[skybrian]

Computing is fairly general-purpose, so I suspect that the data centers at least will be used for something. Reusing so many GPU's might be harder, but not as bad as ASICs. There are a lot of other calculations they could do.

[blibble]

a data centre is a big warehouse

the vast expense is on the GPU silicon, which is essentially useless for compute other than parallel floating point operations

when the bubble pops, the "investment" will be a very expensive total waste of perfectly good sand

[fc417fc802]

Most scientific HPC workloads are designed to utilize GPU equipped nodes. If AI completely flops scientific modeling will see huge benefits. It's a win-win (except for the investors I guess).

[skybrian]

I don't think we're too worried about wasting sand, though? What are the major costs of producing a GPU? Which of those are we worried about wasting?

I'm not going to do the homework for a Hacker News comment, but here are a few guesses:

I suspect that a lot of it is TSMC's capex for building new fabs. But since the fabs are already built, they could run them for longer. (Possibly producing different chips.)

Meanwhile, carbon emissions due to electricity use by data centers can't be taken back.

But also, much of an investment bubble popping wouldn't be about wasting resources. It would be investors' anticipated profits turning out to be a mirage - that is, investors feel poorer, but nothing material was lost.

[BobaFloutist]

Maybe they can use it all to mine crypto.

[haganomy]

If I had to hazard a guess as to why China and the US are building so many GPU farms under the guise of "AI supremacy", I'd say it's to support state sponsored hacking.

[kazinator]

> Reusing so many GPU's might be harder

It could have some unexciting applications like, oh, modeling climate change and other scientific simulations.