Bill Gurley

The one thing I tell you about the depreciation argument as it relates to this company is, you know, a lot of people push on, you know, there's a statement by Jensen at GTC that, you know, hoppers may not have value because Grace Blackwell is so much better.

The one thing I tell you about the depreciation argument as it relates to this company is, you know, a lot of people push on, you know, there's a statement by Jensen at GTC that, you know, hoppers may not have value because Grace Blackwell is so much better.

The one thing I tell you about the depreciation argument as it relates to this company is, you know, a lot of people push on, you know, there's a statement by Jensen at GTC that, you know, hoppers may not have value because Grace Blackwell is so much better.

My view on this is like, listen, because we've got to square this circle. We have the SACS tweet. We know the inference demand is off the charts. Everybody is demonstrating their need for more GPUs to run inference. Everything in the world is becoming inference. We've talked about that at length. And so my view is this. When you talk about two years for GPUs,

My view on this is like, listen, because we've got to square this circle. We have the SACS tweet. We know the inference demand is off the charts. Everybody is demonstrating their need for more GPUs to run inference. Everything in the world is becoming inference. We've talked about that at length. And so my view is this. When you talk about two years for GPUs,

My view on this is like, listen, because we've got to square this circle. We have the SACS tweet. We know the inference demand is off the charts. Everybody is demonstrating their need for more GPUs to run inference. Everything in the world is becoming inference. We've talked about that at length. And so my view is this. When you talk about two years for GPUs,

They're going to—cutting-edge GPUs are going to be used for cutting-edge training for the, you know, frontier models in that first two-year period. But all these things are going to continue to get used for inference.

They're going to—cutting-edge GPUs are going to be used for cutting-edge training for the, you know, frontier models in that first two-year period. But all these things are going to continue to get used for inference.

They're going to—cutting-edge GPUs are going to be used for cutting-edge training for the, you know, frontier models in that first two-year period. But all these things are going to continue to get used for inference.

And the right way to think about CoreWeave, you know, and, you know, I think the consensus margins for this business are like 25% EBIT, you know, over the course of the next couple of years. How do they get there? You know, so think about their unit economics bill. you know, their CapEx, their OpEx. So they got to get a data center. They got to pay for all their operating expenses.

And the right way to think about CoreWeave, you know, and, you know, I think the consensus margins for this business are like 25% EBIT, you know, over the course of the next couple of years. How do they get there? You know, so think about their unit economics bill. you know, their CapEx, their OpEx. So they got to get a data center. They got to pay for all their operating expenses.

And the right way to think about CoreWeave, you know, and, you know, I think the consensus margins for this business are like 25% EBIT, you know, over the course of the next couple of years. How do they get there? You know, so think about their unit economics bill. you know, their CapEx, their OpEx. So they got to get a data center. They got to pay for all their operating expenses.

Then they got to buy the servers. So the way this works, I think, is they sell a four-year deal to Microsoft or a four or five-year deal to OpenAI or four-year deal to Google or whatever. They expect to pay back all the CapEx, OpEx, and GPUs in three years. And so the fourth year, which is a four-year guaranteed contract, the fourth year is your profit margin, right?

Then they got to buy the servers. So the way this works, I think, is they sell a four-year deal to Microsoft or a four or five-year deal to OpenAI or four-year deal to Google or whatever. They expect to pay back all the CapEx, OpEx, and GPUs in three years. And so the fourth year, which is a four-year guaranteed contract, the fourth year is your profit margin, right?

Then they got to buy the servers. So the way this works, I think, is they sell a four-year deal to Microsoft or a four or five-year deal to OpenAI or four-year deal to Google or whatever. They expect to pay back all the CapEx, OpEx, and GPUs in three years. And so the fourth year, which is a four-year guaranteed contract, the fourth year is your profit margin, right?

And then anything you earn past the four years, that's all gravy on top. And the consensus earnings are not giving them any credit for anything after the end of those contract periods. Now, what I'll tell you is, and we've done a lot of research on this, There's still a lot of A100s in use in the world today. In fact, Jensen has talked at length about that. That's a 2020 product.

And then anything you earn past the four years, that's all gravy on top. And the consensus earnings are not giving them any credit for anything after the end of those contract periods. Now, what I'll tell you is, and we've done a lot of research on this, There's still a lot of A100s in use in the world today. In fact, Jensen has talked at length about that. That's a 2020 product.

And then anything you earn past the four years, that's all gravy on top. And the consensus earnings are not giving them any credit for anything after the end of those contract periods. Now, what I'll tell you is, and we've done a lot of research on this, There's still a lot of A100s in use in the world today. In fact, Jensen has talked at length about that. That's a 2020 product.

So we're in the fifth year and A100s are still out there being used by almost everyone that bought A100s. And then if you look at it, I think Jensen at GTC said last year that that OpenAI had just retired the V100s. That was a 2017 GPU. So that's like a seven-year lifecycle that they were using those for.

So we're in the fifth year and A100s are still out there being used by almost everyone that bought A100s. And then if you look at it, I think Jensen at GTC said last year that that OpenAI had just retired the V100s. That was a 2017 GPU. So that's like a seven-year lifecycle that they were using those for.