How AI Data Platforms Are Shaping the Future of Enterprise Storage - Ep. 281

Hello, and welcome to the NVIDIA AI podcast. I'm your host, Noah Kravitz. Quick note before we get started. If you're enjoying the pod, please take a moment to follow us wherever you get your podcasts. It'll only take a second. It helps us deliver a better show to you, and it helps you make sure you don't miss an episode because they'll all show up in your feed. That being said, let's get to it because we've got Jacob Lieberman back on the podcast, and I can't wait to get into this. Jacob is the director of product management for NVIDIA's enterprise product group. He was on the show recently. It feels like just yesterday, but so much has happened since then. We were talking about AgenTek AI and at the time it was kind of a new thing and Jacob was explaining what it's all about but really getting getting into the potential, the sort of the promise of human and AI agent collaboration in the workplace and the enterprise in particular. So we've got Jacob back and I can't wait to dive into it, but first man, welcome. How are you? Thank you, Noah. I'm very grateful to be here and I'm very happy to be back. So we're gonna talk to agents. Also, we're gonna talk you're gonna talk. I'm gonna be able to ask some questions about something called the AI data platform, which is a new class of GPU accelerated storage as I understand it that I don't wanna put words in your mouth, but it sounds like it could be game changer, at least like another big step along the path to this this promise of human AI agent collaboration that we're fulfilling. I use agents all the time, but, I'm excited to get into it. So why don't you dive in and tell us how it's going with Agintiq AI adoption in the enterprise? Yeah. It I it's interesting to hear that you said, you're using it yourself because I think many of us are. Many of us are now starting to use AI agents in our daily lives as consumers. Right. But the needs of a consumer are very different than the needs of an enterprise. Yeah. And so since last time we talked, AI agents, the technology's come a long way. The open models of today are just as powerful as the commercial models were a little while ago, but it's still challenging for enterprises to put agents into production. So it sounds like the technology's there or, you know, there enough because it's always advancing. Right? Yes. What are the challenges then, that enterprises are facing to actually deploy and gain adoption of agents? That's a great question. So almost every enterprise and every CEO and CIO, CTO, they are increasing their spending on AI. They want to deploy AIs to production, but it's difficult to move from a POC state to production. So the enterprise adoption is happening, …