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Live from GTC: Powering AI Development with Anaconda CEO David DeSanto
00:07:09
Anaconda CEO David DeSanto breaks down how his company is helping organizations build AI-native applications, from secure Python packages to curated, production-ready AI models.
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Transcript15 lines
- [00:00]
A
Foreign. Welcome to Reshaping Workflows with Dell Pro Precision and Nvidia, where innovation meets real world impact in high performance computing.
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B
Welcome back to another episode of Reshaping workflows live at GTC 2026. I'm Logan, your host. I'm here with David DeSanto, the CEO of Anaconda. I'm. Before we jump into it, David, really appreciate the time. Give everyone who's listening a little bit of background on what you do. Obviously you're a CEO, but what that entails at Anaconda, no.
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A
Thank you for having me, Lohan. So at Anaconda, as you said, I'm the CEO. I actually joined Anaconda about six months ago. Prior to that, I was the Chief product officer at GitLab, where I was at for six years. Anaconda is focused on helping companies build AI native applications. We do this through our AI platform, which supports AI native development starting at the beginning of development, all the way out through production.
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B
Amazing. So if you are a technical listener, you're probably familiar with like conda, all the types of stuff that Anaconda does. But let's start kind of high level for Those that are ITDMs or people that aren't as technical. Can you kind of run through the core, you know, basic products of what Anaconda offers?
- [01:19]
A
Absolutely. So Anaconda offers a platform. It's broken into two parts, so we'll take them each individually. Anaconda Core is the packages for Anaconda. We provide secure AI and data science packages within the Python programming language. So that way people know they're building on a trusted foundation. That's what Anaconda Core offers. That also includes security and governance vulnerability information. So if you're an IT professional, maybe in a platform engineering team, or say you're in IT and you're worried about are we doing things that are secure with AI, that's what that ends up helping you with. The second module is AI Catalyst. It actually offers a very similar thing but for open source AI models. So we test models, whether we're curating them through security testing, performance testing, and then we add those to our model catalog so people can use them. We offer them in different quant sizes so you can actually run them locally on your laptop if you're want to do your development that way or you can deploy them into a production environment. The best way I kind of look at it is really the first part. Anaconda Core is at the beginning of your development and AI Catalyst is helping you get ready to move into production at a high level. The way I've explained Anaconda to people who are not familiar with AI enough or AI architecture, I refer to this as like the foundation between the physical hardware and the application you're building. And the best way to kind of look at that is we provide all the CUDA packages for Nvidia for their gpu. So if you're doing development on Nvidia gpu, you're most likely using Anaconda.
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B
Makes sense. And I am not a developer by trade, but I know enough to be dangerous.
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A
Right.
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B
So, like, everyone's kind of familiar with Python, like, you know, the CUDA acceleration that Anaconda provides. So what at GTC this year, what is new for Anaconda? Launch announcements? Anything new you want to talk about?
- [03:10]
A
Yeah, I think there's really two things that are probably interesting to your listeners. The first is we've continued to add additional support to the Nvidia DGX Spark. For those who are not familiar, it's there, they call it an AI supercomputer that you can actually put on your desk and then connect your keyboard monitor to and do all of your AI development there. As part of that, we are launching our alpha version of our new desktop, and that's what's running on top of the DGX Spark in our booth. So if you're listening to this and you happen to be here, it's well worth stopping by and seeing that demo. The second thing is just the continued maturity of AI Catalyst. We're looking to begin to allow others to bring their own models in. We're also working with some commercial providers as well, so we have those models also available there and ready to use.
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B
So for those who know the sparc, the Dell equivalent, every OEM kind of has one. Ours is the Dell Pro Max with GB10. So, Anaconda Desktop. Right. Tell us a little bit more about how that interacts with the Grace Blackwell architecture.
- [04:11]
A
Yeah, it's a great question. So, traditionally, Anaconda has had two different desktop applications. The original one launched in 2016, it was called Navigator. Very simple name. And about two years ago, we launched an updated version that served a similar purpose, called AI Navigator. And so here we're showing off the new desktop application and. And it'll be available for anyone to download starting in May. What it does is it actually takes the best of both those applications, brings it into a single application, and then you can use it, whether it's local or you can connect it to your platform. The best way to kind of think about it is if you're just an individual user, whether you're a hobbyist or you're working at a company, you're really starting to do AI work. All of our desktop applications are free. They also include a set of CONDA packages, as well as the tools you need to get started. And this will continue that when it becomes available. It's beta in May, and that'll also then include all the stuff that's in the platform as well. So all the AI models will be there. You can deploy Anaconda local inference, so you can run the models right there as well. And so it's kind of like your peek into what the platform does as a free view. But if you end up becoming a subscriber, you buy either our starter plan or a business plan. You can then interconnect that back up and then you'll get vulnerability information, deployment information, all the other stuff that's sitting in the platform.
- [05:36]
B
All right, well, you heard it first here from Anaconda. Lots of new things. So, David, if anyone's interested in, like, learning more, where can they go to find out about all the new things?
- [05:47]
A
So the best place to go is anaconda.com we're constantly posting blogs and talking about what we're doing. We're also at a lot of events like we are here. So if you're at an event that's in the IT space, there's a good chance we're here. So I would say stop by a booth and check it out. But what I will kind of leave everyone with is AI has been a really hard thing for some enterprises to adopt. Lots of reasons, that's what we're here to solve. The best way I describe it is like, hey, if you're needing to get from an idea to AI to an actual production application, which 80% of those projects don't make it to production, Anaconda is here to help that and help you bridge that gap. So, yeah, check out anaconda.com, check out our YouTube channel, as well as see demos. But yeah, we're very active. We look forward to helping everyone be better with deploying AI and securing their environment.
- [06:34]
B
I love that. So check out Anaconda, all the places that David just mentioned. So with that, Logan, we'll see you on the next one.
- [06:47]
A
Do what you want. Do what you want. Do it. This podcast was produced in partnership with Amaze Media Labs.