The Future of AI Infrastructure with CoreWeave

**SPEAKER_1** (0:02)
Welcome to the Practical AI Podcast, where we break down the real world applications of artificial intelligence and how it's shaping the way we live, work and create. Our goal is to help make AI technology practical, productive and accessible to everyone. Whether you're a developer, business leader, or just curious about the tech behind the buzz, you're in the right place.
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**Chris Benson** (0:41)
Welcome to another episode of Practical AI.
We are the podcast that tries to make AI practical, productive and accessible for everyone. We get to talk to all sorts of cool people in industry. And today, I want to introduce you to Corey Sanders, who is the Senior Vice President of Product at CoreWeave, which we've been seeing in the news quite a lot lately, and looking forward to learning more about CoreWeave and the various problems it solves and the position in the AI world that it's fulfilling. Welcome to the show, Corey.

**Corey Sanders** (1:14)
Thanks, Chris, for having me. I was going to say, you got to talk to all kinds of cool people, but today you're stuck with me, so here we are.

**Chris Benson** (1:19)
Oh, no, no. That's fine.
No, no, I got to say, you have a really interesting background. I know, like with things changing as fast as they are, I know you did a long period at Microsoft before coming to CoreWeave, and you have seen so much of the cloud landscape change. Like, I can't think of anyone better to address that in terms of kind of like all the things you did in Azure and then coming to a little bit of a different problem set as I'm looking forward to hearing from you about. And so anyway, yeah, if you could kind of start us off and kind of what problems are you interested in and kind of paint a picture of how you see the world from where you're sitting.

**Corey Sanders** (2:12)
Yeah, no, it's a great question. And yeah, I mean, absolutely right. Like I've been, you know, did 20 years at Microsoft before I joined CoreWeave and worked in the early days of Azure. And so, you know, it's been it's been a trip now to kind of take a step into CoreWeave and think about many of the same approaches we had with Azure in the early days now applying with an AI specific lens. And that's really sort of the right way to think about what, you know, I think CoreWeave is doing and sort of my view on sort of the world and the industry right now is, you know, we are seeing the opportunities for AI-based applications to evolve and grow into a similar way that cloud-based opportunities back in the early days grew and evolved, where, you know, it starts off with one or two things and suddenly people are expanding and growing and building.
And then, seemingly overnight, obviously it took many years, and I think will take many years this time, every single application, everything, single service, every single thing that we sort of touch and experience in tech has AI as a significant component of it. And that, you know, I think that pivot is a critical part of the places that I'm working, right? Which is, with that being a pivot of how applications and how services are built, the need for AI-specific capabilities, AI-centric application models are paramount, right? Sort of asking people to apply that AI concept to their legacy way of building applications will end up slowing them down, right? End up creating challenges. And so the opportunity and what I get to really focus on every single day is asking the questions, you know, great, I understand this is how it was done, but how could it be done different with an AI-centric perspective, right? How can I focus and how are we building these services to make it so that people who want to go build AI have a place that can do it where that's the entire focus of the platform?

**Chris Benson** (4:09)
When you talk about that kind of AI-centric approach that you're taking with a lot of people, and we certainly are guilty of it on the show, like people here, for a long time, we were talking about the latest models coming out, and we were in that, and the last year, it's been a gentic everything and stuff like that.
There's a perspective shift here, I think, where people, when they're thinking AI, and those first things that pop into their head, can you talk a little bit about what was missing? If you were coming from the old way of doing Cloud, what was missing that needed to be there, instead of just as an add-on? Because that's what happened early on, is like, oh, hey, you can get a GPU in our Cloud and everything. But now, with this kind of different approach that you've just talked about, which goes all the way from infrastructure to application, what has been missing that needs fulfilling? How are you thinking about that problem? And what are some of the details around what infrastructure should be going forward?