How CoreWeave Sees the Market for Compute Right Now

**Brannin McBee** (0:02)
Bloomberg Audio Studios, podcasts, radio, news.

**Joe Weisenthal** (0:18)
Hello, and welcome to another episode of the Odd Lots Podcast. I'm Joe Weisenthal.

**Tracy Alloway** (0:22)
And I'm Tracy Alloway.

**Joe Weisenthal** (0:24)
Tracy, I'm envisioning this future, where we have to do a state of the sort of AI inference market episode once a month, you know? Where it's like, things are moving so rapidly, and there's so much change, either in terms of what models are using, or what they're being used for, et cetera, that in the same way we would do the occasional regular stock market episode, or whatever, we would just do, okay, what are we seeing right now in AI inference trends? Because it just feels like the moment we do an episode a few weeks later, it may be out of date.

**Tracy Alloway** (0:58)
We should just bite the bullet and do a weekly episode. Transform Lots More into a market update on compute.

**Joe Weisenthal** (1:04)
We could do inference, I don't know, we'll have to workshop a bit.

**Tracy Alloway** (1:08)
Odd inference?

**Joe Weisenthal** (1:09)
No, no, we'd have to, but anyway, this is like-

**Tracy Alloway** (1:12)
Lots of inference.

**Joe Weisenthal** (1:13)
Lots of inference.
This is like the story of the moment, and we know that a couple of years ago, everyone was dabbling around with various things, and experimenting, and using AI, like, write a poem for me about this, etc. That phase of AI is long over, and we know that companies specifically are spending a ton on compute, so much so that CFOs around the world are getting sticker shock about their compute budget, and there was even a headline of Uber saying, okay, $1,500 or max per employee, don't spend more than that in a month on token. So this is a very fast moving area.

**Tracy Alloway** (1:54)
Yeah. You're starting to get headlines about, I guess, a corporate reckoning with AI as more people experiment and spend money on it. The Uber headline that you mentioned, apparently Uber burned through its entire 2026 AI budget in four months, basically, and what's more important is the COO was actually asking whether or not that was worth it, like whether they saw productivity gains or whatever as a result of that.
The other very amusing headline that I saw, and it was citing an unnamed source. It's from Axios, so not entirely sure it's true, but reportedly, it was a great headline. An AI consultant told Axios that one of their clients recently spent half a billion dollars in a single month after failing to put usage limits on the floor.

**Joe Weisenthal** (2:40)
It's because everyone is like, I just have a simple question. I want to look up our guests' title. I'm going to use the most advanced model to do that, etc. I have a theory, and we will get into this with our guests, that one of the things that will, and we've talked about this with Goldman's Marco Argenti, but one of the things I predict is that companies are clearly, they're going to keep using it more and more, would be my guess. But there were probably a lot of investment made in sort of like optimal model routing, because some models are like a hundredth per query of what a frontier model is. Probably a lot of people don't know, like, what is the sort of like efficient frontier model usage. And so actually routing the query to the sort of most efficient model, I have a feeling we're going to see a lot of investment in that area specifically.

**Tracy Alloway** (3:27)
Well, there's also just the question of whether or not the models get cheaper overall as they advance, right? And we have seen some, I think Nvidia has a new system called chip out or something that is supposed to reduce token usage, we can get into that as well.

**Joe Weisenthal** (3:41)
And we did that live episode recently with Ian Dunning of Hudson River Trading. And he said a lot of interesting things in that. But one of the things he said is that the scarcity is increasingly just the real estate component, finding a suitable place to plug in your GPUs, at least from his perspective right now, is as much, if not more so of a challenge than securing GPUs themselves. So like-

**Tracy Alloway** (4:08)
Which is different to what it was like three years ago, yeah.

**Joe Weisenthal** (4:10)
Yeah, so it's just like where you plug it in, we know there's all the like the anti data center politics out there. So it's like, yeah, we gotta take the pulse of this market.