Older GPUs keep finding buyers after the training cycle

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 10:13

   So that's been a big debate is, I think, for your company, for Microsoft, and I guess Michael Burry, you know, who you must have known when you were a quant, you know, saying, oh, my God, the whole industry is the sky's falling. And then we all know in the industry that people don't just throw this hardware away, that they find uses for it. The street finds its own use for technology. So what's the reality of the lifespan of these things?

2. 10:36

   So my take on the GPU depreciation debate is that it's nonsense, right? It's a debate that is being brought to the forefront by some traders that have a short position in the stock and they're trying to talk down. Look, here's what we know, right? When we buy infrastructure, we're a success based company, right? We're a small company on a relative basis compared to the enormous companies that we're competing with.

3. 11:04

   And so our clients come into us and they buy Compute for five years, for six years. Our average contract is five years. So any commentary by anyone either inside or outside of the industry that this stuff becomes obsolete in 16 months or whatever nonsense they're spewing, it doesn't in any way match up with the facts on the ground. The facts on the ground is they're buying it for five years. right if and my approach to this has always been if people are willing to pay me for it it still has value correct pretty simple way of uh of approaching it we use a six-year depreciation um we believe that the gpus will last in excess of six years but we felt like that was a fair and reasonable approach to a technology cycle that's moving at this velocity um the a100s the amperes this year the price has appreciated through the year why is that i i think it's

4. 11:59

   because One of the things that happens is as more installed capacity becomes available, you have new companies that come into existence that have new use cases that have different size models that are trying to build new commercial ventures that maybe have been blocked out of the H100s and never had an opportunity to run on that. I mean, to make a very simple example for the audience, like when you trade in your iPhone after three or four years, you're like, who's going to use an iPhone 12?

5. 12:29

   And it's like, have you been to South America or Africa where you go to the store and you buy an iPhone 12 or you buy the Pixel 7 and it costs $50? That's still got great life left in it. Absolutely. Yeah. You know. And so, look, you know, we find these amazing use cases, new companies that have come into existence or existing companies that have integrated new models into their workflow that are able to use the Amperes. And so they keep buying any GPUs that we have available.

6. 13:02

   And once again, you know, the concept that a GPU is no longer relevant or commercially viable after 16 more, 18 months or two years. Yeah, that's farcical. It just doesn't make any sense. It's obviously farcical. I think sometimes people get caught up in Moore's Law or in just how fast our industry is growing and that there's so much at stake that big companies are demanding the most recent products, that doesn't mean that the lifespan has gotten shorter.

7. 13:29

   It means the opportunity and the surface area of the opportunity has gotten much larger. Yeah. One of the things is, is like, you know, the industry has gotten so much attention for the unprecedented scale of capital that is coming to bear on this. And because of that, there tends to be an incredible focus on the companies that are building on these most advanced chipsets. And the truth of the matter is, even within those companies, they have a long tail of useful life to provide inference horsepower, to work on other experiments, to do less bleeding edge activity, but still needs to be done.

8. 14:14

   And yeah, I mean, rendering comes to mind as well. Or yeah, we're making images on Nano Banana. Like there will be a use for it. There is a moment in time where maybe the compute to power ratio doesn't make sense. My expectation is obsolescence will be defined by the moment in time where the power in the data center, for me, will be able to be repurposed for a higher margin than the existing infrastructure provides. And, you know, like I said, I fully expect this infrastructure to last in excess of six years. But the standard in the space has really been used with one exception, which is Amazon, which is, yeah, it's six years. That seems like the right schedule. I'm not making it up.

9. 15:03

   that's what everybody's using yeah and the energy cost is the opportunity because hey it's just we need that space there's a better uh reward here and that might get resold that hardware to somebody else who wants it a hobbyist or something it's yeah or it could be sent someplace else where they have more capacity when they can repurpose it there but i i um i kind of feel like you know we'll we'll deal with that part of the business when we get there what i know right now is it is extraordinarily profitable.

10. 15:36

    It's very creative to my company to continue to keep the infrastructure that's been up and running, that's been on these long-term contracts. And as it rolls off, as it's been in use for five years, as it becomes available, I am still able to sell it at a higher price than it was at a year ago. There's competition now. When you were buying these from Jensen back in the day,