 theCUBE presents Dell Technologies World, brought to you by Dell. Good afternoon everyone, welcome back to theCUBE's third day of coverage live from the show floor at Dell Technologies World 2022. Lisa Martin here with Dave Vellante. We've been having lots of great conversations the last day and a half. One of the things we love to do is really hear from the voice of Dell's customers and we're going to do that next. Please welcome Jonathan Sechler, the Senior Director of Product Marketing for Dell and Keith Bradley, the VP of IT at Nature Fresh Farms. Guys, welcome. Hey, great to be here, thank you. Thank you for letting us be here. Of course, thanks for joining us. So, Jonathan, we're going to start with you. We've been hearing a lot about, we've been talking about AI for decades. We've been hearing a lot about AI at the show. It's pervasive, right? It's in our refrigerators and our thermostats and our cars and that hockey puck thing that's in the kitchen that plays music when you're cooking. What's going on? What do you think from Dell's perspective is fueling the adoption of AI now? You know, I think that there's this huge interest in AI right now and you're definitely pointing out a lot of the great success stories around AI, but the real benefit of it is with artificial intelligence applied to a lot of business problems, you can solve them in ways that are much quicker than you would expect, you know? And you can solve them in ways you wouldn't have expected, then you do. What's really surprising, though, is as many people are interested in using it and all of the benefits that come from it, though, is that we really don't see the adoption being as quick as we would like to, right? I mean, I want to say that like 80% of companies out there want to use AI, they're testing AI, you know, they're planning projects around AI applications, but when you ask them what's in production, it really is still, it's an innovator's game. Like, you know, companies like Nature Fresh Farms with what they're doing is truly at the tip of the spear. What are some of the challenges, Jonathan, that you're seeing from an adoption perspective of 80% say we want to actually be able to leverage this emerging technology, but in production? The challenges are, I think it's a perceived challenge issue, right? I think there's like three big issues that people perceive as being barriers to adoption. The first one is pretty obvious, it's cost, right? They see artificial intelligence, they hear about all of the specialized hardware and the software and the people and the talent you've got to acquire as being a barrier to that, and they don't see the benefit or they balance that against the benefit. I think there's an issue also with complexity, right? Because at the same time that you're building these infrastructures around what you need to do for an artificial intelligence-enabled application, there's this expectation that it needs to be separate and different and special, and that becomes an issue from a management perspective, right? And I think finally, it's changed, right? I mean, you're bringing in new talent, new skill sets, you're bringing in new technology, and I think a lot of companies still today, look at that as being like, well, what if I do this? Am I really going to see the benefit? Am I stuck going down a path that I'm going to change later on? And I think that's really the issue. But they're all perceived issues. In reality, they're really not that true. I mean, Keith has done, Nature Fresh Farms has done some incredible stuff with AI in an area that I would never have guessed being right for that kind of innovation, you know? So, Alisa, Keith knows that I love fresh tomatoes. I live in the Northeast where it's cold six months a year, so we plant our tomatoes at Memorial Day weekend, right? And then maybe you're lucky if you get tomatoes late August, September, and then you're done. However, you and I met a couple years ago, you sent me all these vegetables. I was popping the tomatoes like candy, and then I interviewed you, you were live in the giant greenhouse, and it's just amazing what you guys have going. To Jonathan's point, you're using AI to really create sustainable, continuing flow of awesome vegetables. Tell us more about Nature Fresh. So, at Nature Fresh Farms, we're a 200-acre greenhouse, just shy of 200 acres growing bell peppers and tomatoes. And one of the biggest use cases for us in our AI is everything we do, we need to be proactive. So, we need that AI to not be reactive to climate change, to what happens to the weather, to be proactive so it changes before the plant reacts, because every time the plant doesn't do as great, we've lost production from it. So, we're always using our AI to help increase the yield per square meter inside of our greenhouses. So, everything from the growth, the length, the weight of the plant, we monitor everything. We want to know every aspect of that plant's life. It's almost like doing EKG on a plant, 24 by seven, and wanting to know everything out of it. How old is the company? Nature Fresh Farms started in 1999, so we're just hitting 23 years now. So, we started off as a 16-acre little greenhouse. Our owner kind of got into it saying, I think this is going to be new, and he was one of the first ones to say, I want to be all computers. I want to do it. So, culturally, this was not an upsell or a hard sell for you from a VPFIT perspective. No, no, he's always been one saying that technology will change the greenhouse industry, and that by adding technology, the expertise is in the growers, and letting technology help them do more, because when we first started in the greenhouse industry, you'd need a grower for every range. So, every 16-acre range would need a very senior grower. Now, we have one grower that does 64 or almost 100 acres of greenhouse. He'll have junior growers, but he's able to do so much more. So, where do you specifically apply the AI? Can you talk about that? So, we specifically apply the AI in almost all areas. Anything from picking the plant to the climate of the plant, we'll do all those areas, even on the packing line. We actually have one robot, well, not a robot, sorry, a machine that looks at a box of tomatoes, and basically tells us which one doesn't match the proper red, because how you see red, how you guys see red is slightly different. So, it'll tell us that this red tomato doesn't match, so change it out to the right one, so that when it goes down the line into the consumers, they're all exactly the same. So, it looks unified, it looks beautiful like that. How about that? You send it out red tomatoes. Yeah, that's what we do. Now, what is Dell's role in all this? So, Dell's role has helped us grow what we do. We started off with PowerScale and VxRail and stuff like that. So, everything's hosted on that and they have been a great partner at finding that solution to them. I've been able to go to them and say, hey, I'm running into a storage problem, I'm running into a compute problem. They've been able to find a validated solution for us to use and to put out there and help us grow. And then the next part that was really great that we've really now done is a scalable. As we're growing, we've been able to communally add more compute and more storage, but not have to take things down to do it. And that's what we really wanted to do. I think what you're talking about there is really one of the big issues that I was talking about earlier, which is around complexity and cost, right? One of the answers to doing artificial intelligence in the enterprise is making sure that you can maintain and have an infrastructure that scales that's part of everything else. And to do that, you've got to virtualize it. And with Dell, VxRail and PowerScale, which it's all running VMware with the containers and the VMs on top of that, actually managing and running those applications, it takes a lot of the complexity of worrying about where you're going to, how are you going to manage that infrastructure and who's going to do it? Who's going to back it up? How are you going to keep costs down? So it really helps, I think. Yeah. And we just love it because we're able to take that solution, make it better and make it do more and more every day. And it's allowed our growers to see exponential time where they've did it. Years ago, it used to be overnight to get results sometimes from our system doing it. Now we're seeing it in real time. And that's where I really got to that point now, where we're being reactive, proactive to the plant, to the weather, to stuff. We know exactly what needs to happen before happens. And that makes the plant grow more. And that's what we're always aiming to do. You know, if you don't mind, one of the things that you were telling me about, I think it's really fascinating. So is this idea that, you know, you need to have a data scientist. You need a whole new staff to manage these applications, these technologies. But you were talking about your growers are actually, they're actually data scientists in a way, right? That's what we like to call them. We call them grower scientists right now. Green scientists. It is since data scientists. Yeah, because they've researched this data. They know what the plant does. And it's been a neat transition. We talked about how they went from being out in the greenhouse so much, to being in front of the computer now, but now with the help of AI, they're more able to get back out into the greenhouse to now watch the plant, see what's going on, and be a part of the growth again. And they said it's been great. But they're the ones that are looking at these numbers every day, every second. If it's not remotely from home, it's remote on the greenhouse. They're launching everything. Because yeah, think about it. They're watching 64 acres of land and making sure that does everything it needs to do. So Lisa, this is a really good example of sort of distributed data at work. I'm at this whole notion of data mesh where you have domain experts actually own the data. They know they can bring context to the data. It's not somebody who's just, oh, it's just data. I don't really know what to do with it. It's somebody who actually knows what it means. To me is a future use case that's going to explode. Yep. It's like me, I look at their data and they always tease me because I'll look at it and I'll go, yeah, I have no idea. But it's giving you numbers, so are they right or not? And it's always a joke in the plant that I'm like, ah, you don't got question marks. So it's working. And then I'll go to them and say, is this right? And they'll say, yep, we're getting what we need. I love the idea that we've heard of this term citizen scientist or citizen data scientist. And you have a grower data scientist. And I think that eliminates, again, those problems or challenges I mentioned earlier. That kind of eliminates the complexity issue, the uncertainty issue, the fear of change. When you've got your own teams who know what they need to do and they have the data to do it, it just changes the game, right? Yeah, and the other thing too we found is I've always believed in it myself. If you love what you do, you commit so much more to it. And our growers, they love what they do. So their passion just exudes into the data and then it comes right back into the product. Well, the technology is an enabler of their passion, really. I'm curious, Keith, how obviously the events of the last two years have been quite challenging. How has AI been a facilitator of what seems like a competitive differentiation for your company? It actually really accelerated it because we really had to invest in it. That's when we started the big journey to the VxRail, the power protect out of management. We really had to invest in it and then we heavily invested in the AI. We've always had some lingering in the background and it's always been there and we've been using it for years and years now but it really brought it right to the forefront though we have to do this better. And we had to really push everything. And as we grew, it became more and more apparent that we were taking that road. That investment was paying off for us now. How do I buy AI from you? So it's interesting, like I said, we want to make it easy for customers to implement an AI solution at Dell and it's not so much that you go out and you buy an AI or something like that. What you're doing is you're making your infrastructure ready for the applications that you need to run. And so at Dell we have these predefined architectures that we call validated designs. They're validated to work in a common environment. We take the guesswork out of how to put these systems together and in the case of artificial intelligence we validate with our partners like VMware and like NVIDIA to make sure that the technologies work together so that they fit into the existing infrastructure they already have. And in a way, I think of it as virtualized AI but I think even more importantly, it's AI for any company. It's not for the special scientist and not for the researcher at the university. It's for nature-fresh farms, right? So with VxRail and software defined you're able to bring in a GPU. You've got the flexibility to do that, for example. Whereas with the traditional, the old days you wouldn't be able to do that. You'd have a lot of time on your hands and a lot of compute power. You spend a lot of money doing what you need to do. Yeah, oh yeah, we'd be spending all the time working at it, growing it and doing more. And it just made our life easier. Not to manage the life cycle of the AI systems that we have is so much easier now because it's all predefined, it's all ready to go, upgrade process, all that is built into it. So the life cycle is much easier from the IT side. So Keith, talk to those folks in the audience who might have those perceived challenges or limitations that Jonathan was talking about because you're making it sound like this has been such an enabler of a business that's 23 years old. We're taking growers who are experts at growing and they're playing and loving, playing with data and AI. How do you help, how do you advise folks to really eliminate some of those preconceived challenges that are out there? I would say you have to sit there and just dive in. You have to actually start to do it. But you have to think about not where you, the first two steps. Say where we want to be five steps from now and then say talk to a partner like Dell with us and say this is where we want to get to. This is, and then figure out a way how to get there and committing to that path. You can't get frustrated the first few times. AI is very frustrating sometimes, the first few paths don't work and just saying going back to the drawing board each time we'll do it. We've had a couple experiments where it didn't work and we didn't get the results we wanted and we had to just say let's change our thought process and how do we optimize this AI? And then all of a sudden we started getting the right results. But it's like falling over, the first time you fall over as a child. It's going to hurt, but each time it gets a little less, each time. Failure is progress. That's right, that's right. Fail fast. Failure can be a good f-word. But you have to be open-minded. Yep, oh yes, every minute you have to be open-minded and you have to think outside the box too. And that's the biggest part of things. It's just not accepting things and just saying we have to do it. You have to have the culture that will embrace that and it sounds like the growers, these are people that are expert in growing. How, it sounds like it wasn't an uphill battle to get them to come on board and become these citizen growers, data scientists. Well, you know what, it was funny because with the technology, it kind of gave them that work-life balance that they didn't have before. Their life was inside the greenhouse because the plants grow 24 by seven. So now all of a sudden, they just kept growing. They could, they could go home, they kept doing their thing. They could go home at five o'clock. And because of the VDI solutions and stuff like that and the AI that's helping them grow, they could kind of turn off. And instead of having to come in Sunday morning and that, the one joke we used to have is that on Sundays, if you're in church and there's clouds that come rolling out, all the growers would stand up and leave because they had to go to their church, they had to go back to their farm. Now the system does that automatically for them. So they're able to get their work-life home balance back. So it was different for them, it was a jump for them. Anybody that's not used to technology and jumping into it is hard. But once they started to see the benefits and what more yield they can get and the home work-life balance, it was amazing. There's no, I can't underestimate the work-life balance. And I think it's a very challenging thing for people in any industry to achieve. We've seen that in the last two years with, do I live at work? Do I work from home? So achieving that is, kudos to you and for Del for enabling that because that's big, that affects everybody. Guys, thank you so much for joining us, talking about AI, what you're doing at Nature Fresh. The future, what's possible, and how you buy AI from Dell. Do you want to say thank you? No, I think it's great. I think Nature Fresh Farms is a great year. You've been a great, like a great partner for sure, but also this great kind of beacon to show people how it can be done. And I think it's just a- Thank you very much. We really enjoyed it. Well, thanks for bringing the beacon on the show. We appreciate it. We want to thank you for watching. For our guests, I'm Lisa Martin. For Dave Vellante, I'm Lisa Martin. I should say you're watching theCUBE day three of our coverage live from the show floor of Dell Tech World 2022. Stick around. We'll be right back with our next guest after a short break.