line burned money by the billions. I'm sure 2036 will have lots of AI in it, but you can't just spend money to bring it forward 10 years by sheer force of will. It has to happen at its own pace.

> The other question I have is... who exactly is doing all of 1. Using AI right now 2. Making substantial money on it or getting real value and 3. Capacity constrained?

Almost all enterprise users for one. At least from what I have seen it is a massive productivity boost for coding and general research. If the costs were ~4x lower, we would be able to do much much more with them. Building datacenters will reduce the cost because increasing supply would reduce the cost.

> It's not like they triple data center capacity (and increasing AI capacity by, what, 10x? 20x?), stick them full of AI systems, and into that 10x+ greater AI capacity they can sell it at the prices they are now. Higher capacity would crash the selling price but the costs would be as high or higher than now.

This is false. Part of the costs are unit costs which are really high margin. I think the margins are around 50% to 60%. By increasing the capacity, the are bound to make even more profit.

But the other part is reflecting the lack of capacity.

"Building datacenters will reduce the cost because increasing supply would reduce the cost."

That's great for us users but I'm talking from the point of view of the people trying to make money on the data centers.

"This is false. Part of the costs are unit costs which are really high margin."

Can you explain how everybody throwing their money at nVidia lowers the costs? When they are already apparently at max capacity?

Everybody trying to build a data center at once raises the costs of the data center. Everyone competing for power has already raised power prices and we've barely begun bringing this stuff online. Everyone demanding multiples of what nVidia is producing means nVidias isn't going to reduce prices any time soon.

Your use of "even more profit" also implies that you think that the AI world is making lots of money? nVidia is making lots of money. To a first approximation, everybody else involved has lost billions. Maybe not Apple. But everyone else you can name is deep in the negative on AI.

> That's great for us users but I'm talking from the point of view of the people trying to make money on the data centers.

Why wouldn't they make money if they are the ones on whom money is thrown at?

> Can you explain how everybody throwing their money at nVidia lowers the costs? When they are already apparently at max capacity?

Increasing supply lowers the cost, I'm unsure which part of this is surprising.

> Your use of "even more profit" also implies that you think that the AI world is making lots of money? nVidia is making lots of money. To a first approximation, everybody else involved has lost billions. Maybe not Apple. But everyone else you can name is deep in the negative on AI.

The companies using AI are making money out of it. OpenAI will make money in the future but are losing it because of R&D and training.

> To a first approximation, everybody else involved has lost billions.

"Lost" implies they have nothing to show for it. But they do. Depending on who you're looking at, they have data centers, GPUs, as well as billions in revenue and hundreds of millions of users, both rapidly growing. We can't say anything is "lost" because these are investments, and will only be sunk costs if nobody ever makes money.

But people are already making money. The big names are in a growth stage, so their spending is far outpacing their returns, but if you look beyond, people are making a ton of money on AI, which bodes well for these investments. Some data points:

1. AI startups are growing revenue at a record pace, as confirmed by three separate groups adjacent to them -- investors, enterprise purchase decision makers, and Stripe (which processes their payments): https://news.ycombinator.com/item?id=46730182

2. AI is creating a boom in mobile apps, including a surge in revenue -- https://techcrunch.com/2026/01/21/consumers-spent-more-on-mo...

So much that Apple made a billion more just from their App Store cut: https://www.macrumors.com/2026/03/20/apple-made-nearly-900m-...

3. AI agents boosting holiday sales: https://www.salesforce.com/news/stories/2025-holiday-shoppin...

Keep in mind we are only ~3 years since ChatGPT kicked this whole thing off

> At least from what I have seen it is a massive productivity boost for coding and general research

Are companies release more software with less developers? If the answer is no, then the productivity has not improved. It might SEEM like it improves because you're able to produce more code and you spend less time programming, but that might not be the case in actuality.

From what I've seen, AI is very good and very popular but it hasn't improved programming productivity in a meaningful way. The bottlenecks are unchanged so writing more code faster doesn't help anything. A lot of companies let a lot of employees go due to AI, and their product velocity has noticably gone down and their quality is noticably worse.

In xAI's case, they've gotten gas turbines installed on site with which to make up the electricity generation shortfall onsite. It's unclear exactly how long that short term solution is going to be there, but probably quite a while.

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