Four CEOs on the Future of AI: CoreWeave, Perplexity, Mistral, and IREN
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What insights does Michael Intrator share about the early days of CoreWeave?
I'm here at NVIDIA's annual GTC conference, and I'm going to interview four amazing AI CEOs. Stick with us.
Our episode is sponsored by the New York Stock Exchange. Are you looking to change the world and raise capital? Do it at the NYSE. The NYSE is a modern marketplace and a massive platform built for scale and long-term impact. So if you're building for the future, the NYSE is where it happens. One of the great companies of the AI era is, of course, CoreWeave. They're building massive infrastructure for these hyperscalers. And in some ways, Michael, Intrader, welcome to the program. You're the original hyperscaler. You guys got in very early and secured your, I don't know which GPUs you wound up getting. You were very early to this trend. How did you... get to it so early and how did you build out this, you know, first, I guess at the time, Neocloud?
Yeah, so we didn't really start it as a Neocloud and I was running an algorithmic hedge fund focused on natural gas and when you build an algorithmic hedge fund, once the algorithms are built, you're really just monitoring it and testing different theses and doing all that. But there's also a lot of downtime and we got super interested in crypto and you know, we're pretty nerdy, we kind of dig under the hood and we started to get interested in the security layer. We looked at Bitcoin and the mining for Bitcoin and we didn't like it. We just thought that like, there's some brilliant engineer that built the ASIC and they're probably gonna be better at running it than we are. So we really began to focus on the GPUs
mostly because the GPUs were, you can mine Ethereum with them, but you could also do all these other things. And really, so right from the start, we looked at the compute as an option to be able to deploy our computing power to different use cases. And so, you know, began the company in 2017, you know, spent the first kind of three years mining crypto, went through a couple of crypto winters. Because we had come from a hedge fund, we have real chops in risk management and how we think about capital and risk exposure and allocation and all of that. And so we were really careful around that right from the start. So we weathered crypto winter really well and began to scale the company and immediately started to look for other use cases that you could use this compute for, because crypto was pretty volatile.
Yeah. And crypto was a question mark at that time. Absolutely. Yeah. I mean, Bitcoin was speculative and there were many other speculative projects. The only other people using this type of hardware, quants, medical researchers.
So a good way to think about it is like the progression of products that we kind of started to work on. You know, first was crypto, but we immediately moved from crypto to CGI rendering and we built projects that would allow uh um folks that were trying to animate and render images um you know kind of what makes the movies cool right and and uh we started to work on that and then we moved to batch computing and started to look at medical research and different ways of using the compute to be able to drive science um and we just kind of kept moving up the stack in terms of complexity um on how GPUs could be used. And ultimately in like, call it like 2020, 2021, we started to really try to figure out how you can go ahead and use GPUs for neural networks.
And that was not something that we knew how to do. And so we actually went out and bought a bunch of A100s and donated them to a group that was working on Luther AI. They were working on an open source project with the thought that, these guys are taking the GPU compute because we're donating it. They can't really get pissed at us if we're not very good at it initially. And that worked out really well because they can't complain about the SLA. They kept telling us like, we need more of this. You got to work on this. And that began to really give us an understanding of what was necessary to run scale parallelized computing. And we went through it.
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Chapters
8 chapters
1
What insights does Michael Intrator share about the early days of CoreWeave?
0:00–5:06
2
How did CoreWeave transition from crypto mining to AI computing?
5:06–12:40
3
What challenges did CoreWeave face during the crypto winters?
12:40–18:25
4
What role do GPUs play in AI and how has their use evolved?
18:25–33:39
5
How does Mistral AI plan to innovate in the AI space?
33:39–38:38
6
What is IREN's strategy for leveraging AI in their operations?
38:38–44:36
7
How do energy sources impact AI data centers?
44:36–48:50
8
What future developments are expected in AI technology?
48:50–1:37:17
Speakers
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