(chill electronic music) >> Hello everyone, welcome to theCUBE's presentation of the AWS Startups Showcase, AI and machine learning, the top startups building generative AI on AWS. This is the season three, episode one of the ongoing series covering the exciting startups from the AWS ecosystem, talk about AI and machine learning. Can't believe it's three years and season one. I'm your host, John Furrier. Got a great guest today, we're joined by Joseph Nelson, the co-founder and CEO of Roboflow, doing some cutting edge stuff around computer vision and really at the front end of this massive wave coming around, large language models, computer vision. The next gen AI is here, and it's just getting started. We haven't even scratched a service. Thanks for joining us today. >> Thanks for having me. >> So you got to love the large language model, foundation models, really educating the mainstream world. ChatGPT has got everyone in the frenzy. This is educating the world around this next gen AI capabilities, enterprise, image and video data, all a big part of it. I mean the edge of the network, Mobile World Conference is happening right now, this month, and it's just ending up, it's just continue to explode. Video is huge. So take us through the company, do a quick explanation of what you guys are doing, when you were founded. Talk about what the company's mission is, and what's your North Star, why do you exist? >> Yeah, Roboflow exists to really kind of make the world programmable. I like to say make the world be read and write access. And our North Star is enabling developers, predominantly, to build that future. If you look around, anything that you see will have software related to it, and can kind of be turned into software. The limiting reactant though, is how to enable computers and machines to understand things as well as people can. And in a lot of ways, computer vision is that missing element that enables anything that you see to become software. So in the virtue of, if software is eating the world, computer vision kind of makes the aperture infinitely wide. It's something that I kind of like, the way I like to frame it. And the capabilities are there, the open source models are there, the amount of data is there, the computer capabilities are only improving annually, but there's a pretty big dearth of tooling, and an early but promising sign of the explosion of use cases, models, and data sets that companies, developers, hobbyists alike will need to bring these capabilities to bear. So Roboflow is in the game of building the community around that capability, building the use cases that allow developers and enterprises to use computer vision, and providing the tooling for companies and developers to be able to add computer vision, create better data sets, and deploy to production, quickly, easily, safely, invaluably. >> You know, Joseph, the word in production is actually real now. You're seeing a lot more people doing in production activities. That's a real hot one and usually it's slower, but it's gone faster, and I think that's going to be more the same. And I think the parallel between what we're seeing on the large language models coming into computer vision, and as you mentioned, video's data, right? I mean we're doing video right now, we're transcribing it into a transcript, linking up to your linguistics, times and the timestamp, I mean everything's data and that really kind of feeds. So this connection between what we're seeing, the large language and computer vision are coming together kind of cousins, brothers. I mean, how would you compare, how would you explain to someone, because everyone's like on this wave of watching people bang out their homework assignments, and you know, write some hacks on code with some of the open AI technologies, there is a corollary directly related to to the vision side. Can you explain? >> Yeah, the rise of large language models are showing what's possible, especially with text, and I think increasingly will get multimodal as the images and video become ingested. Though there's kind of this still core missing element of basically like understanding. So the rise of large language models kind of create this new area of generative AI, and generative AI in the context of computer vision is a lot of, you know, creating video and image assets and content. There's also this whole surface area to understanding what's already created. Basically digitizing physical, real world things. I mean the Metaverse can't be built if we don't know how to mirror or create or identify the objects that we want to interact with in our everyday lives. And where computer vision comes to play in, especially what we've seen at Roboflow is, you know, a little over a hundred thousand developers now have built with our tools. That's to the tune of a hundred million labeled open source images, over 10,000 pre-trained models. And they've kind of showcased to us all of the ways that computer vision is impacting and bringing the world to life. And these are things that, you know, even before large language models and generative AI, you had pretty impressive capabilities, and when you add the two together, it actually unlocks these kind of new capabilities. So for example, you know, one of our users actually powers the broadcast feeds at Wimbledon. So here we're talking about video, we're streaming, we're doing things live, we've got folks that are cropping and making sure we look good, and audio/visual all plugged in correctly. When you broadcast Wimbledon, you'll notice that the camera controllers need to do things like track the ball, which is moving at extremely high speeds and zoom crop, pan tilt, as well as determine if the ball bounced in or out. The very controversial but critical key to a lot of tennis matches. And a lot of that has been historically done with the trained, but fallible human eye and computer vision is, you know, well suited for this task to say, how do we track, pan, tilt, zoom, and see, track the tennis ball in real time, run at 30 plus frames per second, and do it all on the edge. And those are capabilities that, you know, were kind of like science fiction, maybe even a decade ago, and certainly five years ago. Now the interesting thing, is that with the advent of of generative AI, you can start to do things like create your own training data sets, or kind of create logic around once you have this visual input. And teams at Tesla have actually been speaking about, of course the autopilot team's focused on doing vision tasks, but they've combined large language models to add reasoning and logic. So given that you see, let's say the tennis ball, what do you want to do? And being able to combine the capabilities of what LLM's represent, which is really a lot of basically, core human reasoning and logic, with computer vision for the inputs of what's possible, creates these new capabilities, let alone multimodality, which I'm sure we'll talk more about. >> Yeah, and it's really, I mean it's almost intoxicating. It's amazing that this is so capable because the cloud scales here, you got the edge developing, you can decouple compute power, and let Moore's law and all the new silicone and the processors and the GPUs do their thing, and you got open source booming. You're kind of getting at this next segment I wanted to get into, which is the, how people should be thinking about these advances of the computer vision. So this is now a next wave, it's here. I mean I'd love to have that for baseball because I'm always like, "Oh, it should have been a strike." I'm sure that's going to be coming soon, but what is the computer vision capable of doing today? I guess that's my first question. You hit some of it, unpack that a little bit. What does general AI mean in computer vision? What's the new thing? Because there are old technology's been around, proprietary, bolted onto hardware, but hardware advances at a different pace, but now you got new capabilities, generative AI for vision, what does that mean? >> Yeah, so computer vision, you know, at its core is basically enabling machines, computers, to understand, process, and act on visual data as effective or more effective than people can. Traditionally this has been, you know, task types like classification, which you know, identifying if a given image belongs in a certain category of goods on maybe a retail site, is the shoes or is it clothing? Or object detection, which is, you know, creating bounding boxes, which allows you to do things like count how many things are present, or maybe measure the speed of something, or trigger an alert when something becomes visible in frame that wasn't previously visible in frame, or instant segmentation where you're creating pixel wise segmentations for both instance and semantic segmentation, where you often see these kind of beautiful visuals of the polygon surrounding objects that you see. Then you have key point detection, which is where you see, you know, athletes, and each of their joints are kind of outlined is another more traditional type problem in signal processing and computer vision. With generative AI, you kind of get a whole new class of problem types that are opened up. So in a lot of ways I think about generative AI in computer vision as some of the, you know, problems that you aimed to tackle, might still be better suited for one of the previous task types we were discussing. Some of those problem types may be better suited for using a generative technique, and some are problem types that just previously wouldn't have been possible absent generative AI. And so if you make that kind of Venn diagram in your head, you can think about, okay, you know, visual question answering is a task type where if I give you an image and I say, you know, "How many people are in this image?" We could either build an object detection model that might count all those people, or maybe a visual question answering system would sufficiently answer this type of problem. Let alone generative AI being able to create new training data for old systems. And that's something that we've seen be an increasingly prominent use case for our users, as much as things that we advise our customers and the community writ large to take advantage of. So ultimately those are kind of the traditional task types. I can give you some insight, maybe, into how I think about what's possible today, or five years or ten years as you sort go back. >> Yes, definitely. Let's get into that vision. >> So I kind of think about the types of use cases in terms of what's possible. If you just imagine a very simple bell curve, your normal distribution, for the longest time, the types of things that are in the center of that bell curve are identifying objects that are very common or common objects in context. Microsoft published the COCO Dataset in 2014 of common objects and contexts, of hundreds of thousands of images of chairs, forks, food, person, these sorts of things. And you know, the challenge of the day had always been, how do you identify just those 80 objects? So if we think about the bell curve, that'd be maybe the like dead center of the curve, where there's a lot of those objects present, and it's a very common thing that needs to be identified. But it's a very, very, very small sliver of the distribution. Now if you go out to the way long tail, let's go like deep into the tail of this imagined visual normal distribution, you're going to have a problem like one of our customers, Rivian, in tandem with AWS, is tackling, to do visual quality assurance and manufacturing in production processes. Now only Rivian knows what a Rivian is supposed to look like. Only they know the imagery of what their goods that are going to be produced are. And then between those long tails of proprietary data of highly specific things that need to be understood, in the center of the curve, you have a whole kind of messy middle, type of problems I like to say. The way I think about computer vision advancing, is it's basically you have larger and larger and more capable models that eat from the center out, right? So if you have a model that, you know, understands the 80 classes in COCO, well, pretty soon you have advances like Clip, which was trained on 400 million image text pairs, and has a greater understanding of a wider array of objects than just 80 classes in context. And over time you'll get more and more of these larger models that kind of eat outwards from that center of the distribution. And so the question becomes for companies, when can you rely on maybe a model that just already exists? How do you use your data to get what may be capable off the shelf, so to speak, into something that is usable for you? Or, if you're in those long tails and you have proprietary data, how do you take advantage of the greatest asset you have, which is observed visual information that you want to put to work for your customers, and you're kind of living in the long tails, and you need to adapt state of the art for your capabilities. So my mental model for like how computer vision advances is you have that bell curve, and you have increasingly powerful models that eat outward. And multimodality has a role to play in that, larger models have a role to play in that, more compute, more data generally has a role to play in that. But it will be a messy and I think long condition. >> Well, the thing I want to get, first of all, it's great, great mental model, I appreciate that, 'cause I think that makes a lot of sense. The question is, it seems now more than ever, with the scale and compute that's available, that not only can you eat out to the middle in your example, but there's other models you can integrate with. In the past there was siloed, static, almost bespoke. Now you're looking at larger models eating into the bell curve, as you said, but also integrating in with other stuff. So this seems to be part of that interaction. How does, first of all, is that really happening? Is that true? And then two, what does that mean for companies who want to take advantage of this? Because the old model was operational, you know? I have my cameras, they're watching stuff, whatever, and like now you're in this more of a, distributed computing, computer science mindset, not, you know, put the camera on the wall kind of- I'm oversimplifying, but you know what I'm saying. What's your take on that? >> Well, to the first point of, how are these advances happening? What I was kind of describing was, you know, almost uni-dimensional in that you have like, you're only thinking about vision, but the rise of generative techniques and multi-modality, like Clip is a multi-modal model, it has 400 million image text pairs. That will advance the generalizability at a faster rate than just treating everything as only vision. And that's kind of where LLMs and vision will intersect in a really nice and powerful way. Now in terms of like companies, how should they be thinking about taking advantage of these trends? The biggest thing that, and I think it's different, obviously, on the size of business, if you're an enterprise versus a startup. The biggest thing that I think if you're an enterprise, and you have an established scaled business model that is working for your customers, the question becomes, how do you take advantage of that established data moat, potentially, resource moats, and certainly, of course, establish a way of providing value to an end user. So for example, one of our customers, Walmart, has the advantage of one of the largest inventory and stock of any company in the world. And they also of course have substantial visual data, both from like their online catalogs, or understanding what's in stock or out of stock, or understanding, you know, the quality of things that they're going from the start of their supply chain to making it inside stores, for delivery of fulfillments. All these are are visual challenges. Now they already have a substantial trove of useful imagery to understand and teach and train large models to understand each of the individual SKUs and products that are in their stores. And so if I'm a Walmart, what I'm thinking is, how do I make sure that my petabytes of visual information is utilized in a way where I capture the proprietary benefit of the models that I can train to do tasks like, what item was this? Or maybe I'm going to create AmazonGo-like technology, or maybe I'm going to build like delivery robots, or I want to automatically know what's in and out of stock from visual input fees that I have across my in-store traffic. And that becomes the question and flavor of the day for enterprises. I've got this large amount of data, I've got an established way that I can provide more value to my own customers. How do I ensure I take advantage of the data advantage I'm already sitting on? If you're a startup, I think it's a pretty different question, and I'm happy to talk about. >> Yeah, what's startup angle on this? Because you know, they're going to want to take advantage. It's like cloud startups, cloud native startups, they were born in the cloud, they never had an IT department. So if you're a startup, is there a similar role here? And if I'm a computer vision startup, what's that mean? So can you share your your take on that, because there'll be a lot of people starting up from this. >> So the startup on the opposite advantage and disadvantage, right? Like a startup doesn't have an proven way of delivering repeatable value in the same way that a scaled enterprise does. But it does have the nimbleness to identify and take advantage of techniques that you can start from a blank slate. And I think the thing that startups need to be wary of in the generative AI enlarged language model, in multimodal world, is building what I like to call, kind of like sandcastles. A sandcastle is maybe a business model or a capability that's built on top of an assumption that is going to be pretty quickly wiped away by improving underlying model technology. So almost like if you imagine like the ocean, the waves are coming in, and they're going to wipe away your progress. You don't want to be in the position of building sandcastle business where, you don't want to bet on the fact that models aren't going to get good enough to solve the task type that you might be solving. In other words, don't take a screenshot of what's capable today. Assume that what's capable today is only going to continue to become possible. And so for a startup, what you can do, that like enterprises are quite comparatively less good at, is embedding these capabilities deeply within your products and delivering maybe a vertical based experience, where AI kind of exists in the background. >> Yeah. >> And we might not think of companies as, you know, even AI companies, it's just so embedded in the experience they provide, but that's like the vertical application example of taking AI and making it be immediately usable. Or, of course there's tons of picks and shovels businesses to be built like Roboflow, where you're enabling these enterprises to take advantage of something that they have, whether that's their data sets, their computes, or their intellect. >> Okay, so if I hear that right, by the way, I love, that's horizontally scalable, that's the large language models, go up and build them the apps, hence your developer focus. I'm sure that's probably the reason that the tsunami of developer's action. So you're saying picks and shovels tools, don't try to replicate the platform of what could be the platform. Oh, go to a VC, I'm going to build a platform. No, no, no, no, those are going to get wiped away by the large language models. Is there one large language model that will rule the world, or do you see many coming? >> Yeah, so to be clear, I think there will be useful platforms. I just think a lot of people think that they're building, let's say, you know, if we put this in the cloud context, you're building a specific type of EC2 instance. Well, it turns out that Amazon can offer that type of EC2 instance, and immediately distribute it to all of their customers. So you don't want to be in the position of just providing something that actually ends up looking like a feature, which in the context of AI, might be like a small incremental improvement on the model. If that's all you're doing, you're a sandcastle business. Now there's a lot of platform businesses that need to be built that enable businesses to get to value and do things like, how do I monitor my models? How do I create better models with my given data sets? How do I ensure that my models are doing what I want them to do? How do I find the right models to use? There's all these sorts of platform wide problems that certainly exist for businesses. I just think a lot of startups that I'm seeing right now are making the mistake of assuming the advances we're seeing are not going to accelerate or even get better. >> So if I'm a customer, if I'm a company, say I'm a startup or an enterprise, either one, same question. And I want to stand up, and I have developers working on stuff, I want to start standing up an environment to start doing stuff. Is that a service provider? Is that a managed service? Is that you guys? So how do you guys fit into your customers leaning in? Is it just for developers? Are you targeting with a specific like managed service? What's the product consumption? How do you talk to customers when they come to you? >> The thing that we do is enable, we give developers superpowers to build automated inventory tracking, self-checkout systems, identify if this image is malignant cancer or benign cancer, ensure that these products that I've produced are correct. Make sure that that the defect that might exist on this electric vehicle makes its way back for review. All these sorts of problems are immediately able to be solved and tackled. In terms of the managed services element, we have solutions as integrators that will often build on top of our tools, or we'll have companies that look to us for guidance, but ultimately the company is in control of developing and building and creating these capabilities in house. I really think the distinction is maybe less around managed service and tool, and more around ownership in the era of AI. So for example, if I'm using a managed service, in that managed service, part of their benefit is that they are learning across their customer sets, then it's a very different relationship than using a managed service where I'm developing some amount of proprietary advantages for my data sets. And I think that's a really important thing that companies are becoming attuned to, just the value of the data that they have. And so that's what we do. We tell companies that you have this proprietary, immense treasure trove of data, use that to your advantage, and think about us more like a set of tools that enable you to get value from that capability. You know, the HashiCorp's and GitLab's of the world have proven like what these businesses look like at scale. >> And you're targeting developers. When you go into a company, do you target developers with freemium, is there a paid service? Talk about the business model real quick. >> Sure, yeah. The tools are free to use and get started. When someone signs up for Roboflow, they may elect to make their work open source, in which case we're able to provide even more generous usage limits to basically move the computer vision community forward. If you elect to make your data private, you can use our hosted data set managing, data set training, model deployment, annotation tooling up to some limits. And then usually when someone validates that what they're doing gets them value, they purchase a subscription license to be able to scale up those capabilities. So like most developer centric products, it's free to get started, free to prove, free to poke around, develop what you think is possible. And then once you're getting to value, then we're able to capture the commercial upside in the value that's being provided. >> Love the business model. It's right in line with where the market is. There's kind of no standards bodies these days. The developers are the ones who are deciding kind of what the standards are by their adoption. I think making that easy for developers to get value as the model open sources continuing to grow, you can see more of that. Great perspective Joseph, thanks for sharing that. Put a plug in for the company. What are you guys doing right now? Where are you in your growth? What are you looking for? How should people engage? Give the quick commercial for the company. >> So as I mentioned, Roboflow is I think one of the largest, if not the largest collections of computer vision models and data sets that are open source, available on the web today, and have a private set of tools that over half the Fortune 100 now rely on those tools. So we're at the stage now where we know people want what we're working on, and we're continuing to drive that type of adoption. So companies that are looking to make better models, improve their data sets, train and deploy, often will get a lot of value from our tools, and certainly reach out to talk. I'm sure there's a lot of talented engineers that are tuning in too, we're aggressively hiring. So if you are interested in being a part of making the world programmable, and being at the ground floor of the company that's creating these capabilities to be writ large, we'd love to hear from you. >> Amazing, Joseph, thanks so much for coming on and being part of the AWS Startup Showcase. Man, if I was in my twenties, I'd be knocking on your door, because it's the hottest trend right now, it's super exciting. Generative AI is just the beginning of massive sea change. Congratulations on all your success, and we'll be following you guys. Thanks for spending the time, really appreciate it. >> Thanks for having me. >> Okay, this is season three, episode one of the ongoing series covering the exciting startups from the AWS ecosystem, talking about the hottest things in tech. I'm John Furrier, your host. Thanks for watching. (chill electronic music)

(gentle upbeat music) >> Hey, friends of theCUBE. It's Lisa Martin live at Stanford University covering the Eighth Annual Women In Data Science. But you've been a Cube fan for a long time. So you know that we've been here since the beginning of WiDS, which is 2015. We always loved to come and cover this event. We learned great things about data science, about women leaders, underrepresented minorities. And this year we have a special component. We've got two grad students from Stanford's Master's program and Data Journalism joining. One of my them is here with me, Hannah Freitag, my co-host. Great to have you. And we are pleased to welcome from Intuit for the first time, Shir Meir Lador Group Manager at Data Science. Shir, it's great to have you. Thank you for joining us. >> Thank you for having me. >> And I was just secrets girl talking with my boss of theCUBE who informed me that you're in great company. Intuit's Chief Technology Officer, Marianna Tessel is an alumni of theCUBE. She was on at our Supercloud event in January. So welcome back into it. >> Thank you very much. We're happy to be with you. >> Tell us a little bit about what you're doing. You're a data science group manager as I mentioned, but also you've had you've done some cool things I want to share with the audience. You're the co-founder of the PyData Tel Aviv Meetups the co-host of the unsupervised podcast about data science in Israel. You give talks, about machine learning, about data science. Tell us a little bit about your background. Were you always interested in STEM studies from the time you were small? >> So I was always interested in mathematics when I was small, I went to this special program for youth going to university. So I did my test in mathematics earlier and studied in university some courses. And that's when I understood I want to do something in that field. And then when I got to go to university, I went to electrical engineering when I found out about algorithms and how interested it is to be able to find solutions to problems, to difficult problems with math. And this is how I found my way into machine learning. >> Very cool. There's so much, we love talking about machine learning and AI on theCUBE. There's so much potential. Of course, we have to have data. One of the things that I love about WiDS and Hannah and I and our co-host Tracy, have been talking about this all day is the impact of data in everyone's life. If you break it down, I was at Mobile World Congress last week, all about connectivity telecom, and of course we have these expectation that we're going to be connected 24/7 from wherever we are in the world and we can do whatever we want. I can do an Uber transaction, I can watch Netflix, I can do a bank transaction. It all is powered by data. And data science is, some of the great applications of it is what it's being applied to. Things like climate change or police violence or health inequities. Talk about some of the data science projects that you're working on at Intuit. I'm an intuit user myself, but talk to me about some of those things. Give the audience really a feel for what you're doing. >> So if you are a Intuit product user, you probably use TurboTax. >> I do >> In the past. So for those who are not familiar, TurboTax help customers submit their taxes. Basically my group is in charge of getting all the information automatically from your documents, the documents that you upload to TurboTax. We extract that information to accelerate your tax submission to make it less work for our customers. So- >> Thank you. >> Yeah, and this is why I'm so proud to be working at this team because our focus is really to help our customers to simplify all the you know, financial heavy lifting with taxes and also with small businesses. We also do a lot of work in extracting information from small business documents like bill, receipts, different bank statements. Yeah, so this is really exciting for me, the opportunity to work to apply data science and machine learning to solution that actually help people. Yeah >> Yeah, in the past years there have been more and more digital products emerging that needs some sort of data security. And how did your team, or has your team developed in the past years with more and more products or companies offering digital services? >> Yeah, so can you clarify the question again? Sorry. >> Yeah, have you seen that you have more customers? Like has your team expanded in the past years with more digital companies starting that need kind of data security? >> Well, definitely. I think, you know, since I joined Intuit, I joined like five and a half years ago back when I was in Tel Aviv. I recently moved to the Bay Area. So when I joined, there were like a dozens of data scientists and machine learning engineers on Intuit. And now there are a few hundreds. So we've definitely grown with the year and there are so many new places we can apply machine learning to help our customers. So this is amazing, so much we can do with machine learning to get more money in the pocket of our customers and make them do less work. >> I like both of those. More money in my pocket and less work. That's awesome. >> Exactly. >> So keep going Intuit. But one of the things that is so cool is just the the abstraction of the complexity that Intuit's doing. I upload documents or it scans my receipts. I was just in Barcelona last week all these receipts and conversion euros to dollars and it takes that complexity away from the end user who doesn't know all that's going on in the background, but you're making people's lives simpler. Unfortunately, we all have to pay taxes, most of us should. And of course we're in tax season right now. And so it's really cool what you're doing with ML and data science to make fundamental processes to people's lives easier and just a little bit less complicated. >> Definitely. And I think that's what's also really amazing about Intuit it, is how it combines human in the loop as well as AI. Because in some of the tax situation it's very complicated maybe to do it yourself. And then there's an option to work with an expert online that goes on a video with you and helps you do your taxes. And the expert's work is also accelerated by AI because we build tools for those experts to do the work more efficiently. >> And that's what it's all about is you know, using data to be more efficient, to be faster, to be smarter, but also to make complicated processes in our daily lives, in our business lives just a little bit easier. One of the things I've been geeking out about recently is ChatGPT. I was using it yesterday. I was telling everyone I was asking it what's hot in data science and I didn't know would it know what hot is and it did, it gave me trends. But one of the things that I was so, and Hannah knows I've been telling this all day, I was so excited to learn over the weekend that the the CTO of OpenAI is a female. I didn't know that. And I thought why are we not putting her on a pedestal? Because people are likening ChatGPT to like the launch of the iPhone. I mean revolutionary. And here we have what I think is exciting for all of us females, whether you're in tech or not, is another role model. Because really ultimately what WiDS is great at doing is showcasing women in technical roles. Because I always say you can't be what you can't see. We need to be able to see more role models, female role role models, underrepresented minorities of course men, because a lot of my sponsors and mentors are men, but we need more women that we can look up to and see ah, she's doing this, why can't I? Talk to me about how you stay the course in data science. What excites you about the potential, the opportunities based on what you've already accomplished what inspires you to continue and be one of those females that we say oh my God, I could be like Shir. >> I think that what inspires me the most is the endless opportunities that we have. I think we haven't even started tapping into everything that we can do with generative AI, for example. There's so much that can be done to further help you know, people make more money and do less work because there's still so much work that we do that we don't need to. You know, this is with Intuit, but also there are so many other use cases like I heard today you know, with the talk about the police. So that was really exciting how you can apply machine learning and data to actually help people, to help people that been through wrongful things. So I was really moved by that. And I'm also really excited about all the medical applications that we can have with data. >> Yeah, yeah. It's true that data science is so diverse in terms of what fields it can cover but it's equally important to have diverse teams and have like equity and inclusion in your teams. Where is Intuit at promoting women, non-binary minorities in your teams to progress data science? >> Yeah, so I have so much to say on this. >> Good. >> But in my work in Tel Aviv, I had the opportunity to start with Intuit women in data science branch in Tel Aviv. So that's why I'm super excited to be here today for that because basically this is the original conference, but as you know, there are branches all over the world and I got the opportunity to lead the Tel Aviv branch with Israel since 2018. And we've been through already this year it's going to be it's next week, it's going to be the sixth conference. And every year our number of submission to make talk in the conference doubled itself. >> Nice. >> We started with 20 submission, then 50, then 100. This year we have over 200 submissions of females to give talk at the conference. >> Ah, that's fantastic. >> And beyond the fact that there's so much traction, I also feel the great impact it has on the community in Israel because one of the reason we started WiDS was that when I was going to conferences I was seeing so little women on stage in all the technical conferences. You know, kind of the reason why I guess you know, Margaret and team started the WiDS conference. So I saw the same thing in Israel and I was always frustrated. I was organizing PyData Meetups as you mentioned and I was always having such a hard time to get female speakers to talk. I was trying to role model, but that's not enough, you know. We need more. So once we started WiDS and people saw you know, so many examples on the stage and also you know females got opportunity to talk in a place for that. Then it also started spreading and you can see more and more female speakers across other conferences, which are not women in data science. So I think just the fact that Intuits started this conference back in Israel and also in Bangalore and also the support Intuit does for WiDS in Stanford here, it shows how much WiDS values are aligned with our values. Yeah, and I think that to chauffeur that I think we have over 35% females in the data science and machine learning engineering roles, which is pretty amazing I think compared to the industry. >> Way above average. Yeah, absolutely. I was just, we've been talking about some of the AnitaB.org stats from 2022 showing that 'cause usually if we look at the industry to you point, over the last, I don't know, probably five, 10 years we're seeing the number of female technologists around like a quarter, 25% or so. 2022 data from AnitaB.org showed that that number is now 27.6%. So it's very slowly- >> It's very slowly increasing. >> Going in the right direction. >> Too slow. >> And that representation of women technologists increase at every level, except intern, which I thought was really interesting. And I wonder is there a covid relation there? >> I don't know. >> What do we need to do to start opening up the the top of the pipeline, the funnel to go downstream to find kids like you when you were younger and always interested in engineering and things like that. But the good news is that the hiring we've seen improvements, but it sounds like Intuit is way ahead of the curve there with 35% women in data science or technical roles. And what's always nice and refreshing that we've talked, Hannah about this too is seeing companies actually put action into initiatives. It's one thing for a company to say we're going to have you know, 50% females in our organization by 2030. It's a whole other ball game to actually create a strategy, execute on it, and share progress. So kudos to Intuit for what it's doing because that is more companies need to adopt that same sort of philosophy. And that's really cultural. >> Yeah. >> At an organization and culture can be hard to change, but it sounds like you guys kind of have it dialed in. >> I think we definitely do. That's why I really like working and Intuit. And I think that a lot of it is with the role modeling, diversity and inclusion, and by having women leaders. When you see a woman in leadership position, as a woman it makes you want to come work at this place. And as an evidence, when I build the team I started in Israel at Intuit, I have over 50% women in my team. >> Nice. >> Yeah, because when you have a woman in the interviewers panel, it's much easier, it's more inclusive. That's why we always try to have at least you know, one woman and also other minorities represented in our interviews panel. Yeah, and I think that in general it's very important as a leader to kind of know your own biases and trying to have defined standard and rubrics in how you evaluate people to avoid for those biases. So all of that inclusiveness and leadership really helps to get more diversity in your teams. >> It's critical. That thought diversity is so critical, especially if we talk about AI and we're almost out of time, I just wanted to bring up, you brought up a great point about the diversity and equity. With respect to data science and AI, we know in AI there's biases in data. We need to have more inclusivity, more representation to help start shifting that so the biases start to be dialed down and I think a conference like WiDS and it sounds like someone like you and what you've already done so far in the work that you're doing having so many females raise their hands to want to do talks at events is a good situation. It's a good scenario and hopefully it will continue to move the needle on the percentage of females in technical roles. So we thank you Shir for your time sharing with us your story, what you're doing, how Intuit and WiDS are working together. It sounds like there's great alignment there and I think we're at the tip of the iceberg with what we can do with data science and inclusion and equity. So we appreciate all of your insights and your time. >> Thank you very much. >> All right. >> I enjoyed very, very much >> Good. We hope, we aim to please. Thank you for our guests and for Hannah Freitag. This is Lisa Martin coming to you live from Stanford University. This is our coverage of the eighth Annual Women in Data Science Conference. Stick around, next guest will be here in just a minute.

(gentle music) >> Hey! Welcome back to theCUBE's coverage of WiDS 2023, the eighth Annual Women In Data Science Conference. I'm your host, Lisa Martin. We are at Stanford University, as you know we are every year, having some wonderful conversations with some very inspiring women and men in data science and technical roles. I'm very pleased to introduce Tracy Zhang, my co-host, who is in the Data Journalism program at Stanford. And Tracy and I are pleased to welcome our next guest, Rhonda Crate, Principal Data Scientist at Boeing. Great to have you on the program, Rhonda. >> Tracy: Welcome. >> Hey, thanks for having me. >> Were you always interested in data science or STEM from the time you were young? >> No, actually. I was always interested in archeology and anthropology. >> That's right, we were talking about that, anthropology. Interesting. >> We saw the anthropology background, not even a bachelor's degree, but also a master's degree in anthropology. >> So you were committed for a while. >> I was, I was. I actually started college as a fine arts major, but I always wanted to be an archeologist. So at the last minute, 11 credits in, left to switch to anthropology. And then when I did my master's, I focused a little bit more on quantitative research methods and then I got my Stat Degree. >> Interesting. Talk about some of the data science projects that you're working on. When I think of Boeing, I always think of aircraft. But you are doing a lot of really cool things in IT, data analytics. Talk about some of those intriguing data science projects that you're working on. >> Yeah. So when I first started at Boeing, I worked in information technology and data analytics. And Boeing, at the time, had cored up data science in there. And so we worked as a function across the enterprise working on anything from shared services to user experience in IT products, to airplane programs. So, it has a wide range. I worked on environment health and safety projects for a long time as well. So looking at ergonomics and how people actually put parts onto airplanes, along with things like scheduling and production line, part failures, software testing. Yeah, there's a wide spectrum of things. >> But I think that's so fantastic. We've been talking, Tracy, today about just what we often see at WiDS, which is this breadth of diversity in people's background. You talked about anthropology, archeology, you're doing data science. But also all of the different opportunities that you've had at Boeing. To see so many facets of that organization. I always think that breadth of thought diversity can be hugely impactful. >> Yeah. So I will say my anthropology degree has actually worked to my benefit. I'm a huge proponent of integrating liberal arts and sciences together. And it actually helps me. I'm in the Technical Fellowship program at Boeing, so we have different career paths. So you can go into management, you can be a regular employee, or you can go into the Fellowship program. So right now I'm an Associate Technical Fellow. And part of how I got into the Fellowship program was that diversity in my background, what made me different, what made me stand out on projects. Even applying a human aspect to things like ergonomics, as silly as that sounds, but how does a person actually interact in the space along with, here are the actual measurements coming off of whatever system it is that you're working on. So, I think there's a lot of opportunities, especially in safety as well, which is a big initiative for Boeing right now, as you can imagine. >> Tracy: Yeah, definitely. >> I can't go into too specifics. >> No, 'cause we were like, I think a theme for today that kind of we brought up in in all of our talk is how data is about people, how data is about how people understand the world and how these data can make impact on people's lives. So yeah, I think it's great that you brought this up, and I'm very happy that your anthropology background can tap into that and help in your day-to-day data work too. >> Yeah. And currently, right now, I actually switched over to Strategic Workforce Planning. So it's more how we understand our workforce, how we work towards retaining the talent, how do we get the right talent in our space, and making sure overall that we offer a culture and work environment that is great for our employees to come to. >> That culture is so important. You know, I was looking at some anitab.org stats from 2022 and you know, we always talk about the number of women in technical roles. For a long time it's been hovering around that 25% range. The data from anitab.org showed from '22, it's now 27.6%. So, a little increase. But one of the biggest challenges still, and Tracy and I and our other co-host, Hannah, have been talking about this, is attrition. Attrition more than doubled last year. What are some of the things that Boeing is doing on the retention side, because that is so important especially as, you know, there's this pipeline leakage of women leaving technical roles. Tell us about what Boeing's, how they're invested. >> Yeah, sure. We actually have a publicly available Global Diversity Report that anybody can go and look at and see our statistics for our organization. Right now, off the top of my head, I think we're hovering at about 24% in the US for women in our company. It has been a male majority company for many years. We've invested heavily in increasing the number of women in roles. One interesting thing about this year that came out is that even though with the great resignation and those types of things, the attrition level between men and women were actually pretty close to being equal, which is like the first time in our history. Usually it tends on more women leaving. >> Lisa: That's a good sign. >> Right. >> Yes, that's a good sign. >> And we've actually focused on hiring and bringing in more women and diversity in our company. >> Yeah, some of the stats too from anitab.org talked about the increase, and I have to scroll back and find my notes, the increase in 51% more women being hired in 2022 than 2021 for technical roles. So the data, pun intended, is showing us. I mean, the data is there to show the impact that having females in executive leadership positions make from a revenue perspective. >> Tracy: Definitely. >> Companies are more profitable when there's women at the head, or at least in senior leadership roles. But we're seeing some positive trends, especially in terms of representation of women technologists. One of the things though that I found interesting, and I'm curious to get your thoughts on this, Rhonda, is that the representation of women technologists is growing in all areas, except interns. >> Rhonda: Hmm. >> So I think, we've got to go downstream. You teach, I have to go back to my notes on you, did my due diligence, R programming classes through Boeings Ed Wells program, this is for WSU College of Arts and Sciences, talk about what you teach and how do you think that intern kind of glut could be solved? >> Yeah. So, they're actually two separate programs. So I teach a data analytics course at Washington State University as an Adjunct Professor. And then the Ed Wells program is a SPEEA, which is an Aerospace Union, focused on bringing up more technology and skills to the actual workforce itself. So it's kind of a couple different audiences. One is more seasoned employees, right? The other one is our undergraduates. I teach a Capstone class, so it's a great way to introduce students to what it's actually like to work on an industry project. We partner with Google and Microsoft and Boeing on those. The idea is also that maybe those companies have openings for the students when they're done. Since it's Senior Capstone, there's not a lot of opportunities for internships. But the opportunities to actually get hired increase a little bit. In regards to Boeing, we've actually invested a lot in hiring more women interns. I think the number was 40%, but you'd have to double check. >> Lisa: That's great, that's fantastic. >> Tracy: That's way above average, I think. >> That's a good point. Yeah, it is above average. >> Double check on that. That's all from my memory. >> Is this your first WiDS, or have you been before? >> I did virtually last year. >> Okay. One of the things that I love, I love covering this event every year. theCUBE's been covering it since it's inception in 2015. But it's just the inspiration, the vibe here at Stanford is so positive. WiDS is a movement. It's not an initiative, an organization. There are going to be, I think annually this year, there will be 200 different events. Obviously today we're live on International Women's Day. 60 plus countries, 100,000 plus people involved. So, this is such a positive environment for women and men, because we need everybody, underrepresented minorities, to be able to understand the implication that data has across our lives. If we think about stripping away titles in industries, everybody is a consumer, not everybody, most of mobile devices. And we have this expectation, I was in Barcelona last week at a Mobile World Congress, we have this expectation that we're going to be connected 24/7. I can get whatever I want wherever I am in the world, and that's all data driven. And the average person that isn't involved in data science wouldn't understand that. At the same time, they have expectations that depend on organizations like Boeing being data driven so that they can get that experience that they expect in their consumer lives in any aspect of their lives. And that's one of the things I find so interesting and inspiring about data science. What are some of the things that keep you motivated to continue pursuing this? >> Yeah I will say along those lines, I think it's great to invest in K-12 programs for Data Literacy. I know one of my mentors and directors of the Data Analytics program, Dr. Nairanjana Dasgupta, we're really familiar with each other. So, she runs a WSU program for K-12 Data Literacy. It's also something that we strive for at Boeing, and we have an internal Data Literacy program because, believe it or not, most people are in business. And there's a lot of disconnect between interpreting and understanding data. For me, what kind of drives me to continue data science is that connection between people and data and how we use it to improve our world, which is partly why I work at Boeing too 'cause I feel that they produce products that people need like satellites and airplanes, >> Absolutely. >> and everything. >> Well, it's tangible, it's relatable. We can understand it. Can you do me a quick favor and define data literacy for anyone that might not understand what that means? >> Yeah, so it's just being able to understand elements of data, whether that's a bar chart or even in a sentence, like how to read a statistic and interpret a statistic in a sentence, for example. >> Very cool. >> Yeah. And sounds like Boeing's doing a great job in these programs, and also trying to hire more women. So yeah, I wanted to ask, do you think there's something that Boeing needs to work on? Or where do you see yourself working on say the next five years? >> Yeah, I think as a company, we always think that there's always room for improvement. >> It never, never stops. >> Tracy: Definitely. (laughs) >> I know workforce strategy is an area that they're currently really heavily investing in, along with safety. How do we build safer products for people? How do we help inform the public about things like Covid transmission in airports? For example, we had the Confident Traveler Initiative which was a big push that we had, and we had to be able to inform people about data models around Covid, right? So yeah, I would say our future is more about an investment in our people and in our culture from my perspective >> That's so important. One of the hardest things to change especially for a legacy organization like Boeing, is culture. You know, when I talk with CEO's or CIO's or COO's about what's your company's vision, what's your strategy? Especially those companies that are on that digital journey that have no choice these days. Everybody expects to have a digital experience, whether you're transacting an an Uber ride, you're buying groceries, or you're traveling by air. That culture sounds like Boeing is really focused on that. And that's impressive because that's one of the hardest things to morph and mold, but it's so essential. You know, as we look around the room here at WiDS it's obviously mostly females, but we're talking about women, underrepresented minorities. We're talking about men as well who are mentors and sponsors to us. I'd love to get your advice to your younger self. What would you tell yourself in terms of where you are now to become a leader in the technology field? >> Yeah, I mean, it's kind of an interesting question because I always try to think, live with no regrets to an extent. >> Lisa: I like that. >> But, there's lots of failures along the way. (Tracy laughing) I don't know if I would tell myself anything different because honestly, if I did, I wouldn't be where I am. >> Lisa: Good for you. >> I started out in fine arts, and I didn't end up there. >> That's good. >> Such a good point, yeah. >> We've been talking about that and I find that a lot at events like WiDS, is women have these zigzaggy patterns. I studied biology, I have a master's in molecular biology, I'm in media and marketing. We talked about transportable skills. There's a case I made many years ago when I got into tech about, well in science you learn the art of interpreting esoteric data and creating a story from it. And that's a transportable skill. But I always say, you mentioned failure, I always say failure is not a bad F word. It allows us to kind of zig and zag and learn along the way. And I think that really fosters thought diversity. And in data science, that is one of the things we absolutely need to have is that diversity and thought. You know, we talk about AI models being biased, we need the data and we need the diverse brains to help ensure that the biases are identified, extracted, and removed. Speaking of AI, I've been geeking out with ChatGPT. So, I'm on it yesterday and I ask it, "What's hot in data science?" And I was like, is it going to get that? What's hot? And it did it, it came back with trends. I think if I ask anything, "What's hot?", I should be to Paris Hilton, but I didn't. And so I was geeking out. One of the things I learned recently that I thought was so super cool is the CTO of OpenAI is a woman, Mira Murati, which I didn't know until over the weekend. Because I always think if I had to name top females in tech, who would they be? And I always default to Sheryl Sandberg, Carly Fiorina, Susan Wojcicki running YouTube. Who are some of the people in your history, in your current, that are really inspiring to you? Men, women, indifferent. >> Sure. I think Boeing is one of the companies where you actually do see a lot of women in leadership roles. I think we're one of the top companies with a number of women executives, actually. Susan Doniz, who's our Chief Information Officer, I believe she's actually slotted to speak at a WiDS event come fall. >> Lisa: Cool. >> So that will be exciting. Susan's actually relatively newer to Boeing in some ways. A Boeing time skill is like three years is still kind of new. (laughs) But she's been around for a while and she's done a lot of inspiring things, I think, for women in the organization. She does a lot with Latino communities and things like that as well. For me personally, you know, when I started at Boeing Ahmad Yaghoobi was one of my mentors and my Technical Lead. He came from Iran during a lot of hard times in the 1980s. His brother actually wrote a memoir, (laughs) which is just a fun, interesting fact. >> Tracy: Oh my God! >> Lisa: Wow! >> And so, I kind of gravitate to people that I can learn from that's not in my sphere, that might make me uncomfortable. >> And you probably don't even think about how many people you're influencing along the way. >> No. >> We just keep going and learning from our mentors and probably lose sight of, "I wonder how many people actually admire me?" And I'm sure there are many that admire you, Rhonda, for what you've done, going from anthropology to archeology. You mentioned before we went live you were really interested in photography. Keep going and really gathering all that breadth 'cause it's only making you more inspiring to people like us. >> Exactly. >> We thank you so much for joining us on the program and sharing a little bit about you and what brought you to WiDS. Thank you so much, Rhonda. >> Yeah, thank you. >> Tracy: Thank you so much for being here. >> Lisa: Yeah. >> Alright. >> For our guests, and for Tracy Zhang, this is Lisa Martin live at Stanford University covering the eighth Annual Women In Data Science Conference. Stick around. Next guest will be here in just a second. (gentle music)

(upbeat music) >> Hey everyone. Welcome back to "The Cube"'s live coverage of "Women in Data Science 2023". As every year we are here live at Stanford University, profiling some amazing women and men in the fields of data science. I have my co-host for this segment is Hannah Freitag. Hannah is from Stanford's Data Journalism program, really interesting, check it out. We're very pleased to welcome our first guest of the day fresh from the keynote stage, Gayatree Ganu, the VP of Data Science at Meta. Gayatree, It's great to have you on the program. >> Likewise, Thank you for having me. >> So you have a PhD in Computer Science. You shared some really cool stuff. Everyone knows Facebook, everyone uses it. I think my mom might be one of the biggest users (Gayatree laughs) and she's probably watching right now. People don't realize there's so much data behind that and data that drives decisions that we engage with. But talk to me a little bit about you first, PhD in Computer Science, were you always, were you like a STEM kid? Little Gayatree, little STEM, >> Yeah, I was a STEM kid. I grew up in Mumbai, India. My parents are actually pharmacists, so they were not like math or stats or anything like that, but I was always a STEM kid. I don't know, I think it, I think I was in sixth grade when we got our first personal computer and I obviously used it as a Pacman playing machine. >> Oh, that's okay. (all laugh) >> But I was so good at, and I, I honestly believe I think being good at games kind of got me more familiar and comfortable with computers. Yeah. I think I always liked computers, I, yeah. >> And so now you lead, I'm looking at my notes here, the Engagement Ecosystem and Monetization Data Science teams at Facebook, Meta. Talk about those, what are the missions of those teams and how does it impact the everyday user? >> Yeah, so the engagement is basically users coming back to our platform more, there's, no better way for users to tell us that they are finding value on the things that we are doing on Facebook, Instagram, WhatsApp, all the other products than coming back to our platform more. So the Engagement Ecosystem team is looking at trends, looking at where there are needs, looking at how users are changing their behaviors, and you know, helping build strategy for the long term, using that data knowledge. Monetization is very different. You know, obviously the top, top apex goal is have a sustainable business so that we can continue building products for our users. And so, but you know, I said this in my keynote today, it's not about making money, our mission statement is not, you know, maximize as much money as you can make. It's about building a meaningful connection between businesses, customers, users, and, you know especially in these last two or three funky, post-pandemic years, it's been such a big, an important thing to do for small businesses all over all, all around the world for users to find like goods and services and products that they care about and that they can connect to. So, you know, there is truly an connection between my engagement world and the monetization world. And you know, it's not very clear always till you go in to, like, you peel the layers. Everything we do in the ads world is also always first with users as our, you know, guiding principle. >> Yeah, you mentioned how you supported especially small businesses also during the pandemic. You touched a bit upon it in the keynote speech. Can you tell our audience what were like special or certain specific programs you implemented to support especially small businesses during these times? >> Yeah, so there are 200 million businesses on our platform. A lot of them small businesses, 10 million of them run ads. So there is a large number of like businesses on our platform who, you know use the power of social media to connect to the customers that matter to them, to like you, you know use the free products that we built. In the post-pandemic years, we built a lot of stuff very quickly when Covid first hit for business to get the word out, right? Like, they had to announce when special shopping hours existed for at-risk populations, or when certain goods and services were available versus not. We had grants, there's $100 million grant that we gave out to small businesses. Users could show sort of, you know show their support with a bunch of campaigns that we ran, and of course we continue running ads. Our ads are very effective, I guess, and, you know getting a very reliable connection with from the customer to the business. And so, you know, we've run all these studies. We support, I talked about two examples today. One of them is the largest black-owned, woman black-owned wine company, and how they needed to move to an online program and, you know, we gave them a grant, and supported them through their ads campaign and, you know, they saw 60% lift in purchases, or something like that. So, a lot of good stories, small stories, you know, on a scale of 200 million, that really sort of made me feel proud about the work we do. And you know, now more than ever before, I think people can connect so directly with businesses. You can WhatsApp them, I come from India, every business is on WhatsApp. And you can, you know, WhatsApp them, you can send them Facebook messages, and you can build this like direct connection with things that matter to you. >> We have this expectation that we can be connected anywhere. I was just at Mobile World Congress for MWC last week, where, obviously talking about connectivity. We want to be able to do any transaction, whether it's post on Facebook or call an Uber, or watch on Netflix if you're on the road, we expect that we're going to be connected. >> Yeah. >> And what we, I think a lot of us don't realize I mean, those of us in tech do, but how much data science is a facilitator of all of those interactions. >> Yeah! >> As we, Gayatree, as we talk about, like, any business, whether it is the black women-owned wine business, >> Yeah. >> great business, or a a grocer or a car dealer, everybody has to become data-driven. >> Yes. >> Because the consumer has the expectation. >> Yes. >> Talk about data science as a facilitator of just pretty much everything we are doing and conducting in our daily lives. >> Yeah, I think that's a great question. I think data science as a field wasn't really defined like maybe 15 years ago, right? So this is all in our lifetimes that we are seeing this. Even in data science today, People come from so many different backgrounds and bring their own expertise here. And I think we, you know, this conference, all of us get to define what that means and how we can bring data to do good in the world. Everything you do, as you said, there is a lot of data. Facebook has a lot of data, Meta has a lot of data, and how do we responsibly use this data? How do we use this data to make sure that we're, you know representing all diversity? You know, minorities? Like machine learning algorithms don't do well with small data, they do well with big data, but the small data matters. And how do you like, you know, bring that into algorithms? Yeah, so everything we do at Meta is very, very data-driven. I feel proud about that, to be honest, because while data gets a bad rap sometimes, having no data and making decisions in the blind is just the absolute worst thing you can do. And so, you know, we, the job as a data scientist at Facebook is to make sure that we use this data, use this responsibly, make sure that we are representing every aspect of the, you know, 3 billion users who come to our platform. Yeah, data serves all the products that we build here. >> The responsibility factor is, is huge. You know, we can't talk about AI without talking about ethics. One of the things that I was talking with Hannah and our other co-host, Tracy, about during our opening is something I just learned over the weekend. And that is that the CTO of ChatGPT is a woman. (Gayatree laughs) I didn't know that. And I thought, why isn't she getting more awareness? There's a lot of conversations with their CEO. >> Yeah. >> Everyone's using it, playing around with it. I actually asked it yesterday, "What's hot in Data Science?" (all laugh) I was like, should I have asked that to let itself in, what's hot? (Gayatree laughs) But it, I thought that was phenomenal, and we need to be talking about this more. >> Yeah. >> This is something that they're likening to the launch of the iPhone, which has transformed our lives. >> I know, it is. >> ChatGPT, and its chief technologist is a female, how great is that? >> And I don't know whether you, I don't know the stats around this, but I think CTO is even less, it's even more rare to have a woman there, like you have women CEOs because I mean, we are building upon years and years of women not choosing technical fields and not choosing STEM, and it's going to take some time, but yeah, yeah, she's a woman. Isn't it amazing? It's wonderful. >> Yes, there was a great, there's a great "Fast Company" article on her that I was looking at yesterday and I just thought, we need to do what we can to help spread, Mira Murati is her name, because what she's doing is, one of the biggest technological breakthroughs we may ever see in our lifetime. It gives me goosebumps just thinking about it. (Gayatree laughs) I also wanted to share some stats, oh, sorry, go ahead, Hannah. >> Yeah, I was going to follow up on the thing that you mentioned that we had many years with like not enough women choosing a career path in STEM and that we have to overcome this trend. What are some, like what is some advice you have like as the Vice-President Data Science? Like what can we do to make this feel more, you know, approachable and >> Yeah. >> accessible for women? >> Yeah, I, there's so much that we have done already and you know, want to continue, keep doing. Of course conferences like these were, you know and I think there are high school students here there are students from my Alma Mater's undergrad year. It's amazing to like get all these women together to get them to see what success could look like. >> Yeah. >> What being a woman leader in this space could look like. So that's, you know, that's one, at Meta I lead recruiting at Meta and we've done a bunch to sort of open up the thinking around data science and technical jobs for women. Simple things like what you write in your job description. I don't know whether you know this, or this is a story you've heard before, when you see, when you have a job description and there are like 10 things that you need to, you know be good at to apply to this job, a woman sees those 10 and says, okay, I don't meet the qualifications of one of them and she doesn't apply. And a man sees one that he meets the qualifications to and he applies. And so, you know, there's small things you can do, and just how you write your job description, what goals you set for diversity and inclusion for your own organization. We have goals, Facebook's always been pretty up there in like, you know, speaking out for diversity and Sheryl Sandberg has been our Chief Business Officer for a very long time and she's been, like, amazing at like pushing from more women. So yeah, every step of the way, I think, we made a lot of progress, to be honest. I do think women choose STEM fields a lot more than they did. When I did my Computer Science I was often one of one or two women in the Computer Science class. It takes some time to, for it to percolate all the way to like having more CTOs and CEOs, >> Yeah. >> but it's going to happen in our lifetime, and you know, three of us know this, women are going to rule the world, and it (laughs) >> Drop the mic, girl! >> And it's going to happen in our lifetime, so I'm excited about it. >> And we have responsibility in helping make that happen. You know, I'm curious, you were in STEM, you talked about Computer Science, being one of the only females. One of the things that the nadb.org data from 2022 showed, some good numbers, the number of women in technical roles is now 27.6%, I believe, so up from 25, it's up in '22, which is good, more hiring of women. >> Yeah. >> One of the biggest challenges is attrition. What keeps you motivated? >> Yeah. >> To stay what, where you are doing what you're doing, managing a family and helping to drive these experiences at Facebook that we all expect are just going to happen? >> Yeah, two things come to mind. It does take a village. You do need people around you. You know, I'm grateful for my husband. You talked about managing a family, I did the very Indian thing and my parents live with us, and they help take care of the kids. >> Right! (laughs) >> (laughs) My kids are young, six and four, and I definitely needed help over the last few years. It takes mentors, it takes other people that you look up to, who've gone through all of those same challenges and can, you know, advise you to sort of continue working in the field. I remember when my kid was born when he was six months old, I was considering quitting. And my husband's like, to be a good role model for your children, you need to continue working. Like, just being a mother is not enough. And so, you know, so that's one. You know, the village that you build around you your supporters, your mentors who keep encouraging you. Sheryl Sandberg said this to me in my second month at Facebook. She said that women drop out of technical fields, they become managers, they become sort of administrative more, in their nature of their work, and her advice was, "Don't do that, Don't stop the technical". And I think that's the other thing I'd say to a lot of women. Technical stuff is hard, but you know, keeping up with that and keeping sort of on top of it actually does help you in the long run. And it's definitely helped me in my career at Facebook. >> I think one of the things, and Hannah and I and Tracy talked about this in the open, and I think you'll agree with us, is the whole saying of you can't be what you can't see, and I like to way, "Well, you can be what you can see". That visibility, the great thing that WiDS did, of having you on the stage as a speaker this morning so people can understand, everyone, like I said, everyone knows Meta, >> Yeah. >> everyone uses Facebook. And so it's important to bring that connection, >> Yeah. >> of how data is driving the experiences, the fact that it's User First, but we need to be able to see women in positions, >> Yes. >> like you, especially with Sheryl stepping down moving on to something else, or people that are like YouTube influencers, that have no idea that the head of YouTube for a very long time, Susan Wojcicki is a woman. >> (laughs) Yes. Who pioneered streaming, and I mean how often do you are you on YouTube every day? >> Yep, every day. >> But we have to be able to see and and raise the profile of these women and learn from them and be inspired, >> Absolutely. >> to keep going and going. I like what I do, I'm making a difference here. >> Yeah, yeah, absolutely. >> And I can be the, the sponsor or the mentor for somebody down the road. >> Absolutely. >> Yeah, and then referring back to what we talked in the beginning, show that data science is so diverse and it doesn't mean if you're like in IT, you're like sitting in your dark room, >> Right. (laughs) >> coding all day, but you know, >> (laughs) Right! >> to show the different facets of this job and >> Right! >> make this appealing to women, >> Yeah. for sure. >> And I said this in my keynote too, you know, one of the things that helped me most is complimenting the data and the techniques and the algorithms with how you work with people, and you know, empathy and alignment building and leadership, strategic thinking. And I think honestly, I think women do a lot of this stuff really well. We know how to work with people and so, you know, I've seen this at Meta for sure, like, you know, all of these skills soft skills, as we call them, go a long way, and like, you know, doing the right things and having a lasting impact. And like I said, women are going to rule the world, you know, in our lifetimes. (laughs) >> Oh, I can't, I can't wait to see that happen. There's some interesting female candidates that are already throwing their hats in the ring for the next presidential election. >> Yes. >> So we'll have to see where that goes. But some of the things that are so interesting to me, here we are in California and Palo Alto, technically Stanford is its own zip code, I believe. And we're in California, we're freaking out because we've gotten so much rain, it's absolutely unprecedented. We need it, we had a massive drought, an extreme drought, technically, for many years. I've got friends that live up in Tahoe, I've been getting pictures this morning of windows that are >> (laughs) that are covered? >> Yes, actually, yes. (Gayatree laughs) That, where windows like second-story windows are covered in snow. >> Yeah. >> Climate change. >> Climate change. >> There's so much that data science is doing to power and power our understanding of climate change whether it's that, or police violence. >> Yeah. (all talk together) >> We had talk today on that it was amazing. >> Yes. So I want more people to know what data science is really facilitating, that impacts all of us, whether you're in a technical role or not. >> And data wins arguments. >> Yes, I love that! >> I said this is my slide today, like, you know, there's always going to be doubters and naysayers and I mean, but there's hard evidence, there's hard data like, yeah. In all of these fields, I mean the data that climate change, the data science that we have done in the environmental and climate change areas and medical, and you know, medicine professions just so much, so much more opportunity, and like, how much we can learn more about the world. >> Yeah. >> Yeah, it's a pretty exciting time to be a data scientist. >> I feel like, we're just scratching the surface. >> Yeah. >> With the potential and the global impact that we can make with data science. Gayatree, it's been so great having you on theCUBE, thank you. >> Right, >> Thank you so much, Gayatree. >> So much, I love, >> Thank you. >> I'm going to take Data WiD's arguments into my personal life. (Gayatree laughs) I was actually just, just a quick anecdote, funny story. I was listening to the radio this morning and there was a commercial from an insurance company and I guess the joke is, it's an argument between two spouses, and the the voiceover comes in and says, "Let's watch a replay". I'm like, if only they, then they got the data that helped the woman win the argument. (laughs) >> (laughs) I will warn you it doesn't always help with arguments I have with my husband. (laughs) >> Okay, I'm going to keep it in the middle of my mind. >> Yes! >> Gayatree, thank you so much. >> Thank you so much, >> for sharing, >> Thank you both for the opportunity. >> And being a great female that we can look up to, we really appreciate your insights >> Oh, likewise. >> and your time. >> Thank you. >> All right, for our guest, for Hannah Freitag, I'm Lisa Martin, live at Stanford University covering "Women in Data Science '23". Stick around, our next guest joins us in just a minute. (upbeat music) I have been in the software and technology industry for over 12 years now, so I've had the opportunity as a marketer to really understand and interact with customers across the entire buyer's journey. Hi, I'm Lisa Martin and I'm a host of theCUBE. (upbeat music) Being a host on theCUBE has been a dream of mine for the last few years. I had the opportunity to meet Jeff and Dave and John at EMC World a few years ago and got the courage up to say, "Hey, I'm really interested in this. I love talking with customers, gimme a shot, let me come into the studio and do an interview and see if we can work together". I think where I really impact theCUBE is being a female in technology. We interview a lot of females in tech, we do a lot of women in technology events and one of the things I.

(bright upbeat music) >> Hello and welcome to theCUBE's coverage of International Women's Day. I'm your host, John Furrier here in Palo Alto, California Studio and remoting is a great guest CUBE alumni, co-founder, technical co-founder and she's also the VP of Product at Platform9 Systems. It's a company pioneering Kubernetes infrastructure, been doing it for a long, long time. Madhura Maskasky, thanks for coming on theCUBE. Appreciate you. Thanks for coming on. >> Thank you for having me. Always exciting. >> So I always... I love interviewing you for many reasons. One, you're super smart, but also you're a co-founder, a technical co-founder, so entrepreneur, VP of product. It's hard to do startups. (John laughs) Okay, so everyone who started a company knows how hard it is. It really is and the rewarding too when you're successful. So I want to get your thoughts on what's it like being an entrepreneur, women in tech, some things you've done along the way. Let's get started. How did you get into your career in tech and what made you want to start a company? >> Yeah, so , you know, I got into tech long, long before I decided to start a company. And back when I got in tech it was very clear to me as a direction for my career that I'm never going to start a business. I was very explicit about that because my father was an entrepreneur and I'd seen how rough the journey can be. And then my brother was also and is an entrepreneur. And I think with both of them I'd seen the ups and downs and I had decided to myself and shared with my family that I really want a very well-structured sort of job at a large company type of path for my career. I think the tech path, tech was interesting to me, not because I was interested in programming, et cetera at that time, to be honest. When I picked computer science as a major for myself, it was because most of what you would consider, I guess most of the cool students were picking that as a major, let's just say that. And it sounded very interesting and cool. A lot of people were doing it and that was sort of the top, top choice for people and I decided to follow along. But I did discover after I picked computer science as my major, I remember when I started learning C++ the first time when I got exposure to it, it was just like a light bulb clicking in my head. I just absolutely loved the language, the lower level nature, the power of it, and what you can do with it, the algorithms. So I think it ended up being a really good fit for me. >> Yeah, so it clicked for you. You tried it, it was all the cool kids were doing it. I mean, I can relate, I did the same thing. Next big thing is computer science, you got to be in there, got to be smart. And then you get hooked on it. >> Yeah, exactly. >> What was the next level? Did you find any blockers in your way? Obviously male dominated, it must have been a lot of... How many females were in your class? What was the ratio at that time? >> Yeah, so the ratio was was pretty, pretty, I would say bleak when it comes to women to men. I think computer science at that time was still probably better compared to some of the other majors like mechanical engineering where I remember I had one friend, she was the single girl in an entire class of about at least 120, 130 students or so. So ratio was better for us. I think there were maybe 20, 25 girls in our class. It was a large class and maybe the number of men were maybe three X or four X number of women. So relatively better. Yeah. >> How about the job when you got into the structured big company? How did that go? >> Yeah, so, you know, I think that was a pretty smooth path I would say after, you know, you graduated from undergrad to grad school and then when I got into Oracle first and VMware, I think both companies had the ratios were still, you know, pretty off. And I think they still are to a very large extent in this industry, but I think this industry in my experience does a fantastic job of, you know, bringing everybody and kind of embracing them and treating them at the same level. That was definitely my experience. And so that makes it very easy for self-confidence, for setting up a path for yourself to thrive. So that was it. >> Okay, so you got an undergraduate degree, okay, in computer science and a master's from Stanford in databases and distributed systems. >> That's right. >> So two degrees. Was that part of your pathway or you just decided, "I want to go right into school?" Did it go right after each other? How did that work out? >> Yeah, so when I went into school, undergrad there was no special major and I didn't quite know if I liked a particular subject or set of subjects or not. Even through grad school, first year it wasn't clear to me, but I think in second year I did start realizing that in general I was a fan of backend systems. I was never a front-end person. The backend distributed systems really were of interest to me because there's a lot of complex problems to solve, and especially databases and large scale distributed systems design in the context of database systems, you know, really started becoming a topic of interest for me. And I think luckily enough at Stanford there were just fantastic professors like Mendel Rosenblum who offered operating system class there, then started VMware and later on I was able to join the company and I took his class while at school and it was one of the most fantastic classes I've ever taken. So they really had and probably I think still do a fantastic curriculum when it comes to distributor systems. And I think that probably helped stoke that interest. >> How do you talk to the younger girls out there in elementary school and through? What's the advice as they start to get into computer science, which is changing and still evolving? There's backend, there's front-end, there's AI, there's data science, there's no code, low code, there's cloud. What's your advice when they say what's the playbook? >> Yeah, so I think two things I always say, and I share this with anybody who's looking to get into computer science or engineering for that matter, right? I think one is that it's, you know, it's important to not worry about what that end specialization's going to be, whether it's AI or databases or backend or front-end. It does naturally evolve and you lend yourself to a path where you will understand, you know, which systems, which aspect you like better. But it's very critical to start with getting the fundamentals well, right? Meaning all of the key coursework around algorithm, systems design, architecture, networking, operating system. I think it is just so crucial to understand those well, even though at times you make question is this ever going to be relevant and useful to me later on in my career? It really does end up helping in ways beyond, you know, you can describe. It makes you a much better engineer. So I think that is the most important aspect of, you know, I would think any engineering stream, but definitely true for computer science. Because there's also been a trend more recently, I think, which I'm not a big fan of, of sort of limited scoped learning, which is you decide early on that you're going to be, let's say a front-end engineer, which is fine, you know. Understanding that is great, but if you... I don't think is ideal to let that limit the scope of your learning when you are an undergrad phrase or grad school. Because later on it comes back to sort of bite you in terms of you not being able to completely understand how the systems work. >> It's a systems kind of thinking. You got to have that mindset of, especially now with cloud, you got distributed systems paradigm going to the edge. You got 5G, Mobile World Congress recently happened, you got now all kinds of IOT devices out there, IP of devices at the edge. Distributed computing is only getting more distributed. >> That's right. Yeah, that's exactly right. But the other thing is also happens... That happens in computer science is that the abstraction layers keep raising things up and up and up. Where even if you're operating at a language like Java, which you know, during some of my times of programming there was a period when it was popular, it already abstracts you so far away from the underlying system. So it can become very easier if you're doing, you know, Java script or UI programming that you really have no understanding of what's happening behind the scenes. And I think that can be pretty difficult. >> Yeah. It's easy to lean in and rely too heavily on the abstractions. I want to get your thoughts on blockers. In your career, have you had situations where it's like, "Oh, you're a woman, okay seat at the table, sit on the side." Or maybe people misunderstood your role. How did you deal with that? Did you have any of that? >> Yeah. So, you know, I think... So there's something really kind of personal to me, which I like to share a few times, which I think I believe in pretty strongly. And which is for me, sort of my personal growth began at a very early phase because my dad and he passed away in 2012, but throughout the time when I was growing up, I was his special little girl. And every little thing that I did could be a simple test. You know, not very meaningful but the genuine pride and pleasure that he felt out of me getting great scores in those tests sort of et cetera, and that I could see that in him, and then I wanted to please him. And through him, I think I build that confidence in myself that I am good at things and I can do good. And I think that just set the building blocks for me for the rest of my life, right? So, I believe very strongly that, you know, yes, there are occasions of unfair treatment and et cetera, but for the most part, it comes from within. And if you are able to be a confident person who is kind of leveled and understands and believes in your capabilities, then for the most part, the right things happen around you. So, I believe very strongly in that kind of grounding and in finding a source to get that for yourself. And I think that many women suffer from the biggest challenge, which is not having enough self-confidence. And I've even, you know, with everything that I said, I've myself felt that, experienced that a few times. And then there's a methodical way to get around it. There's processes to, you know, explain to yourself that that's actually not true. That's a fake feeling. So, you know, I think that is the most important aspect for women. >> I love that. Get the confidence. Find the source for the confidence. We've also been hearing about curiosity and building, you mentioned engineering earlier, love that term. Engineering something, like building something. Curiosity, engineering, confidence. This brings me to my next question for you. What do you think the key skills and qualities are needed to succeed in a technical role? And how do you develop to maintain those skills over time? >> Yeah, so I think that it is so critical that you love that technology that you are part of. It is just so important. I mean, I remember as an example, at one point with one of my buddies before we started Platform9, one of my buddies, he's also a fantastic computer scientists from VMware and he loves video games. And so he said, "Hey, why don't we try to, you know, hack up a video game and see if we can take it somewhere?" And so, it sounded cool to me. And then so we started doing things, but you know, something I realized very quickly is that I as a person, I absolutely hate video games. I've never liked them. I don't think that's ever going to change. And so I was miserable. You know, I was trying to understand what's going on, how to build these systems, but I was not enjoying it. So, I'm glad that I decided to not pursue that. So it is just so important that you enjoy whatever aspect of technology that you decide to associate yourself with. I think that takes away 80, 90% of the work. And then I think it's important to inculcate a level of discipline that you are not going to get sort of... You're not going to get jaded or, you know, continue with happy path when doing the same things over and over again, but you're not necessarily challenging yourself, or pushing yourself, or putting yourself in uncomfortable situation. I think a combination of those typically I think works pretty well in any technical career. >> That's a great advice there. I think trying things when you're younger, or even just for play to understand whether you abandon that path is just as important as finding a good path because at least you know that skews the value in favor of the choices. Kind of like math probability. So, great call out there. So I have to ask you the next question, which is, how do you keep up to date given all the changes? You're in the middle of a world where you've seen personal change in the past 10 years from OpenStack to now. Remember those days when I first interviewed you at OpenStack, I think it was 2012 or something like that. Maybe 10 years ago. So much changed. How do you keep up with technologies in your field and resources that you rely on for personal development? >> Yeah, so I think when it comes to, you know, the field and what we are doing for example, I think one of the most important aspect and you know I am product manager and this is something I insist that all the other product managers in our team also do, is that you have to spend 50% of your time talking to prospects, customers, leads, and through those conversations they do a huge favor to you in that they make you aware of the other things that they're keeping an eye on as long as you're doing the right job of asking the right questions and not just, you know, listening in. So I think that to me ends up being one of the biggest sources where you get tidbits of information, new things, et cetera, and then you pursue. To me, that has worked to be a very effective source. And then the second is, you know, reading and keeping up with all of the publications. You guys, you know, create a lot of great material, you interview a lot of people, making sure you are watching those for us you know, and see there's a ton of activities, new projects keeps coming along every few months. So keeping up with that, listening to podcasts around those topics, all of that helps. But I think the first one I think goes in a big way in terms of being aware of what matters to your customers. >> Awesome. Let me ask you a question. What's the most rewarding aspect of your job right now? >> So, I think there are many. So I think I love... I've come to realize that I love, you know, the high that you get out of being an entrepreneur independent of, you know, there's... In terms of success and failure, there's always ups and downs as an entrepreneur, right? But there is this... There's something really alluring about being able to, you know, define, you know, path of your products and in a way that can potentially impact, you know, a number of companies that'll consume your products, employees that work with you. So that is, I think to me, always been the most satisfying path, is what kept me going. I think that is probably first and foremost. And then the projects. You know, there's always new exciting things that we are working on. Even just today, there are certain projects we are working on that I'm super excited about. So I think it's those two things. >> So now we didn't get into how you started. You said you didn't want to do a startup and you got the big company. Your dad, your brother were entrepreneurs. How did you get into it? >> Yeah, so, you know, it was kind of surprising to me as well, but I think I reached a point of VMware after spending about eight years or so where I definitely packed hold and I could have pushed myself by switching to a completely different company or a different organization within VMware. And I was trying all of those paths, interviewed at different companies, et cetera, but nothing felt different enough. And then I think I was very, very fortunate in that my co-founders, Sirish Raghuram, Roopak Parikh, you know, Bich, you've met them, they were kind of all at the same journey in their careers independently at the same time. And so we would all eat lunch together at VMware 'cause we were on the same team and then we just started brainstorming on different ideas during lunchtime. And that's kind of how... And we did that almost for a year. So by the time that the year long period went by, at the end it felt like the most logical, natural next step to leave our job and to, you know, to start off something together. But I think I wouldn't have done that had it not been for my co-founders. >> So you had comfort with the team as you knew each other at VMware, but you were kind of a little early, (laughing) you had a vision. It's kind of playing out now. How do you feel right now as the wave is hitting? Distributed computing, microservices, Kubernetes, I mean, stuff you guys did and were doing. I mean, it didn't play out exactly, but directionally you were right on the line there. How do you feel? >> Yeah. You know, I think that's kind of the challenge and the fun part with the startup journey, right? Which is you can never predict how things are going to go. When we kicked off we thought that OpenStack is going to really take over infrastructure management space and things kind of went differently, but things are going that way now with Kubernetes and distributed infrastructure. And so I think it's been interesting and in every path that you take that does end up not being successful teaches you so much more, right? So I think it's been a very interesting journey. >> Yeah, and I think the cloud, certainly AWS hit that growth right at 2013 through '17, kind of sucked all the oxygen out. But now as it reverts back to this abstraction layer essentially makes things look like private clouds, but they're just essentially DevOps. It's cloud operations, kind of the same thing. >> Yeah, absolutely. And then with the edge things are becoming way more distributed where having a single large cloud provider is becoming even less relevant in that space and having kind of the central SaaS based management model, which is what we pioneered, like you said, we were ahead of the game at that time, is becoming sort of the most obvious choice now. >> Now you look back at your role at Stanford, distributed systems, again, they have world class program there, neural networks, you name it. It's really, really awesome. As well as Cal Berkeley, there was in debates with each other, who's better? But that's a separate interview. Now you got the edge, what are some of the distributed computing challenges right now with now the distributed edge coming online, industrial 5G, data? What do you see as some of the key areas to solve from a problem statement standpoint with edge and as cloud goes on-premises to essentially data center at the edge, apps coming over the top AI enabled. What's your take on that? >> Yeah, so I think... And there's different flavors of edge and the one that we focus on is, you know, what we call thick edge, which is you have this problem of managing thousands of as we call it micro data centers, rather than managing maybe few tens or hundreds of large data centers where the problem just completely shifts on its head, right? And I think it is still an unsolved problem today where whether you are a retailer or a telecommunications vendor, et cetera, managing your footprints of tens of thousands of stores as a retailer is solved in a very archaic way today because the tool set, the traditional management tooling that's designed to manage, let's say your data centers is not quite, you know, it gets retrofitted to manage these environments and it's kind of (indistinct), you know, round hole kind of situation. So I think the top most challenges are being able to manage this large footprint of micro data centers in the most effective way, right? Where you have latency solved, you have the issue of a small footprint of resources at thousands of locations, and how do you fit in your containerized or virtualized or other workloads in the most effective way? To have that solved, you know, you need to have the security aspects around these environments. So there's a number of challenges that kind of go hand-in-hand, like what is the most effective storage which, you know, can still be deployed in that compact environment? And then cost becomes a related point. >> Costs are huge 'cause if you move data, you're going to have cost. If you move compute, it's not as much. If you have an operating system concept, is the data and state or stateless? These are huge problems. This is an operating system, don't you think? >> Yeah, yeah, absolutely. It's a distributed operating system where it's multiple layers, you know, of ways of solving that problem just in the context of data like you said having an intermediate caching layer so that you know, you still do just in time processing at those edge locations and then send some data back and that's where you can incorporate some AI or other technologies, et cetera. So, you know, just data itself is a multi-layer problem there. >> Well, it's great to have you on this program. Advice final question for you, for the folks watching technical degrees, most people are finding out in elementary school, in middle school, a lot more robotics programs, a lot more tech exposure, you know, not just in Silicon Valley, but all around, you're starting to see that. What's your advice for young girls and people who are getting either coming into the workforce re-skilled as they get enter, it's easy to enter now as they stay in and how do they stay in? What's your advice? >> Yeah, so, you know, I think it's the same goal. I have two little daughters and it's the same principle I try to follow with them, which is I want to give them as much exposure as possible without me having any predefined ideas about what you know, they should pursue. But it's I think that exposure that you need to find for yourself one way or the other, because you really never know. Like, you know, my husband landed into computer science through a very, very meandering path, and then he discovered later in his career that it's the absolute calling for him. It's something he's very good at, right? But so... You know, it's... You know, the reason why he thinks he didn't pick that path early is because he didn't quite have that exposure. So it's that exposure to various things, even things you think that you may not be interested in is the most important aspect. And then things just naturally lend themselves. >> Find your calling, superpower, strengths. Know what you don't want to do. (John chuckles) >> Yeah, exactly. >> Great advice. Thank you so much for coming on and contributing to our program for International Women's Day. Great to see you in this context. We'll see you on theCUBE. We'll talk more about Platform9 when we go KubeCon or some other time. But thank you for sharing your personal perspective and experiences for our audience. Thank you. >> Fantastic. Thanks for having me, John. Always great. >> This is theCUBE's coverage of International Women's Day, I'm John Furrier. We're talking to the leaders in the industry, from developers to the boardroom and everything in between and getting the stories out there making an impact. Thanks for watching. (bright upbeat music)

(upbeat intro music) >> Hello everyone. Welcome to theCUBE's coverage of International Women's Day. I'm your host, John Furrier, here in Palo Alto, California. Got a special remote guest coming in. Teresa Carlson, President and Chief Commercial Officer at Flexport, theCUBE alumni, one of the first, let me go back to 2013, Teresa, former AWS. Great to see you. Thanks for coming on. >> Oh my gosh, almost 10 years. That is unbelievable. It's hard to believe so many years of theCUBE. I love it. >> It's been such a great honor to interview you and follow your career. You've had quite the impressive run, executive level woman in tech. You've done such an amazing job, not only in your career, but also helping other women. So I want to give you props to that before we get started. Thank you. >> Thank you, John. I, it's my, it's been my honor and privilege. >> Let's talk about Flexport. Tell us about your new role there and what it's all about. >> Well, I love it. I'm back working with another Amazonian, Dave Clark, who is our CEO of Flexport, and we are about 3,000 people strong globally in over 90 countries. We actually even have, we're represented in over 160 cities and with local governments and places around the world, which I think is super exciting. We have over 100 network partners and growing, and we are about empowering the global supply chain and trade and doing it in a very disruptive way with the use of platform technology that allows our customers to really have visibility and insight to what's going on. And it's a lot of fun. I'm learning new things, but there's a lot of technology in this as well, so I feel right at home. >> You quite have a knack from mastering growth, technology, and building out companies. So congratulations, and scaling them up too with the systems and processes. So I want to get into that. Let's get into your personal background. Then I want to get into the work you've done and are doing for empowering women in tech. What was your journey about, how did it all start? Like, I know you had a, you know, bumped into it, you went Microsoft, AWS. Take us through your career, how you got into tech, how it all happened. >> Well, I do like to give a shout out, John, to my roots and heritage, which was a speech and language pathologist. So I did start out in healthcare right out of, you know, university. I had an undergraduate and a master's degree. And I do tell everyone now, looking back at my career, I think it was super helpful for me because I learned a lot about human communication, and it has done me very well over the years to really try to understand what environments I'm in and what kind of individuals around the world culturally. So I'm really blessed that I had that opportunity to work in healthcare, and by the way, a shout out to all of our healthcare workers that has helped us get through almost three years of COVID and flu and neurovirus and everything else. So started out there and then kind of almost accidentally got into technology. My first small company I worked for was a company called Keyfile Corporation, which did workflow and document management out of Nashua, New Hampshire. And they were a Microsoft goal partner. And that is actually how I got into big tech world. We ran on exchange, for everybody who knows that term exchange, and we were a large small partner, but large in the world of exchange. And those were the days when you would, the late nineties, you would go and be in the same room with Bill Gates and Steve Ballmer. And I really fell in love with Microsoft back then. I thought to myself, wow, if I could work for a big tech company, I got to hear Bill on stage about saving, he would talk about saving the world. And guess what my next step was? I actually got a job at Microsoft, took a pay cut and a job downgrade. I tell this story all the time. Took like three downgrades in my role. I had been a SVP and went to a manager, and it's one of the best moves I ever made. And I shared that because I really didn't know the world of big tech, and I had to start from the ground up and relearn it. I did that, I just really loved that job. I was at Microsoft from 2000 to 2010, where I eventually ran all of the U.S. federal government business, which was a multi-billion dollar business. And then I had the great privilege of meeting an amazing man, Andy Jassy, who I thought was just unbelievable in his insights and knowledge and openness to understanding new markets. And we talked about government and how government needed the same great technology as every startup. And that led to me going to work for Andy in 2010 and starting up our worldwide public sector business. And I pinch myself some days because we went from two people, no offices, to the time I left we had over 10,000 people, billions in revenue, and 172 countries and had done really amazing work. I think changing the way public sector and government globally really thought about their use of technology and Cloud computing in general. And that kind of has been my career. You know, I was there till 2020, 21 and then did a small stint at Splunk, a small stint back at Microsoft doing a couple projects for Microsoft with CEO, Satya Nadella, who is also an another amazing CEO and leader. And then Dave called me, and I'm at Flexport, so I couldn't be more honored, John. I've just had such an amazing career working with amazing individuals. >> Yeah, I got to say the Amazon One well-documented, certainly by theCUBE and our coverage. We watched you rise and scale that thing. And like I said at a time, this will when we look back as a historic run because of the build out. I mean as a zero to massive billions at a historic time where government was transforming, I would say Microsoft had a good run there with Fed, but it was already established stuff. Federal business was like, you know, blocking and tackling. The Amazon was pure build out. So I have to ask you, what was your big learnings? Because one, you're a Seattle big tech company kind of entrepreneurial in the sense of you got, here's some working capital seed finance and go build that thing, and you're in DC and you're a woman. What did you learn? >> I learned that you really have to have a lot of grit. You, my mom and dad, these are kind of more southern roots words, but stick with itness, you know. you can't give up and no's not in your vocabulary. I found no is just another way to get to yes. That you have to figure out what are all the questions people are going to ask you. I learned to be very patient, and I think one of the things John, for us was our secret sauce was we said to ourselves, if we're going to do something super transformative and truly disruptive, like Cloud computing, which the government really had not utilized, we had to be patient. We had to answer all their questions, and we could not judge in any way what they were thinking because if we couldn't answer all those questions and prove out the capabilities of Cloud computing, we were not going to accomplish our goals. And I do give so much credit to all my colleagues there from everybody like Steve Schmidt who was there, who's still there, who's the CISO, and Charlie Bell and Peter DeSantis and the entire team there that just really helped build that business out. Without them, you know, we would've just, it was a team effort. And I think that's the thing I loved about it was it was not just sales, it was product, it was development, it was data center operations, it was legal, finance. Everybody really worked as a team and we were on board that we had to make a lot of changes in the government relations team. We had to go into Capitol Hill. We had to talk to them about the changes that were required and really get them to understand why Cloud computing could be such a transformative game changer for the way government operates globally. >> Well, I think the whole world and the tech world can appreciate your work and thank you later because you broke down those walls asking those questions. So great stuff. Now I got to say, you're in kind of a similar role at Flexport. Again, transformative supply chain, not new. Computing wasn't new when before Cloud came. Supply chain, not a new concept, is undergoing radical change and transformation. Online, software supply chain, hardware supply chain, supply chain in general, shipping. This is a big part of our economy and how life is working. Similar kind of thing going on, build out, growth, scale. >> It is, it's very much like that, John, I would say, it's, it's kind of a, the model with freight forwarding and supply chain is fairly, it's not as, there's a lot of technology utilized in this global supply chain world, but it's not integrated. You don't have a common operating picture of what you're doing in your global supply chain. You don't have easy access to the information and visibility. And that's really, you know, I was at a conference last week in LA, and it was, the themes were so similar about transparency, access to data and information, being able to act quickly, drive change, know what was happening. I was like, wow, this sounds familiar. Data, AI, machine learning, visibility, common operating picture. So it is very much the same kind of themes that you heard even with government. I do believe it's an industry that is going through transformation and Flexport has been a group that's come in and said, look, we have this amazing idea, number one to give access to everyone. We want every small business to every large business to every government around the world to be able to trade their goods, think about supply chain logistics in a very different way with information they need and want at their fingertips. So that's kind of thing one, but to apply that technology in a way that's very usable across all systems from an integration perspective. So it's kind of exciting. I used to tell this story years ago, John, and I don't think Michael Dell would mind that I tell this story. One of our first customers when I was at Keyfile Corporation was we did workflow and document management, and Dell was one of our customers. And I remember going out to visit them, and they had runners and they would run around, you know, they would run around the floor and do their orders, right, to get all those computers out the door. And when I think of global trade, in my mind I still see runners, you know, running around and I think that's moved to a very digital, right, world that all this stuff, you don't need people doing this. You have machines doing this now, and you have access to the information, and you know, we still have issues resulting from COVID where we have either an under-abundance or an over-abundance of our supply chain. We still have clogs in our shipping, in the shipping yards around the world. So we, and the ports, so we need to also, we still have some clearing to do. And that's the reason technology is important and will continue to be very important in this world of global trade. >> Yeah, great, great impact for change. I got to ask you about Flexport's inclusion, diversity, and equity programs. What do you got going on there? That's been a big conversation in the industry around keeping a focus on not making one way more than the other, but clearly every company, if they don't have a strong program, will be at a disadvantage. That's well reported by McKinsey and other top consultants, diverse workforces, inclusive, equitable, all perform better. What's Flexport's strategy and how are you guys supporting that in the workplace? >> Well, let me just start by saying really at the core of who I am, since the day I've started understanding that as an individual and a female leader, that I could have an impact. That the words I used, the actions I took, the information that I pulled together and had knowledge of could be meaningful. And I think each and every one of us is responsible to do what we can to make our workplace and the world a more diverse and inclusive place to live and work. And I've always enjoyed kind of the thought that, that I could help empower women around the world in the tech industry. Now I'm hoping to do my little part, John, in that in the supply chain and global trade business. And I would tell you at Flexport we have some amazing women. I'm so excited to get to know all. I've not been there that long yet, but I'm getting to know we have some, we have a very diverse leadership team between men and women at Dave's level. I have some unbelievable women on my team directly that I'm getting to know more, and I'm so impressed with what they're doing. And this is a very, you know, while this industry is different than the world I live in day to day, it's also has a lot of common themes to it. So, you know, for us, we're trying to approach every day by saying, let's make sure both our interviewing cycles, the jobs we feel, how we recruit people, how we put people out there on the platforms, that we have diversity and inclusion and all of that every day. And I can tell you from the top, from Dave and all of our leaders, we just had an offsite and we had a big conversation about this is something. It's a drum beat that we have to think about and live by every day and really check ourselves on a regular basis. But I do think there's so much more room for women in the world to do great things. And one of the, one of the areas, as you know very well, we lost a lot of women during COVID, who just left the workforce again. So we kind of went back unfortunately. So we have to now move forward and make sure that we are giving women the opportunity to have great jobs, have the flexibility they need as they build a family, and have a workplace environment that is trusted for them to come into every day. >> There's now clear visibility, at least in today's world, not withstanding some of the setbacks from COVID, that a young girl can look out in a company and see a path from entry level to the boardroom. That's a big change. A lot than even going back 10, 15, 20 years ago. What's your advice to the folks out there that are paying it forward? You see a lot of executive leaderships have a seat at the table. The board still underrepresented by most numbers, but at least you have now kind of this solidarity at the top, but a lot of people doing a lot more now than I've seen at the next levels down. So now you have this leveled approach. Is that something that you're seeing more of? And credit compare and contrast that to 20 years ago when you were, you know, rising through the ranks? What's different? >> Well, one of the main things, and I honestly do not think about it too much, but there were really no women. There were none. When I showed up in the meetings, I literally, it was me or not me at the table, but at the seat behind the table. The women just weren't in the room, and there were so many more barriers that we had to push through, and that has changed a lot. I mean globally that has changed a lot in the U.S. You know, if you look at just our U.S. House of Representatives and our U.S. Senate, we now have the increasing number of women. Even at leadership levels, you're seeing that change. You have a lot more women on boards than we ever thought we would ever represent. While we are not there, more female CEOs that I get an opportunity to see and talk to. Women starting companies, they do not see the barriers. And I will share, John, globally in the U.S. one of the things that I still see that we have that many other countries don't have, which I'm very proud of, women in the U.S. have a spirit about them that they just don't see the barriers in the same way. They believe that they can accomplish anything. I have two sons, I don't have daughters. I have nieces, and I'm hoping someday to have granddaughters. But I know that a lot of my friends who have granddaughters today talk about the boldness, the fortitude, that they believe that there's nothing they can't accomplish. And I think that's what what we have to instill in every little girl out there, that they can accomplish anything they want to. The world is theirs, and we need to not just do that in the U.S., but around the world. And it was always the thing that struck me when I did all my travels at AWS and now with Flexport, I'm traveling again quite a bit, is just the differences you see in the cultures around the world. And I remember even in the Middle East, how I started seeing it change. You've heard me talk a lot on this program about the fact in both Saudi and Bahrain, over 60% of the tech workers were females and most of them held the the hardest jobs, the security, the architecture, the engineering. But many of them did not hold leadership roles. And that is what we've got to change too. To your point, the middle, we want it to get bigger, but the top, we need to get bigger. We need to make sure women globally have opportunities to hold the most precious leadership roles and demonstrate their capabilities at the very top. But that's changed. And I would say the biggest difference is when we show up, we're actually evaluated properly for those kind of roles. We have a ways to go. But again, that part is really changing. >> Can you share, Teresa, first of all, that's great work you've done and I wan to give you props of that as well and all the work you do. I know you champion a lot of, you know, causes in in this area. One question that comes up a lot, I would love to get your opinion 'cause I think you can contribute heavily here is mentoring and sponsorship is huge, comes up all the time. What advice would you share to folks out there who were, I won't say apprehensive, but maybe nervous about how to do the networking and sponsorship and mentoring? It's not just mentoring, it's sponsorship too. What's your best practice? What advice would you give for the best way to handle that? >> Well yeah, and for the women out there, I would say on the mentorship side, I still see mentorship. Like, I don't think you can ever stop having mentorship. And I like to look at my mentors in different parts of my life because if you want to be a well-rounded person, you may have parts of your life every day that you think I'm doing a great job here and I definitely would like to do better there. Whether it's your spiritual life, your physical life, your work life, you know, your leisure life. But I mean there's, and there's parts of my leadership world that I still seek advice from as I try to do new things even in this world. And I tried some new things in between roles. I went out and asked the people that I respected the most. So I just would say for sure have different mentorships and don't be afraid to have that diversity. But if you have mentorships, the second important thing is show up with a real agenda and questions. Don't waste people's time. I'm very sensitive today. If you're, if you want a mentor, you show up and you use your time super effectively and be prepared for that. Sponsorship is a very different thing. And I don't believe we actually do that still in companies. We worked, thank goodness for my great HR team. When I was at AWS, we worked on a few sponsorship programs where for diversity in general, where we would nominate individuals in the company that we felt that weren't, that had a lot of opportunity for growth, but they just weren't getting a seat at the table. And we brought 'em to the table. And we actually kind of had a Chatham House rules where when they came into the meetings, they had a sponsor, not a mentor. They had a sponsor that was with them the full 18 months of this program. We would bring 'em into executive meetings. They would read docs, they could ask questions. We wanted them to be able to open up and ask crazy questions without, you know, feeling wow, I just couldn't answer this question in a normal environment or setting. And then we tried to make sure once they got through the program that we found jobs and support and other special projects that they could go do. But they still had that sponsor and that group of individuals that they'd gone through the program with, John, that they could keep going back to. And I remember sitting there and they asked me what I wanted to get out of the program, and I said two things. I want you to leave this program and say to yourself, I would've never had that experience if I hadn't gone through this program. I learned so much in 18 months. It would probably taken me five years to learn. And that it helped them in their career. The second thing I told them is I wanted them to go out and recruit individuals that look like them. I said, we need diversity, and unless you all feel that we are in an inclusive environment sponsoring all types of individuals to be part of this company, we're not going to get the job done. And they said, okay. And you know, but it was really one, it was very much about them. That we took a group of individuals that had high potential and a very diverse with diverse backgrounds, held 'em up, taught 'em things that gave them access. And two, selfishly I said, I want more of you in my business. Please help me. And I think those kind of things are helpful, and you have to be thoughtful about these kind of programs. And to me that's more sponsorship. I still have people reach out to me from years ago, you know, Microsoft saying, you were so good with me, can you give me a reference now? Can you talk to me about what I should be doing? And I try to, I'm not pray 100%, some things pray fall through the cracks, but I always try to make the time to talk to those individuals because for me, I am where I am today because I got some of the best advice from people like Don Byrne and Linda Zecker and Andy Jassy, who were very honest and upfront with me about my career. >> Awesome. Well, you got a passion for empowering women in tech, paying it forward, but you're quite accomplished and that's why we're so glad to have you on the program here. President and Chief Commercial Officer at Flexport. Obviously storied career and your other jobs, specifically Amazon I think, is historic in my mind. This next chapter looks like it's looking good right now. Final question for you, for the few minutes you have left. Tell us what you're up to at Flexport. What's your goals as President, Chief Commercial Officer? What are you trying to accomplish? Share a little bit, what's on your mind with your current job? >> Well, you kind of said it earlier. I think if I look at my own superpowers, I love customers, I love partners. I get my energy, John, from those interactions. So one is to come in and really help us build even a better world class enterprise global sales and marketing team. Really listen to our customers, think about how we interact with them, build the best executive programs we can, think about new ways that we can offer services to them and create new services. One of my favorite things about my career is I think if you're a business leader, it's your job to come back around and tell your product group and your services org what you're hearing from customers. That's how you can be so much more impactful, that you listen, you learn, and you deliver. So that's one big job. The second job for me, which I am so excited about, is that I have an amazing group called flexport.org under me. And flexport.org is doing amazing things around the world to help those in need. We just announced this new funding program for Tech for Refugees, which brings assistance to millions of people in Ukraine, Pakistan, the horn of Africa, and those who are affected by earthquakes. We just took supplies into Turkey and Syria, and Flexport, recently in fact, just did sent three air shipments to Turkey and Syria for these. And I think we did over a hundred trekking shipments to get earthquake relief. And as you can imagine, it was not easy to get into Syria. But you know, we're very active in the Ukraine, and we are, our goal for flexport.org, John, is to continue to work with our commercial customers and team up with them when they're trying to get supplies in to do that in a very cost effective, easy way, as quickly as we can. So that not-for-profit side of me that I'm so, I'm so happy. And you know, Ryan Peterson, who was our founder, this was his brainchild, and he's really taken this to the next level. So I'm honored to be able to pick that up and look for new ways to have impact around the world. And you know, I've always found that I think if you do things right with a company, you can have a beautiful combination of commercial-ity and giving. And I think Flexport does it in such an amazing and unique way. >> Well, the impact that they have with their system and their technology with logistics and shipping and supply chain is a channel for societal change. And I think that's a huge gift that you have that under your purview. So looking forward to finding out more about flexport.org. I can only imagine all the exciting things around sustainability, and we just had Mobile World Congress for Big Cube Broadcast, 5Gs right around the corner. I'm sure that's going to have a huge impact to your business. >> Well, for sure. And just on gas emissions, that's another thing that we are tracking gas, greenhouse gas emissions. And in fact we've already reduced more than 300,000 tons and supported over 600 organizations doing that. So that's a thing we're also trying to make sure that we're being climate aware and ensuring that we are doing the best job we can at that as well. And that was another thing I was honored to be able to do when we were at AWS, is to really cut out greenhouse gas emissions and really go global with our climate initiatives. >> Well Teresa, it's great to have you on. Security, data, 5G, sustainability, business transformation, AI all coming together to change the game. You're in another hot seat, hot roll, big wave. >> Well, John, it's an honor, and just thank you again for doing this and having women on and really representing us in a big way as we celebrate International Women's Day. >> I really appreciate it, it's super important. And these videos have impact, so we're going to do a lot more. And I appreciate your leadership to the industry and thank you so much for taking the time to contribute to our effort. Thank you, Teresa. >> Thank you. Thanks everybody. >> Teresa Carlson, the President and Chief Commercial Officer of Flexport. I'm John Furrier, host of theCUBE. This is International Women's Day broadcast. Thanks for watching. (upbeat outro music)

(gentle music) >> Hello everyone. Welcome to this CUBE conversation here in Palo Alto, California. I'm John Furrier, host of theCUBE. We got a great remote guest coming in. Joseph Nelson, co-founder and CEO of RoboFlow hot startup in AI, computer vision. Really interesting topic in this wave of AI next gen hitting. Joseph, thanks for coming on this CUBE conversation. >> Thanks for having me. >> Yeah, I love the startup tsunami that's happening here in this wave. RoboFlow, you're in the middle of it. Exciting opportunities, you guys are in the cutting edge. I think computer vision's been talked about more as just as much as the large language models and these foundational models are merging. You're in the middle of it. What's it like right now as a startup and growing in this new wave hitting? >> It's kind of funny, it's, you know, I kind of describe it like sometimes you're in a garden of gnomes. It's like we feel like we've got this giant headstart with hundreds of thousands of people building with computer vision, training their own models, but that's a fraction of what it's going to be in six months, 12 months, 24 months. So, as you described it, a wave is a good way to think about it. And the wave is still building before it gets to its full size. So it's a ton of fun. >> Yeah, I think it's one of the most exciting areas in computer science. I wish I was in my twenties again, because I would be all over this. It's the intersection, there's so many disciplines, right? It's not just tech computer science, it's computer science, it's systems, it's software, it's data. There's so much aperture of things going on around your world. So, I mean, you got to be batting all the students away kind of trying to get hired in there, probably. I can only imagine you're hiring regiment. I'll ask that later, but first talk about what the company is that you're doing. How it's positioned, what's the market you're going after, and what's the origination story? How did you guys get here? How did you just say, hey, want to do this? What was the origination story? What do you do and how did you start the company? >> Yeah, yeah. I'll give you the what we do today and then I'll shift into the origin. RoboFlow builds tools for making the world programmable. Like anything that you see should be read write access if you think about it with a programmer's mind or legible. And computer vision is a technology that enables software to be added to these real world objects that we see. And so any sort of interface, any sort of object, any sort of scene, we can interact with it, we can make it more efficient, we can make it more entertaining by adding the ability for the tools that we use and the software that we write to understand those objects. And at RoboFlow, we've empowered a little over a hundred thousand developers, including those in half the Fortune 100 so far in that mission. Whether that's Walmart understanding the retail in their stores, Cardinal Health understanding the ways that they're helping their patients, or even electric vehicle manufacturers ensuring that they're making the right stuff at the right time. As you mentioned, it's early. Like I think maybe computer vision has touched one, maybe 2% of the whole economy and it'll be like everything in a very short period of time. And so we're focused on enabling that transformation. I think it's it, as far as I think about it, I've been fortunate to start companies before, start, sell these sorts of things. This is the last company I ever wanted to start and I think it will be, should we do it right, the world's largest in riding the wave of bringing together the disparate pieces of that technology. >> What was the motivating point of the formation? Was it, you know, you guys were hanging around? Was there some catalyst? What was the moment where it all kind of came together for you? >> You know what's funny is my co-founder, Brad and I, we were making computer vision apps for making board games more fun to play. So in 2017, Apple released AR kit, augmented reality kit for building augmented reality applications. And Brad and I are both sort of like hacker persona types. We feel like we don't really understand the technology until we build something with it and so we decided that we should make an app that if you point your phone at a Sudoku puzzle, it understands the state of the board and then it kind of magically fills in that experience with all the digits in real time, which totally ruins the game of Sudoku to be clear. But it also just creates this like aha moment of like, oh wow, like the ability for our pocket devices to understand and see the world as good or better than we can is possible. And so, you know, we actually did that as I mentioned in 2017, and the app went viral. It was, you know, top of some subreddits, top of Injure, Reddit, the hacker community as well as Product Hunt really liked it. So it actually won Product Hunt AR app of the year, which was the same year that the Tesla model three won the product of the year. So we joked that we share an award with Elon our shared (indistinct) But frankly, so that was 2017. RoboFlow wasn't incorporated as a business until 2019. And so, you know, when we made Magic Sudoku, I was running a different company at the time, Brad was running a different company at the time, and we kind of just put it out there and were excited by how many people liked it. And we assumed that other curious developers would see this inevitable future of, oh wow, you know. This is much more than just a pedestrian point your phone at a board game. This is everything can be seen and understood and rewritten in a different way. Things like, you know, maybe your fridge. Knowing what ingredients you have and suggesting recipes or auto ordering for you, or we were talking about some retail use cases of automated checkout. Like anything can be seen and observed and we presume that that would kick off a Cambrian explosion of applications. It didn't. So you fast forward to 2019, we said, well we might as well be the guys to start to tackle this sort of problem. And because of our success with board games before, we returned to making more board game solving applications. So we made one that solves Boggle, you know, the four by four word game, we made one that solves chess, you point your phone at a chess board and it understands the state of the board and then can make move recommendations. And each additional board game that we added, we realized that the tooling was really immature. The process of collecting images, knowing which images are actually going to be useful for improving model performance, training those models, deploying those models. And if we really wanted to make the world programmable, developers waiting for us to make an app for their thing of interest is a lot less efficient, less impactful than taking our tool chain and releasing that externally. And so, that's what RoboFlow became. RoboFlow became the internal tools that we used to make these game changing applications readily available. And as you know, when you give developers new tools, they create new billion dollar industries, let alone all sorts of fun hobbyist projects along the way. >> I love that story. Curious, inventive, little radical. Let's break the rules, see how we can push the envelope on the board games. That's how companies get started. It's a great story. I got to ask you, okay, what happens next? Now, okay, you realize this new tooling, but this is like how companies get built. Like they solve their own problem that they had 'cause they realized there's one, but then there has to be a market for it. So you actually guys knew that this was coming around the corner. So okay, you got your hacker mentality, you did that thing, you got the award and now you're like, okay, wow. Were you guys conscious of the wave coming? Was it one of those things where you said, look, if we do this, we solve our own problem, this will be big for everybody. Did you have that moment? Was that in 2019 or was that more of like, it kind of was obvious to you guys? >> Absolutely. I mean Brad puts this pretty effectively where he describes how we lived through the initial internet revolution, but we were kind of too young to really recognize and comprehend what was happening at the time. And then mobile happened and we were working on different companies that were not in the mobile space. And computer vision feels like the wave that we've caught. Like, this is a technology and capability that rewrites how we interact with the world, how everyone will interact with the world. And so we feel we've been kind of lucky this time, right place, right time of every enterprise will have the ability to improve their operations with computer vision. And so we've been very cognizant of the fact that computer vision is one of those groundbreaking technologies that every company will have as a part of their products and services and offerings, and we can provide the tooling to accelerate that future. >> Yeah, and the developer angle, by the way, I love that because I think, you know, as we've been saying in theCUBE all the time, developer's the new defacto standard bodies because what they adopt is pure, you know, meritocracy. And they pick the best. If it's sell service and it's good and it's got open source community around it, its all in. And they'll vote. They'll vote with their code and that is clear. Now I got to ask you, as you look at the market, we were just having this conversation on theCUBE in Barcelona at recent Mobile World Congress, now called MWC, around 5G versus wifi. And the debate was specifically computer vision, like facial recognition. We were talking about how the Cleveland Browns were using facial recognition for people coming into the stadium they were using it for ships in international ports. So the question was 5G versus wifi. My question is what infrastructure or what are the areas that need to be in place to make computer vision work? If you have developers building apps, apps got to run on stuff. So how do you sort that out in your mind? What's your reaction to that? >> A lot of the times when we see applications that need to run in real time and on video, they'll actually run at the edge without internet. And so a lot of our users will actually take their models and run it in a fully offline environment. Now to act on that information, you'll often need to have internet signal at some point 'cause you'll need to know how many people were in the stadium or what shipping crates are in my port at this point in time. You'll need to relay that information somewhere else, which will require connectivity. But actually using the model and creating the insights at the edge does not require internet. I mean we have users that deploy models on underwater submarines just as much as in outer space actually. And those are not very friendly environments to internet, let alone 5g. And so what you do is you use an edge device, like an Nvidia Jetson is common, mobile devices are common. Intel has some strong edge devices, the Movidius family of chips for example. And you use that compute that runs completely offline in real time to process those signals. Now again, what you do with those signals may require connectivity and that becomes a question of the problem you're solving of how soon you need to relay that information to another place. >> So, that's an architectural issue on the infrastructure. If you're a tactical edge war fighter for instance, you might want to have highly available and maybe high availability. I mean, these are words that mean something. You got storage, but it's not at the edge in real time. But you can trickle it back and pull it down. That's management. So that's more of a business by business decision or environment, right? >> That's right, that's right. Yeah. So I mean we can talk through some specifics. So for example, the RoboFlow actually powers the broadcaster that does the tennis ball tracking at Wimbledon. That runs completely at the edge in real time in, you know, technically to track the tennis ball and point the camera, you actually don't need internet. Now they do have internet of course to do the broadcasting and relay the signal and feeds and these sorts of things. And so that's a case where you have both edge deployment of running the model and high availability act on that model. We have other instances where customers will run their models on drones and the drone will go and do a flight and it'll say, you know, this many residential homes are in this given area, or this many cargo containers are in this given shipping yard. Or maybe we saw these environmental considerations of soil erosion along this riverbank. The model in that case can run on the drone during flight without internet, but then you only need internet once the drone lands and you're going to act on that information because for example, if you're doing like a study of soil erosion, you don't need to be real time. You just need to be able to process and make use of that information once the drone finishes its flight. >> Well I can imagine a zillion use cases. I heard of a use case interview at a company that does computer vision to help people see if anyone's jumping the fence on their company. Like, they know what a body looks like climbing a fence and they can spot it. Pretty easy use case compared to probably some of the other things, but this is the horizontal use cases, its so many use cases. So how do you guys talk to the marketplace when you say, hey, we have generative AI for commuter vision. You might know language models that's completely different animal because vision's like the world, right? So you got a lot more to do. What's the difference? How do you explain that to customers? What can I build and what's their reaction? >> Because we're such a developer centric company, developers are usually creative and show you the ways that they want to take advantage of new technologies. I mean, we've had people use things for identifying conveyor belt debris, doing gas leak detection, measuring the size of fish, airplane maintenance. We even had someone that like a hobby use case where they did like a specific sushi identifier. I dunno if you know this, but there's a specific type of whitefish that if you grew up in the western hemisphere and you eat it in the eastern hemisphere, you get very sick. And so there was someone that made an app that tells you if you happen to have that fish in the sushi that you're eating. But security camera analysis, transportation flows, plant disease detection, really, you know, smarter cities. We have people that are doing curb management identifying, and a lot of these use cases, the fantastic thing about building tools for developers is they're a creative bunch and they have these ideas that if you and I sat down for 15 minutes and said, let's guess every way computer vision can be used, we would need weeks to list all the example use cases. >> We'd miss everything. >> And we'd miss. And so having the community show us the ways that they're using computer vision is impactful. Now that said, there are of course commercial industries that have discovered the value and been able to be out of the gate. And that's where we have the Fortune 100 customers, like we do. Like the retail customers in the Walmart sector, healthcare providers like Medtronic, or vehicle manufacturers like Rivian who all have very difficult either supply chain, quality assurance, in stock, out of stock, anti-theft protection considerations that require successfully making sense of the real world. >> Let me ask you a question. This is maybe a little bit in the weeds, but it's more developer focused. What are some of the developer profiles that you're seeing right now in terms of low-hanging fruit applications? And can you talk about the academic impact? Because I imagine if I was in school right now, I'd be all over it. Are you seeing Master's thesis' being worked on with some of your stuff? Is the uptake in both areas of younger pre-graduates? And then inside the workforce, What are some of the devs like? Can you share just either what their makeup is, what they work on, give a little insight into the devs you're working with. >> Leading developers that want to be on state-of-the-art technology build with RoboFlow because they know they can use the best in class open source. They know that they can get the most out of their data. They know that they can deploy extremely quickly. That's true among students as you mentioned, just as much as as industries. So we welcome students and I mean, we have research grants that will regularly support for people to publish. I mean we actually have a channel inside our internal slack where every day, more student publications that cite building with RoboFlow pop up. And so, that helps inspire some of the use cases. Now what's interesting is that the use case is relatively, you know, useful or applicable for the business or the student. In other words, if a student does a thesis on how to do, we'll say like shingle damage detection from satellite imagery and they're just doing that as a master's thesis, in fact most insurance businesses would be interested in that sort of application. So, that's kind of how we see uptick and adoption both among researchers who want to be on the cutting edge and publish, both with RoboFlow and making use of open source tools in tandem with the tool that we provide, just as much as industry. And you know, I'm a big believer in the philosophy that kind of like what the hackers are doing nights and weekends, the Fortune 500 are doing in a pretty short order period of time and we're experiencing that transition. Computer vision used to be, you know, kind of like a PhD, multi-year investment endeavor. And now with some of the tooling that we're working on in open source technologies and the compute that's available, these science fiction ideas are possible in an afternoon. And so you have this idea of maybe doing asset management or the aerial observation of your shingles or things like this. You have a few hundred images and you can de-risk whether that's possible for your business today. So there's pretty broad-based adoption among both researchers that want to be on the state of the art, as much as companies that want to reduce the time to value. >> You know, Joseph, you guys and your partner have got a great front row seat, ground floor, presented creation wave here. I'm seeing a pattern emerging from all my conversations on theCUBE with founders that are successful, like yourselves, that there's two kind of real things going on. You got the enterprises grabbing the products and retrofitting into their legacy and rebuilding their business. And then you have startups coming out of the woodwork. Young, seeing greenfield or pick a specific niche or focus and making that the signature lever to move the market. >> That's right. >> So can you share your thoughts on the startup scene, other founders out there and talk about that? And then I have a couple questions for like the enterprises, the old school, the existing legacy. Little slower, but the startups are moving fast. What are some of the things you're seeing as startups are emerging in this field? >> I think you make a great point that independent of RoboFlow, very successful, especially developer focused businesses, kind of have three customer types. You have the startups and maybe like series A, series B startups that you're building a product as fast as you can to keep up with them, and they're really moving just as fast as as you are and pulling the product out at you for things that they need. The second segment that you have might be, call it SMB but not enterprise, who are able to purchase and aren't, you know, as fast of moving, but are stable and getting value and able to get to production. And then the third type is enterprise, and that's where you have typically larger contract value sizes, slower moving in terms of adoption and feedback for your product. And I think what you see is that successful companies balance having those three customer personas because you have the small startups, small fast moving upstarts that are discerning buyers who know the market and elect to build on tooling that is best in class. And so you basically kind of pass the smell test of companies who are quite discerning in their purchases, plus are moving so quick they're pulling their product out of you. Concurrently, you have a product that's enterprise ready to service the scalability, availability, and trust of enterprise buyers. And that's ultimately where a lot of companies will see tremendous commercial success. I mean I remember seeing the Twilio IPO, Uber being like a full 20% of their revenue, right? And so there's this very common pattern where you have the ability to find some of those upstarts that you make bets on, like the next Ubers of the world, the smaller companies that continue to get developed with the product and then the enterprise whom allows you to really fund the commercial success of the business, and validate the size of the opportunity in market that's being creative. >> It's interesting, there's so many things happening there. It's like, in a way it's a new category, but it's not a new category. It becomes a new category because of the capabilities, right? So, it's really interesting, 'cause that's what you're talking about is a category, creating. >> I think developer tools. So people often talk about B to B and B to C businesses. I think developer tools are in some ways a third way. I mean ultimately they're B to B, you're selling to other businesses and that's where your revenue's coming from. However, you look kind of like a B to C company in the ways that you measure product adoption and kind of go to market. In other words, you know, we're often tracking the leading indicators of commercial success in the form of usage, adoption, retention. Really consumer app, traditionally based metrics of how to know you're building the right stuff, and that's what product led growth companies do. And then you ultimately have commercial traction in a B to B way. And I think that that actually kind of looks like a third thing, right? Like you can do these sort of funny zany marketing examples that you might see historically from consumer businesses, but yet you ultimately make your money from the enterprise who has these de-risked high value problems you can solve for them. And I selfishly think that that's the best of both worlds because I don't have to be like Evan Spiegel, guessing the next consumer trend or maybe creating the next consumer trend and catching lightning in a bottle over and over again on the consumer side. But I still get to have fun in our marketing and make sort of fun, like we're launching the world's largest game of rock paper scissors being played with computer vision, right? Like that's sort of like a fun thing you can do, but then you can concurrently have the commercial validation and customers telling you the things that they need to be built for them next to solve commercial pain points for them. So I really do think that you're right by calling this a new category and it really is the best of both worlds. >> It's a great call out, it's a great call out. In fact, I always juggle with the VC. I'm like, it's so easy. Your job is so easy to pick the winners. What are you talking about its so easy? I go, just watch what the developers jump on. And it's not about who started, it could be someone in the dorm room to the boardroom person. You don't know because that B to C, the C, it's B to D you know? You know it's developer 'cause that's a human right? That's a consumer of the tool which influences the business that never was there before. So I think this direct business model evolution, whether it's media going direct or going direct to the developers rather than going to a gatekeeper, this is the reality. >> That's right. >> Well I got to ask you while we got some time left to describe, I want to get into this topic of multi-modality, okay? And can you describe what that means in computer vision? And what's the state of the growth of that portion of this piece? >> Multi modality refers to using multiple traditionally siloed problem types, meaning text, image, video, audio. So you could treat an audio problem as only processing audio signal. That is not multimodal, but you could use the audio signal at the same time as a video feed. Now you're talking about multi modality. In computer vision, multi modality is predominantly happening with images and text. And one of the biggest releases in this space is actually two years old now, was clip, contrastive language image pre-training, which took 400 million image text pairs and basically instead of previously when you do classification, you basically map every single image to a single class, right? Like here's a bunch of images of chairs, here's a bunch of images of dogs. What clip did is used, you can think about it like, the class for an image being the Instagram caption for the image. So it's not one single thing. And by training on understanding the corpora, you basically see which words, which concepts are associated with which pixels. And this opens up the aperture for the types of problems and generalizability of models. So what does this mean? This means that you can get to value more quickly from an existing trained model, or at least validate that what you want to tackle with a computer vision, you can get there more quickly. It also opens up the, I mean. Clip has been the bedrock of some of the generative image techniques that have come to bear, just as much as some of the LLMs. And increasingly we're going to see more and more of multi modality being a theme simply because at its core, you're including more context into what you're trying to understand about the world. I mean, in its most basic sense, you could ask yourself, if I have an image, can I know more about that image with just the pixels? Or if I have the image and the sound of when that image was captured or it had someone describe what they see in that image when the image was captured, which one's going to be able to get you more signal? And so multi modality helps expand the ability for us to understand signal processing. >> Awesome. And can you just real quick, define clip for the folks that don't know what that means? >> Yeah. Clip is a model architecture, it's an acronym for contrastive language image pre-training and like, you know, model architectures that have come before it captures the almost like, models are kind of like brands. So I guess it's a brand of a model where you've done these 400 million image text pairs to match up which visual concepts are associated with which text concepts. And there have been new releases of clip, just at bigger sizes of bigger encoding's, of longer strings of texture, or larger image windows. But it's been a really exciting advancement that OpenAI released in January, 2021. >> All right, well great stuff. We got a couple minutes left. Just I want to get into more of a company-specific question around culture. All startups have, you know, some sort of cultural vibe. You know, Intel has Moore's law doubles every whatever, six months. What's your culture like at RoboFlow? I mean, if you had to describe that culture, obviously love the hacking story, you and your partner with the games going number one on Product Hunt next to Elon and Tesla and then hey, we should start a company two years later. That's kind of like a curious, inventing, building, hard charging, but laid back. That's my take. How would you describe the culture? >> I think that you're right. The culture that we have is one of shipping, making things. So every week each team shares what they did for our customers on a weekly basis. And we have such a strong emphasis on being better week over week that those sorts of things compound. So one big emphasis in our culture is getting things done, shipping, doing things for our customers. The second is we're an incredibly transparent place to work. For example, how we think about giving decisions, where we're progressing against our goals, what problems are biggest and most important for the company is all open information for those that are inside the company to know and progress against. The third thing that I'd use to describe our culture is one that thrives with autonomy. So RoboFlow has a number of individuals who have founded companies before, some of which have sold their businesses for a hundred million plus upon exit. And the way that we've been able to attract talent like that is because the problems that we're tackling are so immense, yet individuals are able to charge at it with the way that they think is best. And this is what pairs well with transparency. If you have a strong sense of what the company's goals are, how we're progressing against it, and you have this ownership mentality of what can I do to change or drive progress against that given outcome, then you create a really healthy pairing of, okay cool, here's where the company's progressing. Here's where things are going really well, here's the places that we most need to improve and work on. And if you're inside that company as someone who has a preponderance to be a self-starter and even a history of building entire functions or companies yourself, then you're going to be a place where you can really thrive. You have the inputs of the things where we need to work on to progress the company's goals. And you have the background of someone that is just necessarily a fast moving and ambitious type of individual. So I think the best way to describe it is a transparent place with autonomy and an emphasis on getting things done. >> Getting shit done as they say. Getting stuff done. Great stuff. Hey, final question. Put a plug out there for the company. What are you going to hire? What's your pipeline look like for people? What jobs are open? I'm sure you got hiring all around. Give a quick plug for the company what you're looking for. >> I appreciate you asking. Basically you're either building the product or helping customers be successful with the product. So in the building product category, we have platform engineering roles, machine learning engineering roles, and we're solving some of the hardest and most impactful problems of bringing such a groundbreaking technology to the masses. And so it's a great place to be where you can kind of be your own user as an engineer. And then if you're enabling people to be successful with the products, I mean you're working in a place where there's already such a strong community around it and you can help shape, foster, cultivate, activate, and drive commercial success in that community. So those are roles that tend themselves to being those that build the product for developer advocacy, those that are account executives that are enabling our customers to realize commercial success, and even hybrid roles like we call it field engineering, where you are a technical resource to drive success within customer accounts. And so all this is listed on roboflow.com/careers. And one thing that I actually kind of want to mention John that's kind of novel about the thing that's working at RoboFlow. So there's been a lot of discussion around remote companies and there's been a lot of discussion around in-person companies and do you need to be in the office? And one thing that we've kind of recognized is you can actually chart a third way. You can create a third way which we call satellite, which basically means people can work from where they most like to work and there's clusters of people, regular onsite's. And at RoboFlow everyone gets, for example, $2,500 a year that they can use to spend on visiting coworkers. And so what's sort of organically happened is team numbers have started to pull together these resources and rent out like, lavish Airbnbs for like a week and then everyone kind of like descends in and works together for a week and makes and creates things. And we call this lighthouses because you know, a lighthouse kind of brings ships into harbor and we have an emphasis on shipping. >> Yeah, quality people that are creative and doers and builders. You give 'em some cash and let the self-governing begin, you know? And like, creativity goes through the roof. It's a great story. I think that sums up the culture right there, Joseph. Thanks for sharing that and thanks for this great conversation. I really appreciate it and it's very inspiring. Thanks for coming on. >> Yeah, thanks for having me, John. >> Joseph Nelson, co-founder and CEO of RoboFlow. Hot company, great culture in the right place in a hot area, computer vision. This is going to explode in value. The edge is exploding. More use cases, more development, and developers are driving the change. Check out RoboFlow. This is theCUBE. I'm John Furrier, your host. Thanks for watching. (gentle music)

(inspirational music) >> theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (uplifting electronic music) (crowd chattering in background) >> Hi everybody. We're back at the Fira in Barcelona. Winding up our four day wall-to-wall coverage of MWC23 theCUBE has been thrilled to cover the telco transformation. Dave Vellante with Dave Nicholson. Really excited to have NTT on. Shahid Ahmed is the Group EVP of New Ventures and Innovation at NTT in from Chicago. Welcome to Barcelona. Welcome to theCUBE. >> Thank you for having me over. >> So, really interesting title. You have, you know, people might not know NTT you know, huge Japan telco but a lot of other businesses, explain your business. >> So we do a lot of things. Most of us are known for our Docomo business in Japan. We have one of the largest wireless cellular carriers in the world. We serve most of Japan. Outside of Japan, we are B2B systems, integration, professional services company. So we offer managed services. We have data centers, we have undersea cables. We offer all kinds of outsourcing services. So we're a big company. >> So there's a narrative out there that says, you know, 5G, it's a lot of hype, not a lot of adoption. Nobody's ever going to make money at 5G. You have a different point of view, I understand. You're like leaning into 5G and you've actually got some traction there. Explain that. >> So 5G can be viewed from two lenses. One is just you and I using our cell phones and we get 5G coverage over it. And the other one is for businesses to use 5G, and we call that private 5G or enterprise grade 5G. Two very separate distinct things, but it is 5G in the end. Now the big debate here in Europe and US is how to monetize 5G. As a consumer, you and I are not going to pay extra for 5G. I mean, I haven't. I just expect the carrier to offer faster, cheaper services. And so would I pay extra? Not really. I just want a reliable network from my carrier. >> Paid up for the good camera though, didn't you? >> I did. (Dave and Dave laughing) >> I'm waiting for four cameras now. >> So the carriers are in this little bit of a pickle at the moment because they've just spent billions of dollars, not only on spectrum but the infrastructure needed to upgrade to 5G, yet nobody's willing to pay extra for that 5G service. >> Oh, right. >> So what do they do? And one idea is to look at enterprises, companies, industrial companies, manufacturing companies who want to build their own 5G networks to support their own use cases. And these use cases could be anything from automating the surveyor belt to cameras with 5G in it to AGVs. These are little carts running around warehouses picking up products and goods, but they have to be connected all the time. Wifi doesn't work all the time there. And so those businesses are willing to pay for 5G. So your question is, is there a business case for 5G? Yes. I don't think it's in the consumer side. I think it's in the business side. And that's where NTT is finding success. >> So you said, you know, how they going to make money, right? You very well described the telco dilemma. We heard earlier this week, you know, well, we could tax the OTT vendors, like Netflix of course shot back and said, "Well, we spent a lot of money on content. We're driving a lot of value. Why don't you help us pay for the content development?" Which is incredibly expensive. I think I heard we're going to tax the developers for API calls on the network. I'm not sure how well that's going to work out. Look at Twitter, you know, we'll see. And then yeah, there's the B2B piece. What's your take on, we heard the Orange CEO say, "We need help." You know, maybe implying we're going to tax the OTT vendors, but we're for net neutrality, which seems like it's completely counter-posed. What's your take on, you know, fair share in the network? >> Look, we've seen this debate unfold in the US for the last 10 years. >> Yeah. >> Tom Wheeler, the FCC chairman started that debate and he made great progress and open internet and net neutrality. The thing is that if you create a lane, a tollway, where some companies have to pay toll and others don't have to, you create an environment where the innovation could be stifled. Content providers may not appear on the scene anymore. And with everything happening around AI, we may see that backfire. So creating a toll for rich companies to be able to pay that toll and get on a faster speed internet, that may work some places may backfire in others. >> It's, you know, you're bringing up a great point. It's one of those sort of unintended consequences. You got to be be careful because the little guy gets crushed in that environment, and then what? Right? Then you stifle innovation. So, okay, so you're a fan of net neutrality. You think the balance that the US model, for a change, maybe the US got it right instead of like GDPR, who sort of informed the US on privacy, maybe the opposite on net neutrality. >> I think so. I mean, look, the way the US, particularly the FCC and the FTC has mandated these rules and regulation. I think it's a nice balance. FTC is all looking at big tech at the moment, but- >> Lena Khan wants to break up big tech. I mean for, you know, you big tech, boom, break 'em up, right? So, but that's, you know- >> That's a whole different story. >> Yeah. Right. We could talk about that too, if you want. >> Right. But I think that we have a balanced approach, a measured approach. Asking the content providers or the developers to pay for your innovative creative application that's on your phone, you know, that's asking for too much in my opinion. >> You know, I think you're right though. Government did do a good job with net neutrality in the US and, I mean, I'm just going to go my high horse for a second, so forgive me. >> Go for it. >> Market forces have always done a better job at adjudicating, you know, competition. Now, if a company's a monopoly, in my view they should be, you know, regulated, or at least penalized. Yeah, but generally speaking, you know the attack on big tech, I think is perhaps misplaced. I sat through, and the reason it's relevant to Mobile World Congress or MWC, is I sat through a Nokia presentation this week and they were talking about Bell Labs when United States broke up, you know, the US telcos, >> Yeah. >> Bell Labs was a gem in the US and now it's owned by Nokia. >> Yeah. >> Right? And so you got to be careful about, you know what you wish for with breaking up big tech. You got AI, you've got, you know, competition with China- >> Yeah, but the upside to breaking up Ma Bell was not just the baby Bells and maybe the stranded orphan asset of Bell Labs, but I would argue it led to innovation. I'm old enough to remember- >> I would say it made the US less competitive. >> I know. >> You were in junior high school, but I remember as an adult, having a rotary dial phone and having to pay for that access, and there was no such- >> Yeah, but they all came back together. The baby Bells are all, they got all acquired. And the cable company, it was no different. So I don't know, do you have a perspective of this? Because you know this better than I do. >> Well, I think look at Nokia, just they announced a whole new branding strategy and new brand. >> I like the brand. >> Yeah. And- >> It looks cool. >> But guess what? It's B2B oriented. >> (laughs) Yeah. >> It's no longer consumer, >> Right, yeah. >> because they felt that Nokia brand phone was sort of misleading towards a lot of business to business work that they do. And so they've oriented themselves to B2B. Look, my point is, the carriers and the service providers, network operators, and look, I'm a network operator, too, in Japan. We need to innovate ourselves. Nobody's stopping us from coming up with a content strategy. Nobody's stopping a carrier from building a interesting, new, over-the-top app. In fact, we have better control over that because we are closer to the customer. We need to innovate, we need to be more creative. I don't think taxing the little developer that's building a very innovative application is going to help in the long run. >> NTT Japan, what do they have a content play? I, sorry, I'm not familiar with it. Are they strong in content, or competitive like Netflix-like, or? >> We have relationships with them, and you remember i-mode? >> Yeah. Oh yeah, sure. >> Remember in the old days. I mean, that was a big hit. >> Yeah, yeah, you're right. >> Right? I mean, that was actually the original app marketplace. >> Right. >> And the application store. So, of course we've evolved from that and we should, and this is an evolution and we should look at it more positively instead of looking at ways to regulate it. We should let it prosper and let it see where- >> But why do you think that telcos generally have failed at content? I mean, AT&T is sort of the exception that proves the rule. I mean, they got some great properties, obviously, CNN and HBO, but generally it's viewed as a challenging asset and others have had to diversify or, you know, sell the assets. Why do you think that telcos have had such trouble there? >> Well, Comcast owns also a lot of content. >> Yeah. Yeah, absolutely. >> And I think, I think that is definitely a strategy that should be explored here in Europe. And I think that has been underexplored. I, in my opinion, I believe that every large carrier must have some sort of content strategy at some point, or else you are a pipe. >> Yeah. You lose touch with a customer. >> Yeah. And by the way, being a dump pipe is okay. >> No, it's a lucrative business. >> It's a good business. You just have to focus. And if you start to do a lot of ancillary things around it then you start to see the margins erode. But if you just focus on being a pipe, I think that's a very good business and it's very lucrative. Everybody wants bandwidth. There's insatiable demand for bandwidth all the time. >> Enjoy the monopoly, I say. >> Yeah, well, capital is like an organism in and of itself. It's going to seek a place where it can insert itself and grow. Do you think that the questions around fair share right now are having people wait in the wings to see what's going to happen? Because especially if I'm on the small end of creating content, creating services, and there's possibly a death blow to my fixed costs that could be coming down the line, I'm going to hold back and wait. Do you think that the answer is let's solve this sooner than later? What are your thoughts? >> I think in Europe the opinion has been always to go after the big tech. I mean, we've seen a lot of moves either through antitrust, or other means. >> Or the guillotine! >> That's right. (all chuckle) A guillotine. Yes. And I've heard those directly. I think, look, in the end, EU has to decide what's right for their constituents, the countries they operate, and the economy. Frankly, with where the economy is, you got recession, inflation pressures, a war, and who knows what else might come down the pipe. I would be very careful in messing with this equilibrium in this economy. Until at least we have gone through this inflation and recessionary pressure and see what happens. >> I, again, I think I come back to markets, ultimately, will adjudicate. I think what we're seeing with chatGPT is like a Netscape moment in some ways. And I can't predict what's going to happen, but I can predict that it's going to change the world. And there's going to be new disruptors that come about. That just, I don't think Amazon, Google, Facebook, Apple are going to rule the world forever. They're just, I guarantee they're not, you know. They'll make it through. But there's going to be some new companies. I think it might be open AI, might not be. Give us a plug for NTT at the show. What do you guys got going here? Really appreciate you coming on. >> Thank you. So, you know, we're showing off our private 5G network for enterprises, for businesses. We see this as a huge opportunities. If you look around here you've got Rohde & Schwarz, that's the industrial company. You got Airbus here. All the big industrial companies are here. Automotive companies and private 5G. 5G inside a factory, inside a hospital, a warehouse, a mining operation. That's where the dollars are. >> Is it a meaningful business for you today? >> It is. We just started this business only a couple of years ago. We're seeing amazing growth and I think there's a lot of good opportunities there. >> Shahid Ahmed, thanks so much for coming to theCUBE. It was great to have you. Really a pleasure. >> Thanks for having me over. Great questions. >> Oh, you're welcome. All right. For David Nicholson, Dave Vellante. We'll be back, right after this short break, from the Fira in Barcelona, MWC23. You're watching theCUBE. (uplifting electronic music)

(upbeat music) >> Hey everyone, Lisa Martin here with you on theCUBE Live from Mobile World Congress '23 in Barcelona. We're having a great day at the show. We hope you are too. I've got two guests here with me next. We're going to be talking about telco's 5G, all that exciting stuff. Please welcome Jason Inskeep, the AVP 5G, and Private 5G Center of Excellence at AT&T Business. And Doug Lieberman is here as well. Senior Director, Global Solutions Co-Creation Services at Dell Technologies. Guys, it's great to have you on the show, live from the show floor, talk to me about what's going on, how are you? >> Hey, thanks for having us on. It's a great show, I'm happy to be back here this year and really looking forward to the conversations that are going on and really continuing these partnerships that Dell has with companies like AT&T to truly drive the realities and the benefits of 5G. >> Absolutely, Doug, talk to me a little bit. You have an interesting title, Director of Global Solutions Co-Creation Services at Dell. Tell me a little bit about your role, what you're responsible for, and then Jason we'll have you do the same. >> Yeah, thanks for bringing that up. So, I have a very interesting role and a very exciting role at Dell because we have a unique organization that I run globally whose job it is, is to work with telcos to co-create services for enterprise and jointly go to market with those. So that basically take the combined power of AT&T and Dell and bring that to enterprise customers and other telcos so that enterprises can realize the value of, and truly leverage and harness the capabilities of 5G for private mobility and Mac and IOT and connected devices. >> Jason, let's bring you into the conversation now. You have an interesting title as well. You're with the 5G Center of Excellence at AT&T. Talk a little bit about your role and that COE. >> Yeah, thanks for having me again as well. The role with my team at AT&T is we're on the cutting edge. We're sitting in between our customers and our product houses that are working with folks at Dell, really helping putting our products together in the space of 5G. A lot of open opportunities here, a lot of things changing really fast. So my teams are off as well as putting this stuff in customers production sites it's also taking and capturing that information, working with my internal partners, both on the technology side, on the product side, and partners like Dell who are coming in helping us enabling those products and services that we can take and scale out through the different opportunities that we're seeing in this space. >> Let's double click on that partner angle, Jason, will stay with you. The 5G revolution, it's here, we are all excited about it. There's so much potential that will come from that. Let's talk about the AT&T/Dell partnership. How are you guys working together to deliver 5G globally? Jason, we'll start with you and then Doug will go to you. >> Yeah, at the core of it, when we started looking at 5G and seeing the changes that were happening, one of the biggest changes is it became software defined. So, the way we could deploy the hardware with the software becomes a whole new conversation. And what we saw coming out of that is it's not going to be a single winner and loser to really execute the way it's necessary for the experiences of tomorrow. It has to be an ecosystem that comes together. Dell creates a great opportunity for us from the hardware perspective to move those services around, to scale those services ultimately to all kinds of site types up to cities right down to small offices. And those different form factors that they bring with the software and the network pieces that we're adding on top of it help to streamline the flows and processes and really gets to that next generation that we see happening, which is this converged architecture. This meeting of network and application, creating a whole new skillset along with products. So we're at the very top we've got Dell/AT&T, at a partner level, it gets at a granular level too. The users and the developers underneath are starting to change as well, so very interesting dichotomy happening right now. >> Right, Doug, what's through Dell's lens? Tell us a little bit about the partnership and how you're working together to deliver 5G and really unlock its potential globally. >> Yeah, thank you, I'd love to bonus off of what Jason was saying, for Dell, what we look at is through the lens of an enterprise. An enterprise needs to execute their business function, their outcome, their mission that they need to operate. And so therefore they have workloads that they need to run. And 5G is an enabler for that technology, and there's lots of other enablers but the key piece is how can they get their business work done better, faster, cheaper, more efficiently, more securely? And the combination of AT&T and Dell truly is a combination that brings in a partnership that brings together a full breadth of those capabilities, with understanding what those enterprise workloads are and how they work and how an enterprise would leverage these capabilities. And then bonus on top of that and merge together with that the capabilities of AT&T. And when you look at 5G, there's a lot of people that talk about 5G being the enterprise G. And a lot of that is because of things that Jason mentioned. As we move to a disaggregated stack where you have software-defined aspects of it, and the ability in the underlying definition of what 5G in the specifications to allow much more customization. It means that enterprises now cannot just take connectivity as it is and use it however it comes but actually work with a telco and work with Dell to customize that connectivity in a way that better meets their requirements. Whether that be with slicing or private mobility or roaming between private and the public network and things like profiles and being able to have different views of how different users and devices connect to that network are all key in truly harnessing the power of that connectivity to have always on, always connected, always integrated systems from the edge, the core, to the cloud. >> Always on, always connected. That's what we all expect these days. Wherever we are in the world, whatever we're trying to do. But to be able to take advantage of all that 5G offers for all of us, telcos have to create infrastructures that can support it, let's double click guys on the infrastructure that Dell and AT&T have put in place to enable this. Jason, I want to get your perspective first and then Doug will go to you. >> Yeah, I mean, it's foundational, the things that we're trying to do and build out here and there's a lot of complexity in it now that we didn't have before because of the flexibility in it. It's one of those things like the good news in software is you can do whatever you want. The bad news in software is you can do whatever you want. Once you have that foundation there though in terms of infrastructure, which for us is really air to glass. Fiber through the spectrum on top. But underneath of that, we have the servers, we have that infrastructure where those fibers come together where that air meets the radios and so forth. And we've got to have that great foundation. So working with Dell and getting those spaces built together preps the area as needed so that there's additional place now for compute and scale at that new converged meet-me point. And that's going to be the opportunity that we're trying to think about really to get that foundation in a way that maximizes capacity and maximizes control for the customers and enterprises in particular. And more importantly, maximizes the time horizon. Because if you're putting in a foundation like this, you're not looking at two to three years. You're trying to skate beyond, skate where the puck is going, look at five, 10 years out, set that foundation. And that's what we're trying to look at with Dell. What can our network do already? Where can we push it? In return, they're going to build their solutions to help maximize that potential. >> From an infrastructure perspective, Doug, I want to understand really where Dell is really shining there but also what are some of the differentiators that Dell brings to this foundational infrastructure that to your point, is built for scale? >> Yeah, so it really all comes down to as we start to see this transition that's been happening for years, but it's accelerating because of always-connected devices and everything connected and the great proliferation of data at the edge. As we move assets from the data center and out to the edge we introduce new challenges that have to be overcome. You have things like security, automation, infrastructure cost, maintenance, day-one operations, day-two operations, all of these things are new complexities which enterprises want to enable their workloads, enable the outcomes that they want to generate. But they need to make sure that they're not taking a step backwards when it comes to things like regulations. In Europe, you've got GDPR, and in the US you've got different security regulations. No one wants to be the next front page headline about their company being attacked and having a ransomware attack. And so as we spread out these assets, what Dell is here to do is to work with AT&T and enable enterprises to effectively build their virtual enterprise around the world where those assets, whether they're at the edge or the core or in the cloud, are all managed with the same profiles and the same security features and the same automation that they have in a core data center. So my ability to deploy an edge cloud so that I can leverage AT&T's network and have end-user devices do things like gaming or connect to video services or get directed retail advertising to you are not basically introducing new vectors for security vulnerabilities into that network. And so Dell has worked really hard and is a leader in the industry in providing automation and lower cost of ownership and security for those solutions. So it's not just about putting a server out there but it's about putting an infrastructure and a cloud that is connected by AT&T's backbone and to a central core of automation management and orchestration capabilities so that I can leverage those assets securely and efficiently. >> That security element that you bring up, Doug, is so incredibly critical. We talk about it at every event, we talk about it every day. We've seen such dramatic changes in the threat landscape in the last couple of years with covid and things like that. So that security element isn't trivial, it's essential for every type of enterprise regardless of where they are. I want to talk a little bit now about best practices. And Doug, go back to you, looking at what AT&T is achieving, the 5G COE, what you're doing with Dell. From your lens and your experiences, what are some of the best practices for telcos deploying secured network and connectivity at the edge? >> Yeah, well, I think the first one is that automation and that orchestration, right? The answer is that you cannot have snowflakes at every single ag point. You need to make sure that those infrastructures are consistent and compliant with the integrations and with the policies that have been set across the network. The second thing is that you want to make sure that the connectivity is monitored and metered and managed so that we know whether, for example that endpoint is there and it's not there, if it goes offline. And ensuring the end-user experience is consistent throughout. And so what we are seeing is that it's really important that we provide an implementation where the enterprise can get a consistent and a predictable outcome for what they're trying to accomplish. What they don't want to do, what enterprises hate and is really bad for them is when they provide an inconsistent or inappropriate results to their users, to their customer base. So if your website goes offline or you're a gaming platform, if people can't get to your game you're going to lose customers, you're going to lose business you're going to have people lose faith in your network. And so our partnership with AT&T and with other telcos is about ensuring that we have all those aspects covered, day zero, day one, and day two, as well as the security aspects. And that back haul is an essential piece of that because as we get more and more devices and more and more edge devices set up, there's more sprawl. And so the complexity goes up substantially, but what really wins is when you can take that complexity and use it to your advantage and be able to manage and deploy those systems as though they were all within your virtual enterprise. >> Using complexity to your advantage. That's an interesting one, Doug, that you're bringing up. Jason, I want to know, what does that mean for you and how is AT&T leveraging complexity to its advantage for its customers all over the globe? >> You know, first thing is if you're thinking about, we're a network company we're not just a 5G company, so we're wireline, we're wireless, we're global in terms of the amount of fiber we have in the ground, the amount of in the US, domestic sailor deployments, our investments in FirstNet, is our first responder network here in the US. So we have a big portfolio inclusive of IOT. That is a global brand as well. That, if you look at it through the outside lens, that's super complex, all over the planet. So when we're talking to our customers now in this new world, which is very much, "Hey, you can do these things on your own." We go back and the bigger, obviously have the products, and the network and the tech but now that customers can take advantage of it and take things that Dell have rolled out, they need that new new age expertise. You also got the Dell expertise of building these platforms from maybe a software level, from an orchestration level, those kind of things. And at the edge that's creating a new type of person and a new type of workflow, a new type of way to respond and work. So that combination of those two is going to be that new skillset. It's in small pockets now, it's growing in how that looks because it's a little combination of both the app developer and the network developer, that's coming together. Our footprint and in terms of what we provide in there is not just 5G, it's 5G, it's fiber, it's all of those pieces together. And that's what's going to super enable that experience that Doug talked about when you're thinking about gaming or transportation, it's not just the network performance, it's the roundtrip, so we're really trying to focus on that and educate our customers in that way with the expertise that we bring over years and years of building these things. >> And if I could just jump in there. I'd like to just emphasize something Jason just said. When we look at workloads at the edge, very rarely are those workloads uniquely just an edge workload, there are components. The example I like to use is video surveillance. If you are a big box store and you have video surveillance inside your store, there is a set of workloads and outcomes you need for immediate response at that edge. You want to know if there's a safety hazard, if there is a theft or those things. Those things need to be processed real time in the store before the thief leaves the store. But then there's a set of connectivity as well where you want to process that data up in the cloud to get long-term analytics and data off of that information. What's my average store density on a Thursday afternoon in November when it's 20 degrees out. Because that would drive how many employees I have, how much inventory I carry, et cetera. And that combination is a factor that drives all the different aspects of AT&T's network. We need the connectivity in the store for the practicability and the spectrum for the cameras that talk to a central server. We need the high-speed backup and throughput in order to provide cyber recovery as well as point-of-sales services so that they can do credit card transactions flawlessly, which is using a lot of wireline services for AT&T. And together with their cloud and their other capabilities, an enterprise needs all those different aspects to work, both the edge, the core and the cloud coming together to form an outcome from one piece of input. So that one piece of input, that video stream is used in multiple different ways and because of that, that network that AT&T brings can support the end-to-end outcome and use cases for that implementation, as an example. >> That end-to-end roundtrip that you guys talked about is essential for every type of enterprise. A lot of great work that Dell and AT&T are doing together to really enable enterprises to really capitalize on all that the new technology that 5G has the potential to deliver. So I got to wrap things up, Jason, with you. From a business-customer perspective, what's next for AT&T? What can those business customers expect? >> Just continued to scaling because you're looking at a space that's evolving rapidly. It's evolving rapidly, there's a lot of opportunity. You look at the private wireless space in particular, it's nascent, but growing rapidly with the customers having their ability to do this on their own. So for us, and really where we're starting to think now is we're seeing the things move from POC, starting to move to production, customers are starting to think about what's next. For us, we're trying to skate ahead of that knowing how we built our own networks, knowing how we engaged in our own partnerships like with Dell and trying to bring that expertise back to the customer, because it isn't cookie cutter anymore. There's a lot of flexibility and each input creates a different output. So it's up to us to at least help them balance that. Define what I like to affectionately call, "Find their Goldilocks." What is that just right for them? >> Great point, Jason, it is no longer a cookie cutter. Cookie cutter isn't going to cut it. Jason, Doug, thank you so much for joining me on theCUBE today from Mobile World Congress in Barcelona. We appreciate thank you all of your insights. Sounds like some great work that AT&T and Dell are doing together. Enterprises have a lot to look forward to. Thank you again for your time. >> Thank you very much, >> Thank you. >> Looking forward to seeing you at the show. >> I'm Lisa Martin from theCUBE at Mobile World Congress '23 in Barcelona. Thanks for watching. (upbeat music)

(gentle upbeat music) >> Announcer: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (bright upbeat music) >> We're back in Barcelona at the Fira. My name is Dave Vellante. I'm here with David Nicholson. We're live at MWC23, day four of the coverage. The show is still rocking. You walk the floor, it's jamming. People are lined up to get in the copter, in the right. It's amazing. Planes, trains, automobiles, digitization of analog businesses. We're going to talk private wireless here with Dell. Sarvesh Sharma, the Global Director for Edge and Private Mobility Solutions practice at Dell. And John McCready is a Senior Director for 5G Solutions and product management at Dell Technologies. Guys, good to see you. >> Likewise, likewise. >> Good to see you too. >> Private wireless. It's the buzz of the show. Everybody's talking about it. What's Dell's point of view on that? >> So Dell is, obviously, interested entering the private wireless game, as it's a good part of the overall enterprise IT space. As you move more and more into the different things. What we announced here, is sort of our initial partnerships with some key players like Airspan and expedo and AlphaNet. Players that are important in the space. Dell's going to provide an overall system integration solution wrap along with our Edge BU as well. And we think that we can bring really good solutions to our enterprise customers. >> Okay, I got to ask you about AlphaNet. So HPE pulled a little judo move they waited till you announced your partnership and then they bought the company. What, you know, what's your opinion on that? You going to, you going to dump AlphaNet, you're going to keep 'em? >> No. >> We're open Ecosystem. >> Yeah, it's an open ecosystem. We announce these are our initial partners, you know we're going to announce additional partners that was always the case. You know, there's a lot of good players in this space that bring different pros and cons. We got to be able to match the solution requirements of all our customers. And so we'll continue to partner with them and with others. >> Good, good answer, I like that. So some of these solutions are sort of out of the box, others require more integration. Can you talk about your, the spectrum of your portfolio? >> So I'm glad you brought up the integration part, right? I mean, if you look at private wireless, private mobility it is not a sell by itself. At the end of the day what the enterprise wants is not just private mobility. They're looking for an outcome. Which means from an integration perspective, you need somebody who can integrate the infrastructure stack. But that's not enough. You need somebody who can bring in the application stack to play and integrate that application stack with the enterprises IT OT. And that's not enough. You need somebody to put those together. And Dell is ideally suited to do all of this, right? We have strong partners that can bring the infrastructure stack to play. We have a proven track record of managing the IT and the enterprise stack. So we are very excited to say, "Hey, this is the sweet spot for us. And if there was a right to win the edge, we have it." >> Can you explain, I mean, people might be saying, well, why do I even need private wireless? I got Wi-Fi. I know it's kind of a dumb question for people who are in the business, but explain to folks in the audience who may not understand the intersection of the two. >> So, yeah, so I think, you know, wireless is a great techno- pardon me, Wi-Fi is a great technology for taking your laptop to the conference room. You know, it's effectively wireless LAN Where private 5G and before that private LTE had come into play is where there's a number of attributes of your application, what you're using it for, for which Wi-Fi is not as well suited. And so, you know, that plays out in different verticals in different ways. Either maybe you need a much higher capacity than Wi-Fi, better security than Wi-Fi, wider coverage like outdoor, and in many cases a more predictable reliability. So cellular is just a different way of handling the wireless interface that provides those attributes. So, you know, I think at the beginning, the first several years, you know Wi-Fi and 5G are going to live side by side in the enterprise for their different roles. How that plays out in the long term? We'll see how they each evolve. >> But I think anybody can relate to that. I mean, Wi-Fi's fine, you know, we have our issues with Wi-Fi. I'm having a lot of issues with Wi-Fi this week, but generally speaking, it works just fine. It's ubiquitous, it's cheap, okay. But I would not want to run my factory on it and rely on it for my robots that are shipping products, right? So that really is kind of the difference. It's really an industry 4.0 type. >> Yeah, exactly. So I mean, manufacturing's an important vertical, but things of energy and mining and things like that they're all outdoor, right? So you actually need the scale that comes, with a higher power technology, and even, you know just basic things like running cameras in a retail store and using AI to watch for certain things. You get a much better latency performance on private 5G and therefore are able to run more sophisticated applications. >> So I could be doing realtime inference. I can imagine Dave, I got an arm processor I'm doing some realtime inference AI at the Edge. You know, you need something like 5G to be able to do that, you can't be doing that over Wi-Fi. >> Yeah >> You nailed it. I mean that's exactly the difference, right? I mean if you look at Wi-Fi, it grow out from a IT enabled mode, right? You got to replace an ethernet. It was an IT extension. A LAN extension. Cellular came up from the mode of, "Hey, when I have that call, I need for it to be consistent and I need for it to be always available," right? So it's a different way of looking at it. Not to say one is better, the other is not better. It's just a different philosophy behind the technologies and they're going to coexist because they meet diverse needs. >> Now you have operators who embrace the idea of 5G obviously, and even private 5G. But the sort of next hurdle to overcome for some, is the idea of open standards. What does the landscape look like right now in terms of those conversations? Are you still having to push people over that hump, to get them beyond the legacy of proprietary closed stacks? >> Yeah, so I think I look, there are still people who are advocating that. And I think in the carrier's core networks it's going to take a little longer their main, you know macro networks that they serve the general public. In the private network though, the opportunity to use open standard and open technology is really strong because that's how you bring the innovation. And that's what we need in order to be able to solve all these different business problems. You know, the problems in retail, and healthcare and energy, they're different. And so you need to be able to use this open stack and be able to bring different elements of technology and blend it together in order to serve it. Otherwise we won't serve it. We'll all fail. So that's why I think it's going to have a quicker path in private. >> And the only thing to add to that is if you look at private 5G and the deployment of private LTE or private 5G, right? There is no real technology debt that you carry. So it's easy for us to say, "Hey, the operators are not listening, they're not going open." But hey, they have a technical debt, they have 2G, 3G, 4G, 5G, systems, right? >> Interviewer: Sure. >> But the reason we are so excited about private 5G and private 4G, is right off the bat when we go into an enterprise space, we can go open. >> So what exactly is Dell's role here? How do you see, obviously you make hardware and you have solutions, but you got to open ecosystems. You got, you know, you got labs, what do you see your role in the ecosystem? Kind of a disruptor here in this, when I walk around this show. >> Well a disruptor, also a solution provider, and system integrator. You know, Sarvesh and I are part of the telecom practice. We have a big Edge practice in Dell as well. And so for this space around private 5G, we're really teamed up with our cohort in the Edge business unit. And think about this as, it's not just private 5G. It's what are you doing with it? That requires storage, it requires compute, it requires other applications. So Dell brings that entire package. There definitely are players who are just focused on the connectivity, but our view is, that's not enough. To ask the enterprise to integrate that all themself. I don't think that's going to work. You need to bring the connectivity and the application to storage compute the whole solution. >> Explain Telecom and and Edge. They're different but they're like cousins in the Dell organization. Where do you guys divide the two? >> You're saying within Dell? >> Yeah, within Dell. >> Yeah, so if you look at Dell, right? Telecom is one of our most newest business units. And the way it has formed is like we talk Edge all the time, right? It's not new. Edge has always been around. So our enterprise Edge has always been around. What has changed with 5G is now you can seamlessly move between the enterprise Edge and the telecom Edge. And for that happen you had to bring in a telecom systems business unit that can facilitate that evolution. The next evolution of seamless Edge that goes across from enterprise all the way into the telco and other places where Edge needs to be. >> Same question for the market, because I remember at Dell Tech World last year, I interviewed Lowe's and the discussion was about the Edge. >> John: Yep. >> What they're doing in their Edge locations. So that's Edge. That's cool. But then I had, I had another discussion with an agriculture firm. They had like the massive greenhouses and they were growing these awesome tomatoes. Well that was Edge too. It was actually further Edge. So I guess those are both Edge, right? >> Sarvesh: Yeah, yeah, yeah. >> Spectrum there, right? And then the telecom business, now you're saying is more closely aligned with that? >> Right. >> Depending on what you're trying to do. The appropriate place for the Edge is different. You, you nailed it exactly, right. So if you need wide area, low latency, the Edge being in the telecom network actually makes a lot of sense 'cause they can serve wide area low latency. If you're just doing your manufacturing plant or your logistics facility or your agricultural growing site, that's the Edge. So that's exactly right. And the tech, the reason why they're close cousins between telecom and that is, you're going to need some kind of connectivity, some kind of connectivity from that Edge, in order to execute whatever it's you're trying to do with your business. >> Nature's Fresh was the company. I couldn't think of Nature's Fresh. They're great. Keith awesome Cube guest. >> You mentioned this mix of Wi-Fi and 5G. I know it's impossible to predict with dates certain, you know, when this, how's this is going to develop. But can you imagine a scenario where at some point in time we don't think in terms of Wi-Fi because everything is essentially enabled by a SIM or am I missing a critical piece there, in terms of management of spectrum and the complicated governmental? >> Yeah, there is- >> Situation, am I missing something? It seems like a logical progression to me, but what am I missing? >> Well, there is something to be said about spectrum, right? If you look at Wi-Fi, as I said, the driver behind the technology is different. However, I fully agree with you that at some point in time, whether it's Wi-Fi behind, whether it's private 5G behind becomes a moot point. It's simply a matter of, where is my data being generated? What is the best technology for me to use to ingest that data so I can derive value out of that data. If it means Wi-Fi, so be it. If it means cellular, so be it. And if you look at cellular right? The biggest thing people talk about SIMs. Now if you look at 5G standard. In 5G standard, you have EAPTLS, which means there is a possibility that SIMs in the future go away for IoT devices. I'm not saying they need to go away for consumer devices, they probably need to be there. But who's to say going ahead for IoT devices, they all become SIM free. So at that point, whether you Wi-Fi or 5G doesn't matter. >> Yeah, by the way, on the spectrum side people are starting to think about the concept. You might have heard this NRU, new radio unlicensed. So it's running the Wi-Fi standard, but in the unlicensed bands like Wi-Fi. So, and then the last piece is of course you know, the cost, the reality it stays 5G still new technology, the endpoints, you know, what would go in your laptop or a sensor et cetera. Today that's more expensive than Wi-Fi. So we need to get the volume curve down a little bit for that to really hit every application. I would guess your vision is correct. >> David: Yep >> But who can predict? >> Yeah, so explain more about what the unlicensed piece means for organizations. What does that for everybody? >> That's more of a future thing. So you know, just- >> No, right, but let's put on our telescope. >> Okay, so it's true today that Wi-Fi traditionally runs in the bands that have been licensed by the government and it's a country by country thing, right? >> Dave: Right. >> What we did in the United States was CBRS, is different than what they've done in Germany where they took part of the Zurich C-band and gave it to the enterprises. The telco's not involved. And now that's been copied in Japan and Korea. So it's one of the complications unfortunately in the market. Is that you have this different approach by regulators in different countries. Wi-Fi, the unlicensed band is a nice global standard. So if you could run NR just as 5G, right? It's another name for 5G, run that in the unlicensed bands, then you solve the spectrum problem that Dave was asking about. >> Which means that the market really opens up and now. >> It would be a real enabler >> Innovation. >> Exactly. >> And the only thing I would add to that is, right, there are some enterprises who have the size and scale to kind of say, "Hey, I'm going the unlicensed route. I can do things on my own." There are some enterprises that still are going to rely on the telcos, right? So I don't want to make a demon out of the telcos that you own the spectrum, no. >> David: Sure. >> They will be offering a very valuable service to a massive number of small, medium enterprises and enterprises that span regional boundaries to say, hey we can bring that consistent experience to you. >> But the primary value proposition has been connectivity, right? >> Yes. >> I mean, we can all agree on that. And you hear different monetization models, we can't allow the OTT vendors to do it again. You know, we want to tax Netflix. Okay, we've been talking about that all week. But there may be better models. >> Sarvesh: Yes. >> Right, and so where does private network fit into the monetization models? Let's follow the money here. >> Actually you've brought up an extremely important point, right? Because if you look at why haven't 5G networks taken off, one of the biggest things people keep contrasting is what is the cost of a Wi-Fi versus the cost of deploying a 5G, right? And a portion of the cost of deploying a 5G is how do you commercialize that spectrum? What is going to be the cost of that spectrum, right? So the CSPs will have to eventually figure out a proper commercialization model to say, hey listen, I can't just take what I've been doing till date and say this is how I make. Because if you look at 5G, the return of investment is incremental. Any use case you take, unless, let's take smart manufacturing, unless the factory decides I'm going to rip and replace everything by a 5G, they're going to introduce a small use case. You look at the investment for that use case, you'll say Hmm, I'm not making money. But guess what? Once you've deployed it and you bring use case number two, three, four, five, now it starts to really add value. So how can a CSP acknowledge that and create commercial models to enable that is going to be key. Like one of the things that Dell does in terms of as a service solution that we offer. I think that is a crucial way of really kick starting 5G adoption. >> It's Metcalfe's Law in this world, right? The first telephone, not a lot of value, second, I can call one person, but you know if I can call a zillion now it's valuable. >> John: Now you got data. >> Yeah, right, you used a phrase, rip and replace. What percentage of the market that you are focusing on is the let's go in and replace something, versus the let's help you digitally transform your business. And this is a networking technology that we can use to help you digitally transform? The example that you guys have with the small breweries, a perfect example. >> Sarvesh: Yeah. >> You help digitize, you know, digitally transform their business. You weren't going in and saying, I see that you have these things connected via Wi-Fi, let's rip those out and put SIMs in. >> No. >> Nope, so you know- >> That's exactly right. It's enabling new things that either couldn't be achieved before or weren't. So from a private 5G perspective, it's not going to be rip and replaced. As I said, I think we'll coexist with Wi-Fi, it's still got a great role. It's enabling those, solving those business problems that either hadn't been solved before or could not be solved with other technology. >> How are you guys using AI? Everybody's talking about ChatGPT. I love ChatGPT, we use it all the time. Love it, hate it, you know, whatever. It's a fun topic. But AI generally is here in a way that it wasn't when the enterprise disaggregated. >> John: Right. >> So there's AI, there's automation, there's opportunities there. How do they fit into private 5G? >> So if you look at it, right, AI, AI/ML is actually crucial to value extraction from that data, because all private 5G is doing is giving you access to that precious data. But that data by itself means nothing, right? You get access to the data, extracting value out of the data that bring in business value is all going to be AI/ML. Whether it's computer vision, whether it's data analytics on the fly so that you can, you know do your closed loop controls or what have you. All of these are going to be AI/ML models. >> Dave: Does it play into automation as well? >> Absolutely, 'cause they drive the automation, right? You learn your AI models, drive their automation. Control, closed loop control systems are a perfect example of their automation. >> Explain that further. Like give us an example. >> So for example, let's say we're talking about a smart manufacturing, right? So you have widgets coming down the pipe, right? You have your computer vision, you have your AI/ML model that says, "Hey, I'm starting to detect a consistent error in the product being manufactured. I'm going to close loop that automation and either tweak the settings of the machine, shut down the machine, open a workflow, escalate it for human intervention." All that automation is facilitated by the AI/ML models >> And that, and by the way, there's real money in that, right? If you're making your power and you're making it wrong, you don't detect it for hours, there's real money in fixing that >> Right. >> So I've got a, I've got an example albeit a slight, not even slightly, but a tragic one. Let's say you have a train that's rolling down the tracks at every several miles or so, temperature readings are taken from bearings in the train. >> Sarvesh: Yes, yes. >> Wouldn't it be nice to have that be happening in real time? >> Sarvesh: Yes. >> So it doesn't reach that critical point >> Yes. >> Where then you have a derailment. >> Yes. >> Yeah, absolutely. >> I mean, those are, it's doesn't sound sexy in terms of "Hey, what a great business use case that we can monetize." >> John: Yeah. >> But I'll bet you in hindsight that operator would've loved to have that capability. >> John: Yeah. >> Sarvesh: Right. >> To be able to shut the train down and not run. >> That's a great example where the carrier is actually, probably in a good position, right? Cause you got wide area, you want low latency. So the traditional carriers would be able in great position to provide that exact service. Telemetry is another great example. We've been talking about other kinds of automation, but just picking up measurements and so on. The other example of that is in oil and gas, right? As you've got pipelines running around you're measuring pressure, temperature, you detect a leak, >> David: Right. >> in minutes, not weeks. >> David: Right. >> So there's a lot of good examples of things like that >> To pick up in a point, Dave. You know, it's like you look at these big huge super tankers, right? They have big private networks on that super tanker to monitor everything. If on this train we had, you know, we hear about so many Edges, let's call one more the rolling Edge. >> Yeah. >> Right, that, that Edge is right on that locomotive tracking everything with AI/ML models, detecting things, warning people ahead of time shutting it down as needed. And that connectivity doesn't have to be wired. It can be a rolling wireless. It potentially could be a spectrum that's you know, open spectrum in the future. Or as you said, an operator could facilitate that. So many options, right? >> Yeah, got to double down on this. Look, I know 'cause I've been involved in some of these projects. Amusement park operators are doing this for rides. >> John: Yes. >> Sarvesh: Yep. >> So that they can optimize the amount of time the ride is up, so they can shorten lines >> Yes. >> So that they can get people into shops to buy food and souvenirs. >> John: Yes. >> Certainly we should be able to do it to protect infrastructure. >> Sarvesh: Absolutely. >> Right, so- >> But I think the ultimate point you're making is, it's actually quite finally segmented. There's so many different applications. And so that's why again, we come back to what we started with is at Dell, we're bringing the solution from Edge, compute, application, connectivity, and be able to bring that across all these different verticals and these different solutions. The other amusement park example, by the way, is as the rides start to invest in virtual reality, so you're moving, but you're seeing something, you need some technology like 5G to have low latency and keep that in sync and have a good experience on the ride. >> To 5G and beyond, gents. Thanks so much for coming on theCUBE. >> All right, thank you Dave. >> It was great to have you. >> Thank, thank you guys. >> Great to meet you guys. Thank you very much. >> Great, all right. Keep it right there. For David Nicholson and Dave Vellante, This is theCUBE's coverage of MWC23. Check out siliconangle.com for all the news. theCUBE.net is where all these videos live. John Furrier is in our Palo Alto office, banging out that news. Keep it right there. Be right back after this short break. (gentle upbeat music)

>> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Hey, welcome back to the Fira in Barcelona. My name is Dave Vellante. I'm here with David Nicholson, day four of MWC '23. Show's winding down a little bit, but it's still pretty packed here. Lot of innovation, planes, trains, automobiles, and we're talking 5G all week, private networks, connected breweries. It's super exciting. Really happy to have Warren Jackson here as the Edge Gateway Product Technologist at Dell Technologies, and Scott Waller, the CTO of the 5G Open Innovation Lab. Folks, welcome to theCUBE. >> Good to be here. >> Really interesting stories that we're going to talk about. Let's start, Scott, with you, what is the Open Innovation Lab? >> So it was hatched three years ago. Ideated about a bunch of guys from Microsoft who ran startup ventures program, started the developers program over at Microsoft, if you're familiar with MSDN. And they came three years ago and said, how does CSPs working with someone like T-Mobile who's in our backyard, I'm from Seattle. How do they monetize the edge? You need a developer ecosystem of applications and use cases. That's always been the thing. The carriers are building the networks, but where's the ecosystem of startups? So we built a startup ecosystem that is sponsored by partners, Dell being one sponsor, Intel, Microsoft, VMware, Aspirant, you name it. The enterprise folks who are also in the connectivity business. And with that, we're not like a Y Combinator or a Techstars where it's investment first and it's all about funding. It's all about getting introductions from a startup who might have a VR or AI type of application or observability for 5G slicing, and bring that in front of the Microsoft's of the world, or the Intel's and the Dell's of the world that they might not have the capabilities to do it because they're still a small little startup with an MVP. So we really incubate. We're the connectors and build a network. We've had 101 startups over the last three years. They've raised over a billion dollars. And it's really valuable to our partners like T-Mobile and Dell, et cetera, where we're bringing in folks like Expedo and GenXComm and Firecell. Start up private companies that are around here they were cohorts from our program in the past. >> That's awesome because I've often, I mean, I've seen Dell get into this business and I'm like, wow, they've done a really good job of finding these guys. I wonder what the pipeline is. >> We're trying to create the pipeline for the entire industry, whether it's 5G on the edge for the CSPs, or it's for private enterprise networks. >> Warren, what's this cool little thing you got here? >> Yeah, so this is very unique in the Dell portfolio. So when people think of Dell, they think of servers laptops, et cetera. But what this does is it's designed to be deployed at the edge in harsh environments and it allows customers to do analytics, data collection at the edge. And what's unique about it is it's got an extended temperature range. There's no fan in this and there's lots of ports on it for data ingestion. So this is a smaller box Edge Gateway 3200. This is the product that we're using in the brewery. And then we have a bigger brother of this, the Edge Gateway 5200. So the value of it, you can scale depending on what your edge compute requirements are at the edge. >> So tell us about the brewery story. And you covered it, I know you were in the Dell booth, but it's basically an analog brewery. They're taking measurements and temperatures and then writing it down and then entering it in and somebody from your company saw it and said, "We can help you with this problem." Explain the story. >> Yeah, so Scott and I did a walkthrough of the brewery back in November timeframe. >> It's in Framingham, Mass. >> Framingham, Mass, correct. And basically, we talked to him, and we said, what keeps you guys up at night? What's a problem that we can solve? Very simple, a kind of a lower budget, didn't have a lot money to spend on it, but what problem can we solve that will realize great benefit for you? So we looked at their fermentation process, which was completely analog. Somebody was walking around with a clipboard looking at analog gauges. And what we did is we digitized that process. So what this did for them rather than being completely reactive, and by the time they realized there was something going wrong with the fermentation process, it's too late. A batch of scrap. This allowed them to be proactive. So anytime, anywhere on the tablet or a phone, they can see if that fermentation process is going out of range and do something about it before the batch gets scrapped. >> Okay. Amazing. And Scott, you got a picture of this workflow here? >> Yeah, actually this is the final product. >> Explain that. >> As Warren mentioned, the data is actually residing in the industrial side of the network So we wanted to keep the IT/OT separation, which is critical on the factory floor. And so all the data is brought in from the sensors via digital connection once it's converted and into the edge gateway. Then there's a snapshot of it using Telit deviceWISE, their dashboarding application, that is decoding all the digital readings, putting them in a nice dashboard. And then when we gave them, we realized another problem was they're using cheap little Chromebooks that they spill beer on once a week and throw them out. That's why they bought the cheap ones 'cause they go through them so fast. So we got a Dell Latitude Rugged notebook. This is a brand new tablet, but they have the dashboarding software. So no matter if they're out there on the floor, but because the data resides there on the factory they have access to be able to change the parameters. This one's in the maturation cycle. This one's in the crashing cycle where they're bringing the temperature back down, stopping the fermentation process, getting it ready to go to the canning side of the house. >> And they're doing all that from this dashboard. >> They're doing all from the dashboard. They also have a giant screen that we put up there that in the floor instead of walking a hundred yards back behind a whole bunch of machinery equipment from a safety perspective, now they just look up on the screen and go, "Oh, that's red. That's out of range." They're actually doing a bunch of cleaning and a bunch of other things right now, too. So this is real time from Boston. >> Dave: Oh okay. >> Scott: This is actually real time from Boston. >> I'm no hop master, but I'm looking at these things flashing at me and I'm thinking something's wrong with my beer. >> We literally just lit this up last week. So we're still tweaking a few things, but they're also learning around. This is a new capability they never had. Oh, we have the ability to alert and monitor at different processes with different batches, different brews, different yeast types. Then now they're also training and learning. And we're going to turn that into eventually a product that other breweries might be able to use. >> So back to the kind of nuts and bolts of the system. The device that you have here has essentially wifi antennas on the back. >> Warren: Correct. >> Pull that up again if you would, please. >> Now I've seen this, just so people are clear, there are also paddle 5G antennas that go on the other side. >> Correct. >> That's sort of the connection from the 5G network that then gets transmogrified, technical term guys, into wifi so the devices that are physically connected to the brew vats, don't know what they're called. >> Fermentation tanks. >> Fermentation tanks, thank you. Those are wifi. That's a wifi signal that's going into this. Is that correct? >> Scott: No. >> No, it's not. >> It's a hard wire. >> Okay, okay. >> But, you're right. This particular gateway. >> It could be wifi if it's hard wire. >> It could be, yes. Could be any technology really. >> This particular gateway is not outfitted with 5G, but something that was very important in this application was to isolate the IT network, which is on wifi and physically connected from the OT network, which is the 5G connection. So we're sending the data directly from the gateway up to the cloud. The two partners that we worked with on this project were ifm, big sensor manufacturer that actually did the wired sensors into an industrial network called IO-Link. So they're physically wired into the gateway and then in the gateway we have a solution from our partner Telit that has deviceWISE software that actually takes the data in, runs the analytics on it, the logic, and then visualizes that data locally on those panels and also up to their cloud, which is what we're looking at. So they can look at it locally, they're in the plant and then up in the cloud on a phone or a tablet, whatever, when they're at home. >> We're talking about a small business here. I don't know how many employees they have, but it's not thousands. And I love that you're talking about an IT network and an OT network. And so they wanted, it is very common when we talk about industrial internet of things use cases, but we're talking about a tiny business here. >> Warren: Correct. >> They wanted to separate those networks because of cost, because of contention. Explain why. >> Yeah, just because, I mean, they're running their ERP system, their payroll, all of their kind of the way they run their business on their IT network and you don't want to have the same traffic out on the factory floor on that network, so it was pretty important. And the other thing is we really, one of the things that we didn't want to do in this project is interrupt their production process at all. So we installed this entire system in two days. They didn't have to shut down, they didn't have to stop. We didn't have to interrupt their process at all. It was like we were invisible there and we spun the thing up and within two days, very simple, easy, but tremendous value for their business. >> Talk about new markets here. I mean, it's like any company that's analog that needs to go digital. It's like 99% of the companies on the planet. What are you guys seeing out there in terms of the types of examples beyond breweries? >> Yeah, I could talk to that. So I spent a lot of time over the last couple years running my own little IoT company and a lot of it being in agriculture. So like in Washington state, 70% of the world's hops is actually grown in Washington state. It's my hometown. But in the Ag producing regions, there's lack of connectivity. So there's interest in private networks because the carriers aren't necessarily deploying it. But because we have the vast amount of hops there's a lot of IPAs, a lot of hoppy IPAs that come out of Seattle. And with that, there's a ton of craft breweries that are about the same size, some are a little larger. Anheuser-Busch and InBev and Heineken they've got great IoT platforms. They've done it. They're mass scale, they have to digitize. But the smaller shops, they don't, when we talk about IT/OT separation, they're not aware of that. They think it's just, I get local broadband and I get wifi and one hotspot inside my facility and it works. So a little bit of it was the education. I have got years in IT/OT security in my background so that education and we come forward with a solution that actually does that for them. And now they're aware of it. So now when they're asking questions of other vendors that are trying to sell them some type of solution, they're inherently aware of what should be done so they're not vulnerable to ransomware attacks, et cetera. So it's known as the Purdue Model. >> Well, what should they do? >> We came in and keep it completely separated and educated them because in the end too we'll build a design guide and a starter kit out of this that other brewers can use. Because I've toured dozens of breweries in Washington, the exact same scenario, analog gauges, analog process, very manual. And in the end, when you ask the brewer, what do they want out of this? It keeps them up at night because if the temperature goes out of range, because the chiller fails, >> They ruined. >> That's $30,000 lost in beer. That's a lot to a small business. However, it's also once they start digitizing the data and to Warren's point, it's read-only. We're not changing any of the process. We augmented on top of their existing systems. We didn't change their process. But now they have the ability to look at the data and see batch to batch consistency. Quality doesn't always mean best, it means consistency from batch to batch. Every beer from exhibit A from yesterday to two months from now of the same style of beer should be the same taste, flavor, boldness, et cetera. This is giving them the insights on it. >> It's like St. Louis Buds, when we were kids. We would buy the St. Louis Buds 'cause they tasted better than the Merrimack Buds. And then Budweiser made them all the same. >> Must be an East coast thing. >> It's an old guy thing, Dave. You weren't born yet. >> I was in high school. Yeah, I was in high school. >> We like the hops. >> We weren't 21. Do me a favor, clarify OT versus IT. It's something we talk about all the time, but not everyone's familiar with that separation. Define OT for me. >> It's really the factory floor. You got IT systems that are ERP systems, billing, you're getting your emails, stuff like that. Where the ransomware usually gets infected in. The OT side is the industrial control network. >> David: What's the 'O' stand for? >> Operation. >> David: Operation? >> Yeah, the operations side. >> 'Cause some people will think objects 'cause we think internet of things. >> The industrial operations, think of it that way. >> But in a sense those are things that are connected. >> And you think of that as they are the safety systems as well. So a machine, if someone doesn't push the stop button, you'd think if there's a lot of traffic on that network, it isn't guaranteed that that stop button actually stops that blade from coming down, someone's going to lose their arm. So it's very tied to safety, reliability, low latency. It is crafted in design that it never touches the internet inherently without having to go through a security gateway which is what we did. >> You mentioned the large companies like InBev, et cetera. You're saying they're already there. Are they not part of your target market? Or are there ways that you can help them? Is this really more of a small to mid-size company? >> For this particular solution, I think so, yeah. Because the cost to entry is low. I mean, you talk about InBev, they have millions of dollars of budgets to spend on OT. So they're completely automated from top to bottom. But these little craft brewers, which they're everywhere in the US. Vermont, Washington state, they're completely manual. A lot of these guys just started in their garage. And they just scaled up and they got a cult kind of following around their beers. One thing that we found here this week, when you talk around edge and 5G and beer, those things get people excited. In our booth we're serving beer, and all these kind of topics, it brings people together. >> And it lets the little guy compete more effectively with the big giants. >> Correct. >> And how do you do more with less as the little guy is kind of the big thing and to Warren's point, we have folks come up and say, "Great, this is for beer, but what about wine? What about the fermentation process of wine?" Same materials in the end. A vessel of some sort, maybe it's stainless steel. The clamps are the same, the sensors are the same. The parameters like temperature are key in any type of fermentation. We had someone talking about olive oil and using that. It's the same sanitary beverage style equipment. We grabbed sensors that were off the shelf and then we integrated them in and used the set of platforms that we could. How do we rapidly enable these guys at the lowest possible cost with stuff that's at the shelf. And there's four different companies in the solution. >> We were having a conversation with T-Mobile a little earlier and she mentioned the idea of this sounding scary. And this is a great example of showing that in fact, at a relatively small scale, this technology makes a lot of sense. So from that perspective, of course you can implement private 5G networks at an industrial scale with tens of millions of dollars of investment. But what about all of the other things below? And that seems to be a perfect example. >> Yeah, correct. And it's one of the things with the gateway and having flexibility the way Dell did a great job of putting really good modems in it. It had a wide spectrum range of what bands they support. So being able to say, at a larger facility, I mean, if Heineken wants to deploy something like this, oh, heck yeah, they probably could do it. And they might have a private 5G network, but let's say T-Mobile offers a private offering on their public via a slice. It's easy to connect that radio to it. You just change the sims. >> Is that how the CSPs fit here? How are they monetized? >> Yeah, correct. So one of our partners is T-Mobile and so we're working with them. We've got other telco partners that are coming on board in our lab. And so we'll do the same thing. We're going to take this back and put it in the lab and offer it up as others because the baseline building blocks or Lego blocks per se can be used in a bunch of different industries. It's really that starter point of giving folks the idea of what's possible. >> So small manufacturing, agriculture you mentioned, any other sort of use cases we should tune into? >> I think it's environmental monitoring, all of that stuff, I see it in IoT deployments all over the world. Just the simple starter kits 'cause a farmer doesn't want to get sold a solution, a platform, where he's got to hire a bunch of coders and partner with the big carriers. He just wants something that works. >> Another use case that we see a lot, a high cost in a lot of these places is the cost of energy. And a lot of companies don't know what they're spending on electricity. So a very simple energy monitoring system like that, it's a really good ROI. I'm going to spend five or $10,000 on a system like this, but I'm going to save $20,000 over a year 'cause I'm able to see, have visibility into that data. That's a lot of what this story's about, just giving visibility into the process. >> It's very cool, and like you said, it gets people excited. Is it a big market? How do you size it? Is it a big TAM? >> Yeah, so one thing that Dell brings to the table in this space is people are buying their laptops, their servers and whatnot from Dell and companies are comfortable in doing business with Dell because of our model direct to customer and whatnot. So our ability to bring a device like this to the OT space and have them have that same user experience they have with laptops and our client products in a ruggedized solution like this and bring a lot of partners to the table makes it easy for our customers to implement this across all kinds of industries. >> So we're talking to billions, tens of billions. Do we know how big this market is? What's the TAM? I mean, come on, you work for Dell. You have to do a TAM analysis. >> Yes, no, yeah. I mean, it really is in the billions. The market is huge for this one. I think we just tapped into it. We're kind of focused in on the brewery piece of it and the liquor piece of it, but the possibilities are endless. >> Yeah, that's tip of the spear. Guys, great story. >> It's scalable. I think the biggest thing, just my final feedback is working and partnering with Dell is we got something as small as this edge gateway that I can run a Packet Core on and run a 5G standalone node and then have one of the small little 5G radios out there. And I've got these deployed in a farm. Give the farmer an idea of what's possible, give him a unit on his tractor, and now he can do something that, we're providing connectivity he had never had before. But as we scale up, we've got the big brother to this. When we scale up from that, we got the telco size units that we can put. So it's very scalable. It's just a great suite of offerings. >> Yeah, outstanding. Guys, thanks for sharing the story. Great to have you on theCUBE. >> Good to be with you today. >> Stop by for beer later. >> You know it. All right, Dave Vellante for Dave Nicholson and the entire CUBE team, we're here live at the Fira in Barcelona MWC '23 day four. Keep it right there. (upbeat music)

(gentle music) >> Narrator: "TheCUBE's" live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music) >> Hello everybody, welcome back to day four of "theCUBE's" coverage of MWC '23. We're here live at the Fira in Barcelona. Wall-to-wall coverage, John Furrier is in our Palo Alto studio, banging out all the news. Really, the whole week we've been talking about the disaggregation of the telco network, the new opportunities in telco. We're really excited to have AT&T and Snowflake here. Dave Whittington is the AVP, at the Chief Data Office at AT&T. Roddy Tranum is the Assistant Vice President, for Channel Performance Data and Tools at AT&T. And Phil Kippen, the Global Head Of Industry-Telecom at Snowflake, Snowflake's new telecom business. Snowflake just announced earnings last night. Typical Scarpelli, they beat earnings, very conservative guidance, stocks down today, but we like Snowflake long term, they're on that path to 10 billion. Guys, welcome to "theCUBE." Thanks so much >> Phil: Thank you. >> for coming on. >> Dave and Roddy: Thanks Dave. >> Dave, let's start with you. The data culture inside of telco, We've had this, we've been talking all week about this monolithic system. Super reliable. You guys did a great job during the pandemic. Everything shifting to landlines. We didn't even notice, you guys didn't miss a beat. Saved us. But the data culture's changing inside telco. Explain that. >> Well, absolutely. So, first of all IoT and edge processing is bringing forth new and exciting opportunities all the time. So, we're bridging the world between a lot of the OSS stuff that we can do with edge processing. But bringing that back, and now we're talking about working, and I would say traditionally, we talk data warehouse. Data warehouse and big data are now becoming a single mesh, all right? And the use cases and the way you can use those, especially I'm taking that edge data and bringing it back over, now I'm running AI and ML models on it, and I'm pushing back to the edge, and I'm combining that with my relational data. So that mesh there is making all the difference. We're getting new use cases that we can do with that. And it's just, and the volume of data is immense. >> Now, I love ChatGPT, but I'm hoping your data models are more accurate than ChatGPT. I never know. Sometimes it's really good, sometimes it's really bad. But enterprise, you got to be clean with your AI, don't you? >> Not only you have to be clean, you have to monitor it for bias and be ethical about it. We're really good about that. First of all with AT&T, our brand is Platinum. We take care of that. So, we may not be as cutting-edge risk takers as others, but when we go to market with an AI or an ML or a product, it's solid. >> Well hey, as telcos go, you guys are leaning into the Cloud. So I mean, that's a good starting point. Roddy, explain your role. You got an interesting title, Channel Performance Data and Tools, what's that all about? >> So literally anything with our consumer, retail, concenters' channels, all of our channels, from a data perspective and metrics perspective, what it takes to run reps, agents, all the way to leadership levels, scorecards, how you rank in the business, how you're driving the business, from sales, service, customer experience, all that data infrastructure with our great partners on the CDO side, as well as Snowflake, that comes from my team. >> And that's traditionally been done in a, I don't mean the pejorative, but we're talking about legacy, monolithic, sort of data warehouse technologies. >> Absolutely. >> We have a love-hate relationship with them. It's what we had. It's what we used, right? And now that's evolving. And you guys are leaning into the Cloud. >> Dramatic evolution. And what Snowflake's enabled for us is impeccable. We've talked about having, people have dreamed of one data warehouse for the longest time and everything in one system. Really, this is the only way that becomes a reality. The more you get in Snowflake, we can have golden source data, and instead of duplicating that 50 times across AT&T, it's in one place, we just share it, everybody leverages it, and now it's not duplicated, and the process efficiency is just incredible. >> But it really hinges on that separation of storage and compute. And we talk about the monolithic warehouse, and one of the nightmares I've lived with, is having a monolithic warehouse. And let's just go with some of my primary, traditional customers, sales, marketing and finance. They are leveraging BSS OSS data all the time. For me to coordinate a deployment, I have to make sure that each one of these units can take an outage, if it's going to be a long deployment. With the separation of storage, compute, they own their own compute cluster. So I can move faster for these people. 'Cause if finance, I can implement his code without impacting finance or marketing. This brings in CI/CD to more reality. It brings us faster to market with more features. So if he wants to implement a new comp plan for the field reps, or we're reacting to the marketplace, where one of our competitors has done something, we can do that in days, versus waiting weeks or months. >> And we've reported on this a lot. This is the brilliance of Snowflake's founders, that whole separation >> Yep. >> from compute and data. I like Dave, that you're starting with sort of the business flexibility, 'cause there's a cost element of this too. You can dial down, you can turn off compute, and then of course the whole world said, "Hey, that's a good idea." And a VC started throwing money at Amazon, but Redshift said, "Oh, we can do that too, sort of, can't turn off the compute." But I want to ask you Phil, so, >> Sure. >> it looks from my vantage point, like you're taking your Data Cloud message which was originally separate compute from storage simplification, now data sharing, automated governance, security, ultimately the marketplace. >> Phil: Right. >> Taking that same model, break down the silos into telecom, right? It's that same, >> Mm-hmm. >> sorry to use the term playbook, Frank Slootman tells me he doesn't use playbooks, but he's not a pattern matcher, but he's a situational CEO, he says. But the situation in telco calls for that type of strategy. So explain what you guys are doing in telco. >> I think there's, so, what we're launching, we launched last week, and it really was three components, right? So we had our platform as you mentioned, >> Dave: Mm-hmm. >> and that platform is being utilized by a number of different companies today. We also are adding, for telecom very specifically, we're adding capabilities in marketplace, so that service providers can not only use some of the data and apps that are in marketplace, but as well service providers can go and sell applications or sell data that they had built. And then as well, we're adding our ecosystem, it's telecom-specific. So, we're bringing partners in, technology partners, and consulting and services partners, that are very much focused on telecoms and what they do internally, but also helping them monetize new services. >> Okay, so it's not just sort of generic Snowflake into telco? You have specific value there. >> We're purposing the platform specifically for- >> Are you a telco guy? >> I am. You are, okay. >> Total telco guy absolutely. >> So there you go. You see that Snowflake is actually an interesting organizational structure, 'cause you're going after verticals, which is kind of rare for a company of your sort of inventory, I'll say, >> Absolutely. >> I don't mean that as a negative. (Dave laughs) So Dave, take us through the data journey at AT&T. It's a long history. You don't have to go back to the 1800s, but- (Dave laughs) >> Thank you for pointing out, we're a 149-year-old company. So, Jesse James was one of the original customers, (Dave laughs) and we have no longer got his data. So, I'll go back. I've been 17 years singular AT&T, and I've watched it through the whole journey of, where the monolithics were growing, when the consolidation of small, wireless carriers, and we went through that boom. And then we've gone through mergers and acquisitions. But, Hadoop came out, and it was going to solve all world hunger. And we had all the aspects of, we're going to monetize and do AI and ML, and some of the things we learned with Hadoop was, we had this monolithic warehouse, we had this file-based-structured Hadoop, but we really didn't know how to bring this all together. And we were bringing items over to the relational, and we were taking the relational and bringing it over to the warehouse, and trying to, and it was a struggle. Let's just go there. And I don't think we were the only company to struggle with that, but we learned a lot. And so now as tech is finally emerging, with the cloud, companies like Snowflake, and others that can handle that, where we can create, we were discussing earlier, but it becomes more of a conducive mesh that's interoperable. So now we're able to simplify that environment. And the cloud is a big thing on that. 'Cause you could not do this on-prem with on-prem technologies. It would be just too cost prohibitive, and too heavy of lifting, going back and forth, and managing the data. The simplicity the cloud brings with a smaller set of tools, and I'll say in the data space specifically, really allows us, maybe not a single instance of data for all use cases, but a greatly reduced ecosystem. And when you simplify your ecosystem, you simplify speed to market and data management. >> So I'm going to ask you, I know it's kind of internal organizational plumbing, but it'll inform my next question. So, Dave, you're with the Chief Data Office, and Roddy, you're kind of, you all serve in the business, but you're really serving the, you're closer to those guys, they're banging on your door for- >> Absolutely. I try to keep the 130,000 users who may or may not have issues sometimes with our data and metrics, away from Dave. And he just gets a call from me. >> And he only calls when he has a problem. He's never wished me happy birthday. (Dave and Phil laugh) >> So the reason I asked that is because, you describe Dave, some of the Hadoop days, and again love-hate with that, but we had hyper-specialized roles. We still do. You've got data engineers, data scientists, data analysts, and you've got this sort of this pipeline, and it had to be this sequential pipeline. I know Snowflake and others have come to simplify that. My question to you is, how is that those roles, how are those roles changing? How is data getting closer to the business? Everybody talks about democratizing business. Are you doing that? What's a real use example? >> From our perspective, those roles, a lot of those roles on my team for years, because we're all about efficiency, >> Dave: Mm-hmm. >> we cut across those areas, and always have cut across those areas. So now we're into a space where things have been simplified, data processes and copying, we've gone from 40 data processes down to five steps now. We've gone from five steps to one step. We've gone from days, now take hours, hours to minutes, minutes to seconds. Literally we're seeing that time in and time out with Snowflake. So these resources that have spent all their time on data engineering and moving data around, are now freed up more on what they have skills for and always have, the data analytics area of the business, and driving the business forward, and new metrics and new analysis. That's some of the great operational value that we've seen here. As this simplification happens, it frees up brain power. >> So, you're pumping data from the OSS, the BSS, the OKRs everywhere >> Everywhere. >> into Snowflake? >> Scheduling systems, you name it. If you can think of what drives our retail and centers and online, all that data, scheduling system, chat data, call center data, call detail data, all of that enters into this common infrastructure to manage the business on a day in and day out basis. >> How are the roles and the skill sets changing? 'Cause you're doing a lot less ETL, you're doing a lot less moving of data around. There were guys that were probably really good at that. I used to joke in the, when I was in the storage world, like if your job is bandaging lungs, you need to look for a new job, right? So, and they did and people move on. So, are you able to sort of redeploy those assets, and those people, those human resources? >> These folks are highly skilled. And we were talking about earlier, SQL hasn't gone away. Relational databases are not going away. And that's one thing that's made this migration excellent, they're just transitioning their skills. Experts in legacy systems are now rapidly becoming experts on the Snowflake side. And it has not been that hard a transition. There are certainly nuances, things that don't operate as well in the cloud environment that we have to learn and optimize. But we're making that transition. >> Dave: So just, >> Please. >> within the Chief Data Office we have a couple of missions, and Roddy is a great partner and an example of how it works. We try to bring the data for democratization, so that we have one interface, now hopefully know we just have a logical connection back to these Snowflake instances that we connect. But we're providing that governance and cleansing, and if there's a business rule at the enterprise level, we provide it. But the goal at CDO is to make sure that business units like Roddy or marketing or finance, that they can come to a platform that's reliable, robust, and self-service. I don't want to be in his way. So I feel like I'm providing a sub-level of platform, that he can come to and anybody can come to, and utilize, that they're not having to go back and undo what's in Salesforce, or ServiceNow, or in our billers. So, I'm sort of that layer. And then making sure that that ecosystem is robust enough for him to use. >> And that self-service infrastructure is predominantly through the Azure Cloud, correct? >> Dave: Absolutely. >> And you work on other clouds, but it's predominantly through Azure? >> We're predominantly in Azure, yeah. >> Dave: That's the first-party citizen? >> Yeah. >> Okay, I like to think in terms sometimes of data products, and I know you've mentioned upfront, you're Gold standard or Platinum standard, you're very careful about personal information. >> Dave: Yeah. >> So you're not trying to sell, I'm an AT&T customer, you're not trying to sell my data, and make money off of my data. So the value prop and the business case for Snowflake is it's simpler. You do things faster, you're in the cloud, lower cost, et cetera. But I presume you're also in the business, AT&T, of making offers and creating packages for customers. I look at those as data products, 'cause it's not a, I mean, yeah, there's a physical phone, but there's data products behind it. So- >> It ultimately is, but not everybody always sees it that way. Data reporting often can be an afterthought. And we're making it more on the forefront now. >> Yeah, so I like to think in terms of data products, I mean even if the financial services business, it's a data business. So, if we can think about that sort of metaphor, do you see yourselves as data product builders? Do you have that, do you think about building products in that regard? >> Within the Chief Data Office, we have a data product team, >> Mm-hmm. >> and by the way, I wouldn't be disingenuous if I said, oh, we're very mature in this, but no, it's where we're going, and it's somewhat of a journey, but I've got a peer, and their whole job is to go from, especially as we migrate from cloud, if Roddy or some other group was using tables three, four and five and joining them together, it's like, "Well look, this is an offer for data product, so let's combine these and put it up in the cloud, and here's the offer data set product, or here's the opportunity data product," and it's a journey. We're on the way, but we have dedicated staff and time to do this. >> I think one of the hardest parts about that is the organizational aspects of it. Like who owns the data now, right? It used to be owned by the techies, and increasingly the business lines want to have access, you're providing self-service. So there's a discussion about, "Okay, what is a data product? Who's responsible for that data product? Is it in my P&L or your P&L? Somebody's got to sign up for that number." So, it sounds like those discussions are taking place. >> They are. And, we feel like we're more the, and CDO at least, we feel more, we're like the guardians, and the shepherds, but not the owners. I mean, we have a role in it all, but he owns his metrics. >> Yeah, and even from our perspective, we see ourselves as an enabler of making whatever AT&T wants to make happen in terms of the key products and officers' trade-in offers, trade-in programs, all that requires this data infrastructure, and managing reps and agents, and what they do from a channel performance perspective. We still ourselves see ourselves as key enablers of that. And we've got to be flexible, and respond quickly to the business. >> I always had empathy for the data engineer, and he or she had to service all these different lines of business with no business context. >> Yeah. >> Like the business knows good data from bad data, and then they just pound that poor individual, and they're like, "Okay, I'm doing my best. It's just ones and zeros to me." So, it sounds like that's, you're on that path. >> Yeah absolutely, and I think, we do have refined, getting more and more refined owners of, since Snowflake enables these golden source data, everybody sees me and my organization, channel performance data, go to Roddy's team, we have a great team, and we go to Dave in terms of making it all happen from a data infrastructure perspective. So we, do have a lot more refined, "This is where you go for the golden source, this is where it is, this is who owns it. If you want to launch this product and services, and you want to manage reps with it, that's the place you-" >> It's a strong story. So Chief Data Office doesn't own the data per se, but it's your responsibility to provide the self-service infrastructure, and make sure it's governed properly, and in as automated way as possible. >> Well, yeah, absolutely. And let me tell you more, everybody talks about single version of the truth, one instance of the data, but there's context to that, that we are taking, trying to take advantage of that as we do data products is, what's the use case here? So we may have an entity of Roddy as a prospective customer, and we may have a entity of Roddy as a customer, high-value customer over here, which may have a different set of mix of data and all, but as a data product, we can then create those for those specific use cases. Still point to the same data, but build it in different constructs. One for marketing, one for sales, one for finance. By the way, that's where your data engineers are struggling. >> Yeah, yeah, of course. So how do I serve all these folks, and really have the context-common story in telco, >> Absolutely. >> or are these guys ahead of the curve a little bit? Or where would you put them? >> I think they're definitely moving a lot faster than the industry is generally. I think the enabling technologies, like for instance, having that single copy of data that everybody sees, a single pane of glass, right, that's definitely something that everybody wants to get to. Not many people are there. I think, what AT&T's doing, is most definitely a little bit further ahead than the industry generally. And I think the successes that are coming out of that, and the learning experiences are starting to generate momentum within AT&T. So I think, it's not just about the product, and having a product now that gives you a single copy of data. It's about the experiences, right? And now, how the teams are getting trained, domains like network engineering for instance. They typically haven't been a part of data discussions, because they've got a lot of data, but they're focused on the infrastructure. >> Mm. >> So, by going ahead and deploying this platform, for platform's purpose, right, and the business value, that's one thing, but also to start bringing, getting that experience, and bringing new experience in to help other groups that traditionally hadn't been data-centric, that's also a huge step ahead, right? So you need to enable those groups. >> A big complaint of course we hear at MWC from carriers is, "The over-the-top guys are killing us. They're riding on our networks, et cetera, et cetera. They have all the data, they have all the client relationships." Do you see your client relationships changing as a result of sort of your data culture evolving? >> Yes, I'm not sure I can- >> It's a loaded question, I know. >> Yeah, and then I, so, we want to start embedding as much into our network on the proprietary value that we have, so we can start getting into that OTT play, us as any other carrier, we have distinct advantages of what we can do at the edge, and we just need to start exploiting those. But you know, 'cause whether it's location or whatnot, so we got to eat into that. Historically, the network is where we make our money in, and we stack the services on top of it. It used to be *69. >> Dave: Yeah. >> If anybody remembers that. >> Dave: Yeah, of course. (Dave laughs) >> But you know, it was stacked on top of our network. Then we stack another product on top of it. It'll be in the edge where we start providing distinct values to other partners as we- >> I mean, it's a great business that you're in. I mean, if they're really good at connectivity. >> Dave: Yeah. >> And so, it sounds like it's still to be determined >> Dave: Yeah. >> where you can go with this. You have to be super careful with private and for personal information. >> Dave: Yep. >> Yeah, but the opportunities are enormous. >> There's a lot. >> Yeah, particularly at the edge, looking at, private networks are just an amazing opportunity. Factories and name it, hospital, remote hospitals, remote locations. I mean- >> Dave: Connected cars. >> Connected cars are really interesting, right? I mean, if you start communicating car to car, and actually drive that, (Dave laughs) I mean that's, now we're getting to visit Xen Fault Tolerance people. This is it. >> Dave: That's not, let's hold the traffic. >> Doesn't scare me as much as we actually learn. (all laugh) >> So how's the show been for you guys? >> Dave: Awesome. >> What're your big takeaways from- >> Tremendous experience. I mean, someone who doesn't go outside the United States much, I'm a homebody. The whole experience, the whole trip, city, Mobile World Congress, the technologies that are out here, it's been a blast. >> Anything, top two things you learned, advice you'd give to others, your colleagues out in general? >> In general, we talked a lot about technologies today, and we talked a lot about data, but I'm going to tell you what, the accelerator that you cannot change, is the relationship that we have. So when the tech and the business can work together toward a common goal, and it's a partnership, you get things done. So, I don't know how many CDOs or CIOs or CEOs are out there, but this connection is what accelerates and makes it work. >> And that is our audience Dave. I mean, it's all about that alignment. So guys, I really appreciate you coming in and sharing your story in "theCUBE." Great stuff. >> Thank you. >> Thanks a lot. >> All right, thanks everybody. Thank you for watching. I'll be right back with Dave Nicholson. Day four SiliconANGLE's coverage of MWC '23. You're watching "theCUBE." (gentle music)

(gentle pulsating music) >> Narrator: TheCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (light airy music) >> Good evening from Fira, Barcelona in Spain. It's Lisa Martin and Dave Vellante. We are covering with theCUBE MWC '23. This is day three. Three full days, almost, of coverage we've given you. And don't worry, we've got a great conversation next, and another day tomorrow. We're going to be talking with Singtel and Dell next about 5G network slicing. Sexy stuff. Please welcome Dennis Wong, VP Enterprise 5G and Platform from Singtel. And Douglas Lieberman is back with us. Our alumni, Global Senior Director, GTM and Co-Creation Services, Telecom Systems Business at Dell. Welcome, guys. Great to have you. >> Thank you very much. >> Thanks for having us. >> So Dennis, go ahead and start with you. Talk to the audience about Singtel. You've got a unique insight into some of the challenges that 5G brings and the opportunities. What is Singtel seeing there? >> I think from a Singtel perspective, I think 5G technology brings about a new era of opportunities for all the enterprises, you know, from big to small. I think that's one thing that we are aiming to do. How do we put technology together? And that's why I think that 5G brings about a lot more capabilities, a lot more parameters that, you know, for the new technology, new devices, new services that we can explore. I mean, we are giving ourself a new opportunity to try something that's better than Wi-Fi, that is better 4G. So I think that's something very exciting for me. >> What are some of the challenges that you see that are, that you look to partners like Dell to help wipe off the table? >> I think one of the things that Dell has been doing very closely with us, I think in terms of the network technology, in terms of the RAN, in terms of the, you know, kind of virtualization, in terms of marketplace, in terms of ecosystem, they are all over the place. So I think for them, they are not looking at just hardware, they are looking at how to support us as a whole ecosystem to work things together. >> You know, it's interesting because it's maybe an overused term, but everyone talks about 5G being the enterprise G. And really, what's interesting about 5G, and where Dell is really able to add value in working with partners like Singtel, is the disaggregation of 5G and the open side of it, and the ability to take different workloads and customize them because of the fact that the whole packet core and the CU and the DU and that architecture is not locked into a single proprietary architecture, allows for customization and injection of workloads, and allows enterprises to really tune the network to what their workloads need to be. >> So I wonder, Dennis, can you take us through the anatomy of a 5G deployment? How does it work? Do you start with a sort of greenfield, sort of test bed? How do you connect it to your 4G networks? Take us through the process. >> Maybe I will go through from a customer lens. What does the customer think, and what does the customer feels about when we approach them for 5G? I think for most of the customers who are thinking about 5G, they are usually already having some kind of a services that's running on the current technology. Could be 4G, could be Wi-Fi. And one very typical example that I can share with you is that one of the customers, he was saying that, "I'm having Wi-Fi already. Can you prove to me that 5G is better?" So, what we did was that we actually rolled out our, this little proprietary 5G in the box. We call it 5G GENIE. GENIE stands for Generating Instant Experience. You know, very interesting name. We pushed that to the customer place. Within 30 minutes, he set up a 5G connectivity in his area, and he tested his performance of his Wi-Fi with the GENIE on the spot. And immediately, wow, he see that there's a lot of difference in the performance. Now, so the first part, is really about getting the customer to feel that, why 5G is truly better. Let them experience it. Then after which, we went through with them, because of this performance, what does it do to your business? From a productivity perspective, security perspective, safety perspective. And they kind of look at it and say, "Wow." that is where the ROI comes from. Then after which, then is where I think, you know, where Dave says, you know, he comes in whereby then, we will design, if it's a factory, we are to design the coverage in the factory because robots are moving. You want to ensure that every part of them, of their factories have the coverage. So we are to design it, we are to build it, put in all the controls and put in all the devices. And then after which, you know, then all things will go. And of course, from a customer perspective, they will still need to run the application. We need to check that the performance is, you know, up to the mark. So I think in all, the 5G journey is not really just about putting the network and, "Here, customer, let's use it." There's a lot of conviction, there's a lot of testing, there's a lot of what we call trial and error with the customer. Yeah. >> So thank you for that explanation. So that's there, we're going to make a business case, and they're going to see immediate performance improvements. Then, I presume they're going to start building new applications on top. And then maybe that'll negatively affect the performance, but that's okay. It's like we were talking about the other day, there's so much data pumping, you get equivalent performance, but so much more capability. So how are you guys thinking about that ultimate layer, where that value is, the application, the workloads, that are going to be new to these networks? >> Well, let's, you know, we can take a step back and talk about, for example, the use case he just talked about, which was in, you know, autonomous vehicles or robots inside a factory. It's not that it's just more performance. It's reliable performance and consistent performance. Because the difference with a cellular solution, a mobile solution, a 5G solution, than a Wi-Fi, is the guaranteed spectrum and the isolated spectrum and the lack of competition for that space. I mean, I tell people this all the time, and you can see it right now. If you were to open your phone and look at all the Wi-Fi hotspots that exist right here, there is an enormous amount of contention for the exact same spectrum and we're all competing with each other. >> Dave: I can't get into the network. >> Right, and so the more people that walk past us in this cube, the more that there's going to be interference. And so the performance is not guaranteed. And if you have an automated factory, if you have machines that are moving around a factory, if you have robots that need to work together, you can't afford for it to be great one minute, and lousy the next minute. You need consistent high performance. And that's where these 5G networks and private 5G networks are really, really important. 'Cause it's not just about faster. Sometimes it's not all about can I get it there faster? I want it faster, but reliably and consistently, and make sure I get the same experience every time, so that I can then build more intricate and complicated applications. If you have a warehouse that's got autonomous robots, the closer I can have those robots get to each other, means the more packages I can move, or the more welds I can make, or the more machine parts I can get out the door because I don't have to build into the, "Oh my God, I lost Wi-Fi connectivity for 10 seconds," and I got, "And everything stops, until the connectivity comes back and they can resume." >> And anybody would choose consistent, predictable performance over spiky performance. >> Doug: Right. >> And you're saying the technology, you're able to better leverage the spectrum, isolate the spectrum for that specific use case. That is a technology enabler. >> Dennis: Maybe I can also give you another perspective. Together with the 5G technology is where the multi-edge computing comes into place. And that's where I think one of the things that we work very closely with Dell as well. Because that is very important. With that compute at the edge, means that your latency is low. And, like what you said, it's not just low latency, it's consistently low latency. Today, let's say in Singapore, Singapore is a very small city. You can travel from one end of the city to the other end in one and a half hour, and that's it. Singapore is so- >> If there's no traffic. >> And if there's no traffic. (all laugh) Now, so everyone was saying, "Singapore is such a small city, why would you need a edge?" So I explained to them, we did a test from a cloud gaming perspective. As we use 4G over the public cloud, it's true that you can get about 10, 15, 20 milliseconds, you know, on a good day, but it's, on average, it's about 15, 20 milliseconds. However, you will find that there are times, whereby it'll spike to 150, spike to 90, spike to 200. So you can see that it's not just about low latency, it's about consistent low latency. So that's where I think 5G and MEC come as a good pair to make sure that, you know, the performance of our, for those factories or what, you know, kind of Doug has mentioned, the high performance, you know, synchronized services is very important. Beside packing the, you know, the drones, or the robots who go close together, you want it to be synchronized. And you know, if you've seen some of those robots that work together, it's almost synchronized. That is the one thing that, our dreams that we going to make sure that we going to achieve, yeah. >> And then, of course, on top of all that, is security, which is really, really important on all these. I mean the vulnerabilities of Wi-Fi are well known. There is a hundred different tools that you can download for free to test the security of any Wi-Fi network. So there's- >> Dave: I got my VPN and it won't let me on the network. >> Right, exactly. (all laugh) You know, so the benefit of a 5G solution, a 4G solution, is the added layer of security. I'm not saying that it's perfect, you know, there are obviously ways to get around those as well, but every additional layer of security is one less attack factor that you have to worry about every single day. >> So Dennis, you're pro on the 5G adoption journey. You both have talked about the ostensible benefits there and then the capabilities. I want to understand, how is Dell actually helping, under the covers, Singtel, deliver this connectivity and this consistency and the reliability that your customers expect? >> Yeah. I think, you know, having all these services together, I think, other than just what we call the 5G connectivity, it's like what you mentioned about the RAN, the disaggregated kind of services, I think that gives us a lot of opportunity in terms of flexibility, in terms, of course. But I think one of the things that we also work closely together is about new technology. As I've mentioned also that, you know, the marketplace or the partners that Dell brings, that's very, very important for us. And then for me, I think that, if I look at it again from the customer lens again, right? Having the kind of right equipment, which we are working together with Dell, is important, but I think having the right ecosystem that use the equipment, is even more important. I will give you a very simple example. For any organization, for any services that you need to deploy, let's choose a SMB. You'll realize that, if I want to deploy an application in my office, there's a few things you need to consider. Networks, which could be provided by 5G, right? Then you talk about the public cloud. Then you talk about the, what we call the public cloud and you talk about the edge. Now, in order for you to deploy this, you'll realize that every one of them could be orchestrated and synchronized. And then, as well, Doug has mentioned, after you implemented three of them, you've still got to consider security across them. >> Lisa: Yeah, yeah. >> So what happens there for us, what we want to do is that, we actually build a platform that actually sits on top of all this. This platform actually controls the 5G network, the MEC, as well as the, what we call the public all together. And on top, sitting on top of that is all the applications. Why so? Because again, anytime you have an application, you know that you have to make sure that the VMs works, the hypervisor works, you know, connectivity works, the compatibility works. So, when we build this platform, we put all the ecosystem on board and then it makes it like, the customer can have a one stop shop, look at the equipment, look at the, what we call the equipment, look at the networks, look at the, you know, the cloud, the IaaS as well as the application, it works. And so, working together with Dell, we actually come up and look at some solution that's fit for the market. One of the opportunity that we are looking together with this Dell is in Singapore. How do we actually ship a really packaged bundle to SMEs that has a Dell equipment, our 5G network, plus the platform product ecosystem, that can ship to any restaurant around? So that, you know, we are thinking out loud. Like for example, as you move into the restaurant, you know, we always say that, please scan your barcode on the table for the menu. >> Lisa: Yeah. >> You can just go in, and by facial recognition, knowing that you are not a staff. So it's a reverse privacy. And then after that, push, you know, the menu to your phone directly. And so, therefore, it cuts again the stuff of me trying to scan the menu or waiting for it to load. And because with the on-prem equipment from Dell, let's say for example, there's things is pushed to the phone instantly. You know, sometimes we know that, when some of this goes to the public web or public cloud, and by the time it loads the menu, you are just waiting to avoid the load. So you can see that all these become a experience for the SMEs and the restaurant's staff. So I think these are some of these great use cases that we can foresee in the future. >> And I think, you know, something you just said is really a key part, right? As technologists, sometimes we get wrapped around the technology, and we forget about the fact that it's all about the outcome. To the enterprise, they're looking at a workload. They have a very specific thing they want to accomplish. And all this stuff, private 5G, and edge, and cloud, they're all really irrelevant. They're just means to get to what their outcome that they want to be is. And when we look at them atomically, and as independent little units, we end up with sprawl, and honestly, enterprises are telling us more and more and more, "I don't want that. I don't want a science project. I don't want to be responsible for figuring out how all these things are going to play together and have one rack of equipment for my network, and one rack of equipment for my private 5G, and another rack of equipment for my edge cloud and another rack of equipment for the MEC." And you start to get data centers inside of a pizza shop where there's no space to put a data center, right? And so the partnership we have with Singtel, and exactly what Dennis was just talking about, is how do we take all of those and start realizing that with virtualization and containerization and the open architecture that exists with function virtualization in networking today, in private 5G. We're able to utilize a common infrastructure stack, a common platform to be able to give you all those functions to run the 5G, to run your core applications, to run the MEC, to do all those things, so that we're minimizing the footprint, but also minimizing the complexity. And that's really the point. >> So how mature are we today? Where are we? When can we expect deployments? You know, are there any sort of early case examples you can share? >> Yeah, like I said, you know, in Singapore itself, we have already saw a little bit of success. Especially in Singapore, we have 5G SA already. So I think one of the few things that like I mentioned, some of these use cases that we did. So the company that I talked earlier about is a factory. They took the 5G GENIE, went there, and tested against the Wi-Fi, agree with it. They say, "Let's deploy." They have deployed it now, and it's running. So it's using the 5G for safety, you know, and safety inspection and remote assistance, for training, et cetera. We're using the VR goggles. So I think that's really a live use case. The other live use case is that in Singapore, one of the, you know, kind of automotive manufacturing plants is actually using the AGV that's controlled by our 5G, that's moving around in the factory in a very, what we call random manner. In a way that, in the past, whereby you would never conceive the automotive factories that is going to go on conveyor belts. But now, the AGV is moving as in where at in the ad hoc manner, yeah. >> Yeah, I mean we've got solutions. We've implemented with customers for mining, for example. For the autonomous vehicles in a mine where the, you know, after the mine explosion goes off and you got to gather the minerals and the ores, there's a lot of time that you have to wait before humans can go in. But with a 5G solution, we've been able to enable autonomous vehicles to go in there and start the process of collecting that ore without waiting for the humans, substantially improving safety, security, and the output and revenue of those mines. >> Dave: No, no canary necessary. (Dennis laughs) Is that correct that this capability is not really going to cannibalize Wi-Fi, right? It's going to go into use cases, or will it? Are there situations that overlap, where customers have sort of on the edge, no pun intended, tried to use Wi-Fi and then this will cannibalize some piece of the market? >> Look, there's a Venn diagram somewhere, right? (Lisa and Dennis chuckle) And at the end of the day, no one who's being honest is going to say that 5G is going to replace Wi-Fi, right? >> Yeah, yeah, sure. >> There are, and there's a lot of reasons for that. You know, challenges in adding new devices, you know, if you go to a store, and you want to get on their Wi-Fi, you don't want to necessarily add a new SIM to your phone. So there are places where Wi-Fi is still going to remain a very powerful long-term solution that's not going anywhere, especially at the moment because the cost of Wi-Fi, you know, the chips for Wi-Fi are pennies a piece to put in devices. So we're a long way away from 5G being at the same monetary scale as Wi-Fi. But, there are a lot of use cases where Wi-Fi is simply doesn't work. I talked about that mining solution, Wi-Fi doesn't work in a mine. It's got the wrong physics properties, it's got the wrong distance limitations, there's all sorts of problems. And so, what 5G has opened up, is where in the past, people tried to make Wi-Fi work and either gave up and ran wired, or just dealt with constant problems, like all their machines shutting down simultaneously. 5G is enabling them to now have a real solution that works. So it's carving out a niche for itself. In some places it's replacing Wi-Fi without a doubt 'cause it is a better solution. But there are some use cases that are going to remain Wi-Fi for a long time. >> And how flexible and mobile can that solution be? 'Cause we can't use Wi-Fi here. (Dennis chuckles) We have to use a hard line. >> Yep. >> Right? So, could we use 5G, our own private network on theCUBE? Or is it because we're going too many places? It's just just too complicated for us? >> That's where it comes from. >> Stick with fixed lines. >> That's where the next technology of 5G come from. >> Yeah. >> Slicing. >> Talk about that. >> You see that, you know, somebody ask me, "Why would somebody need slicing?" Then I'll ask you, "That if you are in US, or in any country in the world, there's always two way. You can use a highway and you pay toll. Or you use your small roads. Exactly, why do you have a highway, that you have to pay toll?" There is a highway, there's a path, there's a slice. So for operators, we can always say that based on your mission criticality, based on the speed you want, based on the kind of urgency you need, our works give you a slice, and that you have to pay a premium for it. So similarly, would be that 5G is going to be available here, and say that Cube will purchase a slice from Californica. And say that for Cube, this is your 5G, you have a freeway, green way, it's highly possible. >> Believe me, we're paying a premium for hard lines at Mobile World Congress or MWC. (all laugh) >> And to that point, right, you know, and those slicing gives you the opportunity to do profiling and, you know, setting up. When I say profiling, you know, different devices and different customers getting different metrics on how they use that network. So some of them will get a superhighway, some of them will get a medium size highway, somebody- >> Dennis: Somebody getting a secured highway. >> Right, so a more secure highway. So, there's a lot more flexibility with 5G, and that's why I said, you know, there's a lot of use cases, where it will replace Wi-Fi, and it will be very powerful. And that's the places where we're really seeing the adoption really taking off. >> You guys have done a great job explaining 5G, really. Why you're pro 5G, the opportunities of the use cases. Thank you so much for joining us today. >> Dennis: Thank you, Lisa. >> Also talking about what Dell and Singtel are doing together. I imagine the journey probably has just begun, but you've made tremendous amount of progress so far. It's a great use case. Thank you for sharing it with us today. >> Thank you very much. >> Thank you. Thank you, Dave. Thank you, Lisa. >> All right, our pleasure. For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, live at MWC '23 from Barcelona, Spain. Stick around. Dave comes up with a very cool wrap, after this. (light airy music)

>> And I'm here at Dell's Presence at MWC with vice president of marketing for telecom and Edge Computing, Aaron Chaisson. Aaron, how's it going? >> Doing great. How's it going today, Dave? >> It's going pretty well. Pretty excited about what you've got going here and I'm looking forward to getting the tour. You ready to take a closer look? >> Ready to do it. Let's go take a look! For us in the telecom ecosystem, it's really all about how we bring together the different players that are innovating across the industry to drive value for our CSP customers. So, it starts really, for us, at the ecosystem layer, bringing partners, bringing telecommunication providers, bringing (stutters) a bunch of different technologies together to innovate together to drive new value. So Paul, take us a little bit through what we're doing to- to develop and bring in these partnerships and develop our ecosystem. >> Uh, sure. Thank you Aaron. Uh, you know, one of the things that we've been focusing on, you know, Dell is really working with many players in the open telecom ecosystem. Network equipment providers, independent software vendors, and the communication service providers. And, you know, through our lines of business or open telecom ecosystem labs, what we want to do is bring 'em together into a community with the goal of really being able to accelerate open innovation and, uh, open solutions into the market. And that's what this community is really about, is being able to, you know, have those communications, develop those collaborations whether it's through, you know, sharing information online, having webinars dedicated to sharing Dell information, whether it's our next generation hardware portfolio we announced here at the show, our use case directory, our- how we're dealing with new service opportunities, but as well as the community to share, too, which I think is an exciting way for us to be able to, you know- what is the knowledge thing? As well as activities at other events that we have coming up. So really the key thing I think about, the- the open telecom ecosystem community, it's collaboration and accelerating the open industry forward. >> So- So Aaron, if I'm hearing this correctly you're saying that you can't just say, "Hey, we're open", and throw a bunch of parts in a box and have it work? >> No, we've got to work together to integrate these pieces to be able to deliver value, and, you know, we opened up a- (stutters) in our open ecosystem labs, we started a- a self-certification process a couple of months back. We've already had 13 partners go through that, we've got 16 more in the pipeline. Everything you see in this entire booth has been innovated and worked with partnerships from Intel to Microsoft to, uh, to (stutters) Wind River and Red Hat and others. You go all the way around the booth, everything here has partnerships at its core. And why don't we go to the next section here where we're going to be showing how we're pulling that all together in our open ecosystems labs to drive that innovation? >> So Aaron, you talked about the kinds of validation and testing that goes on, so that you can prove out an open stack to deliver the same kinds of reliability and performance and availability that we expect from a wireless network. But in the opens- in the open world, uh, what are we looking at here? >> Yeah absolutely. So one of the- one of the challenges to a very big, broad open ecosystem is the complexity of integrating, deploying, and managing these, especially at telecom scale. You're not talking about thousands of servers in one site, you're talking about one server in thousands of sites. So how do you deploy that predictable stack and then also manage that at scale? I'm going to show you two places where we're talkin' about that. So, this is actually representing an area that we've been innovating in recently around creating an integrated infrastructure and virtualization stack for the telecom industry. We've been doing this for years in IT with VxBlocks and VxRails and others. Here what you see is we got, uh, Dell hardware infrastructure, we've got, uh, an open platform for virtualization providers, in this case we've created an infrastructure block for Red Hat to be able to supply an infrastructure for core operations and Packet Cores for telecoms. On the other side of this, you can actually see what we're doing with Wind River to drive innovation around RAN and being able to simplify RAN- vRAN and O-RAN deployments. >> What does that virtualization look like? Are we talking about, uh, traditional virtual machines with OSs, or is this containerized cloud native? What does it look like? >> Yeah, it's actually both, so it can support, uh, virtual, uh-uh, software as well as containerized software, so we leverage the (indistinct) distributions for these to be able to deploy, you know, cloud native applications, be able to modernize how they're deploying these applications across the telecom network. So in this case with Red Hat, uh, (stutters) leveraging OpenShift in order to support containerized apps in your Packet Core environments. >> So what are- what are some of the kinds of things that you can do once you have infrastructure like this deployed? >> Yeah, I mean by- by partnering broadly across the ecosystem with VMware, with Red Hat, uh, with- with Wind River and with others, it gives them the ability to be able to deploy the right virtualization software in their network for the types of applications they're deploying. They might want to use Red Hat in their core, they may want to use Wind River in their RAM, they may want to use, uh, Microsoft or VMware for their- for their Edge workloads, and we allow them to be able to deploy all those, but centrally manage those with a common user interface and a common set of APIs. >> Okay, well I'm dying to understand the link between this and the Lego city that the viewers can't see, yet, but it's behind me. Let's take a look. >> So let's take a look at the Lego city that shows how we not deploy just one of these, but dozens or hundreds of these at scale across a cityscape. >> So Aaron, I know we're not in Copenhagen. What's all the Lego about? >> Yeah, so the Lego city here is to show- and, uh, really there's multiple points of Presence across an entire Metro area that we want to be able to manage if we're a telecom provider. We just talked about one infrastructure block. What if I wanted to deploy dozens of these across the city to be able to manage my network, to be able to manage, uh, uh- to be able to deploy private mobility potentially out into a customer enterprise environment, and be able to manage all of these, uh, very simply and easily from a common interface? >> So it's interesting. Now I think I understand why you are VP of marketing for both telecom and Edge. Just heard- just heard a lot about Edge and I can imagine a lot of internet of things, things, hooked up at that Edge. >> Yeah, so why don't we actually go over to another area? We're actually going to show you how one small microbrewery (stutters) in one of our cities nearby, uh, (stutters) my hometown in Massachusetts is actually using this technology to go from more of an analyzed- analog world to digitizing their business to be able to brew better beer. >> So Aaron, you bring me to a brewery. What do we have- what do we have going on here? >> Yeah, so, actually (stutters) about- about a year ago or so, I- I was able to get my team to come together finally after COVID to be able to meet each other and have a nice team event. One of those nights, we went out to dinner at a- at a brewery called "Exhibit 'A'" in Massachusetts, and they actually gave us a tour of their facilities and showed us how they actually go through the process of brewing beer. What we saw as we were going through it, interestingly, was that everything was analog. They literally had people with pen and paper walking around checking time and temperature and the process of brewing the beer, and they weren't asking for help, but we actually saw an opportunity where what we're doing to help businesses digitize what they're doing in their manufacturing floor can actually help them optimize how they build whatever product they're building, in this case it was beer. >> Hey Warren, good to meet you! What do we have goin' on? >> Yeah, it's all right. So yeah, basically what we did is we took some of their assets in the, uh, brewery that were completely manually monitored. People were literally walking around the floor with clipboards, writing down values. And we censorized the asset, in this case fermentation tanks and we measured the, uh, pressure and the temperature, which in fermentation are very key to monitor those, because if they get out of range the entire batch of beer can go bad or you don't get the consistency from batch to batch if you don't tightly monitor those. So we censorized the fermentation tank, brought that into an industrial I/O network, and then brought that into a Dell gateway which is connected 5G up to the cloud, which then that data comes to a tablet or a phone, which they, rather than being out on the floor and monitor it, can look at this data remotely at any time. >> So I'm not sure the exact date, the first time we have evidence of beer being brewed by humanity... >> Yep. >> But I know it's thousands of years ago. So it's taken that long to get to the point where someone had to come along, namely Dell, to actually digitally transform the beer business. Is this sort of proof that if you can digitally transform this, you can digitally transform anything? >> Absolutely. You name it, anything that's being manufactured, sold, uh, uh, taken care of, (stutters) any business out there that's looking to be able to be modernize and deliver better service to their customers can benefit from technologies like this. >> So we've taken a look at the ecosystem, the way that you validate architectures, we've seen an example of that kind of open architecture. Now we've seen a real world use case. Do you want to take a look a little deeper under the covers and see what's powering all of this? >> We just this week announced a new line of servers that power Edge and RAN use cases, and I want to introduce Mike to kind of take us through what we've been working on and really what the power of what this providing. >> Hey Mike, welcome to theCube. >> Oh, glad- glad to be here. So, what I'd really like to talk about are the three new XR series servers that we just announced last week and we're showing here at Mobile World Congress. They are all short depth, ruggedized, uh, very environmentally tolerant, and able to withstand, you know, high temperatures, high humidities, and really be deployed to places where traditional data center servers just can't handle, you know, due to one fact or another, whether it's depth or the temperature. And so, the first one I'd like to show you is the XR7620. This is, uh, 450 millimeters deep, it's designed for, uh, high levels of acceleration so it can support up to 2-300 watt, uh, GPUs. But what I really want to show you over here, especially for Mobile World Congress, is our new XR8000. The XR8000 is based on Intel's latest Sapphire Rapids technology, and this is- happens to be one of the first, uh, EE boost processors that is out, and basically what it is (stutters) an embedded accelerator that makes, uh, the- the processing of vRAN loads very, uh, very efficient. And so they're actually projecting a, uh, 3x improvement, uh, of processing per watt over the previous generation of processors. This particular unit is also sledded. It's very much like, uh, today's traditional baseband unit, so it's something that is designed for low TCO and easy maintenance in the field. This is the frew. When anything fails, you'll pull one out, you pop a new one in, it comes back into service, and the- the, uh, you know, your radio is- is, uh, minimally disrupted. >> Yeah, would you describe this as quantitative and qualitative in terms of the kinds of performance gains that these underlying units are delivering to us? I mean, this really kind of changes the game, doesn't it? It's not just about more, is it about different also in terms of what we can do? >> Well we are (stutters) to his point, we are able to bring in new accelerator technologies. Not only are we doing it with the Intel, uh, uh, uh, of the vRAN boost technologies, but also (stutters) we can bring it, too, but there's another booth here where we're actually working with our own accelerator cards and other accelerator cards from our partners across the industry to be able to deliver the price and performance capabilities required by a vRAN or an O-RAN deployment in the network. So it's not- it's not just the chip technology, it's the integration and the innovation we're doing with others, as well as, of course, the unique power cooling capabilities that Dell provides in our servers that really makes these the most efficient way of being able to power a network. >> Any final thoughts recapping the whole picture here? >> Yeah, I mean I would just say if anybody's, uh, i- is still here in Mobile World Congress, wants to come and learn what we're doing, I only showed you a small section of the demos we've got here. We've got 13 demos across on 8th floor here. Uh, for those of you who want to talk to us (stutters) and have meetings with us, we've got 13 meeting rooms back there, over 500 costumer partner meetings this week, we've got some whisper suites for those of you who want to come and talk to us but we're innovating on going forward. So, you know, there's a lot that we're doing, we're really excited, there's a ton of passion at this event, and, uh, we're really excited about where the industry is going and our role in it. >> 'Preciate the tour, Aaron. Thanks Mike. >> Mike: Thank you! >> Well, for theCube... Again, Dave Nicholson here. Thanks for joining us on this tour of Dell's Presence here at MWC 2023.

>> (Narrator) The CUBE's live coverage is made possible by funding by Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Welcome back to Fira Barcelona. It's theCUBE live at MWC23 our third day of coverage of this great, huge event continues. Lisa Martin and Dave Nicholson here. We've got Dell and Dish here, we are going to be talking about what they're doing together. Andy Sheahen joins as global director of Telecom Cloud Core and Next Gen Ops at Dell. And Marc Rouanne, one of our alumni is back, EVP and Chief Network Officer at Dish Wireless. Welcome guys. >> Great to be here. >> (Both) Thank you. >> (Lisa) Great to have you. Mark, talk to us about what's going on at Dish wireless. Give us the update. >> Yeah so we've built a network from scratch in the US, that covered the US, we use a cloud base Cloud native, so from the bottom of the tower all the way to the internet uses cloud distributed cloud, emits it, so there are a lot of things about that. But it's unique, and now it's working, so we're starting to play with it and that's pretty cool. >> What's some of the proof points, proof in the pudding? >> Well, for us, first of all it was to do basic voice and data on a smartphone and for me the success would that you won't see the difference for a smartphone. That's base line. the next step is bringing this to the enterprise for their use case. So we've covered- now we have services for smartphones. We use our brand, Boost brand, and we are distributing that across the US. But as I said, the real good stuff is when you start to making you know the machines and all the data and the applications for the enterprise. >> Andy, how is Dell a facilitator of what Marc just described and the use cases and what their able to deliver? >> We're providing a number of the servers that are being used out in their radio access network. The virtual DU servers, we're also providing some bare metal orchestration capabilities to help automate the process of deploying all these hundreds and thousands of nodes out in the field. Both of these, the servers and the bare metal orchestra product are things that we developed in concert with Dish, working together to understand the way, the best way to automate, based on the tooling their using in other parts of their network, and we've been with you guys since day one, really. >> (Marc) Absolutely, yeah. >> Making each others solutions better the whole way. >> Marc, why Dell? >> So, the way the networks work is you have a cloud, and you have a distributed edge you need someone who understands the diversity of the edge in order to bring the cloud software to the edge, and Dell is the best there, you know, you can, we can ask them to mix and match accelerators, processors memory, it's very diverse distributed edge. We are building twenty thousands sides so you imagine the size and the complexity and Dell was the right partner for that. >> (Andy) Thank you. >> So you mentioned addressing enterprise leads, which is interesting because there's nothing that would prevent you from going after consumer wireless technically, right but it sounds like you have taken a look at the market and said "we're going to go after this segment of the market." >> (Marc) Yeah. >> At least for now. Are there significant differences between what an enterprise expects from a 5G network than, verses a consumer? >> Yeah. >> (Dave) They have higher expectations, maybe, number one I guess is, if my bill is 150 dollars a month I can have certain levels of expectations whereas a large enterprise the may be making a much more significant investment, are their expectations greater? >> (Marc) Yeah. >> Do you have a higher bar to get over? >> So first, I mean first we use our network for consumers, but for us it's an enterprise. That's the consumer segment, an enterprise. So we expose the network like we would to a car manufacturer, or to a distributor of goods of food and beverage. But what you expect when you are an enterprise, you expect, manage your services. You expect to control the goodness of your services, and for this you need to observe what's happening. Are you delivering the right service? What is the feedback from the enterprise users, and that's what we call the observability. We have a data centric network, so our enterprises are saying "Yeah connecting is enough, but show us how it works, and show us how we can learn from the data, improve, improve, and become more competitive." That's the big difference. >> So what you say Marc, are some of the outcomes you achieved working with Dell? TCO, ROI, CapX, OpX, what are some of the outcomes so far, that you've been able to accomplish? >> Yeah, so obviously we don't share our numbers, but we're very competitive. Both on the CapX and the OpX. And the second thing is that we are much faster in terms of innovation, you know one of the things that Telecorp would not do, was to tap into the IT industry. So we access to the silicon and we have access to the software and at a scale that none of the Telecorp could ever do and for us it's like "wow" and it's a very powerful industry and we've been driving the consist- it's a bit technical but all the silicone, the accelerators, the processors, the GPU, the TPUs and it's like wow. It's really a transformation. >> Andy, is there anything anagallis that you've dealt with in the past to the situation where you have this true core edge, environment where you have to instrument the devices that you provide to give that level of observation or observability, whatever the new word is, that we've invented for that. >> Yeah, yeah. >> I mean has there, is there anything- >> Yeah absolutely. >> Is this unprecedented? >> No, no not at all. I mean Dell's been really working at the edge since before the edge was called the edge right, we've been selling, our hardware and infrastructure out to retail shops, branch office locations, you know just smaller form factors outside of data centers for a very long time and so that's sort of the consistency from what we've been doing for 30 years to now the difference is the volume, the different number of permutations as Marc was saying. The different type of accelerator cards, the different SKUS of different server types, the sheer volume of nodes that you have in a nationwide wireless network. So the volumes are much different, the amount of data is much different, but the process is really the same. It's about having the infrastructure in the right place at the right time and being able to understand if it's working well or if it's not and it's not just about a red light or a green light but healthy and unhealthy conditions and predicting when the red lights going to come on. And we've been doing that for a while it's just a different scale, and a different level of complexity when you're trying to piece together all these different components from different vendors. >> So we talk a lot about ecosystem, and sometimes because of the desire to talk about the outcomes and what the end users, customers, really care about sometimes we will stop at the layer where say a Dell lives, and we'll see that as the sum total of the component when really, when you talk about a server that Dish is using that in and of itself is an ecosystem >> Yep, yeah >> (Dave) or there's an ecosystem behind it you just mentioned it, the kinds of components and the choices that you make when you optimize these devices determine how much value Dish, >> (Andy) Absolutely. >> Can get out of that. How deep are you on that hardware? I'm a knuckle dragging hardware guy. >> Deep, very deep, I mean just the number of permutations that were working through with Dish and other operators as well, different accelerator cards that we talked about, different techniques for timing obviously there's different SKUs with the silicon itself, different chip sets, different chips from different providers, all those things have to come together, and we build the basic foundation and then we also started working with our cloud partners Red Hat, Wind River, all these guys, VM Ware, of course and that's the next layer up, so you've got all the different hardware components, you've got the extraction layer, with your virtualization layer and or ubernetise layer and all of that stuff together has to be managed compatibility matrices that get very deep and very big, very quickly and that's really the foundational challenge we think of open ran is thinking all these different pieces are going to fit together and not just work today but work everyday as everything gets updated much more frequently than in the legacy world. >> So you care about those things, so we don't have to. >> That's right. >> That's the beauty of it. >> Yes. >> Well thank you. (laughter) >> You're welcome. >> I want to understand, you know some of the things that we've been talking about, every company is a data company, regardless of whether it's telco, it's a retailer, if it's my bank, it's my grocery store and they have to be able to use data as quickly as possible to make decisions. One of the things they've been talking here is the monetization of data, the monetization of the network. How do you, how does Dell help, like a Dish be able to achieve the monetization of their data. >> Well as Marc was saying before the enterprise use cases are what we are all kind of betting on for 5G, right? And enterprises expect to have access to data and to telemetry to do whatever use cases they want to execute in their particular industry, so you know, if it's a health care provider, if it's a factory, an agricultural provider that's leveraging this network, they need to get the data from the network, from the devices, they need to correlate it, in order to do things like automatically turn on a watering system at a certain time, right, they need to know the weather around make sure it's not too windy and you're going to waste a lot of water. All that has data, it's going to leverage data from the network, it's going to leverage data from devices, it's going to leverage data from applications and that's data that can be monetized. When you have all that data and it's all correlated there's value, inherit to it and you can even go onto a forward looking state where you can intelligently move workloads around, based on the data. Based on the clarity of the traffic of the network, where is the right place to put it, and even based on current pricing for things like on demand insists from cloud providers. So having all that data correlated allows any enterprise to make an intelligent decision about how to move a workload around a network and get the most efficient placing of that workload. >> Marc, Andy mentions things like data and networks and moving data across the networks. You have on your business card, Chief Network Officer, what potentially either keeps you up at night in terror or gets you very excited about the future of your network? What's out there in the frontier and what are those key obstacles that have to be overcome that you work with? >> Yeah, I think we have the network, we have the baseline, but we don't yet have the consumption that is easy by the enterprise, you know an enterprise likes to say "I have 4K camera, I connect it to my software." Click, click, right? And that's where we need to be so we're talking about it APIs that are so simple that they become a click and we engineers we have a tendency to want to explain but we should not, it should become a click. You know, and the phone revolution with the apps became those clicks, we have to do the same for the enterprise, for video, for surveillance, for analytics, it has to be clicks. >> While balancing flexibility, and agility of course because you know the folks who were fans of CLIs come in light interfaces, who hate gooeys it's because they feel they have the ability to go down to another level, so obviously that's a balancing act. >> But that's our job. >> Yeah. >> Our job is to hide the complexity, but of course there is complexity. It's like in the cloud, an emprise scaler, they manage complex things but it's successful if they hide it. >> (Dave) Yeah. >> It's the same. You know we have to be emprise scaler of connectivity but hide it. >> Yeah. >> So that people connect everything, right? >> Well it's Andy's servers, we're all magicians hiding it all. >> Yeah. >> It really is. >> It's like don't worry about it, just know, >> Let us do it. >> Sit down, we will serve you the meal. Don't worry how it's cooked. >> That's right, the enterprises want the outcome. >> (Dave) Yeah. >> They don't want to deal with that bottom layer. But it is tremendously complex and we want to take that on and make it better for the industry. >> That's critical. Marc I'd love to go back to you and just I know that you've been in telco for such a long time and here we are day three of MWC the name changed this year, from Mobile World Congress, reflecting mobilism isn't the only thing, obviously it was the catalyst, but what some of the things that you've heard at the event, maybe seen at the event that give you the confidence that the right players are here to help move Dish wireless forward, for example. >> You know this is the first, I've been here for decades it's the first time, and I'm a Chief Network Officer, first time we don't talk about the network. >> (Andy) Yeah. >> Isn't that surprising? People don't tell me about speed, or latency, they talk about consumption. Apps, you know videos surveillance, or analytics or it's, so I love that, because now we're starting to talk about how we can consume and monetize but that's the first time. We use to talk about gigabytes and this and that, none of that not once. >> What does that signify to you, in terms of the evolution? >> Well you know, we've seen that the demand for the healthcare, for the smart cities, has been here for a decade, proof of concepts for a decade but the consumption has been behind and for me this is the oldest team is waking up to we are going to make it easy, so that the consumption can take off. The demand is there, we have to serve it. And the fact that people are starting to say we hide the complexity that's our problem, but don't even mention it, I love it. >> Yep. Drop the mic. >> (Andy and Marc) Yeah, yeah. >> Andy last question for you, some of the things we know Dell has a big and verging presents in telco, we've had a chance to see the booth, see the cool things you guys are featuring there, Dave did a great tour of it, talk about some of the things you've heard and maybe even from customers at this event that demonstrate to you that Dell is going in the right direction with it's telco strategy. >> Yeah, I mean personally for me this has been an unbelievable event for Dell we've had tons and tons of customer meetings of course and the feedback we're getting is that the things we're bring to market whether it's infrablocks, or purposeful servers that are designed for the telecom network are what our customers need and have always wanted. We get a lot of wows, right? >> (Lisa) That's nice. >> "Wow we didn't know Dell was doing this, we had no idea." And the other part of it is that not everybody was sure that we were going to move as fast as we have so the speed in which we've been able to bring some of these things to market and part of that was working with Dish, you know a pioneer, to make sure we were building the right things and I think a lot of the customers that we talked to really appreciate the fact that we're doing it with the industry, >> (Lisa) Yeah. >> You know, not at the industry and that comes across in the way they are responding and what their talking to us about now. >> And that came across in the interview that you just did. Thank you both for joining Dave and me. >> Thank you >> Talking about what Dell and Dish are doing together the proof is in the pudding, and you did a great job at explaining that, thanks guys, we appreciate it. >> Thank you. >> All right, our pleasure. For our guest and for Dave Nicholson, I'm Lisa Martin, you're watching theCUBE live from MWC 23 day three. We will be back with our next guest, so don't go anywhere. (upbeat music)

>> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Welcome back to Barcelona, Spain, everyone. It's theCUBE live at MWC '23, day three of four days of CUBE coverage. It's like a cannon of CUBE content coming right at you. I'm Lisa Martin with Dave Nicholson. We've got Dell and VMware here. Going to be talking about the ecosystem partnerships and what they're doing to further organizations in the telco industry. Please welcome Jared Woodrey, Director of Partner Engineering Open Telecom Ecosystem Lab, OTEL. Odded Solomon is here as well, Director of Product Management, VMware Service Provider and Edge Business Unit at VMware. Guys, great to have you on the program. >> Thank you for having me. >> Welcome to theCUBE. So Jared, first question for you. Talk about OTEL. I know there's a big announcement this week, but give the audience context and understanding of what OTEL is and how it works. >> Sure. So the Open Telecom Ecosystem Lab is physically located at Round Rock, Texas, it's the heart and soul of it. But this week we also just announced opening up the Cork, Ireland extension of OTEL. The reason for our existence is to to try and make it as easy as possible for both partners and customers to come together and to re-aggregate this disaggregated ecosystem. So that comes with a number of automation tools and basically just giving a known good testing environment so that tests that happen in our lab are as close to real world as they possibly can be and make it as transparent and open as possible for both partners like VMware as well as customers. >> Odded, talk about what you're doing with Dell and OTEL and give us a customer example of maybe one that you're working with or even even mentioning it by a high level descriptor if you have to. >> Yeah. So we provide a telco cloud platform, which is essentially a vertical in VMware. The telco cloud platform is serving network function vendors, such as Ericsson, Nokia, Mavenir, and so on. What we do with Dell as part of this partnership is essentially complementing the platform with some additional functionality that is not coming out of the box. We used to have a data protection in the past, but this is no longer our main business focus. So we do provide APIs that we can expose and work together with Dell PPDM solution so customer can benefit from this and leverage the partnership and have overall solution that is not coming out of the box from VMware. >> I'm curious, from a VMware perspective. VMware is associated often with the V in VMware, virtualization, and we've seen a transition over time between sort of flavors of virtualization and what is the mix currently today in the telecom space between environments that are leveraging what we would think of as more traditional virtualization with full blown Linux, Windows operating systems in a VM versus the world of containerized microservices? What does that mix look like today? Where do you see it going? >> Yeah, so the VMware telco cloud platform exists for about eight years. And the V started around that time. You might heard about open stack in addition to VMware. So this has definitely helped the network equipment providers with virtualizing their network functions. Those are typically VNF, virtualized network functions, inside the VMs. Essentially we have 4G applications, so core applications, EPC, we have IMS. Those are typically, I would say maybe 80 or 90% of the ecosystem right now. 5G is associated with cloud native network functions. So 5G is getting started now, getting deployed. There is an exponential growth on the core side. Now, when we expand towards the edge of the network we see more potential growth. This is 5G ran, we see the vRAN, we see the open RAN, we see early POCs, we see field trials that are starting. We obviously has production customer now. You just spoke to one. So this is really starting, cloud native is really starting I would say about 10 to 20% of the network functions these days are cloud native. >> Jared, question for you. You mentioned data protection, a huge topic there obviously from a security perspective. Data protection used to be the responsibility of the CSPs. You guys are changing that. Can you talk a little bit about how you're doing that and what Dell's play there is? >> Yeah, so PowerProtect Data Management is a product, but it's produced by Dell. So what this does is it enables data protection over virtual cloud as well as the physical infrastructure of specifically in this case of a telecoms ecosystem. So what this does is enables an ability to rapidly redeploy and back up existing configurations all the way up to the TCP and TCA that pulls the basis of our work here with VMware. >> So you've offloaded that responsibility from the CSPs. You freed them from that. >> So the work that we did, honestly was to make sure that we have a very clear and concise and accurate procedures for how to conduct this as well. And to put this through a realistic and real world as if it was in a telecoms own production network, what did that would actually look like, and what it would take to bring it back up as well. So our responsibility is to make sure that when we when we provide these products to the customers that not only do they work exactly as their intended to, but there is also documentation to help support them and to enable them to have their exact specifications met by as well. >> Got it. So talk about a little bit about OTEL expansion into Cork. What you guys are doing together to enable CSPs here in EMEA? >> Yeah, so the reason why we opened up a facility in Cork Island was to give, for an EMEA audience, for an EMEA CSPs and ability to look and feel and touch some of the products that we're working on. It also just facilitates and ease especially for European-based partners to have a chance to very easily come to a lab environment. The difference though, honestly, is the between Round Rock, Texas and Cork Island is that it's virtually an extension of the same thing. Like the physical locations can make it easier to provide access and obviously to showcase the products that we've developed with partners. But the reality is that it's more than just the physical location. It's more about the ability and ease by which customers and partners can access the labs. >> So we should be expecting a lot of Tito's vodka to be consumed in Cork at some point. Might change the national beverage. >> We do need to have some international exchange. >> Yeah, no, that's good to know. Odded, on the VMware side of things. There's a large group of folks who have VMware skillsets. >> Odded: Correct. >> The telecom industry is moving into this world of the kind of agility that those folks are familiar with. How do people come out of the traditional VMware virtualization world and move into that world of cloud native applications and serve the telecom space? What would your recommendation be? If you were speaking at a VMUG, a VMware Users Group meeting with all of your telecom background, what would you share with them that's critical to understand about how telecom is different, or how telecom's spot in its evolution might be different than the traditional IT space? >> So we're talking about the people with the knowledge and the background of. >> Yeah, I'm a V expert, let's say. And I'm looking into the future and I hear that there are 80,000 people in Barcelona at this event, and I hear that Dell is building optimized infrastructure specifically for telecom, and that VMware is involved. And I'm an expert in VMware and I want to be involved. What do I need to do? I know it's a little bit outside of the box question, but especially against the backdrop of economic headwinds globally, there are a lot of people facing transitions. What are your thoughts there? >> So, first of all, we understand the telco requirements, we understand the telco needs, and we make sure that what we learn from the customers, what we learn from the partners is being built into the VMware products. And simplicity is number one thing that is important for us. We want the customer experience, we want the user experience to be the same as they know even though we are transitioning into cloud native networks that require more frequent upgrades and they have more complexity to be honest. And what we do in our vertical inside VMware we are focusing on automation, telco cloud automation, telco cloud service assurance. Think of it as a wrapper around the SDDC stack that we have from VMware that really simplifies the operations for the telcos because it's really a challenge about skillset. You need to be a DevOps, SRE in order to operate these networks. And things are becoming really complex. We simplify it for them with the same VMware experience. We have a very good ability to do that. We sell products in VMware. Unlike our competition that is mostly selling professional services and support, we try to focus more on the products and delivering the value. Of course, we have services offering because telcos requires some customizations, but we do focus on automation simplicity throughout our staff. >> So just follow up. So in other words the investment in education in this VMware ecosystem absolutely can be extended and applied into the telecom world. I think it's an important thing. >> I was going to add to that. Our engagement in OTEL was also something that we created a solutions brief whether we released from Mobile World Congress this week. But in conjunction with that, we also have a white paper coming out that has a much more expansive explanation and documentation of what it was that we accomplished in the work that we've done together. And that's not something that is going to be a one-off thing. This is something that will stay evergreen that we'll continue to expand both the testing scope as well as the documentation for what this solution looks like and how it can be used as well as documentation on for the V experts for how they can then leverage and realize the the potential for what we're creating together. >> Jared, does Dell look at OTEL as having the potential to facilitate the continued evolution of the actual telco industry? And if so, how? >> Well, I mean, it would be a horrible answer if I were to say no to that. >> Right. >> I think, I honestly believe that one of the most difficult things about this idea of having desired ecosystem is not just trying to put it back together, but then also how to give yourself choice. So each time that you build one of those solution sets like that exists as an island out of all the other possibilities that comes with it. And OTEL seeks to not just be able to facilitate building that first solution set. Like that's what solutions engineering can do. And that's generally done relatively protected and internally. The Open Telecom Ecosystem seeks to build that then to also provide the ability to very easily change specific components of that whether that's a hardware component, a NIC, whether a security pass just came out or a change in either TCP or TCA or we talked a little bit about for this specific engagement that it was done on TCP 2.5. >> Odded: Correct. >> Obviously there's already a 2.7 and 3.0 is coming out. It's not like we're going to sit around and write our coattails of what 2.7 has happened. So this isn't intended to be a one and done thing. So when we talk about trying to make that easier and simpler and de-risk all of the risk that comes from trying to put all these things together, it's not just the the one single solution that you built in the lab. It's what's the next one? And how do I optimize this? And I have specific requirements as a CSP, how can I take something you built that doesn't quite match it, but how do I make that adjustment? So that's what we see to do and make it as easy and as painless as possible. >> What's the engagement model with CSPs? Is it led by Dell only, VMware partner? How does that work? >> Yeah, I can take that. So that depends on the customer, but typically customers they want to choose the cloud vendor. So they come to VMware, we want VMware. Typically, they come from the IT side. They said, "Oh, we want to manage the network side of the house the same way as we manage the IT. We don't want to have special skill sets, special teams." So they move from the IT to the network side and they want VMware there. And then obviously they have an RSP process and they have hardware choices. They can go with Dell, they can go with others. We leverage vSphere, other compatibility. So we can be flexible with the customer choice. And then depending on which customer, how large they are, they select the network equipment provider that the runs on top. We position our platform as multi-vendor. So many of them choose multiple network functions providers. So we work with Dell. So assuming that the customer is choosing Dell. We work very closely with them, offering the best solution for the customer. We work with them sometimes to even design the boxes to make sure that it fits their use cases and to make sure that it works properly. So we have a partnership validation certification end-to-end from the applications all the way down to the hardware. >> It's a fascinating place in history to be right now with 5G. Something that a lot of consumers sort of assume. It's like, "Oh, hey, yeah, we're already there. What's the 6G thing going to look like?" Well, wait a minute, we're just at the beginning stages. And so you talk about disaggregation, re-aggregation, or reintegration, the importance of that. Folks like Dell have experience in that space. Folks at VMware have a lot of experience in the virtualization space, but I heard that VMware is being acquired by Broadcom, if it all goes through, of course. You don't need to comment on it. But you mentioned something, SDDC, software-defined data center. That stack is sometimes misunderstood by the public at large and maybe the folks in the EU, I will editorialize for a moment here. It is eliminating capture in a way by larger hyperscale cloud providers. It absolutely introduces more competition into the market space. So it's interesting to hear Broadcom acknowledging that this is part of the future of VMware, no matter what else happens. These capabilities that spill into the telecom space are something that they say they're going to embrace and extend. I think that's important for anyone who's evaluating this if they're concern. Well, wait a minute. Yeah, when I reintegrate, do I want VMware as part of this mix? Is that an unknown? It's pretty clear that that's something that is part of the future of VMware moving forward. That's my personal opinion based on analysis. But you brought up SDDC, so I wanted to mention that. Again, I'm not going to ask you to get into trouble on that at all. What should we be, from a broad perspective, are there any services, outcomes that are going to come out of all of this work? The agility that's being built by you folks and folks in the open world. Are there any specific things that you personally are excited about? Or when we think about consumer devices, getting data, what are the other kinds of things that this facilitates? Anything cool, either one of you. >> So specific use cases? >> Yeah, anything. It's got to be cool though. If it's not cool we're going to ask you to leave. >> All right. I'll take that challenge. (laughs) I think one of the things that is interesting for something like OTEL as an exist, as being an Open Telecom Ecosystem, there are going to be some CSPs that it's very difficult for them to have this optionality existing for themselves. Especially when you start talking about tailoring it for specific CSPs and their needs. One of the things that becomes much more available to some of the smaller CSPs is the ability to leverage OTEL and basically act as one of their pre-production labs. So this would be something that would be very specific to a customer and we would obviously make sure that it's completely isolated but the intention there would be that it would open up the ability for what would normally take a much longer time period for them to receive some of the benefits of some of the changes that are happening within the industry. But they would have immediate benefit by leveraging specifically looking OTEL to provide them some of their solutions. And I know that you were also looking for specific use cases out of it, but like that's a huge deal for a lot of CSPs around the world that don't have the ability to lay out all the different permutations that they are most interested in and start to put each one of those through a test cycle. A specific use cases for what this looks like is honestly the most exciting that I've seen for right now is on the private 5G networks. Specifically within mining industry, we have a, sorry for the audience, but we have a demo at our booth that starts to lay out exactly how it was deployed and kind of the AB of what this looked like before the world of private 5G for this mining company and what it looks like afterwards. And the ability for both safety, as well as operational costs, as well as their ability to obviously do their job better is night and day. It completely opened up a very analog system and opened up to a very digitalized system. And I would be remiss, I didn't also mention OpenBrew, which is also an example in our booth. >> We saw it last night in action. >> We saw it. >> I hope you did. So OpenBrew is small brewery in Northeast America and we basically took a very manual process of checking temperature and pressure on multiple different tanks along the entire brewing process and digitized everything for them. All of that was enabled by a private 5G deployment that's built on Dell hardware. >> You asked for cool. I think we got it. >> Yeah, it's cool. >> Jared: I think beer. >> Cool brew, yes. >> Root beer, I think is trump card there. >> At least for folks from North America, we like our brew cool. >> Exactly. Guys, thank you so much for joining Dave and me talking about what Dell, OTEL, and VMware are doing together, what you're enabling CSPs to do and achieve. We appreciate your time and your insights. >> Absolutely. >> Thank you. >> All right, our pleasure. For our guests and for Dave Nicholson, I'm Lisa Martin. You watching theCUBE live from MWC '23. Day three of our coverage continues right after a short break. (upbeat music)