Is it? The dot-com fiber bubble for instance was famous for laying far more fiber than would be needed for the next decade even as the immediate organic demand was tiny.

In this case however, each and every hyperscaler is bemoaning / low-key boasting that they have been capacity constrained for the past multiple quarters.

The other data point is the climbing rate of AI adoption as reported by non-AI affiliated sources, which also lines up with what AI companies report, like:

https://www.stlouisfed.org/on-the-economy/2025/nov/state-gen...

That article is a little crazy. Not only are 54% of Americans using AI, that is 10 percentage points over last year... and usage at work may even be boosting national-level metrics!

> In fact their math doesn't seem to consider failure at all, which is highly suspicious.

That's a good point! If I had to guess, that may be because Burry et al don't mention failure rates either, and seem to assume a ~2 year obsolescence based on releases of new generations of GPUs.

As such, everybody is responding to those claims. The article I linked was making the point that even 9-year old generations are still in high demand, which also explains the 5 years vs 9 years difference -- two entirely different generations and models, H100 vs M4000.

And while MTBF is not directly related to depreciation, it's Bray who brings up failure rates in a discussion about depreciation. This is one reason I think he's just riffing off what he's heard rather than speaking from deep industry knowledge.

I've been trying to find any discussion that mentions concrete failure rates without luck. Which makes sense, since they're probably heavily-NDA'd numbers.