Susanne Seitinger of CoreWeave, vice president of product marketing, joins John Furrier of theCUBE Research and Dave Vellante of theCUBE Research to discuss CoreWeave's product strategy and role in the evolving artificial intelligence landscape, referred to as AI thereafter. Seitinger explains how CoreWeave's portfolio spanning GPUs, software and services supports agentic AI, customer use cases and ecosystem partnerships presented at the Fully Connected 2026 conference in San Francisco. They provide product marketing perspective on deployment patterns operational requirements and ecosystem integration for AI infrastructure.
Key takeaways include the CoreWeave Forge announcement to accelerate agent development, Agent Lens for observability, Registry for systems of record, RL Rollouts and model distillation for continuous improvement and ARIA for research and iteration. Seitinger highlights that multi-generation GPU and Vera Rubin rack deployments run production workloads. They note that performance at scale and deep partner integrations remain strategic advantages, a point Furrier and Vellante emphasize.
This conversation addresses product strategy, Forge launch details and infrastructure highlights relevant to developers and enterprise architects evaluating AI infrastructure, high-performance compute and deployment strategies.
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Susanne Seitinger, CoreWeave
Susanne Seitinger of CoreWeave, vice president of product marketing, joins John Furrier of theCUBE Research and Dave Vellante of theCUBE Research to discuss CoreWeave's product strategy and role in the evolving artificial intelligence landscape, referred to as AI thereafter. Seitinger explains how CoreWeave's portfolio spanning GPUs, software and services supports agentic AI, customer use cases and ecosystem partnerships presented at the Fully Connected 2026 conference in San Francisco. They provide product marketing perspective on deployment patterns operational requirements and ecosystem integration for AI infrastructure.
Key takeaways include the CoreWeave Forge announcement to accelerate agent development, Agent Lens for observability, Registry for systems of record, RL Rollouts and model distillation for continuous improvement and ARIA for research and iteration. Seitinger highlights that multi-generation GPU and Vera Rubin rack deployments run production workloads. They note that performance at scale and deep partner integrations remain strategic advantages, a point Furrier and Vellante emphasize.
This conversation addresses product strategy, Forge launch details and infrastructure highlights relevant to developers and enterprise architects evaluating AI infrastructure, high-performance compute and deployment strategies.
In this interview from Fully Connected 2026, Susanne Seitinger, vice president of product marketing at CoreWeave, joins theCUBE's John Furrier and Dave Vellante to discuss how the company is operationalizing AI through a coordinated system of compute, networking and software rather than raw GPU capacity alone. Seitinger details the launch of CoreWeave Forge, a platform built around the "AI loop" of run, observe, evaluate, curate and improve, designed to help teams move from a first working agent to a production-ready one faster. She also highlights the indust...Read more
exploreKeep Exploring
How do the recent announcements about AI infrastructure, hardware (e.g., NVL72 Vera Rubin racks), and partnerships contribute to the "AI factory" concept and help drive value and agentic AI?add
What is CoreWeave Forge and how does it help teams collaborate to develop better AI agents and products?add
How are GPU cloud providers like CoreWeave evolving their product offerings, and where are customers typically entering the cloud—through infrastructure/training or via inference/serverless models?add
Why did customers choose CoreWeave instead of hyperscalers like AWS, and how has the mix between model training and inference workloads changed?add
How do you envision CoreWeave’s partner ecosystem evolving, and what kinds of engineering, go‑to‑market, and technology partnerships (e.g., storage, security, model integrations) are needed to enable customers to deploy AI workloads effectively?add
>> Welcome back, everyone, to theCUBE's livestream here of CoreWeave's Fully Connected conference in San Francisco. I'm John Furrier, host, my co-host Dave Vellante. Our 17th year with theCUBE, we've seen many waves, saw the cloud wave, now we got the AI infrastructure wave, and it's certainly a different kind of industry. We're learning a lot today. Our next guest is going to break it all down for us, Susanne Seitinger, VP of Product Marketing at CoreWeave. A lot of news and a lot of Ecosystem activity. Welcome back to theCUBE. Good to see you.>> It's so good to be here. I can't tell you how excited I am to tell you the full story. It's the full stack. It's the full loop. And let's talk about it. Let's dive in.
John Furrier
>> You have a history. You've seen a lot of the infrastructure waves before. Obviously, from core internet, cloud, now AI era. One thing that strikes me, and I wrote a post about this, went viral last week. I said that the AI factory is the computer. And the thesis was the GPU conversation, the model conversation is over. It's transitioned to systems. The entire system is producing intelligence.>> Yeah.
John Furrier
>> And that's a factory.>> Yeah.
John Furrier
>> And all the chip guys are memory first, OpenAI is making their own chips. So there's so much action at scale. You guys are doing extremely well. Congratulations on CoreWeave.>> Appreciate it.
John Furrier
>> Product positioning. Good job. But the value to customers is shining. We're hearing all the AI-native startups. Take us through the most important things in your mind here that people should pay attention to. It's the first annual conference. It's busy. It's still got an insider feel amongst the tech community.>> Yeah.
John Furrier
>> What are the highlights?>> it's super energizing because it's all about the customers. We have these amazing stories. I don't know if you know, it was intentional that the first thing folks heard from, the first person folks heard from on the stage was Caterpillar, right? We had Caterpillar, we had Capital One, and we had Cognition on stage. And at the end of the day, all of this is in service of the ingenuity, the creativity, the value these organizations are bringing. So what you're saying about the AI factory, it's all about that additional step to value, and we're starting to see it happen right in front of our eyes. And that's what all the announcements were about. They're in service of driving more of that value with the AI factory. And then on top of that, the systems.
John Furrier
>> Susanne, I will say, being in Silicon Valley and now in New York with our NYSE studio, I can see the two worlds, the Silicon Valley language and then the Wall Street language— roadmaps, velocity, durability, risk management. They're connecting. And I will say that you guys have such strong technical people. And if you look at what NVIDIA does with their partnerships. They're super technical. So there's a magical alignment on talent, and it's showing in the product. First Vera Rubin.>> Unbelievable.
John Furrier
>> Share that.>> First in the world, the first NVL72 Vera Rubin racks seen in situ with production workloads running on them. You heard from Silas Alberti from Cognition on stage. He's seeing the massive step forward that Ian was describing in practice. Already today. That's just days after these things were delivered. It's unbelievable, thanks to all our partners that we work with like Dell and others. but maybe, if we come back to this value loop that's happening, it's pretty unbelievable because that infrastructure is powering the new era of agentic AI.
John Furrier
>> Yeah.>> And that's what you're hearing
John Furrier
>> from—And Cognition actually was a great use case because the way they're thinking about the neural network, there's mechanisms in there, but they're thinking about it really holistically Yes, they're doing amazing distributed training.>> Unbelievable. And that's where we come back to the AI loop. the thing that took a lot of work was getting really tight and opinionated on the AI loop. Those 5 stages of the AI loop were super intentional, right? If we think about run and observe and evaluate and improve as a sequence, it's— and curate is absolutely critical. So you want to take each step as you go and continue to get that compounding value. And that's what it's all about.
Dave Vellante
>> this is our 17th year doing theCUBE.>> Oh, wow.
Dave Vellante
>> We've seen the emergence of a lot of ecosystems. We were talking off camera, AWS. I remember ServiceNow in 2013. Yeah, pretty much like this.
John Furrier
>> Linux Foundation with KubeCon.
Dave Vellante
>> I was going to say, yes. And then KubeCon, the Linux Foundation.>> Yeah.
Dave Vellante
>> CrowdStrike was almost identical to this when we had our first CrowdStrike event 5 years ago. And I wanted to say, the value loop and the AI loop is interesting because you know this from your AWS experience. We learned so much. Two-pizza teams, customer obsession. There's no compression algorithm for experience. And now we're seeing that all coming back to us now.>> We're seeing it.
Dave Vellante
>> We're seeing it. But right. But now we're seeing an AI version of that. And the infinity loop.>> Yes.
Dave Vellante
>> Is sort of, we're seeing this recurring theme of learning loops and improved quality driving value.>> 100%.
Dave Vellante
>> And I wonder if you can start to see this come together from your experience.>> Yeah.
Dave Vellante
>> There's principles that have started bubbling up and you hear it at all these events. And I would say this ecosystem is going to explode. Your revenue trajectory much higher than most of those companies, maybe with the exception of AWS, but actually maybe not.>> Well, let's see how that goes. it does come back to run, observe, evaluate, curate, and improve, and then run again. Right. And so what we're seeing is just that speed. Patti Han ended her speech on speed of learning.
John Furrier
>> Yeah.>> The faster you learn, the faster you ship, the faster you get value. And that comes back to the entire platform and the entire cloud that we're building. And so that's what we talked about with CoreWeave Forge really is that mechanism for making this more repeatable for more folks, right? Because we want more ideas to come to fruition, more capabilities to be built, more new products to be—
John Furrier
>> Well, let's run down the news real quick. So take us through the news. You got Forge, what else do you have?>> CoreWeave Forge is really the big announcement. It's our new way of thinking about the AI loop in a way that allows you to go from first agent to your very best agent as quickly as possible. And so what it does is it puts all these disparate pieces together so different teams can talk to each other more effectively. Think about it, right? You've got a business unit that knows what they want. They might have some ideas about what good looks like for their AI-based product, but they don't know how to communicate that back into the machine learning team that they wanna collaborate with to build a new model or to come up with a new product idea. And so the loop is what allows them all to have a common language. And that's a lot of the capabilities that we announced. So as you walk through the loop, you see new products. So we can dive into some of those if you all want to.
John Furrier
>> Yeah, go ahead, let's do it, yeah.>> Because there's things that are really hard, right, in all of this. And so a lot of the things we talked about, in particular around agent observability with Agent Lens and really being able to inspect and understand what's going on, to be able to create systems of record with Registry inside the loop so that all of your artifacts are in one place. We also talked about how you can constantly improve, and you saw on stage our RL Rollouts capability and model distillation, right? How do you take the knowledge in a large model and distill it down into something that's specific to your use case? That's so important for all these enterprises and organizations, right?
John Furrier
>> It makes it easier.>> They're not trying to solve everything, but they want to create value for their customer And they are the most knowledgeable about it,
John Furrier
>> right?And the thing about it is the ease of use, 'cause what we're hearing is Capital One >> is—Capital One did this, right? They talked about
John Furrier
>> it.They got it, and you go, okay, I want to get my agentic system, whatever they're calling >> it.Yeah,
John Furrier
>> yeah.They might have models, they might have their own models.>> Totally,
John Furrier
>> yeah.What do I run it >> on?Yeah.
John Furrier
>> Where can I get tokens?
John Furrier
>> 100%.And so how fast can I go from point A to point >> B?
John Furrier
>> 100%.And monitor >> it.Yes,
John Furrier
>> exactly.And not deal with all the plumbing.>> Well, and be able to go back, right? Go back in time and make sure later down the road, we want to know how did we get here? All in one place. And that's so, so powerful. And on top of that, we also talked about CoreWeave ARIA being broadly available now. And ARIA is the AI Research and Iteration Agent. And it's really about having a partner and ally while you're in the loop, helping you see patterns that would be really difficult to see. And so having ARIA right there with you is huge.
John Furrier
>> Talk about the ecosystem. Talk about the network.
Dave Vellante
>> Before you go there, I just want to make a point. For the audience, because people, I think, sometimes just say, oh yeah, CoreWeave, the GPU cloud, I go there for GPUs. But what we're seeing, and again, this pattern similar to what we saw with AWS, you start with compute and then storage and then networking and then software. You did the Weights and Biases acquisition. And so now we're seeing a much broader portfolio so that maybe GPU access brings them to CoreWeave, but then the quality and the portfolio keeps them there.>> Well, and what you see is vice versa happening too now, right? There's all these entry points into the cloud. You can also start small. You saw the collection of serverless models that are available. Folks can get started with right away. It's very easy. You don't need to only start on the infrastructure side. And that's interesting to see happening.
Dave Vellante
>> In the early days, a lot of training. And now you're seeing people enter through the inference side.
John Furrier
>> Share your survey data. You guys don't know this yet, but we did a survey.>> Oh, wow.
John Furrier
>> Okay. On your beat for us. We'll share with you. Dave did it last week. We interviewed your customers and some other non-customers. Share the data.
Dave Vellante
>> So the methodology— we did in-depth interviews.>> Yeah.
Dave Vellante
>> Between 30 and 50 minutes each.>> Wow.
Dave Vellante
>> We did 15 of them.>> Wow.
Dave Vellante
>> And the methodology was we took statements from Michael Intrator and Nitin Agrawal. Okay. At the Goldman conference.>> Yeah.
Dave Vellante
>> And the CFO on recent earnings calls and said, okay, this is what CoreWeave said. Let's see what the customers say.>> Uh-oh. And you're putting me to the test.
John Furrier
>> It's a good result. I wouldn't tee it up.>> Okay, good.
John Furrier
>> There are some comments around, but it was very positive.>> 15, right?
Dave Vellante
>> Yeah, 15 customers.
John Furrier
>> Real time.
Dave Vellante
>> Yeah, 15 customers. 7 were hardcore users.>> Okay.
Dave Vellante
>> 6 were sort of relative newbie users. 2 decided not to go with CoreWeave. They did evaluation, they decided not to go. One did it on-prem and another one I forget. Yeah, right. And by the way, >> it was—It's just time. It's just a matter
Dave Vellante
>> of time.It was a, well, there's some good data coming out of that too I'll share. But first of all, no question that most of these customers came to CoreWeave because they could get access. In fact, one said, it was gonna take me 6 months to get access from AWS. I got it in >> weeks.Yeah, yeah,
Dave Vellante
>> yeah.From >> CoreWeave.It was operational immediately. They probably were able to run their workloads a lot faster.
Dave Vellante
>> And then we asked them, well, what kept you there? And they said that clearly the quality kept them there. Now they're still using hyperscalers because they got data there, they have applications and so forth, but they really valued that piece of it. The other thing is you scored very high marks on compliance and certifications, things like that, BAA equivalents to FedRAMP, etc. So that was very positive.
John Furrier
>> we'll talk about the training versus inference.
Dave Vellante
>> Okay. And then the big news was training a year ago was the mix was 90, 10 training inference.>> Okay.
Dave Vellante
>> 60, 40 training inference this year.>> Yeah.
Dave Vellante
>> Expectation is flipping to 10, 90. And the last point was they're both growing. It's not a zero-sum game.>> But you know what's so interesting about it is it's why I think we're so well positioned to run the AI loop for organizations is because the insights we learn from training around certain requirements, in particular around, say, data throughput in order to keep GPUs fed, etc., really accrue value to things like RL. So this idea that you're never done, that you're going to do post-training, that you're going to continue to improve is a reality. And the expertise we have is able to really drive benefit even later on in the loop and when you're running inference. So even if inference becomes this critical component, all the benefits, all the learnings are really accruing value right now. And so that's why this transition is so interesting and why you see also all the excitement around Vera and Vera CPU like we talked about today. It's really a big deal. These agentic workloads are—
John Furrier
>> I think the RL, the reinforcement learning is a really good point. Because inference is the economic value. Yes, they're going to get money out of that, tokens, etc. But the training sets the table. Reinforcement learning is like training and learning at the same time. That's why I like this living learning system, because this always-on concept that you guys are talking about here.>> Exactly.
John Furrier
>> While you're doing maintenance, by the way.>> Yeah, you're fixing things, you're improving, and you're running in production all at the same time.
John Furrier
>> It's a real deal. Now, I'll tell you what I took away from the survey, Dave. It's got the analytical side, but on the subjective side, the real story is that it's not about the AI clouds or neoclouds, some call it. It's not like—>> not anymore.
John Furrier
>> Not that the AI clouds are replacing the hyperscalers. That's not the story.>> Yeah.
John Furrier
>> You're just disaggregating it and everything's— they're getting their share, but they're going to you guys for specific things.>> Well, it's specific and it's also because the system we're building is open, right? It's open to models, frameworks, frankly, clouds, right? that's the world we live in, and we acknowledge that, and we do what we do best and expect customers to not have to do extra work for no good reason, right? You saw some of the security announcements on our Remote Key Encryption last week, for example, where instead of forcing customers to use our approach, we're saying bring your own. That's this idea of building from first principles in an AI-native way instead of trying to just recreate everything that's already out there. That's not the point.
John Furrier
>> Okay, so I'm going to put you on the spot because we're live, so you have to answer. Uh-oh. Okay, you came here with all your experience. You did a great job on the product portfolio. The marketing is great. Love the conference. If you had to describe the secret >> sauce—Secret sauce—
John Furrier
>> of CoreWeave.>> Yeah.
John Furrier
>> Of why customers, why it's important. Obviously it's the infrastructure layer. There's a new layer, so everyone kind of gets that. But what's the secret sauce of CoreWeave?>> It does come back to the people. It comes back to the relentless focus on customers and delivering for them. That is really the truth, right? In the end, you can only do your best work if you're working hand in glove with folks who are trying to push the limits of what's possible. And that's what we're doing. And that's why it's so much—
John Furrier
>> I'll say that was highlighted, Dave, in our interview with LlamaIndex, we had a great—Jerry came on and Lukas, founder of Weights & Biases. Yeah, that was really kind of a nice yin and yang because he's building— Jerry at LlamaIndex building these thin apps, AI native, and weights becoming important. It's technical, it's kind of in the weeds a little bit, but these weights are super >> important.I mean, they're there. That's where it all ends up, right? that's all the knowledge ends up
John Furrier
>> there.It's like a brain.>> It is a
Dave Vellante
>> brain.Weights are important.
John Furrier
>> Critical. For real fast retrieval intelligence. Put my hand on the stove. I don't think and reason. I just take it off because I'm going to burn my hand. That's pretty low compute.>> Yeah.
John Furrier
>> Value.
Dave Vellante
>> By the way, we also had Cognition on.>> Oh, you did.
Dave Vellante
>> So that was the other big piece of news.
John Furrier
>> Yeah.>> Well, so yeah, we should talk, I mean, we touched on it at the beginning, but obviously, Forge, all the capabilities in Forge that I talked about, like Agent Lens and distillation, et cetera. But then all of that is built on the latest infrastructure. And we were the first with Cognition to talk about that today. Seeing a production workload, seeing the metrics coming from that, and just such a short time period. I mean, let's remember the speed at which this is happening. I mean, we just barely in June talked about the first racks being delivered, and Dell is here too, obviously talking about their amazing work. And then now we're already in production. That's made possible— those 6 generations of concurrent GPUs all operating at the same time is possible because of the operational excellence and that execution.
John Furrier
>> That multi-generation story is pretty big.
Dave Vellante
>> And it's a huge deal. And if you think about the quality of AI as we went from Grace Hopper to Blackwell to Vera Rubin, we're going to see maybe even steepening of the functionality curve. Right.>> I mean, it's really unbelievable. It's really unbelievable.
Dave Vellante
>> And the economics, I think people don't know, sometimes don't appreciate the cost of tokens is going like this, but the volume of tokens going through the roof. So the overall bill is going up, but nonetheless, the capabilities of AI, I think people don't realize a year from now when Vera Rubin starts to really get adopted is going to be enormous.>> Yeah.
John Furrier
>> I love the ecosystem you have here. I see Solidigm right there. VAST is behind us. All the key players are here. I see NVIDIA, key partner. The partnership with NVIDIA I mentioned earlier speaks volumes to the credibility of CoreWeave. But talk about the ecosystem, because in all these growth areas, the ecosystem emerges.>> Yeah.
John Furrier
>> What is your vision there? How do you see that playing out?>> Well, I'll tell you, I was super excited about the announcement of the partner network today. And the CoreWeave partner network is something that we've been noodling on. It's emerged, right? a lot of the things, it's emerged from listening to customers, working with them, and having it on stage today and seeing it all together and then having already, you know, some announcements with CoreWeave Forge and that partner extension around search. Was a really, really big deal. And it's all about providingpartnerships that already are tested. Right. So it's not just about building the biggest set of logos on the wall. It really is about having partners like VAST and others who are already thinking about systems connected in a way that customers can deploy them right away. Right. So it's not like it's just lip service or marketing.
John Furrier
>> Oh, talk about that ecosystem change because in the cloud era, it was very easy. Hey, join the cloud. You're in a marketplace, get APIs, be happy. Now you have MCP servers, more delegation and authority. Talk about the depth of relationship that you have to have on the partnership side.>> You have to have engineering partnership, go-to-market partnership, marketing partnership. You have to be listening to your customers together and actually co-engineering these systems, right? In particular around storage, security, right? If you think about some of the CrowdStrike work we're doing, so it all has to actually be vetted and validated together. You can't just show up
John Furrier
>> and—Funny anecdote I'll share with you since you're here. One of your partners said, "I trust CoreWeave." Wow. And I said, "In what way?" "Well, they do the things I don't have to worry about, but they're important things." It's like, getting the whole. It's like, it's not like, okay, it's available. There's something like a lot of real-time configurations.>> Absolutely. The complexities that are ready to
John Furrier
>> go.Yes, that's this huge difference. Not like yesterday's. Ecosystem playbook.>> No, and that's why it's also— it was really for us about creating a broad set of partnerships with model partners, with different kinds of security and storage and data, and really create a whole set of capabilities and different specializations that are most critical to AI workloads. Right. Because that's what we want to accelerate as an ecosystem. And so having that partner network out there is a big deal. And then with Forge, think about what agents have to do nowadays and having right out of the gate 3 partners with Exa, You.com, and Parallel Web Systems available to customers to execute search so that agents can be even more capable right away is a really big deal as well. And I see us having many more Forge partnerships in particular as well that help extend our network even further.
John Furrier
>> You guys are a young growing company, obviously public. Business performance has been great. Congratulations. Two closing questions. One is more philosophical to your world. It's like a wedding or a party. You notice the little things that don't go well, but at the end of the day, everyone thought the party was great.>> Yes.
John Furrier
>> What are you most proud of in this event? Because it's the first event.>> Yeah.
John Furrier
>> What went well for you? What do you think hit and landed?>> Yeah.
John Furrier
>> And I'll get to the next one after that.>> Well, What I think went really well that I'm super happy about is that I feel like we're meeting the audience where it is. It's a broad audience, right? You've got, you mentioned it, we've got these incredible startups, you've got AI labs, and you have enterprises here all together under one roof, and they all seem to be having really good conversations.
John Furrier
>> Yeah.>> And that was no easy feat. It was really hard to figure out what is the right level of depth, what is the right level of detail, who gets what. And providing something of value for each of those folks in a common language to talk to each other in was just really validating to see. And I can tell by the buzz that they are having these conversations, right? They're finding partners like, oh yeah, we're going to work together going forward. I bet you, a lot of formation now. That's what I was— exactly. A lot of formation deals happening that happened right here today where people have realized we have an idea here and we have a winning AI
John Furrier
>> proposal.Yeah, they're building out. It's a growth. It's awesome. It's being raised here early and people are candid. All right, my second final question is, okay, what are you going to optimize going forward? Because you have a lot of huge market opportunity with the company. It's super high pace as you talked about earlier.
John Furrier
>> Yeah.How's the portfolio look? Yeah. Messaging? Are you meeting customers where they are? What is your focus now? What's the optimization >> plan?Well, you kind of said it, right? When you're asking about what are we offering around the partnerships, it's really about giving folks more recipes and playbooks and use cases and solutions so they can get to value faster. I want to help on our end, with the marketing work, provide more playbooks that folks can deploy quickly so that they don't have to have all the same learnings all over again. And that's how I want to accelerate more real AI value and then demonstrate it, right, with new metrics and new ways of proving that value.
Dave Vellante
>> Oh, that's such an opportunity because AI is difficult for a lot of people. the kids that we had on today, Liquid AI and these startups. yeah, they're capable. They have the AI skills. most organizations don't.
John Furrier
>> And the interesting thing too is the network of influence is not your, go-to-market playbook or partnership playbook. If you look at the people involved, you have institutions, research labs, capital markets, technologists, business people that are all working together and sharing. So you have now a collective kind of core community.>> Yeah.
John Furrier
>> Kind of working together and they're all kind of different and they're coming together. That's new, I've never seen that before.>> I'm telling you, it's coming back to the AI loop, creating a shared language for all of us so we can collaborate more effectively and create value.
John Furrier
>> All right, well we're inspired to create theCUBE Loop, Dave.>> Cube Loop.
John Furrier
>> Let's go.>> Keep learning.
John Furrier
>> We're gonna figure it out.>> Do the loop.
John Furrier
>> Thanks for coming on. Congratulations.
Dave Vellante
>> Thank you.
John Furrier
>> On a great show, great content, great news. Again, this is the beginning of an AI infrastructure layer emerging. It's not really taking away from the old ones, building on top of the new capabilities is an entire system for manufacturing intelligence. That's what NVIDIA is seeing. That's what CoreWeave's doing. And that's what customers will be implementing, putting intelligence in their business and operations. Or trucks like Caterpillar. Physical AI is right around the corner. So these large-scale systems are serving it up, doing our part here, serving up the data. I'm John Furrier with Dave
Dave Vellante
>> Vellante.Just a reminder, we kick off tomorrow, 11:30, right? We got a bunch of customers coming
John Furrier
>> on.The livestream will be tomorrow at 11:30. Yeah, run it down,
Dave Vellante
>> Dave.Deep, deep with CoreWeave product folks. We've got MasterClass coming on tomorrow. We got IBM. And as I say, we're going deep into the products tomorrow.
John Furrier
>> So we've got more NVIDIA coming on. Oh, we didn't talk about the Vera (NVIDIA CPU). That was news. Forgot about that. Another big one. We'll come back to that later.
Dave Vellante
>> .com is compute.
John Furrier
>> Hey, yeah, compute, GPU, all the systems coming together, storage. Thanks for watching. For Dave Vellante, I'm John Furrier. See you tomorrow.
John Furrier
Dave Vellante