this post was submitted on 30 Dec 2025
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[–] Knock_Knock_Lemmy_In@lemmy.world 67 points 3 weeks ago (8 children)

Enron crashed because they were cooking their books and faking income, declaring potential profit where none existed

  • Sell chips to X

  • Receive stock in X

  • Value of stocks = discounted sum of future (fake) income

  • Booked as an asset on the balance sheet

This is exactly like Enron but the underlying commodity isn't energy, it's compute.

[–] enumerator4829@sh.itjust.works 7 points 3 weeks ago (6 children)

Nvidia sells plenty of GPUs for actual money, they are good for it.

No, the real issue is the depreciation for the people owning GPUs. Your GPU will be usable for 4-6 years, and 2-4 of those years will be spent as ”the cheap old GPU. After that time, you need new GPUs. (And as the models are larger by then, you need moahr GPU)

How the actual fuck do these people expect to get any ROI on that scale with those timeframes? With training, maybe the trained model can be an asset (lol), but for inference there are basically no residual benefits.

[–] SlartyBartFast@sh.itjust.works 6 points 3 weeks ago (1 children)

I'm still rocking a GTX970 from 2014

[–] enumerator4829@sh.itjust.works 9 points 3 weeks ago

Do this:

  • Calculate the total power cost of running it at 100% load since 2014
  • Calculate Flops/Watt and compare with modern hardware
  • Calculate MTTF when running at 100% load. Remember that commercial support agreements are 4-5 years for a GPU, and if it dies after that, it stays dead.
  • In AI, consider the full failure domain (1 broken GPU = 7+ GPUs out of commission) for the above calculation.

You’ll probably end up with 4-6 years as the usable lifetime of your billion dollar investment. This entire industry is insane. (GTX 1080 here. Was considering an upgrade until the RAM prices hit.)

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