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▲ treis 4 hours ago

This is quite misleading. It includes numbers for commitments for leases of data centers and payments for power that are decades into the future.

Even if AI completely busts and all of these servers are worthless that doesn't mean the data centers are. There's still a need for data centers to host non-AI servers. The hyperscalers will close/sell other data centers and serve from places where they have long term commitments at.

3.2 trillion sounds like a lot until you spread it over 20 years and half a dozen trillion+ dollar companies. It's hard to tell how much a bag they're holding but it's almost certainly negligible compared to revenue and market cap. The only real systemic risk is the risk of for some reason not needing any data centers.

▲vessenes 4 hours ago | parent | next [-]

As I've been pointing out a little bit recently -- the 'downside' scenario -- somehow we conclude we have enough inference at our world's desired quality and therefore demand stabilizes below that of these datacenters -- would be GREAT for the world. Super cheap intelligence for all.

If some lenders go bankrupt on a datacenter note post-buildout and the capital structure is reworked, lowering the costs by removing capitalization costs from the cashflow of the inference provider, that is all to the good of people who did not do the initial lending.

I think that is extremely unlikely, but it's good for datacenter doomers to think through these scenarios IMO.

▲nickff 3 hours ago | parent | next [-]

Your take seems a bit optimistic if we use the dot-com boom as an analogy. The dot-com boom sped up a massive infrastructure build-out, but also left damage that lasted for a very long time, with many organizations collapsing, and others taking a very long time to recover (e.g. cisco networks). It also seems that these 'data-centers' have a higher depreciation rate than 'dark-fiber' did post-dot-com, which means that there is likely to be greater capital waste.

I am not sure whether the dot-com boom was a net-positive, and the AI boom may be less productive.

▲treis 40 minutes ago | parent | next [-]

My point is that these hyperscalers need X traditional data centers and Y AI data centers. If Y goes to 0 that doesn't mean they eat everything they've spent on those data centers. They get converted to serve non-AI loads while other older ones get abandoned or leases not renewed and so on.

In that scenario the GPUs are a loss. But really at this point inference is so profitable it's hard to imagine these data centers not being able to at least cover operations & rent.

▲alasdair_ 14 minutes ago | parent [-]

Ai datacenters are quite different from traditional datacenters. For example, a massive cost for ai DCs is power and the grid to support it. Regular DCs don’t need anything like the same power.

▲vessenes 3 hours ago | parent | prev | next [-]

It absolutely was a net positive. On the infrastructure side we got datacenters built and tons of dark fiber put down. At the start of the boom we had only 2G cellular for goodness sake. I think you could argue we wouldn't have necessarily had the rise in cloud compute without some of the 'overbuilding' of datacenters in web 1.

For reference this 'massive build-out' resulted in, according to a Berkeley study I found, 500MW of total datacenter power in the US across 320 locations at end of 2020. This wasn't too much for very long: as of 2005, according to Tier1 there were 511 datacenters. And it was likely only really a year or two: Dupont's VA3 utilization numbers published it at 50% utilization in 2003, 89.4% in 2004, then full thereafter.

Meanwhile, these infrastructure improvements allowed, for example, things like the iPhone to be built and deployable -- there was 3g, there were a LOT more web devs that could create the early (web only) apps the iPhone needed to compete. This in turn allowed another round of investment to be built on top of all of that.

On the capital side, investors were also able to buy Amazon at around $1 / share. AAPL at iPhone launch was $7/share. I haven't split adjusted either of these, this is just from memory.

I don't think a bust was necessarily good but the boom undeniably built out infrastructure, a small fraction of what the world is currently using, and did it pretty quickly, and then post bust that infra got bought out in a capital efficient manner. I think that's the bear case here.

Put another way, the Dotcom one boom was wrong about two things: timing was too fast, and the predicted scale of change was way, way, way too small. They undersold the future.

▲mr_toad 3 hours ago | parent | prev | next [-]

A lot of the dot com failures didn’t spend on massive infrastructure, they just burned through cash on salaries and expensive chairs.

They were underpants gnomes who had no realistic way of making money.

▲bahmboo an hour ago | parent | next [-]

This is something people miss when comparing things to dot com. It was a very thin layer on top of something new. 90% of the companies were speculative jokes with no basis in reality. Anthropic makes a profit. Google is a mature company that makes a profit and will continue to do so.

▲hnav an hour ago | parent | prev [-]

Not sure when you last were in SF but there is probably half a billion in Series A capital within 1 mile radius of me raised by very nebulous AI start ups.

▲vkou 3 hours ago | parent | prev [-]

Cisco networks took a very long time to recover, but in the meantime, everyone else enjoyed massive growth in cheap connectivity.

Capital waste is only capital waste if the physical goods that were built are no longer useful for anyone. Otherwise, it's only a waste for the people who lent money.

▲ThrustVectoring 2 hours ago | parent | prev | next [-]

The downside scenario isn't AI equity getting zeroed out and lenders getting crammed down. It's the federal government deciding that AI capabilities are of national strategic importance and throwing trillions of taxpayer dollars onto the bonfire.

▲SpicyLemonZest 3 hours ago | parent | prev [-]

It really depends on the "somehow". The most realistic downside scenario, it seems to me, is that most people don't care too much about super cheap intelligence for all because there ends up being another bottleneck for most of the things we value.

Like, trains are an incredible technology which transformed the world, but very few people go around counting their lucky stars that they live in a world that permits such wonders. It's a train, it gets things where they need to go, and by the way isn't it so annoying that sometimes it doesn't quite arrive when the schedule said it would?

▲vessenes 3 hours ago | parent [-]

Sounds like you live in Europe! Bring me more trains pls

▲ 2 hours ago | parent [-]
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▲smuhakg 2 hours ago | parent | prev | next [-]

> The only real systemic risk is the risk of for some reason not needing any data centers.

How is this not a systemic risk? Asserting that:

> There's still a need for data centers to host non-AI servers.

Isn't true because a NVL72 rack consumes 23x the power of a traditional server rack which is why there's new construction. You could retrofit such a datacenter with normal servers but then you're taking a loss on the GPUs which is the majority of the cost.

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

▲hnav an hour ago | parent [-]

Wonder if we'll see ultra-dense CPU compute (1000s of cores in 1U) to take advantage of this power density whether the AI bubble pops or not.

▲dam_jackalopes 3 hours ago | parent | prev | next [-]

It depends. For Anthropic half of the $900b is going to be incurred by the end of 2030. There's definitely risk.

▲Grimblewald 4 hours ago | parent | prev | next [-]

what do you think debt is? what you've described as misleading, is debt by definition.

▲freediddy 3 hours ago | parent | next [-]

It is, by definition, NOT debt. With debt, you are given a lump sum of money. These are spending contracts, but any contract has the ability to be gotten out of, unless your lawyers are very stupid.

▲tremon 3 hours ago | parent [-]

> With debt, you are given a lump sum of money

That would be called a loan, I think?

▲nomel 2 hours ago | parent [-]

They mean you're obligated to the money. You can't back out. You're in debt to them. But, some of this does not include obligation, so fundamentally isn't the same as debt.

▲treis 3 hours ago | parent | prev [-]

I didn't say it wasn't debt. I said it was 20 years worth of spend on something they need regardless of what happens with AI.

▲dd34e 4 hours ago | parent | prev [-]

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