> Im not convinced by the claims of infrastructure only being expensive to build initially.

The claims seem to be true.

> A typical one-gigawatt AI data center requires $38 billion in up-front capital expenditure (CapEx) and $0.9 billion in annual operating expenses (OpEx). If CapEx is annualized over each asset’s lifespan, the total cost of ownership equates to $8.5 billion per year. Servers dominate this cost at $5 billion per year, or 60% of the total. Operating costs are small by comparison: even energy, the largest OpEx category, costs only $0.6 billion per year.

https://epoch.ai/data-insights/ai-datacenter-cost-breakdown

If new hardware comes online that doesn't allow you to payback your billions in hardware, what then? The level of rigor in the article is low.

If we steel-they the point in the essay, it still doesn't matter because a bubble is setup in the economics of the system, not whether the underlying tech works and/or is profitable. It can both work, be profitable, but have been overcapitalized before the knock on effects are in-place in the rest of the economy. This is a crazy analogy, but what if 1700s earth figured out, theoretically how to build a fusion reactor that could supply all the energy needs of the whole planet. But it cost in their equivalent dollars, 1 quadrillion dollars? You can't even integrate under their money curve to scrape together that many dollars. The only economy you can make about that is in the research side to push the cost down. Then when its dialed in, you can launch that rocket AND the rest of the system has had time at many different levels to integrate AI at various levels. OpenAI dry barebacked its way into the economy and literally screwed everything up. If they really were an altruistic AI safety lab, they should have kept working on ChatGPT, but demoed it to the world including government, so we could as a planet decide where we are taking this.

It is a huge bubble, AI is over capitalized, we have no idea what the knock on effects are and really the only benefit right now is in programming, which is huge and civilization changing. But it also has massive downsides in that it has given the most powerful even longer levers to move the earth.

I just don't think the author really has any clue.

they seem to think that debt markets are infinite. "There's Still Plenty Of Capital To Raise"

> The ones that have issued public debt, like Alphabet and Meta, have excellent bond ratings. If they need more capital, they won't struggle to find people to give them a loan.

Yes, and that bond rating is based on the idea that they really don't have that much debt, and have a net profit of something like 30%. If they hoover up a load of debt, the rating will plunge.

> I don't think the rhetoric about the AI bubble is really about finances

Its exactly about finances. The market participants that are not bollocks deep in fake Private Equity valuations are worried about circular debt obligations that are off books. The SEC has been rather lenient about reporting of non-traditional obligations (hence why spaceX was allow to do what ever the fuck it did)

For example anthropic has about 450 billion in non-cancellable obligations. the S-1 puts it at 895 billion. all of that is someone's debt.

If openAI are doing the same thing, thats pretty close to 1.6trillion in debt, both for the same customers, at the time when customers are going "hmm this isn't giving us what we hoped for the price"

Similarly, the claim that "Once all the data centres are built, AI spending is going to plummet" feels incongruous with "it's hard for me to see AI consumption not being 10x what it is now" and "Anthropics revenue has to grow to 250 billion a year to pay off debt". Scaling up seems like a constant need, especially in a market that values growth and hype about frontier models so much. (that said, the author raises things like P/E ratios that I had no awareness of, so I'm not claiming to be an expert)

That is a weird take and after that I sort of just skimmed the rest. Yes building the datacenter is a huge expense, but you need to replace the hardware to stay competitive, and it doesn't last forever. Previously companies ran three year cycles, now five seems to be the standard. If hardware prices come back down, then.... maybe, if not those refresh cycles are going to put some datacenters out of business.

Another issue is that while e.g. Anthropic and OpenAI seems to be interested in building their own datacenters, they are mostly just renting capacity. If they can shop around, then they can get the price down, but there's a base price, due to power, hardware and staff.

The author also suggest that there's still capital to raise... no there's not. Anthropic is going for an IPO, that means institutional investors, not venture capital or borrowing and Anthropic, CoreWeave and Oracle are rated as junk. That doesn't mean that they can't raise capital exactly, but it will be very expensive and the interest payments needs to be factored into the price of the products.

> electricity is not going to get significantly cheaper

The DC push may be the thing that finally gets renewables over the finish line in the US. For example, TX is around 35% renewables right now. If that continues to rise, we may see power fall in price. It’s all about incentives.

It hardly seems to be a one time expense. GPUs and networking equipment may have a useful lifespan of only about five years before needing replacement, and it could be expensive to do so.

So much this.

The current-gen hardware is expected to have only 2-3 years of useful life. New tech, and especially new architecture is going to make inference much faster and more efficient in the near future, and the big vendors are going to be more limited by datacenter floor space and power/cooling, so that the hardware will be replaced very quickly by better models.