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This guy is peddling the same tired “it’s just like the dot com bubble” talking points that you only draw on if you have no real interest in reality. He’s also the guy who wrote the infamous “advice to a poor black kid” blog. Legendary dipshit

The post-dot com bubble story doesn’t work here. Training ai models at scale is only possible with billions of dollars of funding. Ai data centers are not useful for other stuff at any meaningful scale. A data center will be as expensive to finish building or run in ten years as it is today.

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The capex is expensive, but so is running AI GPUs. People want this to be “like the dot com bubble” to not think about how big the misallocation of capital is. All of the current demand is from companies that can’t afford to pay without endless VC dollars or people renting compute to resell to them.

but even if it *is* like the dot com bubble, all that dark fiber was still useful after sitting for years. in ten years today's GPUs in those DCs will be competing with GPUs 6-7 times as powerful.

Bingo. It is much, much, much worse than the dot.com bubble. Huge circular financing of Capex that is being recognised right now in "earnings". So when the bubble pops earnings won't just stop growing, they will massively contract. It's the ultimate example of the Kalecki profits equation in action.

i love how “it’s just like the dotcom bubble” is seen as a defense. Just because we got cheap fiber or whatever doesn’t mean it was okay to waste all those resources in the bubble.

One (of many) things that bothers me about these datacenters is you see "projections" from AI companies like "we'll be profitable in 2030!" (although even that is based on magically discovering new technologies.) - but the GPUs that are core to their buildout will be obsolete by then.

Fair points but specific to GPUs; they’ll still have a lot of utility come 2030. They’ve been a niche element (ex., VDI) in data centers for many years now. So beyond LLMs there are/will be use cases *Note, I’m not discussing the sheer volume of the build outs making sense, just GPUs as a processor

Those use cases are teeny tiny compared to the amount of data centers being built to the point that they may as well not exist

Well, by 2030 they'll be very outdated, and they're not particularly well suited to other tasks, so they'll be an outdated card being used inefficiently. You can dismantle the datacenter and repurpose the cards, but you're selling them at a tiny fraction of what you paid.

AI inference/training boxes are so weird that it's not really economical to use them for anything else; Nvidia boxes run on their own ARM CPUs and a 4RU box will be pulling like 20kW. They're highly specialized for AI and not a whole lot else - they can't even really do graphics anymore.

I dunno, if I had a business model which was "version 1 loses money, but version 2 will be great and make lots of money" I'd want to spend as little as possible on gear that will only be used on version 1...

Plus, AI art now looks all the same. AI writing is converging. In their best-case scenario, the more the tech gains a foothold, the less new human intelligent input will exist to borrow from. You can see it in the way they are now gathering up so many old pre-AI books for training. It's nonsense.

better climate models. new materials science. modeling protein structures. finding new medicines. image processing. like diagnostic images, or telescope images of deep space. finding patterns in large data sets, could be in medical records, or discrimination in criminal sentencing. lots of stuff.