3 ms·

I could be wrong but it seems like in the case of a crash no one will be buying new GPUs and thus the existing ones could hold their value longer. Of course tha

by wmf 6mo ago

I could be wrong but it seems like in the case of a crash no one will be buying new GPUs and thus the existing ones could hold their value longer. Of course that value will no longer be massively inflated by bubble FOMO.

irishcoffee 6mo ago
It isn’t about holding value, the cards are going to burn up. If they don’t, in 5 years one could run a rack of 4 cards at home at an affordable rate. Either the cards become affordable again and the datacenter is useless, or they don’t, and nobody can fucking afford to rent them.
- wmf 6mo ago
  GPUs definitely have higher failure rates than CPUs but I'm not sure what the absolute rates will turn out to be. If 10% of GPUs die within 5 years that's very high but also probably economically fine. If 50% die that's a disaster.
  - irishcoffee 6mo ago
    Sorry, I meant at some point the current cards in he data centers will be obsolete, financially. They’ll be sold on the secondary market. Buying 8 h200s at $150 a pop will either be a real thing, or they all burn up and capex explodes again, which would be a death knell. Either way, the moat is about 7 inches wide.
fluoridation 6mo ago
>in the case of a crash no one will be buying new GPUs and thus the existing ones could hold their value longer. No, because no one has any use for those monstrous GPUs outside of ML and some research projects. They can't even be dropped onto the consumer market because a SOHO is not equipped to house devices like that. The best case scenario is that the boards get dismantled and the VRAM gets salvaged for refurbishing. They've built these machines so specialized that they're essentially disposable.
- wmf 6mo ago
  There's a baseline paid demand for AI inference that can fully occupy today's GPUs (even after a crash) so there's no need to sell or scrap them.
  - fluoridation 6mo ago
    What are you basing that on? Some of the demand that currently exists, exists because of all the money sloshing around the AI ecosystem (i.e. people using AI to sell AI solutions to other people), so how are you so sure demand can fully utilize all existing compute even after a crash?

by wmf 6mo ago

irishcoffee 6mo ago

It isn’t about holding value, the cards are going to burn up. If they don’t, in 5 years one could run a rack of 4 cards at home at an affordable rate. Either the cards become affordable again and the datacenter is useless, or they don’t, and nobody can fucking afford to rent them.

wmf 6mo ago
GPUs definitely have higher failure rates than CPUs but I'm not sure what the absolute rates will turn out to be. If 10% of GPUs die within 5 years that's very high but also probably economically fine. If 50% die that's a disaster.
- irishcoffee 6mo ago
  Sorry, I meant at some point the current cards in he data centers will be obsolete, financially. They’ll be sold on the secondary market. Buying 8 h200s at $150 a pop will either be a real thing, or they all burn up and capex explodes again, which would be a death knell. Either way, the moat is about 7 inches wide.

fluoridation 6mo ago

>in the case of a crash no one will be buying new GPUs and thus the existing ones could hold their value longer. No, because no one has any use for those monstrous GPUs outside of ML and some research projects. They can't even be dropped onto the consumer market because a SOHO is not equipped to house devices like that. The best case scenario is that the boards get dismantled and the VRAM gets salvaged for refurbishing. They've built these machines so specialized that they're essentially disposable.

wmf 6mo ago
There's a baseline paid demand for AI inference that can fully occupy today's GPUs (even after a crash) so there's no need to sell or scrap them.
- fluoridation 6mo ago
  What are you basing that on? Some of the demand that currently exists, exists because of all the money sloshing around the AI ecosystem (i.e. people using AI to sell AI solutions to other people), so how are you so sure demand can fully utilize all existing compute even after a crash?