(energetic music) >> Everyone, welcome back to theCUBE's coverage of WiDS 2023. This is the eighth annual Women in Data Science Conference. As you know, WiDS is not just a conference or an event, it's a movement. This is going to include over 100,000 people in the next year WiDS 2023 in 200-plus countries. It is such a powerful movement. If you've had a chance to be part of the Livestream or even be here in person with us at Stanford University, you know what I'm talking about. This is Lisa Martin. I have had the pleasure all day of working with two fantastic graduate students in Stanford's Data Journalism Master's Program. Hannah Freitag has been here. Tracy Zhang, ladies, it's been such a pleasure working with you today. >> Same wise. >> I want to ask you both what are, as we wrap the day, I'm so inspired, I feel like I could go build an airplane. >> Exactly. >> Probably can't. But WiDS is just the inspiration that comes from this event. When you walk in the front door, you can feel it. >> Mm-hmm. >> Tracy, talk a little bit about what some of the things are that you heard today that really inspired you. >> I think one of the keyword that's like in my mind right now is like finding a mentor. >> Yeah. >> And I think, like if I leave this conference if I leave the talks, the conversations with one thing is that I'm very positive that if I want to switch, say someday, from Journalism to being a Data Analyst, to being like in Data Science, I'm sure that there are great role models for me to look up to, and I'm sure there are like mentors who can guide me through the way. So, like that, I feel reassured for some reason. >> It's a good feeling, isn't it? What do you, Hannah, what about you? What's your takeaway so far of the day? >> Yeah, one of my key takeaways is that anything's possible. >> Mm-hmm. >> So, if you have your vision, you have the role model, someone you look up to, and even if you have like a different background, not in Data Science, Data Engineering, or Computer Science but you're like, "Wow, this is really inspiring. I would love to do that." As long as you love it, you're passionate about it, and you are willing to, you know, take this path even though it won't be easy. >> Yeah. >> Then you can achieve it, and as you said, Tracy, it's important to have mentors on the way there. >> Exactly. >> But as long as you speak up, you know, you raise your voice, you ask questions, and you're curious, you can make it. >> Yeah. >> And I think that's one of my key takeaways, and I was just so inspiring to hear like all these women speaking on stage, and also here in our conversations and learning about their, you know, career path and what they learned on their way. >> Yeah, you bring up curiosity, and I think that is such an important skill. >> Mm-hmm. >> You know, you could think of Data Science and think about all the hard skills that you need. >> Mm, like coding. >> But as some of our guests said today, you don't have to be a statistician or an engineer, or a developer to get into this. Data Science applies to every facet of every part of the world. >> Mm-hmm. >> Finances, marketing, retail, manufacturing, healthcare, you name it, Data Science has the power and the potential to unlock massive achievements. >> Exactly. >> It's like we're scratching the surface. >> Yeah. >> But that curiosity, I think, is a great skill to bring to anything that you do. >> Mm-hmm. >> And I think we... For the female leaders that we're on stage, and that we had a chance to talk to on theCUBE today, I think they all probably had that I think as a common denominator. >> Exactly. >> That curious mindset, and also something that I think as hard is the courage to raise your hand. I like this, I'm interested in this. I don't see anybody that looks like me. >> But that doesn't mean I shouldn't do it. >> Exactly. >> Exactly, in addition to the curiosity that all the women, you know, bring to the table is that, in addition to that, being optimistic, and even though we don't see gender equality or like general equality in companies yet, we make progress and we're optimistic about it, and we're not like negative and complaining the whole time. But you know, this positive attitude towards a trend that is going in the right direction, and even though there's still a lot to be done- >> Exactly. >> We're moving it that way. >> Right. >> Being optimistic about this. >> Yeah, exactly, like even if it means that it's hard. Even if it means you need to be your own role model it's still like worth a try. And I think they, like all of the great women speakers, all the female leaders, they all have that in them, like they have the courage to like raise their hand and be like, "I want to do this, and I'm going to make it." And they're role models right now, so- >> Absolutely, they have drive. >> They do. >> Right. They have that ambition to take something that's challenging and complicated, and help abstract end users from that. Like we were talking to Intuit. I use Intuit in my small business for financial management, and she was talking about how they can from a machine learning standpoint, pull all this data off of documents that you upload and make that, abstract that, all that complexity from the end user, make something that's painful taxes. >> Mm-hmm. >> Maybe slightly less painful. It's still painful when you have to go, "Do I have to write you a check again?" >> Yeah. (laughs) >> Okay. >> But talking about just all the different applications of Data Science in the world, I found that to be very inspiring and really eye-opening. >> Definitely. >> I hadn't thought about, you know, we talk about climate change all the time, especially here in California, but I never thought about Data Science as a facilitator of the experts being able to make sense of what's going on historically and in real-time, or the application of Data Science in police violence. We see far too many cases of police violence on the news. It's an epidemic that's a horrible problem. Data Science can be applied to that to help us learn from that, and hopefully, start moving the needle in the right direction. >> Absolutely. >> Exactly. >> And especially like one sentence from Guitry from the very beginnings I still have in my mind is then when she said that arguments, no, that data beats arguments. >> Yes. >> In a conversation that if you be like, okay, I have this data set and it can actually show you this or that, it's much more powerful than just like being, okay, this is my position or opinion on this. And I think in a world where increasing like misinformation, and sometimes, censorship as we heard in one of the talks, it's so important to have like data, reliable data, but also acknowledge, and we talked about it with one of our interviewees that there's spices in data and we also need to be aware of this, and how to, you know, move this forward and use Data Science for social good. >> Mm-hmm. >> Yeah, for social good. >> Yeah, definitely, I think they like data, and the question about, or like the problem-solving part about like the social issues, or like some just questions, they definitely go hand-in-hand. Like either of them standing alone won't be anything that's going to be having an impact, but combining them together, you have a data set that illustrate a point or like solves the problem. I think, yeah, that's definitely like where Data Set Science is headed to, and I'm glad to see all these great women like making their impact and combining those two aspects together. >> It was interesting in the keynote this morning. We were all there when Margot Gerritsen who's one of the founders of WiDS, and Margot's been on the program before and she's a huge supporter of what we do and vice versa. She asked the non-women in the room, "Those who don't identify as women, stand up," and there was a handful of men, and she said, "That's what it's like to be a female in technology." >> Oh, my God. >> And I thought that vision give me goosebumps. >> Powerful. (laughs) >> Very powerful. But she's right, and one of the things I think that thematically another common denominator that I think we heard, I want to get your opinions as well from our conversations today, is the importance of community. >> Mm-hmm. >> You know, I was mentioning this stuff from AnitaB.org that showed that in 2022, the percentage of females and technical roles is 27.6%. It's a little bit of an increase. It's been hovering around 25% for a while. But one of the things that's still a problem is attrition. It doubled last year. >> Right. >> And I was asking some of the guests, and we've all done that today, "How would you advise companies to start moving the needle down on attrition?" >> Mm-hmm. >> And I think the common theme was network, community. >> Exactly. >> It takes a village like this. >> Mm-hmm. >> So you can see what you can be to help start moving that needle and that's, I think, what underscores the value of what WiDS delivers, and what we're able to showcase on theCUBE. >> Yeah, absolutely. >> I think it's very important to like if you're like a woman in tech to be able to know that there's someone for you, that there's a whole community you can rely on, and that like you are, you have the same mindset, you're working towards the same goal. And it's just reassuring and like it feels very nice and warm to have all these women for you. >> Lisa: It's definitely a warm fuzzy, isn't it? >> Yeah, and both the community within the workplace but also outside, like a network of family and friends who support you to- >> Yes. >> To pursue your career goals. I think that was also a common theme we heard that it's, yeah, necessary to both have, you know your community within your company or organization you're working but also outside. >> Definitely, I think that's also like how, why, the reason why we feel like this in like at WiDS, like I think we all feel very positive right now. So, yeah, I think that's like the power of the connection and the community, yeah. >> And the nice thing is this is like I said, WiDS is a movement. >> Yes. >> This is global. >> Mm-hmm. >> We've had some WiDS ambassadors on the program who started WiDS and Tel Aviv, for example, in their small communities. Or in Singapore and Mumbai that are bringing it here and becoming more of a visible part of the community. >> Tracy: Right. >> I loved seeing all the young faces when we walked in the keynote this morning. You know, we come here from a journalistic perspective. You guys are Journalism students. But seeing all the potential in the faces in that room just seeing, and hearing stories, and starting to make tangible connections between Facebook and data, and the end user and the perspectives, and the privacy and the responsibility of AI is all... They're all positive messages that need to be reinforced, and we need to have more platforms like this to be able to not just raise awareness, but sustain it. >> Exactly. >> Right. It's about the long-term, it's about how do we dial down that attrition, what can we do? What can we do? How can we help? >> Mm-hmm. >> Both awareness, but also giving women like a place where they can connect, you know, also outside of conferences. Okay, how do we make this like a long-term thing? So, I think WiDS is a great way to, you know, encourage this connectivity and these women teaming up. >> Yeah, (chuckles) girls help girls. >> Yeah. (laughs) >> It's true. There's a lot of organizations out there, girls who Code, Girls Inc., et cetera, that are all aimed at helping women kind of find their, I think, find their voice. >> Exactly. >> And find that curiosity. >> Yeah. Unlock that somewhere back there. Get some courage- >> Mm-hmm. >> To raise your hand and say, "I think I want to do this," or "I have a question. You explained something and I didn't understand it." Like, that's the advice I would always give to my younger self is never be afraid to raise your hand in a meeting. >> Mm-hmm. >> I guarantee you half the people weren't listening or, and the other half may not have understood what was being talked about. >> Exactly. >> So, raise your hand, there goes Margot Gerritsen, the founder of WiDS, hey, Margot. >> Hi. >> Keep alumni as you know, raise your hand, ask the question, there's no question that's stupid. >> Mm-hmm. >> And I promise you, if you just take that chance once it will open up so many doors, you won't even know which door to go in because there's so many that are opening. >> And if you have a question, there's at least one more person in the room who has the exact same question. >> Exact same question. >> Yeah, we'll definitely keep that in mind as students- >> Well, I'm curious how Data Journalism, what you heard today, Tracy, we'll start with you, and then, Hannah, to you. >> Mm-hmm. How has it influenced how you approach data-driven, and storytelling? Has it inspired you? I imagine it has, or has it given you any new ideas for, as you round out your Master's Program in the next few months? >> I think like one keyword that I found really helpful from like all the conversations today, was problem-solving. >> Yeah. >> Because I think, like we talked a lot about in our program about how to put a face on data sets. How to put a face, put a name on a story that's like coming from like big data, a lot of numbers but you need to like narrow it down to like one person or one anecdote that represents a bigger problem. And I think essentially that's problem-solving. That's like there is a community, there is like say maybe even just one person who has, well, some problem about something, and then we're using data. We're, by giving them a voice, by portraying them in news and like representing them in the media, we're solving this problem somehow. We're at least trying to solve this problem, trying to make some impact. And I think that's like what Data Science is about, is problem-solving, and, yeah, I think I heard a lot from today's conversation, also today's speakers. So, yeah, I think that's like something we should also think about as Journalists when we do pitches or like what kind of problem are we solving? >> I love that. >> Or like kind of what community are we trying to make an impact in? >> Yes. >> Absolutely. Yeah, I think one of the main learnings for me that I want to apply like to my career in Data Journalism is that I don't shy away from complexity because like Data Science is oftentimes very complex. >> Complex. >> And also data, you're using for your stories is complex. >> Mm-hmm. >> So, how can we, on the one hand, reduce complexity in a way that we make it accessible for broader audience? 'Cause, we don't want to be this like tech bubble talking in data jargon, we want to, you know, make it accessible for a broader audience. >> Yeah. >> I think that's like my purpose as a Data Journalist. But at the same time, don't reduce complexity when it's needed, you know, and be open to dive into new topics, and data sets and circling back to this of like raising your hand and asking questions if you don't understand like a certain part. >> Yeah. >> So, that's definitely a main learning from this conference. >> Definitely. >> That like, people are willing to talk to you and explain complex topics, and this will definitely facilitate your work as a Data Journalist. >> Mm-hmm. >> So, that inspired me. >> Well, I can't wait to see where you guys go from here. I've loved co-hosting with you today, thank you. >> Thank you. >> For joining me at our conference. >> Wasn't it fun? >> Thank you. >> It's a great event. It's, we, I think we've all been very inspired and I'm going to leave here probably floating above the ground a few inches, high on the inspiration of what this community can deliver, isn't that great? >> It feels great, I don't know, I just feel great. >> Me too. (laughs) >> So much good energy, positive energy, we love it. >> Yeah, so we want to thank all the organizers of WiDS, Judy Logan, Margot Gerritsen in particular. We also want to thank John Furrier who is here. And if you know Johnny, know he gets FOMO when he is not hosting. But John and Dave Vellante are such great supporters of women in technology, women in technical roles. We wouldn't be here without them. So, shout out to my bosses. Thank you for giving me the keys to theCube at this event. I know it's painful sometimes, but we hope that we brought you great stories all day. We hope we inspired you with the females and the one male that we had on the program today in terms of raise your hand, ask a question, be curious, don't be afraid to pursue what you're interested in. That's my soapbox moment for now. So, for my co-host, I'm Lisa Martin, we want to thank you so much for watching our program today. You can watch all of this on-demand on thecube.net. You'll find write-ups on siliconeangle.com, and, of course, YouTube. Thanks, everyone, stay safe and we'll see you next time. (energetic music)

(upbeat music) >> Welcome back to theCUBE's coverage of Women in Data Science 2023 live from Stanford University. This is Lisa Martin. My co-host is Tracy Yuan. We're excited to be having great conversations all day but you know, 'cause you've been watching. We've been interviewing some very inspiring women and some men as well, talking about all of the amazing applications of data science. You're not going to want to miss this next conversation. Our guest is Gabriela de Queiroz, Principal Cloud Advocate Manager of Microsoft. Welcome, Gabriela. We're excited to have you. >> Thank you very much. I'm so excited to be talking to you. >> Yeah, you're on theCUBE. >> Yeah, finally. (Lisa laughing) Like a dream come true. (laughs) >> I know and we love that. We're so thrilled to have you. So you have a ton of experience in the data space. I was doing some research on you. You've worked in software, financial advertisement, health. Talk to us a little bit about you. What's your background in? >> So I was trained in statistics. So I'm a statistician and then I worked in epidemiology. I worked with air pollution and public health. So I was a researcher before moving into the industry. So as I was talking today, the weekly paths, it's exactly who I am. I went back and forth and back and forth and stopped and tried something else until I figured out that I want to do data science and that I want to do different things because with data science we can... The beauty of data science is that you can move across domains. So I worked in healthcare, financial, and then different technology companies. >> Well the nice thing, one of the exciting things that data science, that I geek out about and Tracy knows 'cause we've been talking about this all day, it's just all the different, to your point, diverse, pun intended, applications of data science. You know, this morning we were talking about, we had the VP of data science from Meta as a keynote. She came to theCUBE talking and really kind of explaining from a content perspective, from a monetization perspective, and of course so many people in the world are users of Facebook. It makes it tangible. But we also heard today conversations about the applications of data science in police violence, in climate change. We're in California, we're expecting a massive rainstorm and we don't know what to do when it rains or snows. But climate change is real. Everyone's talking about it, and there's data science at its foundation. That's one of the things that I love. But you also have a lot of experience building diverse teams. Talk a little bit about that. You've created some very sophisticated data science solutions. Talk about your recommendation to others to build diverse teams. What's in it for them? And maybe share some data science project or two that you really found inspirational. >> Yeah, absolutely. So I do love building teams. Every time I'm given the task of building teams, I feel the luckiest person in the world because you have the option to pick like different backgrounds and all the diverse set of like people that you can find. I don't think it's easy, like people say, yeah, it's very hard. You have to be intentional. You have to go from the very first part when you are writing the job description through the interview process. So you have to be very intentional in every step. And you have to think through when you are doing that. And I love, like my last team, we had like 10 people and we were so diverse. Like just talking about languages. We had like 15 languages inside a team. So how beautiful it is. Like all different backgrounds, like myself as a statistician, but we had people from engineering background, biology, languages, and so on. So it's, yeah, like every time thinking about building a team, if you wanted your team to be diverse, you need to be intentional. >> I'm so glad you brought up that intention point because that is the fundamental requirement really is to build it with intention. >> Exactly, and I love to hear like how there's different languages. So like I'm assuming, or like different backgrounds, I'm assuming everybody just zig zags their way into the team and now you're all women in data science and I think that's so precious. >> Exactly. And not only woman, right. >> Tracy: Not only woman, you're right. >> The team was diverse not only in terms of like gender, but like background, ethnicity, and spoken languages, and language that they use to program and backgrounds. Like as I mentioned, not everybody did the statistics in school or computer science. And it was like one of my best teams was when we had this combination also like things that I'm good at the other person is not as good and we have this knowledge sharing all the time. Every day I would feel like I'm learning something. In a small talk or if I was reviewing something, there was always something new because of like the richness of the diverse set of people that were in your team. >> Well what you've done is so impressive, because not only have you been intentional with it, but you sound like the hallmark of a great leader of someone who hires and builds teams to fill gaps. They don't have to know less than I do for me to be the leader. They have to have different skills, different areas of expertise. That is really, honestly Gabriela, that's the hallmark of a great leader. And that's not easy to come by. So tell me, who were some of your mentors and sponsors along the way that maybe influenced you in that direction? Or is that just who you are? >> That's a great question. And I joke that I want to be the role model that I never had, right. So growing up, I didn't have anyone that I could see other than my mom probably or my sister. But there was no one that I could see, I want to become that person one day. And once I was tracing my path, I started to see people looking at me and like, you inspire me so much, and I'm like, oh wow, this is amazing and I want to do do this over and over and over again. So I want to be that person to inspire others. And no matter, like I'll be like a VP, CEO, whoever, you know, I want to be, I want to keep inspiring people because that's so valuable. >> Lisa: Oh, that's huge. >> And I feel like when we grow professionally and then go to the next level, we sometimes we lose that, you know, thing that's essential. And I think also like, it's part of who I am as I was building and all my experiences as I was going through, I became what I mentioned is unique person that I think we all are unique somehow. >> You're a rockstar. Isn't she a rockstar? >> You dropping quotes out. >> I'm loving this. I'm like, I've inspired Gabriela. (Gabriela laughing) >> Oh my God. But yeah, 'cause we were asking our other guests about the same question, like, who are your role models? And then we're talking about how like it's very important for women to see that there is a representation, that there is someone they look up to and they want to be. And so that like, it motivates them to stay in this field and to start in this field to begin with. So yeah, I think like you are definitely filling a void and for all these women who dream to be in data science. And I think that's just amazing. >> And you're a founder too. In 2012, you founded R Ladies. Talk a little bit about that. This is present in more than 200 cities in 55 plus countries. Talk about R Ladies and maybe the catalyst to launch it. >> Yes, so you always start, so I'm from Brazil, I always talk about this because it's such, again, I grew up over there. So I was there my whole life and then I moved to here, Silicon Valley. And when I moved to San Francisco, like the doors opened. So many things happening in the city. That was back in 2012. Data science was exploding. And I found out something about Meetup.com, it's a website that you can join and go in all these events. And I was going to this event and I joke that it was kind of like going to the Disneyland, where you don't know if I should go that direction or the other direction. >> Yeah, yeah. >> And I was like, should I go and learn about data visualization? Should I go and learn about SQL or should I go and learn about Hadoop, right? So I would go every day to those meetups. And I was a student back then, so you know, the budget was very restricted as a student. So we don't have much to spend. And then they would serve dinner and you would learn for free. And then I got to a point where I was like, hey, they are doing all of this as a volunteer. Like they are running this meetup and events for free. And I felt like it's a cycle. I need to do something, right. I'm taking all this in. I'm having this huge opportunity to be here. I want to give back. So that's what how everything started. I was like, no, I have to think about something. I need to think about something that I can give back. And I was using R back then and I'm like how about I do something with R. I love R, I'm so passionate about R, what about if I create a community around R but not a regular community, because by going to this events, I felt that as a Latina and as a woman, I was always in the corner and I was not being able to participate and to, you know, be myself and to network and ask questions. I would be in the corner. So I said to myself, what about if I do something where everybody feel included, where everybody can participate, can share, can ask questions without judgment? So that's how R ladies all came together. >> That's awesome. >> Talk about intentions, like you have to, you had that go in mind, but yeah, I wanted to dive a little bit into R. So could you please talk more about where did the passion for R come from, and like how did the special connection between you and R the language, like born, how did that come from? >> It was not a love at first sight. >> No. >> Not at all. Not at all. Because that was back in Brazil. So all the documentation were in English, all the tutorials, only two. We had like very few tutorials. It was not like nowadays that we have so many tutorials and courses. There were like two tutorials, other documentation in English. So it's was hard for me like as someone that didn't know much English to go through the language and then to learn to program was not easy task. But then as I was going through the language and learning and reading books and finding the people behind the language, I don't know how I felt in love. And then when I came to to San Francisco, I saw some of like the main contributors who are speaking in person and I'm like, wow, they are like humans. I don't know, it was like, I have no idea why I had this love. But I think the the people and then the community was the thing that kept me with the R language. >> Yeah, the community factors is so important. And it's so, at WIDS it's so palpable. I mean I literally walk in the door, every WIDS I've done, I think I've been doing them for theCUBE since 2017. theCUBE has been here since the beginning in 2015 with our co-founders. But you walk in, you get this sense of belonging. And this sense of I can do anything, why not? Why not me? Look at her up there, and now look at you speaking in the technical talk today on theCUBE. So inspiring. One of the things that I always think is you can't be what you can't see. We need to be able to see more people that look like you and sound like you and like me and like you as well. And WIDS gives us that opportunity, which is fantastic, but it's also helping to move the needle, really. And I was looking at some of the Anitab.org stats just yesterday about 2022. And they're showing, you know, the percentage of females in technical roles has been hovering around 25% for a while. It's a little higher now. I think it's 27.6 according to any to Anitab. We're seeing more women hired in roles. But what are the challenges, and I would love to get your advice on this, for those that might be in this situation is attrition, women who are leaving roles. What would your advice be to a woman who might be trying to navigate family and work and career ladder to stay in that role and keep pushing forward? >> I'll go back to the community. If you don't have a community around you, it's so hard to navigate. >> That's a great point. >> You are lonely. There is no one that you can bounce ideas off, that you can share what you are feeling or like that you can learn as well. So sometimes you feel like you are the only person that is going through that problem or like, you maybe have a family or you are planning to have a family and you have to make a decision. But you've never seen anyone going through this. So when you have a community, you see people like you, right. So that's where we were saying about having different people and people like you so they can share as well. And you feel like, oh yeah, so they went through this, they succeed. I can also go through this and succeed. So I think the attrition problem is still big problem. And I'm sure will be worse now with everything that is happening in Tech with layoffs. >> Yes and the great resignation. >> Yeah. >> We are going back, you know, a few steps, like a lot of like advancements that we did. I feel like we are going back unfortunately, but I always tell this, make sure that you have a community. Make sure that you have a mentor. Make sure that you have someone or some people, not only one mentor, different mentors, that can support you through this trajectory. Because it's not easy. But there are a lot of us out there. >> There really are. And that's a great point. I love everything about the community. It's all about that network effect and feeling like you belong- >> That's all WIDS is about. >> Yeah. >> Yes. Absolutely. >> Like coming over here, it's like seeing the old friends again. It's like I'm so glad that I'm coming because I'm all my old friends that I only see like maybe once a year. >> Tracy: Reunion. >> Yeah, exactly. And I feel like that our tank get, you know- >> Lisa: Replenished. >> Exactly. For the rest of the year. >> Yes. >> Oh, that's precious. >> I love that. >> I agree with that. I think one of the things that when I say, you know, you can't see, I think, well, how many females in technology would I be able to recognize? And of course you can be female technology working in the healthcare sector or working in finance or manufacturing, but, you know, we need to be able to have more that we can see and identify. And one of the things that I recently found out, I was telling Tracy this earlier that I geeked out about was finding out that the CTO of Open AI, ChatGPT, is a female. I'm like, (gasps) why aren't we talking about this more? She was profiled on Fast Company. I've seen a few pieces on her, Mira Murati. But we're hearing so much about ChatJTP being... ChatGPT, I always get that wrong, about being like, likening it to the launch of the iPhone, which revolutionized mobile and connectivity. And here we have a female in the technical role. Let's put her on a pedestal because that is hugely inspiring. >> Exactly, like let's bring everybody to the front. >> Yes. >> Right. >> And let's have them talk to us because like, you didn't know. I didn't know probably about this, right. You didn't know. Like, we don't know about this. It's kind of like we are hidden. We need to give them the spotlight. Every woman to give the spotlight, so they can keep aspiring the new generation. >> Or Susan Wojcicki who ran, how long does she run YouTube? All the YouTube influencers that probably have no idea who are influential for whatever they're doing on YouTube in different social platforms that don't realize, do you realize there was a female behind the helm that for a long time that turned it into what it is today? That's outstanding. Why aren't we talking about this more? >> How about Megan Smith, was the first CTO on the Obama administration. >> That's right. I knew it had to do with Obama. Couldn't remember. Yes. Let's let's find more pedestals. But organizations like WIDS, your involvement as a speaker, showing more people you can be this because you can see it, >> Yeah, exactly. is the right direction that will help hopefully bring us back to some of the pre-pandemic levels, and keep moving forward because there's so much potential with data science that can impact everyone's lives. I always think, you know, we have this expectation that we have our mobile phone and we can get whatever we want wherever we are in the world and whatever time of day it is. And that's all data driven. The regular average person that's not in tech thinks about data as a, well I'm paying for it. What's all these data charges? But it's powering the world. It's powering those experiences that we all want as consumers or in our business lives or we expect to be able to do a transaction, whether it's something in a CRM system or an Uber transaction like that, and have the app respond, maybe even know me a little bit better than I know myself. And that's all data. So I think we're just at the precipice of the massive impact that data science will make in our lives. And luckily we have leaders like you who can help navigate us along this path. >> Thank you. >> What advice for, last question for you is advice for those in the audience who might be nervous or maybe lack a little bit of confidence to go I really like data science, or I really like engineering, but I don't see a lot of me out there. What would you say to them? >> Especially for people who are from like a non-linear track where like going onto that track. >> Yeah, I would say keep going. Keep going. I don't think it's easy. It's not easy. But keep going because the more you go the more, again, you advance and there are opportunities out there. Sometimes it takes a little bit, but just keep going. Keep going and following your dreams, that you get there, right. So again, data science, such a broad field that doesn't require you to come from a specific background. And I think the beauty of data science exactly is this is like the combination, the most successful data science teams are the teams that have all these different backgrounds. So if you think that we as data scientists, we started programming when we were nine, that's not true, right. You can be 30, 40, shifting careers, starting to program right now. It doesn't matter. Like you get there no matter how old you are. And no matter what's your background. >> There's no limit. >> There was no limits. >> I love that, Gabriela, >> Thank so much. for inspiring. I know you inspired me. I'm pretty sure you probably inspired Tracy with your story. And sometimes like what you just said, you have to be your own mentor and that's okay. Because eventually you're going to turn into a mentor for many, many others and sounds like you're already paving that path and we so appreciate it. You are now officially a CUBE alumni. >> Yes. Thank you. >> Yay. We've loved having you. Thank you so much for your time. >> Thank you. Thank you. >> For our guest and for Tracy's Yuan, this is Lisa Martin. We are live at WIDS 23, the eighth annual Women in Data Science Conference at Stanford. Stick around. Our next guest joins us in just a few minutes. (upbeat music)

(upbeat music) >> Hey, girls and guys. Welcome back to theCUBE. We are live at Stanford University, covering the 8th Annual Women in Data Science Conference. One of my favorite events. Lisa Martin here. Got a couple of guests from Total Energies. We're going to be talking all things data science, and I think you're going to find this pretty interesting and inspirational. Please welcome Alexandre Lapene, Tech Advisor Data Science at Total Energy. It's great to have you. >> Thank you. >> And Myriam Fayad is here as well, product and value manager at Total Energies. Great to have you guys on theCUBE today. Thank you for your time. >> Thank you for - >> Thank you for receiving us. >> Give the audience, Alexandre, we'll start with you, a little bit about Total Energies, so they understand the industry, and what it is that you guys are doing. >> Yeah, sure, sure. So Total Energies, is a former Total, so we changed name two years ago. So we are a multi-energy company now, working over 130 countries in the world, and more than 100,000 employees. >> Lisa: Oh, wow, big ... >> So we're a quite big company, and if you look at our new logo, you will see there are like seven colors. That's the seven energy that we basically that our business. So you will see the red for the oil, the blue for the gas, because we still have, I mean, a lot of oil and gas, but you will see other color, like blue for hydrogen. >> Lisa: Okay. >> Green for gas, for biogas. >> Lisa: Yeah. >> And a lot of other solar and wind. So we're definitely multi-energy company now. >> Excellent, and you're both from Paris? I'm jealous, I was supposed to go. I'm not going to be there next month. Myriam, talk a little bit about yourself. I'd love to know a little bit about your role. You're also a WiDS ambassador this year. >> Myriam: Yes. >> Lisa: Which is outstanding, but give us a little bit of your background. >> Yes, so today I'm a product manager at the Total Energies' Digital Factory. And at the Digital Factory, our role is to develop digital solutions for all of the businesses of Total Energies. And as a background, I did engineering school. So, and before that I, I would say, I wasn't really aware of, I had never asked myself if being a woman could stop me from being, from doing what I want to do in the professional career. But when I started my engineering school, I started seeing that women are becoming, I would say, increasingly rare in the environment >> Lisa: Yes. >> that, where I was evolving. >> Lisa: Yes. >> So that's why I was, I started to think about, about such initiatives. And then when I started working in the tech field, that conferred me that women are really rare in the tech field and data science field. So, and at Total Energies, I met ambassadors of, of the WiDS initiatives. And that's how I, I decided to be a WiDS Ambassador, too. So our role is to organize events locally in the countries where we work to raise awareness about the importance of having women in the tech and data fields. And also to talk about the WiDS initiative more globally. >> One of my favorite things about WiDS is it's this global movement, it started back in 2015. theCUBE has been covering it since then. I think I've been covering it for theCUBE since 2017. It's always a great day full of really positive messages. One of the things that we talk a lot about when we're focusing on the Q1 Women in Tech, or women in technical roles is you can't be what you can't see. We need to be able to see these role models, but also it, we're not just talking about women, we're talking about underrepresented minorities, we're talking about men like you, Alexander. Talk to us a little bit about what your thoughts are about being at a Women and Data Science Conference and your sponsorship, I'm sure, of many women in Total, and other industries that appreciate having you as a guide. >> Yeah, yeah, sure. First I'm very happy because I'm back to Stanford. So I did my PhD, postdoc, sorry, with Margot, I mean, back in 20, in 2010, so like last decade. >> Lisa: Yeah, yep. >> I'm a film mechanics person, so I didn't start as data scientist, but yeah, WiDS is always, I mean, this great event as you describe it, I mean, to see, I mean it's growing every year. I mean, it's fantastic. And it's very, I mean, I mean, it's always also good as a man, I mean, to, to be in the, in the situation of most of the women in data science conferences. And when Margo, she asked at the beginning of the conference, "Okay, how many men do we have? Okay, can you stand up?" >> Lisa: Yes. I saw that >> It was very interesting because - >> Lisa: I could count on one hand. >> What, like 10 or ... >> Lisa: Yeah. >> Maximum. >> Lisa: Yeah. >> And, and I mean, you feel that, I mean, I mean you could feel what what it is to to be a woman in the field and - >> Lisa: Absolutely. >> Alexandre: That's ... >> And you, sounds like you experienced it. I experienced the same thing. But one of the things that fascinates me about data science is all of the different real world problems it's helping to solve. Like, I keep saying this, we're, we're in California, I'm a native Californian, and we've been in an extreme drought for years. Well, we're getting a ton of rain and snow this year. Climate change. >> Guests: Yeah. We're not used to driving in the rain. We are not very good at it either. But the, just thinking about data science as a facilitator of its understanding climate change better; to be able to make better decisions, predictions, drive better outcomes, or things like, police violence or healthcare inequities. I think the power of data science to help unlock a lot of the unknown is so great. And, and we need that thought diversity. Miriam, you're talking about being in engineering. Talk to me a little bit about what projects interest you with respect to data science, and how you are involved in really creating more diversity and thought. >> Hmm. In fact, at Total Energies in addition to being an energy company we're also a data company in the sense that we produce a lot of data in our activities. For example with the sensors on the fuel on the platforms. >> Lisa: Yes. >> Or on the wind turbines, solar panels and even data related to our clients. So what, what is really exciting about being, working in the data science field at Total Energies is that we really feel the impact of of the project that we're working on. And we really work with the business to understand their problems. >> Lisa: Yeah. >> Or their issues and try to translate it to a technical problem and to solve it with the data that we have. So that's really exciting, to feel the impact of the projects we're working on. So, to take an example, maybe, we know that one of the challenges of the energy transition is the storage of of energy coming from renewable power. >> Yes. >> So I'm working currently on a project to improve the process of creating larger batteries that will help store this energy, by collecting the data, and helping the business to improve the process of creating these batteries. To make it more reliable, and with a better quality. So this is a really interesting project we're working on. >> Amazing, amazing project. And, you know, it's, it's fun I think to think of all of the different people, communities, countries, that are impacted by what you're doing. Everyone, everyone knows about data. Sometimes we think about it as we're paying we're always paying for a lot of data on our phone or "data rates may apply" but we may not be thinking about all of the real world impact that data science is making in our lives. We have this expectation in our personal lives that we're connected 24/7. >> Myriam: Yeah. >> I can get whatever I want from my phone wherever I am in the world. And that's all data driven. And we expect that if I'm dealing with Total Energies, or a retailer, or a car dealer that they're going to have the data, the data to have a personal conversation, conversation with me. We have this expectation. I don't think a lot of people that aren't in data science or technology really realize the impact of data all around their lives. Alexander, talk about some of the interesting data science projects that you're working on. >> There's one that I'm working right now, so I stake advisor. I mean, I'm not the one directly working on it. >> Lisa: Okay. >> But we have, you know, we, we are from the digital factory where we, we make digital products. >> Lisa: Okay. >> And we have different squads. I mean, it's a group of different people with different skills. And one of, one of the, this squad, they're, they're working on the on, on the project that is about safety. We have a lot of site, work site on over the world where we deploy solar panels on on parkings, on, on buildings everywhere. >> Lisa: Okay. Yeah. >> And there's, I mean, a huge, I mean, but I mean, we, we have a lot of, of worker and in term of safety we want to make sure that the, they work safely and, and we want to prevent accidents. So what we, what we do is we, we develop some computer vision approach to help them at improving, you know, the, the, the way they work. I mean the, the basic things is, is detecting, detecting some equipment like the, the the mean the, the vest and so on. But we, we, we, we are working, we're working to really extend that to more concrete recommendation. And that's one a very exciting project. >> Lisa: Yeah. >> Because it's very concrete. >> Yeah. >> And also, I, I'm coming from the R&D of the company and that's one, that's one of this project that started in R&D and is now into the Digital Factory. And it will become a real product deployed over the world on, on our assets. So that's very great. >> The influence and the impact that data can have on every business always is something that, we could talk about that for a very long time. >> Yeah. >> But one of the things I want to address is there, I'm not sure if you're familiar with AnitaB.org the Grace Hopper Institute? It's here in the States and they do this great event every year. It's very pro-women in technology and technical roles. They do a lot of, of survey of, of studies. So they have data demonstrating where are we with respect to women in technical roles. And we've been talking about it for years. It's been, for a while hovering around 25% of technical roles are held by women. I noticed in the AnitaB.org research findings from 2022, It's up to 27.6% I believe. So we're seeing those numbers slowly go up. But one of the things that's a challenge is attrition; of women getting in the roles and then leaving. Miryam, as a woman in, in technology. What inspires you to continue doing what you're doing and to elevate your career in data science? >> What motivates me, is that data science, we really have to look at it as a mean to solve a problem and not a, a fine, a goal in itself. So the fact that we can apply data science to so many fields and so many different projects. So here, for example we took examples of more industrial, maybe, applications. But for example, recently I worked on, on a study, on a data science study to understand what to, to analyze Google reviews of our clients on the service stations and to see what are the the topics that, that are really important to them. So we really have a, a large range of topics, and a diversity of topics that are really interesting, so. >> And that's so important, the diversity of topics alone. There's, I think we're just scratching the surface. We're just at the very beginning of what data science can empower for our daily lives. For businesses, small businesses, large businesses. I'd love to get your perspective as our only male on the show today, Alexandre, you have that elite title. The theme of International Women's Day this year which is today, March 8th, is "Embrace equity." >> Alexandre: Yes. >> Lisa: What is that, when you hear that theme as as a male in technology, as a male in the, in a role where you can actually elevate women and really bring in that thought diversity, what is embracing equity, what does it look like to you? >> To me, it, it's really, I mean, because we, we always talk about how we can, you know, I mean improve, but actually we are fixing a problem, an issue. I mean, it's such a reality. I mean, and the, the reality and and I mean, and force in, in the company. And that's, I think in Total Energy, we, we still have, I mean things, I mean, we, we haven't reached our objective but we're working hard and especially at the Digital Factory to, to, to improve on that. And for example, we have 40% of our women in tech. >> Lisa: 40? >> 40% of our tech people that are women. >> Lisa: Wow, that's fantastic! >> Yeah. That's, that's ... >> You're way ahead of, of the global average. >> Alexandre: Yeah. Yeah. >> That outstanding. >> We're quite proud of that. >> You should be. >> But we, we still, we still know that we, we have at least 10% >> Lisa: Yes. because it's not 50. The target is, the target is to 50 or more. And, and, but I want to insist on the fact that we have, we are correcting an issue. We are fixing an issue. We're not trying to improve something. I mean, that, that's important to have that in mind. >> Lisa: It is. Absolutely. >> Yeah. >> Miryam, I'd love to get your advice to your younger self, before you studied engineering. Obviously you had an interest when you were younger. What advice would you give to young Miriam now, looking back at what you've accomplished and being one of our female, visible females, in a technical role? What do you, what would you say to your younger self? >> Maybe I would say to continue as I started. So as I was saying at the beginning of the interview, when I was at high school, I have never felt like being a woman could stop me from doing anything. >> Lisa: Yeah. Yeah. >> So maybe to continue thinking this way, and yeah. And to, to stay here for, to, to continue this way. Yeah. >> Lisa: That's excellent. Sounds like you have the confidence. >> Mm. Yeah. >> And that's something that, that a lot of people ... I struggled with it when I was younger, have the confidence, "Can I do this?" >> Alexandre: Yeah. >> "Should I do this?" >> Myriam: Yeah. >> And you kind of went, "Why not?" >> Myriam: Yes. >> Which is, that is such a great message to get out to our audience and to everybody else's. Just, "I'm interested in this. I find it fascinating. Why not me?" >> Myriam: Yeah. >> Right? >> Alexandre: Yeah, true. >> And by bringing out, I think, role models as we do here at the conference, it's a, it's a way to to help young girls to be inspired and yeah. >> Alexandre: Yeah. >> We need to have women in leadership positions that we can see, because there's a saying here that we say a lot in the States, which is: "You can't be what you can't see." >> Alexandre: Yeah, that's true. >> And so we need more women and, and men supporting women and underrepresented minorities. And the great thing about WiDS is it does just that. So we thank you so much for your involvement in WiDS, Ambassador, our only male on the program today, Alexander, we thank you. >> I'm very proud of it. >> Awesome to hear that Total Energies has about 40% of females in technical roles and you're on that path to 50% or more. We, we look forward to watching that journey and we thank you so much for joining us on the show today. >> Alexandre: Thank you. >> Myriam: Thank you. >> Lisa: All right. For my guests, I'm Lisa Martin. You're watching theCUBE Live from Stanford University. This is our coverage of the eighth Annual Women in Data Science Conference. We'll be back after a short break, so stick around. (upbeat 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.

(upbeat music) >> Morning guys and girls, welcome back to theCUBE's live coverage of Women in Data Science WIDS 2023 live at Stanford University. Lisa Martin here with my co-host for this segment, Tracy Zhang. We're really excited to be talking with a great female rockstar. You're going to learn a lot from her next, Jacqueline Kuo, solutions engineer at Dataiku. Welcome, Jacqueline. Great to have you. >> Thank you so much. >> Thank for being here. >> I'm so excited to be here. >> So one of the things I have to start out with, 'cause my mom Kathy Dahlia is watching, she's a New Yorker. You are a born and raised New Yorker and I learned from my mom and others. If you're born in New York no matter how long you've moved away, you are a New Yorker. There's you guys have like a secret club. (group laughs) >> I am definitely very proud of being born and raised in New York. My family immigrated to New York, New Jersey from Taiwan. So very proud Taiwanese American as well. But I absolutely love New York and I can't imagine living anywhere else. >> Yeah, yeah. >> I love it. >> So you studied, I was doing some research on you you studied mechanical engineering at MIT. >> Yes. >> That's huge. And you discovered your passion for all things data-related. You worked at IBM as an analytics consultant. Talk to us a little bit about your career path. Were you always interested in engineering STEM-related subjects from the time you were a child? >> I feel like my interests were ranging in many different things and I ended up landing in engineering, 'cause I felt like I wanted to gain a toolkit like a toolset to make some sort of change with or use my career to make some sort of change in this world. And I landed on engineering and mechanical engineering specifically, because I felt like I got to, in my undergrad do a lot of hands-on projects, learn every part of the engineering and design process to build products which is super-transferable and transferable skills sort of is like the trend in my career so far. Where after undergrad I wanted to move back to New York and mechanical engineering jobs are kind of few and fall far in between in the city. And I ended up landing at IBM doing analytics consulting, because I wanted to understand how to use data. I knew that data was really powerful and I knew that working with it could allow me to tell better stories to influence people across different industries. And that's also how I kind of landed at Dataiku to my current role, because it really does allow me to work across different industries and work on different problems that are just interesting. >> Yeah, I like the way that, how you mentioned building a toolkit when doing your studies at school. Do you think a lot of skills are still very relevant to your job at Dataiku right now? >> I think that at the core of it is just problem solving and asking questions and continuing to be curious or trying to challenge what is is currently given to you. And I think in an engineering degree you get a lot of that. >> Yeah, I'm sure. >> But I think that we've actually seen that a lot in the panels today already, that you get that through all different types of work and research and that kind of thoughtfulness comes across in all different industries too. >> Talk a little bit about some of the challenges, that data science is solving, because every company these days, whether it's an enterprise in manufacturing or a small business in retail, everybody has to be data-driven, because the end user, the end customer, whoever that is whether it's a person, an individual, a company, a B2B, expects to have a personalized custom experience and that comes from data. But you have to be able to understand that data treated properly, responsibly. Talk about some of the interesting projects that you're doing at Dataiku or maybe some that you've done in the past that are really kind of transformative across things climate change or police violence, some of the things that data science really is impacting these days. >> Yeah, absolutely. I think that what I love about coming to these conferences is that you hear about those really impactful social impact projects that I think everybody who's in data science wants to be working on. And I think at Dataiku what's great is that we do have this program called Ikig.AI where we work with nonprofits and we support them in their data and analytics projects. And so, a project I worked on was with the Clean Water, oh my goodness, the Ocean Cleanup project, Ocean Cleanup organization, which was amazing, because it was sort of outside of my day-to-day and it allowed me to work with them and help them understand better where plastic is being aggregated across the world and where it appears, whether that's on beaches or in lakes and rivers. So using data to help them better understand that. I feel like from a day-to-day though, we, in terms of our customers, they're really looking at very basic problems with data. And I say basic, not to diminish it, but really just to kind of say that it's high impact, but basic problems around how do they forecast sales better? That's a really kind of, sort of basic problem, but it's actually super-complex and really impactful for people, for companies when it comes to forecasting how much headcount they need to have in the next year or how much inventory to have if they're retail. And all of those are going to, especially for smaller companies, make a huge impact on whether they make profit or not. And so, what's great about working at Dataiku is you get to work on these high-impact projects and oftentimes I think from my perspective, I work as a solutions engineer on the commercial team. So it's just, we work generally with smaller customers and sometimes talking to them, me talking to them is like their first introduction to what data science is and what they can do with that data. And sort of using our platform to show them what the possibilities are and help them build a strategy around how they can implement data in their day-to-day. >> What's the difference? You were a data scientist by title and function, now you're a solutions engineer. Talk about the ascendancy into that and also some of the things that you and Tracy will talk about as those transferable, those transportable skills that probably maybe you learned in engineering, you brought data science now you're bringing to solutions engineering. >> Yeah, absolutely. So data science, I love working with data. I love getting in the weeds of things and I love, oftentimes that means debugging things or looking line by line at your code and trying to make it better. I found that on in the data science role, while those things I really loved, sometimes it also meant that I didn't, couldn't see or didn't have visibility into the broader picture of well like, well why are we doing this project? And who is it impacting? And because oftentimes your day-to-day is very much in the weeds. And so, I moved into sales or solutions engineering at Dataiku to get that perspective, because what a sales engineer does is support the sale from a technical perspective. And so, you really truly understand well, what is the customer looking for and what is going to influence them to make a purchase? And how do you tell the story of the impact of data? Because oftentimes they need to quantify well, if I purchase a software like Dataiku then I'm able to build this project and make this X impact on the business. And that is really powerful. That's where the storytelling comes in and that I feel like a lot of what we've been hearing today about connecting data with people who can actually do something with that data. That's really the bridge that we as sales engineers are trying to connect in that sales process. >> It's all about connectivity, isn't it? >> Yeah, definitely. We were talking about this earlier that it's about making impact and it's about people who we are analyzing data is like influencing. And I saw that one of the keywords or one of the biggest thing at Dataiku is everyday AI, so I wanted to just ask, could you please talk more about how does that weave into the problem solving and then day-to-day making an impact process? >> Yes, so I started working on Dataiku around three years ago and I fell in love with the product itself. The product that we have is we allow for people with different backgrounds. If you're coming from a data analyst background, data science, data engineering, maybe you are more of like a business subject matter expert, to all work in one unified central platform, one user interface. And why that's powerful is that when you're working with data, it's not just that data scientist working on their own and their own computer coding. We've heard today that it's all about connecting the data scientists with those business people, with maybe the data engineers and IT people who are actually going to put that model into production or other folks. And so, they all use different languages. Data scientists might use Python and R, your business people are using PowerPoint and Excel, everyone's using different tools. How do we bring them all in one place so that you can have conversations faster? So the business people can understand exactly what you're building with the data and can get their hands on that data and that model prediction faster. So that's what Dataiku does. That's the product that we have. And I completely forgot your question, 'cause I got so invested in talking about this. Oh, everyday AI. Yeah, so the goal of of Dataiku is really to allow for those maybe less technical people with less traditional data science backgrounds. Maybe they're data experts and they understand the data really well and they've been working in SQL for all their career. Maybe they're just subject matter experts and want to get more into working with data. We allow those people to do that through our no and low-code tools within our platform. Platform is very visual as well. And so, I've seen a lot of people learn data science, learn machine learning by working in the tool itself. And that's sort of, that's where everyday AI comes in, 'cause we truly believe that there are a lot of, there's a lot of unutilized expertise out there that we can bring in. And if we did give them access to data, imagine what we could do in the kind of work that they can do and become empowered basically with that. >> Yeah, we're just scratching the surface. I find data science so fascinating, especially when you talk about some of the real world applications, police violence, health inequities, climate change. Here we are in California and I don't know if you know, we're experiencing an atmospheric river again tomorrow. Californians and the rain- >> Storm is coming. >> We are not good... And I'm a native Californian, but we all know about climate change. People probably don't associate all of the data that is helping us understand it, make decisions based on what's coming what's happened in the past. I just find that so fascinating. But I really think we're truly at the beginning of really understanding the impact that being data-driven can actually mean whether you are investigating climate change or police violence or health inequities or your a grocery store that needs to become data-driven, because your consumer is expecting a personalized relevant experience. I want you to offer me up things that I know I was doing online grocery shopping, yesterday, I just got back from Europe and I was so thankful that my grocer is data-driven, because they made the process so easy for me. And but we have that expectation as consumers that it's going to be that easy, it's going to be that personalized. And what a lot of folks don't understand is the data the democratization of data, the AI that's helping make that a possibility that makes our lives easier. >> Yeah, I love that point around data is everywhere and the more we have, the actually the more access we actually are providing. 'cause now compute is cheaper, data is literally everywhere, you can get access to it very easily. And so, I feel like more people are just getting themselves involved and that's, I mean this whole conference around just bringing more women into this industry and more people with different backgrounds from minority groups so that we get their thoughts, their opinions into the work is so important and it's becoming a lot easier with all of the technology and tools just being open source being easier to access, being cheaper. And that I feel really hopeful about in this field. >> That's good. Hope is good, isn't it? >> Yes, that's all we need. But yeah, I'm glad to see that we're working towards that direction. I'm excited to see what lies in the future. >> We've been talking about numbers of women, percentages of women in technical roles for years and we've seen it hover around 25%. I was looking at some, I need to AnitaB.org stats from 2022 was just looking at this yesterday and the numbers are going up. I think the number was 26, 27.6% of women in technical roles. So we're seeing a growth there especially over pre-pandemic levels. Definitely the biggest challenge that still seems to be one of the biggest that remains is attrition. I would love to get your advice on what would you tell your younger self or the previous prior generation in terms of having the confidence and the courage to pursue engineering, pursue data science, pursue a technical role, and also stay in that role so you can be one of those females on stage that we saw today? >> Yeah, that's the goal right there one day. I think it's really about finding other people to lift and mentor and support you. And I talked to a bunch of people today who just found this conference through Googling it, and the fact that organizations like this exist really do help, because those are the people who are going to understand the struggles you're going through as a woman in this industry, which can get tough, but it gets easier when you have a community to share that with and to support you. And I do want to definitely give a plug to the WIDS@Dataiku team. >> Talk to us about that. >> Yeah, I was so fortunate to be a WIDS ambassador last year and again this year with Dataiku and I was here last year as well with Dataiku, but we have grown the WIDS effort so much over the last few years. So the first year we had two events in New York and also in London. Our Dataiku's global. So this year we additionally have one in the west coast out here in SF and another one in Singapore which is incredible to involve that team. But what I love is that everyone is really passionate about just getting more women involved in this industry. But then also what I find fortunate too at Dataiku is that we have a strong female, just a lot of women. >> Good. >> Yeah. >> A lot of women working as data scientists, solutions engineer and sales and all across the company who even if they aren't doing data work in a day-to-day, they are super-involved and excited to get more women in the technical field. And so. that's like our Empower group internally that hosts events and I feel like it's a really nice safe space for all of us to speak about challenges that we encounter and feel like we're not alone in that we have a support system to make it better. So I think from a nutrition standpoint every organization should have a female ERG to just support one another. >> Absolutely. There's so much value in a network in the community. I was talking to somebody who I'm blanking on this may have been in Barcelona last week, talking about a stat that showed that a really high percentage, 78% of people couldn't identify a female role model in technology. Of course, Sheryl Sandberg's been one of our role models and I thought a lot of people know Sheryl who's leaving or has left. And then a whole, YouTube influencers that have no idea that the CEO of YouTube for years has been a woman, who has- >> And she came last year to speak at WIDS. >> Did she? >> Yeah. >> Oh, I missed that. It must have been, we were probably filming. But we need more, we need to be, and it sounds like Dataiku was doing a great job of this. Tracy, we've talked about this earlier today. We need to see what we can be. And it sounds like Dataiku was pioneering that with that ERG program that you talked about. And I completely agree with you. That should be a standard program everywhere and women should feel empowered to raise their hand ask a question, or really embrace, "I'm interested in engineering, I'm interested in data science." Then maybe there's not a lot of women in classes. That's okay. Be the pioneer, be that next Sheryl Sandberg or the CTO of ChatGPT, Mira Murati, who's a female. We need more people that we can see and lean into that and embrace it. I think you're going to be one of them. >> I think so too. Just so that young girls like me like other who's so in school, can see, can look up to you and be like, "She's my role model and I want to be like her. And I know that there's someone to listen to me and to support me if I have any questions in this field." So yeah. >> Yeah, I mean that's how I feel about literally everyone that I'm surrounded by here. I find that you find role models and people to look up to in every conversation whenever I'm speaking with another woman in tech, because there's a journey that has had happen for you to get to that place. So it's incredible, this community. >> It is incredible. WIDS is a movement we're so proud of at theCUBE to have been a part of it since the very beginning, since 2015, I've been covering it since 2017. It's always one of my favorite events. It's so inspiring and it just goes to show the power that data can have, the influence, but also just that we're at the beginning of uncovering so much. Jacqueline's been such a pleasure having you on theCUBE. Thank you. >> Thank you. >> For sharing your story, sharing with us what Dataiku was doing and keep going. More power to you girl. We're going to see you up on that stage one of these years. >> Thank you so much. Thank you guys. >> Our pleasure. >> Our pleasure. >> For our guests and Tracy Zhang, this is Lisa Martin, you're watching theCUBE live at WIDS '23. #EmbraceEquity is this year's International Women's Day theme. Stick around, our next guest joins us in just a minute. (upbeat music)

(ambient music) >> Good morning, everyone. Lisa Martin with theCUBE, live at the eighth Annual Women in Data Science Conference. This is one of my absolute favorite events of the year. We engage with tons of great inspirational speakers, men and women, and what's happening with WiDS is a global movement. I've got two fabulous co-hosts with me today that you're going to be hearing and meeting. Please welcome Tracy Zhang and Hannah Freitag, who are both from the sata journalism program, master's program, at Stanford. So great to have you guys. >> So excited to be here. >> So data journalism's so interesting. Tracy, tell us a little bit about you, what you're interested in, and then Hannah we'll have you do the same thing. >> Yeah >> Yeah, definitely. I definitely think data journalism is very interesting, and in fact, I think, what is data journalism? Is definitely one of the big questions that we ask during the span of one year, which is the length of our program. And yeah, like you said, I'm in this data journalism master program, and I think coming in I just wanted to pivot from my undergrad studies, which is more like a traditional journalism, into data. We're finding stories through data, so that's why I'm also very excited about meeting these speakers for today because they're all, they have different backgrounds, but they all ended up in data science. So I think they'll be very inspirational and I can't wait to talk to them. >> Data in stories, I love that. Hannah, tell us a little bit about you. >> Yeah, so before coming to Stanford, I was a research assistant at Humboldt University in Berlin, so I was in political science research. And I love to work with data sets and data, but I figured that, for me, I don't want this story to end up in a research paper, which is only very limited in terms of the audience. And I figured, okay, data journalism is the perfect way to tell stories and use data to illustrate anecdotes, but to make it comprehensive and accessible for a broader audience. So then I found this program at Stanford and I was like, okay, that's the perfect transition from political science to journalism, and to use data to tell data-driven stories. So I'm excited to be in this program, I'm excited for the conference today and to hear from these amazing women who work in data science. >> You both brought up great points, and we were chatting earlier that there's a lot of diversity in background. >> Tracy: Definitely. >> Not everyone was in STEM as a young kid or studied computer science. Maybe some are engineering, maybe some are are philosophy or economic, it's so interesting. And what I find year after year at WiDS is it brings in so much thought diversity. And that's what being data-driven really demands. It demands that unbiased approach, that diverse, a spectrum of diverse perspectives, and we definitely get that at WiDS. There's about 350 people in person here, but as I mentioned in the opening, hundreds of thousands will engage throughout the year, tens of thousands probably today at local events going on across the globe. And it just underscores the importance of every organization, whether it's a bank or a grocer, has to be data-driven. We have that expectation as consumers in our consumer lives, and even in our business lives, that I'm going to engage with a business, whatever it is, and they're going to know about me, they're going to deliver me a personalized experience that's relevant to me and my history. And all that is powered by data science, which is I think it's fascinating. >> Yeah, and the great way is if you combine data with people. Because after all, large data sets, they oftentimes consist of stories or data that affects people. And to find these stories or advanced research in whatever fields, maybe in the financial business, or in health, as you mentioned, the variety of fields, it's very powerful, powerful tool to use. >> It's a very power, oh, go ahead Tracy. >> No, definitely. I just wanted to build off of that. It's important to put a face on data. So a dataset without a name is just some numbers, but if there's a story, then I think it means something too. And I think Margot was talking about how data science is about knowing or understanding the past, I think that's very interesting. That's a method for us to know who we are. >> Definitely. There's so many opportunities. I wanted to share some of the statistics from AnitaB.org that I was just looking at from 2022. We always talk at events like WiDS, and some of the other women in tech things, theCUBE is very much pro-women in tech, and has been for a very long, since the beginning of theCUBE. But we've seen the numbers of women technologists historically well below 25%, and we see attrition rates are high. And so we often talk about, well, what can we do? And part of that is raising the awareness. And that's one of the great things about WiDS, especially WiDS happening on International Women's Day, today, March 8th, and around event- >> Tracy: A big holiday. >> Exactly. But one of the nice things I was looking at, the AnitaB.org research, is that representation of tech women is on the rise, still below pre-pandemic levels, but it's actually nearly 27% of women in technical roles. And that's an increase, slow increase, but the needle is moving. We're seeing much more gender diversity across a lot of career levels, which is exciting. But some of the challenges remain. I mean, the representation of women technologists is growing, except at the intern level. And I thought that was really poignant. We need to be opening up that pipeline and going younger. And you'll hear a lot of those conversations today about, what are we doing to reach girls in grade school, 10 year olds, 12 year olds, those in high school? How do we help foster them through their undergrad studies- >> And excite them about science and all these fields, for sure. >> What do you think, Hannah, on that note, and I'll ask you the same question, what do you think can be done? The theme of this year's International Women's Day is Embrace Equity. What do you think can be done on that intern problem to help really dial up the volume on getting those younger kids interested, one, earlier, and two, helping them stay interested? >> Yeah. Yeah, that's a great question. I think it's important to start early, as you said, in school. Back in the day when I went to high school, we had this one day per year where we could explore as girls, explore a STEM job and go into the job for one day and see how it's like to work in a, I dunno, in IT or in data science, so that's a great first step. But as you mentioned, it's important to keep girls and women excited about this field and make them actually pursue this path. So I think conferences or networking is very powerful. Also these days with social media and technology, we have more ability and greater ways to connect. And I think we should even empower ourselves even more to pursue this path if we're interested in data science, and not be like, okay, maybe it's not for me, or maybe as a woman I have less chances. So I think it's very important to connect with other women, and this is what WiDS is great about. >> WiDS is so fantastic for that network effect, as you talked about. It's always such, as I was telling you about before we went live, I've covered five or six WiDS for theCUBE, and it's always such a day of positivity, it's a day of of inclusivity, which is exactly what Embrace Equity is really kind of about. Tracy, talk a little bit about some of the things that you see that will help with that hashtag Embrace Equity kind of pulling it, not just to tech. Because we're talking and we saw Meta was a keynote who's going to come to talk with Hannah and me in a little bit, we see Total Energies on the program today, we see Microsoft, Intuit, Boeing Air Company. What are some of the things you think that can be done to help inspire, say, little Tracy back in the day to become interested in STEM or in technology or in data? What do you think companies can and should be doing to dial up the volume for those youngsters? >> Yeah, 'cause I think somebody was talking about, one of the keynote speakers was talking about how there is a notion that girls just can't be data scientists. girls just can't do science. And I think representation definitely matters. If three year old me see on TV that all the scientists are women, I think I would definitely have the notion that, oh, this might be a career choice for me and I can definitely also be a scientist if I want. So yeah, I think representation definitely matters and that's why conference like this will just show us how these women are great in their fields. They're great data scientists that are bringing great insight to the company and even to the social good as well. So yeah, I think that's very important just to make women feel seen in this data science field and to listen to the great woman who's doing amazing work. >> Absolutely. There's a saying, you can't be what you can't see. >> Exactly. >> And I like to say, I like to flip it on its head, 'cause we can talk about some of the negatives, but there's a lot of positives and I want to share some of those in a minute, is that we need to be, that visibility that you talked about, the awareness that you talked about, it needs to be there but it needs to be sustained and maintained. And an organization like WiDS and some of the other women in tech events that happen around the valley here and globally, are all aimed at raising the profile of these women so that the younger, really, all generations can see what they can be. We all, the funny thing is, we all have this expectation whether we're transacting on Uber ride or we are on Netflix or we're buying something on Amazon, we can get it like that. They're going to know who I am, they're going to know what I want, they're going to want to know what I just bought or what I just watched. Don't serve me up something that I've already done that. >> Hannah: Yeah. >> Tracy: Yeah. >> So that expectation that everyone has is all about data, though we don't necessarily think about it like that. >> Hannah: Exactly. >> Tracy: Exactly. >> But it's all about the data that, the past data, the data science, as well as the realtime data because we want to have these experiences that are fresh, in the moment, and super relevant. So whether women recognize it or not, they're data driven too. Whether or not you're in data science, we're all driven by data and we have these expectations that every business is going to meet it. >> Exactly. >> Yeah. And circling back to young women, I think it's crucial and important to have role models. As you said, if you see someone and you're younger and you're like, oh I want to be like her. I want to follow this path, and have inspiration and a role model, someone you look up to and be like, okay, this is possible if I study the math part or do the physics, and you kind of have a goal and a vision in mind, I think that's really important to drive you. >> Having those mentors and sponsors, something that's interesting is, I always, everyone knows what a mentor is, somebody that you look up to, that can guide you, that you admire. I didn't learn what a sponsor was until a Women in Tech event a few years ago that we did on theCUBE. And I was kind of, my eyes were open but I didn't understand the difference between a mentor and a sponsor. And then it got me thinking, who are my sponsors? And I started going through LinkedIn, oh, he's a sponsor, she's a sponsor, people that help really propel you forward, your recommenders, your champions, and it's so important at every level to build that network. And we have, to your point, Hannah, there's so much potential here for data drivenness across the globe, and there's so much potential for women. One of the things I also learned recently , and I wanted to share this with you 'cause I'm not sure if you know this, ChatGPT, exploding, I was on it yesterday looking at- >> Everyone talking about it. >> What's hot in data science? And it was kind of like, and I actually asked it, what was hot in data science in 2023? And it told me that it didn't know anything prior to 2021. >> Tracy: Yes. >> Hannah: Yeah. >> So I said, Oh, I'm so sorry. But everyone's talking about ChatGPT, it is the most advanced AI chatbot ever released to the masses, it's on fire. They're likening it to the launch of the iPhone, 100 million-plus users. But did you know that the CTO of ChatGPT is a woman? >> Tracy: I did not know, but I learned that. >> I learned that a couple days ago, Mira Murati, and of course- >> I love it. >> She's been, I saw this great profile piece on her on Fast Company, but of course everything that we're hearing about with respect to ChatGPT, a lot on the CEO. But I thought we need to help dial up the profile of the CTO because she's only 35, yet she is at the helm of one of the most groundbreaking things in our lifetime we'll probably ever see. Isn't that cool? >> That is, yeah, I completely had no idea. >> I didn't either. I saw it on LinkedIn over the weekend and I thought, I have to talk about that because it's so important when we talk about some of the trends, other trends from AnitaB.org, I talked about some of those positive trends. Overall hiring has rebounded in '22 compared to pre-pandemic levels. And we see also 51% more women being hired in '22 than '21. So the data, it's all about data, is showing us things are progressing quite slowly. But one of the biggest challenges that's still persistent is attrition. So we were talking about, Hannah, what would your advice be? How would you help a woman stay in tech? We saw that attrition last year in '22 according to AnitaB.org, more than doubled. So we're seeing women getting into the field and dropping out for various reasons. And so that's still an extent concern that we have. What do you think would motivate you to stick around if you were in a technical role? Same question for you in a minute. >> Right, you were talking about how we see an increase especially in the intern level for women. And I think if, I don't know, this is a great for a start point for pushing the momentum to start growth, pushing the needle rightwards. But I think if we can see more increase in the upper level, the women representation in the upper level too, maybe that's definitely a big goal and something we should work towards to. >> Lisa: Absolutely. >> But if there's more representation up in the CTO position, like in the managing level, I think that will definitely be a great factor to keep women in data science. >> I was looking at some trends, sorry, Hannah, forgetting what this source was, so forgive me, that was showing that there was a trend in the last few years, I think it was Fast Company, of more women in executive positions, specifically chief operating officer positions. What that hasn't translated to, what they thought it might translate to, is more women going from COO to CEO and we're not seeing that. We think of, if you ask, name a female executive that you'd recognize, everyone would probably say Sheryl Sandberg. But I was shocked to learn the other day at a Women in Tech event I was doing, that there was a survey done by this organization that showed that 78% of people couldn't identify. So to your point, we need more of them in that visible role, in the executive suite. >> Tracy: Exactly. >> And there's data that show that companies that have women, companies across industries that have women in leadership positions, executive positions I should say, are actually more profitable. So it's kind of like, duh, the data is there, it's telling you this. >> Hannah: Exactly. >> Right? >> And I think also a very important point is work culture and the work environment. And as a woman, maybe if you enter and you work two or three years, and then you have to oftentimes choose, okay, do I want family or do I want my job? And I think that's one of the major tasks that companies face to make it possible for women to combine being a mother and being a great data scientist or an executive or CEO. And I think there's still a lot to be done in this regard to make it possible for women to not have to choose for one thing or the other. And I think that's also a reason why we might see more women at the entry level, but not long-term. Because they are punished if they take a couple years off if they want to have kids. >> I think that's a question we need to ask to men too. >> Absolutely. >> How to balance work and life. 'Cause we never ask that. We just ask the woman. >> No, they just get it done, probably because there's a woman on the other end whose making it happen. >> Exactly. So yeah, another thing to think about, another thing to work towards too. >> Yeah, it's a good point you're raising that we have this conversation together and not exclusively only women, but we all have to come together and talk about how we can design companies in a way that it works for everyone. >> Yeah, and no slight to men at all. A lot of my mentors and sponsors are men. They're just people that I greatly admire who saw raw potential in me 15, 18 years ago, and just added a little water to this little weed and it started to grow. In fact, theCUBE- >> Tracy: And look at you now. >> Look at me now. And theCUBE, the guys Dave Vellante and John Furrier are two of those people that are sponsors of mine. But it needs to be diverse. It needs to be diverse and gender, it needs to include non-binary people, anybody, shouldn't matter. We should be able to collectively work together to solve big problems. Like the propaganda problem that was being discussed in the keynote this morning with respect to China, or climate change. Climate change is a huge challenge. Here, we are in California, we're getting an atmospheric river tomorrow. And Californians and rain, we're not so friendly. But we know that there's massive changes going on in the climate. Data science can help really unlock a lot of the challenges and solve some of the problems and help us understand better. So there's so much real-world implication potential that being data-driven can really lead to. And I love the fact that you guys are studying data journalism. You'll have to help me understand that even more. But we're going to going to have great conversations today, I'm so excited to be co-hosting with both of you. You're going to be inspired, you're going to learn, they're going to learn from us as well. So let's just kind of think of this as a community of men, women, everything in between to really help inspire the current generations, the future generations. And to your point, let's help women feel confident to be able to stay and raise their hand for fast-tracking their careers. >> Exactly. >> What are you guys, last minute, what are you looking forward to most for today? >> Just meeting these great women, I can't wait. >> Yeah, learning from each other. Having this conversation about how we can make data science even more equitable and hear from the great ideas that all these women have. >> Excellent, girls, we're going to have a great day. We're so glad that you're here with us on theCUBE, live at Stanford University, Women in Data Science, the eighth annual conference. I'm Lisa Martin, my two co-hosts for the day, Tracy Zhang, Hannah Freitag, you're going to be seeing a lot of us, we appreciate. Stick around, our first guest joins Hannah and me in just a minute. (ambient music)

(upbeat music) >> Welcome back. We're here at Supercomputing 22 in Dallas. My name's Paul Gill, I'm your host. With me, Dave Nicholson, my co-host. And one thing that struck me about this conference arriving here, was the number of universities that are exhibiting here. I mean, big, big exhibits from universities. Never seen that at a conference before. And one of those universities is Indiana University. Our two guests, Dave Jent, who's the AVP of Networks at Indiana University, Aaron Neal, Deputy CIO at Indiana University. Welcome, thanks for joining us. >> Thank you for having us. >> Thank you. >> I've always thought that the CIO job at a university has got to be the toughest CIO job there is, because you're managing this sprawling network, people are doing all kinds of different things on it. You've got to secure it. You've got to make it performant. And it just seems to be a big challenge. Talk about the network at Indiana University and what you have done particularly since the pandemic, how that has affected the architecture of your network. And what you do to maintain the levels of performance and security that you need. >> On the network side one of the things we've done is, kept in close contact with what the incoming students are looking for. It's a different environment than it was then 10 years ago when a student would come, maybe they had a phone, maybe they had one laptop. Today they're coming with multiple phones, multiple laptops, gaming devices. And the expectation that they have to come on a campus and plug all that stuff in causes lots of problems for us, in managing just the security aspect of it, the capacity, the IP space required to manage six, seven devices per student when you have 35,000 students on campus, has always been a challenge. And keeping ahead of that knowing what students are going to come in with, has been interesting. During the pandemic the campus was closed for a bit of time. What we found was our biggest challenge was keeping up with the number of people who wanted to VPN to campus. We had to buy additional VPN licenses so they could do their work, authenticate to the network. We doubled, maybe even tripled our our VPN license count. And that has settled down now that we're back on campus. But again, they came back with a vengeance. More gaming devices, more things to be connected, and into an environment that was a couple years old, that we hadn't done much with. We had gone through a pretty good size network deployment of new hardware to try to get ready for them. And it's worked well, but it's always challenging to keep up with students. >> Aaron, I want to ask you about security because that really is one of your key areas of focus. And you're collaborating with counties, local municipalities, as well as other educational institutions. How's your security strategy evolving in light of some of the vulnerabilities of VPNs that became obvious during the pandemic, and this kind of perfusion of new devices that that Dave was talking about? >> Yeah, so one of the things that we we did several years ago was establish what we call OmniSOC, which is a shared security operations center in collaboration with other institutions as well as research centers across the United States and in Indiana. And really what that is, is we took the lessons that we've learned and the capabilities that we've had within the institution and looked to partner with those key institutions to bring that data in-house, utilize our staff such that we can look for security threats and share that information across the the other institutions so that we can give each of those areas a heads up and work with those institutions to address any kind of vulnerabilities that might be out there. One of the other things that you mentioned is, we're partnering with Purdue in the Indiana Office of Technology on a grant to actually work with municipalities, county governments, to really assess their posture as it relates to security in those areas. It's a great opportunity for us to work together as institutions as well as work with the state in general to increase our posture as it relates to security. >> Dave, what brings IU to Supercomputing 2022? >> We've been here for a long time. And I think one of the things that we're always interested in is, what's next? What's new? There's so many, there's network vendors, software vendors, hardware vendors, high performance computing suppliers. What is out there that we're interested in? IU runs a large Cray system in Indiana called Big Red 200. And with any system you procure it, you get it running, you operate it, and your next goal is to upgrade it. And what's out there that we might be interested? That I think why we come to IU. We also like to showcase what we do at IU. If you come by the booth you'll see the OmniSOC, there's some video on that. The GlobalNOC, which I manage, which supports a lot of the RNE institutions in the country. We talk about that. Being able to have a place for people to come and see us. If you stand by the booth long enough people come and find you, and want to talk about a project they have, or a collaboration they'd like to partner with. We had a guy come by a while ago wanting a job. Those are all good things having a big booth can do for you. >> Well, so on that subject, in each of your areas of expertise and your purview are you kind of interleaved with the academic side of things on campus? Do you include students? I mean, I would think it would be a great source of cheap labor for you at least. Or is there kind of a wall between what you guys are responsible for and what students? >> Absolutely we try to support faculty and students as much as we can. And just to go back a little bit on the OmniSOC discussion. One of the things that we provide is internships for each of the universities that we work with. They have to sponsor at least three students every year and make that financial commitment. We bring them on site for three weeks. They learn us alongside the other analysts, information security analysts and work in a real world environment and gain those skills to be able to go back to their institutions and do an additional work there. So it's a great program for us to work with students. I think the other thing that we do is we provide obviously the infrastructure that enable our faculty members to do the research that they need to do. Whether that's through Big Red 200, our Supercomputer or just kind of the everyday infrastructure that allows them to do what they need to do. We have an environment on premise called our Intelligent Infrastructure, that we provide managed access to hardware and storage resources in a way that we know it's secure and they can utilize that environment to do virtually anything that they need in a server environment. >> Dave, I want to get back to the GigaPOP, which you mentioned earlier you're the managing director of the Indiana GigaPOP. What exactly is it? >> Well, the GigaPOP and there are a number of GigaPOP around the country. It was really the aggregation facility for Indiana and all of the universities in Indiana to connect to outside resources. GigaPOP has connections to internet too, the commodity internet, Esnet, the Big Ten or the BTAA a network in Chicago. It's a way for all universities in Indiana to connect to a single source to allow them to connect nationally to research organizations. >> And what are the benefits of having this collaboration of university. >> If you could think of a researcher at Indiana wants to do something with a researcher in Wisconsin, they both connect to their research networks in Wisconsin and Indiana, and they have essentially direct connection. There's no commodity internet, there's no throttling of of capacity. Both networks and the interconnects because we use internet too, are essentially UNT throttled access for the researchers to do anything they need to do. It's secure, it's fast, easy to use, in fact, so easy they don't even know that they're using it. It just we manage the networks and organize the networks in a way configure them that's the path of least resistance and that's the path traffic will take. And that's nationally. There are lots of these that are interconnected in various ways. I do want to get back to the labor point, just for a moment. (laughs) Because... >> You're here to claim you're not violating any labor laws. Is that what you're going to be? >> I'm here to hopefully hire, get more people to be interested to coming to IU. >> Stop by the booth. >> It's a great place to work. >> Exactly. >> We hire lots of interns and in the network space hiring really experienced network engineers, really hard to do, hard to attract people. And these days when you can work from anywhere, you don't have to be any place to work for anybody. We try to attract as many students as we can. And really we're exposing 'em to an environment that exists in very few places. Tens of thousands of wireless access points, big fast networks, interconnections and national international networks. We support the Noah network which supports satellite systems and secure traffic. It really is a very unique experience and you can come to IU, spend lots of years there and never see the same thing twice. We think we have an environment that's really a good way for people to come out of college, graduate school, work for some number of years and hopefully stay at IU, but if not, leave and get a good job and talk well about IU. In fact, the wireless network today here at SC was installed and is managed by a person who manages our campus network wireless, James Dickerson. That's the kind of opportunity we can provide people at IU. >> Aaron, I'd like to ask, you hear a lot about everything moving to the cloud these days, but in the HPC world I don't think that move is happening as quickly as it is in some areas. In fact, there's a good argument some workloads should never move to the cloud. You're having to balance these decisions. Where are you on the thinking of what belongs in the data center and what belongs in the cloud? >> I think our approach has really been specific to what the needs are. As an institution, we've not pushed all our chips in on the cloud, whether it be for high performance computing or otherwise. It's really looking at what the specific need is and addressing it with the proper solution. We made an investment several years ago in a data center internally, and we're leveraging that through the intelligent infrastructure that I spoke about. But really it's addressing what the specific need is and finding the specific solution, rather than going all in in one direction or another. I dunno if Jet Stream is something that you would like to bring up as well. >> By having our own data center and having our own facilities we're able to compete for NSF grants and work on projects that provide shared resources for the research community. Just dream is a project that does that. Without a data center and without the ability to work on large projects, we don't have any of that. If you don't have that then you're dependent on someone else. We like to say that, what we are proud of is the people come to IU and ask us if they can partner on our projects. Without a data center and those resources we are the ones who have to go out and say can we partner on your project? We'd like to be the leaders of that in that space. >> I wanted to kind of double click on something you mentioned. Couple of things. Historically IU has been I'm sure closely associated with Chicago. You think of what are students thinking of doing when they graduate? Maybe they're going to go home, but the sort of center of gravity it's like Chicago. You mentioned talking about, especially post pandemic, the idea that you can live anywhere. Not everybody wants to live in Manhattan or Santa Clara. And of course, technology over decades has given us the ability to do things remotely and IU is plugged into the globe, doesn't matter where you are. But have you seen either during or post pandemic 'cause we're really in the early stages of this. Are you seeing that? Are you seeing people say, Hey, thinking about their family, where do I want to live? Where do I want to raise my family? I'm in academia and no, I don't want to live in Manhattan. Hey, we can go to IU and we're plugged into the globe. And then students in California we see this, there's some schools on the central coast where people loved living there when they were in college but there was no economic opportunity there. Are you seeing a shift, are basically houses in Bloomington becoming unaffordable because people are saying, you know what, I'm going to stay here. What does that look like? >> I mean, for our group there are a lot of people who do work from home, have chosen to stay in Bloomington. We have had some people who for various reasons want to leave. We want to retain them, so we allow them to work remotely. And that has turned into a tool for recruiting. The kid that graduates from Caltech. Doesn't want to stay in Caltech in California, we have an opportunity now he can move to wherever between here and there and we can hire him do work. We love to have people come to Indiana. We think it is a unique experience, Bloomington, Indianapolis are great places. But I think the reality is, we're not going to get everybody to come live, be a Hoosier, how do we get them to come and work at IU? In some ways disappointing when we don't have buildings full of people, but 40 paying Zoom or teams window, not kind the same thing. But I think this is what we're going to have to figure out, how do we make this kind of environment work. >> Last question here, give you a chance to put in a plug for Indiana University. For those those data scientists those researchers who may be open to working somewhere else, why would they come to Indiana University? What's different about what you do from what every other academic institution does, Aaron? >> Yeah, I think a lot of what we just talked about today in terms of from a network's perspective, that were plugged in globally. I think if you look beyond the networks I think there are tremendous opportunities for folks to come to Bloomington and experience some bleeding edge technology and to work with some very talented people. I've been amazed, I've been at IU for 20 years and as I look at our peers across higher ed, well, I don't want to say they're not doing as well I do want brag at how well we're doing in terms of organizationally addressing things like security in a centralized way that really puts us in a better position. We're just doing a lot of things that I think some of our peers are catching up to and have been catching up to over the last 10, 12 years. >> And I think to sure scale of IU goes unnoticed at times. IU has the largest medical school in the country. One of the largest nursing schools in the country. And people just kind of overlook some of that. Maybe we need to do a better job of talking about it. But for those who are aware there are a lot of opportunities in life sciences, healthcare, the social sciences. IU has the largest logistics program in the world. We teach more languages than anybody else in the world. The varying kinds of things you can get involved with at IU including networks, I think pretty unparalleled. >> Well, making the case for high performance computing in the Hoosier State. Aaron, Dave, thanks very much for joining you making a great case. >> Thank you. >> Thank you. >> We'll be back right after this short message. This is theCUBE. (upbeat music)

(light techno music) >> Okay, welcome back, everyone from theCUBE's coverage of AWS re:Mars here in Las Vegas. Back in person, I'm John Furrier, host of theCUBE. Re:MARS stands or Machine learning, Automation, Robotics, and Space. And we're covering all the action two days, day two. And we're here with Regina Manfredi, who's the VP of global CSPs, Cloud Service Providers Alliances with Teradata. Great to see you. Cloud service providers or- >> Cloud services providers, the hyperscalers. >> Hyperscalers, the big guys. All the CapEx, Amazon. >> Yes. >> The big guys. >> Indeed, thanks for having me. >> Yeah, Thanks for coming on. So tell about your role. So alliances, you're here with AWS. What's the role with AWS and Teradata? >> So AWS and Teradata have recently entered into a strategic collaboration agreement where we're really focused on building solutions together, leveraging AWS services, as well as Teradata's outstanding architecture, as it relates to the data analytics platform that we provide for our customers in the cloud today. And we're really trying to drive better outcomes for data scientists, business analysts, etc. >> You know, just recently, did a CUBE conversation with Teradata, and I was really surprised to find, not shocked, but kind of surprised, the scale of the computation that's going on in some of the cloud things you're doing. And you have the legacy on-premises data warehouse traditional business as well. >> Regina: We do. >> And there's a huge shift going on. A lot of the kind of upstarts, "Oh, data warehouse, old school. Data warehouse, it's antiquated, old," but that's not true. You guys have a lot of cloud action. >> We do, we have substantial cloud action that's occurring with our customers today. We actually just released earlier this year an announcement around 1,000 node tests in the cloud together with AWS, and had success, no downtime, no failures at all. And so we're pretty proud about that, and excited about what that's going to hold for our customers who need that level of scale. >> Well, Regina, I got to tell you, I have a little bit of a confession here. I'm a cloud data nerd by my training. And, you know, I've always watched all the different kind of levels of transformation with the industry, and you know, this is going to change that, that's going to kill that. Everything's going to be killed and then it never dies, but it just changes. Even today, SQL is still like the prominent language, it's never going to, in fact it's amplified further because that's what people like. So that just proves that things don't always get replaced. And so I wanted to ask you this because as we're here at this event at re:MARS, you have space, you have all these ambitious positive goals, and they just need to do some machine learning. They need some cloud, they need some, they need to have the solutions. >> Regina: Yes. They're not going to like get in the weed and say, "Oh, this is a better Hadoop cluster than this Kubernetes cluster. So it's not about sometimes the tech, it's about the solution. >> It is, and one of the things that was interesting for us in our session earlier this week was the fact that we had so many customers approach us after that session and say, "I just need help preparing my data. Running my models, training my models, and making sure that they run and can be deployed. And I don't want to move all this data all the time and have all this failure rate that I'm experiencing." And so it was very basic requirements and needs as people begin into their journey on AI/ML for their business. And so it was reaffirming that we're on the right track and driving the right tools for them. I want to get your perspective on what you're thinking about the show, but first, I want to ask this since you brought that up. Swami was on stage and he said, "You can spend your entire time and your career just trying to figure out what's going on, machine learning." >> Regina: Yup. >> "Which open source framework's going to be better than the other one." I mean, it's just a lot of work to even figure it out. We just had the Fiddler's AI CEO on who worked out all the hyperscalers, say Facebook tend to, you know, real, you know, super alpha geek, if you will. And he was saying, and we were talking about open source, free software, integrations are a big part of where cloud scale, and the value is being captured for companies and people who are doing projects. Integrating some managed services, so this is where I see you, guys, going right now with Teradata, having all these cloud services built on the install base. >> Right. Which is not, doesn't hurt that at all. It just only helps it as they would migrate to cloud, its integrations, so you take a little bit of Amazon here, a little bit of Teradata there. >> Regina: Absolutely. >> What's your perspective, what's your reaction to that? >> So, I agree. And we think that's part of our secret sauce. You know, what we want to have is a data analytics platform in the cloud that allows data scientists, and architects, etc., to bring their own tools. So whatever they're utilizing today, we want them to be able to utilize it in vantage, and make sure that, A, can drive some efficiencies, and also, some better, smarter economics, as it relates to their particular projects. And so I agree with you 100% , and would tell you that we view that as somewhat our competitive advantage. It's not about being all proprietary. We want those integrations, and we've got dozens of them with AWS, and- >> Can you give example, can you give a couple examples of some integrations that highlight that? >> Sure, so right now we've got an integration with SageMaker today that allows our customers or data scientists to come in, prepare the data, and actually leverage SageMaker to build and train the models, and then deploy very quickly and easily without having to do all the data movement within their architecture. >> It's just so fascinating. I can't wait to have more conversation with you guys about this because I just think the world's spinning in a direction where, with low code, no code, >> Regina: Yup. >> you can see code, companion whisperer, that they have CodeWhisperer they launched today, they're writing subroutines for machine learning. And so it's not autocomplete, it's subroutine. So you're seeing all these advances on the technology. So it comes back to the building blocks, the integration. It just seems like going to be like a plug and play. That's old, were all, are old words. Mix and match, plug and play, interoperability, were old words, like, in the old days. Now they're becoming more relevant. What's your take on all that? >> Yeah, I would agree. I don't think that we should be competing against the algorithms, and neither do we. We want to just actually build out the toolsets that drive the enablement based on what a customer's requirements and needs are, and based on what the investments that they've already made within their own enterprises. >> You know, what's interesting about this event, I love to get your reaction to what re:MARS means to you because it's machine learning, automation, robotics, and space. Not your typical tech conference. >> Regina: No. >> Okay, little bit of a mixed bag there, so to speak. I love it. I think it's like super alpha geek, very nerdy, super nerds are here. And the topics kind of reflect the future. For the people that are watching that aren't here, what's your vibe on the show? What's your takeaway? How would you explain what's going on here from a market perspective, from a vibe perspective, what's happening? >> This is my first re:MARS actually, and I would have to tell you that I feel like it just, general observation, a few things, one, the conversations are more meaningful and we're getting into the meat of what a data scientist truly needs in order to be successful in their role and help drive their enterprise. That's number one. So I think, to your point, we're all kind of geeking out together here. The other thing that I think is pretty exciting is the amount of use cases, and ways in which we are driving impact. AWS and Teradata driving impact for the business analysts in the enterprise environment, but also for the people, their customers. That's pretty exciting to see. >> You know, it's interesting. When I first, was kind of like thinking about the show and what I was going to expect, it kind of overexceeded my expectations in the sense of what I was thinking about IOT, industrial, and digital innovation. 'Cause that's going to scale. I think now we're at a tipping point with machine learning that the industrial, IOT markets is going to explode 'cause machine learning's ready. But there was a whole positive, save the earth angle >> Regina: Yes. >> that caught my attention. >> Regina: Yes. You know, the discoveries from space are going to potentially have impact for the good, not just a cliche some sustainability messaging. It was actually real. >> Right, I think that that's exciting in an area in which we're excited to explore. We're doing a lot of work behind the scenes around sustainability and ESG initiatives for our customers, but also for the greater good. It's about driving outcomes for the greater good and being responsible with how we approach that. You know, the other thing I noticed too from a robotics standpoint, given I live in California, is a huge robotics culture there, you know. It's like bigger than football and baseball, and some sports. They provide A and B team and people get cut from the B team. There's so much demand to be on the robotics team. It's not a club, it's a team. >> Regina: Right. And so, you look at what's going on robotics, it's so exciting in the sense that if you're young and you're into tech, this is like- >> Regina: This is the place to be. >> I mean, why wouldn't you be hanging out here? >> Yeah, well, and I visited the booth over at University of Michigan, and how they're driving robotics to help support the human body to go further distances, and to drive better performance and health for individuals, and was really impressed with the work that they're doing, and even saw a use case and a need where I thought, you know, I have a quadriplegic sister-in-law, who I thought, "Wow, someday, maybe she'll be upright and walking again." >> John: Yeah. >> And those were exciting conversations to have while I was here. >> The advances on the material management robots I think is fascinating to see that growth. Well, let's get back to Teradata real quick to kind of close out future of what's next. Obviously, a lot of migration to the cloud happening. What's the outlook on the landscape and where do you see it evolving? Because you're seeing what the hyperscalers are doing, the cloud service providers, they're providing the CapEx. In fact, we coined the term supercloud, last re:Invent, that's become a thing. And Charles Fitzgerald would think it's not a thing, he debates us online all the time on Twitter. But it's, you can build on top of a CapEx. >> Regina: Yup. >> They did all the heavy lifting. You know, Snowflake, Databricks, the list goes on and on. So building on top of that to build proprietary advantages or even just sustainable advantages is now easier to do. So superclouds are kind of in play. So that means whoever's got the playbook can win. So you guys seem to be executing that playbook of having the installed base, and then working with AWS >> Regina: Yes. >> to ride that wave. Tell us about the migration strategies you're seeing, and what are your customers doing specifically, and take us through a customer that's leaning into the cloud and driving. >> So when I think about specific customers that are leaning in, you know, the first and most important thing that we're hearing is, you've got to be able to scale. I've got 1,000 nodes or 100 nodes, or whatnot. And so we're addressing that because we think that there's a place for hybrid cloud. We think everyone's moving and rushing towards the cloud, but even one of our competitors last week announced that there's a place for on-prem, and we would agree. >> John: Yeah. >> So that is something that we're really focused on, and you take, for example, the automotive industry. We're seeing a lot of work being done together with our joint customers, AWS and Teradata, and some of these auto manufacturers who are experiencing supply chain issues and challenges today, and also need to drive better quality control measures within their own lines, in the manufacturing lines. And so we're working together with them to look at what type of machine learning and AI can we be leveraging together as part of the overall solution to drive those analytics, and make sure that they have better quality control >> You know, that's really good insight about the on-premise thing. And I think that supports what we're seeing around hybrid. We see hybrid as a steady state going forward, period. >> Regina: Yeah. >> And that will evolve into multi thing. Multi-cloud, you want to call it, or superclouds, and more things. Basically, distributed computing. So if you look at the edge here, the edge is just on-premise. What is the premise? It's an edge or big device, small device, data center is a large edge. >> Regina: Right. >> And so if you're using cloud hybrid, the distinction kind of goes away. And I think this is where we'll going to see the winners emerge in data. Because remember, you go back to 2010, Hadoop was the big thing, big data. And that kind of crashed and burned. And then now you're seeing Databricks picking up a lot of that. Snowflake, you guys are there. And so it's still going on, this transformation in data. >> Regina: It is. And I think hybrid's a huge deal. What are customers saying around that? Because I think they're just trying to figure out cloud scale. >> I think they're trying to figure out cloud scale, I think they're also trying to figure out security. And so, you know, when we're talking to our customers, that absolutely is critical. And I would also suggest that the customer base is really looking for, "Hey, don't just help me migrate, I really need to modernize." And so driving the right use cases for the customer is important. >> You know, another thing that you, guys, have a lot of core expertise in is governance. And we've seen how that has played in all the compliance, and all these conversations are kind of converging. Do you have closed, do you have open? Machine learning needs more data, dow do you protect it? So that set a hot area that I see as well. And that's something that's emerging, 'cause cyber's also involved too, like, you have cyber security threats on code, so I'm curious to see how that turns out. What's your perspective on, what's Teradata's perspective on the security, open, closed perspective? Any- >> It's a priority for, security is a priority for us. And I don't think that we've officially made that determination yet, right? We're still exploring, and we're going to do whatever our customers require of us. In terms of an open, closed perspective, I think we want to be flexible. Again, like I said before, it's about being open and supportive of whatever the customer requirement is especially across the different industries. >> Well, Regina, great to have you on theCUBE. Thanks for coming. I really appreciate it. Great insight, great to catch up on Teradata, cloud play. Very strong move. I think it's a good one. Final question I want to ask you though, is a little bit more about the personnel in the industry, like, obviously, if you're young, you're seeing all this space here, machine learning's not obvious. I know schools now are training it, but you start to see new personas come into the workforce. Where are the gaps? I mean, obviously, we have a lot of new opportunities, like, cybersecurity has a lot of job openings. Is there any observations that you have around or advice to younger folks coming in, from a career standpoint? Because a lot of job openings are skills that weren't even taught in school. >> Regina: Right, that's- >> You know. >> And then you got the women in check, and you have all kinds of opportunities now that aren't just engineering, right? >> Regina: Yes. >> It's not just engineering. It's computer science, so there's a whole in-migration of new talent coming in the industry. >> Yes, I think maintaining a curious mind is really critical, and taking time to invest in learning. You know, there are so many resources available to us at our disposal that that don't cost us a dime. And so my advice to anybody who is curious, remain curious, dig in, and get some experience, and don't be afraid to stick your neck out, and try it. >> Well, in this conference we have robots welcome, you know, in this out there. >> Yeah. (laughs) >> Regina, thanks for coming out here. Really appreciate it >> John, thank you, it's a pleasure. >> CUBE coverage here in Las Vegas for Amazon re:MARS. I'm John Furrier, your host. Stay with more live coverage after this short break. (upbeat bright music)

(upbeat music) >> Hello, and welcome to theCUBE special presentation of Unstoppable Domains Partner Showcase. I'm John Furrier, your host of theCUBE. We've got a great conversation talking about the future of the infrastructure of Web3, all around domains, non fungible tokens and more. Two great guests, Charlie Brooks with Business Development of Unstoppable Domains, and Michael Williams, Product Leader and Advisor with Unstoppable Domains. Gentlemen, thanks for coming on theCUBE, Partner Showcase with Unstoppable Domains. >> Thanks John, excited to be here. >> So I love what you guys are doing. Congratulations on all your success. You guys are on the leading edge of what is a major infrastructure. Shift to Web3 is being called, but people who have been doing this for a while know that you see the blockchain, you see decentralization, you see immutability all these future smart contracts. All the decentralized applications are now hitting the scene and NFTs are super hot as you can imagine, you guys in the middle of it. So you guys are in the sweet spot of what I call the Pragmatic pioneers. You guys are the building solutions that are making a difference, like single sign-on you have the login product, let's get into it. What is the path to a digital identity beyond the web? 'Cause we know what web identity is. But now that the web is being abstracted a away by this new Web3 layer, what is digital identity? >> I can take that one. So I think what we're really seeing is this transition away from a purely physical identity. Where your online identity is really just a reflection of the parts of your physical identity. Where you live, where you go to school, all of these things. And we're really seeing this world emerge where your online identity becomes much more of a primary. So if you have a way that you represent yourself in the online world, whether that's an Instagram account, or TikTok, or email address or username, all of these things together make up your digital identity. So congrats, if you have any of those things, you already have one. >> We see that all the time with Linktree, people put their Linktree out there and it's got the zillion handles. We all get up to Instagram. Everyone's got like zillion identities. Is that a problem or an opportunity? >> I think it's just a reality. The fact is our identities are spread across all of these different services and platforms that we use. The problem with something like Linktree is that it is owned by Linktree. If I won the lottery, purchased Linktree and decided I wanted to change your personal website, John, I could easily do that. Moving to the architecture that we have and NFT architecture, changes that significantly. It puts a lot of power back in the hands of the people who actually own those identities. I do a lot of CUBE showcases with folks around talking about machine learning and AI, and the number one conversation that they bring up, the number one issue, is data. And they say, when data's siloed and protected and owned, it is not optimized for machine learning. So I can almost imagine, as you bring NFTs to the digital identity, you mentioned you don't own your identity if someone else is managing the service like Linktree. This is a cultural shift, and infrastructure software shift at the same time. Can you guys expand more about what you guys are doing with the NFT and unstoppable domains with respect to that digital identity, because is that power shifting to the users now? And how does that compare to what's out there today? >> Sure, I think so. Our domains are NFTs, so they are ERC 721 tokens. And if you think about in the past Web2 identities are controlled by the platforms that we use. Twitter, Facebook, whatnot. There's really a lack of data portability there. Our accounts and data live on their servers, they can be deleted any time. So using an NFT to anchor your data identity, really gives you full control over your identity. It can't be deleted, it can't be revoked or edited, or changed without your permission. And really even better, the information you store on your entity domain can be plugged into the services you use, so that you never have to enter the same data twice. So when you go from platform to platform, everything can be tied to your existing domain. You're not going to a new site, entering their ecosystem and providing all this information time and time again, and not really having a clear understanding of how your data's being used and where it's being stored. >> So the innovation here is the NFT is your identity. And a non fungible token NFT is different than say a fungible token. So for the folks out there that's trying to follow the bouncing ball, Michael, what's the difference between an NFT and a fungible token? And why is that important for identity? >> My favorite metaphor here is baseball cards versus dollar bills. So a dollar bill is fungible. If I have a dollar and you have a dollar, we can trade dollars and none of us is richer or poorer. If I have a Babe Ruth and you have a Hank Aaron, and we swap baseball cards, we have changed something fundamental. So the important thing about NFTs is that they are non fungible. So if I have a domain and you have a domain, like I have that identity and you have that identity, they are unique, they're independent, they're owned by each one of us, and then we can't swap them interchangeably. >> And that's why you're seeing NFTs hot with art and artists, because it's like a property. It's a property issue, not so much- >> Absolutely >> Interchangeable or divisible kind of asset. >> Yep, it is ownership rights in digital form, yes. >> All right, so now let's get into what the identity piece. I think find that interesting because if I have something that's an NFT, it's non fungible, it's unique to me, it's property, my property my login, this sounds compelling. So how does login work with the NFT? Can you guys take us through that architecture, what does it do? How does it work? And what's the benefit? >> Good, so the way our login product works is it effectively uses your NFT domain. So Michael.crypto, for example, as the authentication piece of a login session. So basically when I go and I try to log in with my domain, I type in Michael.crypto, I sign it with my wallet which cryptographically proves that I am this human, this is me, I have the rights to log in. And then when I do so, I have the ability to share certain parts of my identity information with the applications that I use. So it really blends the ease of use from Web2 of just a standard like login with Gmail, SSO experience, with all of the security and privacy benefits of Web3. >> How important is single sign-on? Because right now people are used to seeing things like log with your GitHub handle or LinkedIn, or Google, Apple. You seeing people offering login. What's the difference here from those solutions and why does it make sense for the user? >> Sure, the big difference is what we're building is really user first. So if you think about traditional SSOs, you are the product. When you use their product, they're selling your data, they're tracking everything you do. Login with unstoppable handles not only authentication, but data sharing as well. So when you log in a domain owner can choose to share aspects of their online identities, such as first name, preferred language, profile picture, location. So this is a user controlled way of using a sign-on where their permissioning these different of their identity. And really apps can use this information to enable new experiences, such as, for example, website might automatically enable high contrast mode for someone visually impaired. It could pre-populate your friends from a decentralized social graph. So, what we're doing is taking the best parts of Web2 SSO and combining them with the best of Web3. So, no more losing your password, entering in the same data hundreds of times depending on other services to keep your information safe. Login with unstoppable really puts you in complete control of your data. And a big part of that is you're not going to have 80 plus usernames and passwords anymore. We have these tools like password managers that exist to put a bandaid on this issue, but it's not really a long term solution. So what we're building is really seamless onboarding where everything can be tied to your domains so that you can navigate to different apps in a much more seamless way. >> Michael, I got to get your thoughts on this because in the product side, it's interesting, my mind's connecting some dots. If I have first of all, great convenience to reduce all those logins. So, check their little pain reduction. But when you just think about what's different, I can now broker my data as well as login. So let's just say, hypothetically, I'm cruising around some dApps and I'm doing things in earning reputation, or attention, or points, or whatever utility tokens. There could be a way for me to control what I own. I'm the product, I own the data. Is that where this is going? >> I think it's definitely a direction it could go, say, for example, if I'm a e-commerce platform and I'm trying to figure out where I'm going to place a new billboard. One of the things that I could request from a user, is their address. I can figure out where they live, what city they're in, that will help inform me the decision that I need to make as a business. And in return, maybe I give that person a dollar off their purchase. We can start to build a stronger relationship between the applications that people use, and the people that use them. And try to optimize that whole experience, and try to just transfer information back and forth to make everyone's lives better. >> What's the roadmap on the business side Charlie, when you see companies adopting it, they're probably taking babies steps they're crawling before they walk, they're walking before they run. I can see decentralized applications in the future where there's FinTech or whatever, having new kinds of marketplaces that take advantage of the paradigm where the script flips to the user first. Okay, so I see that. How do people get started now? What are some of the success momentum points that you're seeing companies do now with unstoppable? >> Sure, so a lot of Web3 apps are very sensitive about respecting the information that their users are providing. So, what we're doing is offering different ways for apps can touch with their users in a way that is user controlled. So, an example there is that a lot of Web3 companies will use WalletConnect to allow users to log in using a wallet address. An issue there is that one person can have hundreds of wallet addresses, and it's impossible for the app to understand that. So, what we do is we use login, we attach an email address, some other pieces to a wallet address so that we can identify who our unique user is. And the app is able to collect that information, they don't have to deal with passwords or PII storage. They have access to a huge amount of new data for an improved UX. It's really simple to maintain as well. So one example there is if you are a DeFi platform and you want to reward your users for coming to their site for the first time, now that they can identify unique user, they can drop a token into that user's wallet. All because they're able to identify that user as unique. So they have a better way of understanding their customers. They enable their customers to share data. A lot of these companies will ask users to follow them on Twitter or Discord when they need to provide updates or bug bounties, all these different things. And login if unstoppable lets them permission email addresses so they can collect emails if they want to do a newsletter. And instead of harvesting data from elsewhere and forcing people to join this newsletter program, it's all user controlled. So each user saying, yes, you can use my email for your newsletter. I'm supporting your project, I want to be kept up to date with bugs or bounties or rewards programs. So really it's just a better way for users to share the data that they're willing to with dAPPs, and dAPPs can use it to create all sorts of incentives and really just understand their users on a different level. >> How is the development Michael, going on the smart contract side of the business? Ethereum has always been heralded as being very developer focused. There's been created innovations, you still got gas fees out there. You still got to do some things. How is the development environment? How are the applications coming? 'Cause I can see the flywheel kicking in as the developer front gets more streamlined, more efficient. And now you got the identity piece nailed down. I just see a lot of dominoes falling at the same time. What's the status on the DEV side. What you're doing. >> Good. The fascinating thing about crypto is how quickly it changes. When I joined Ethereum there was pretty reasonable still for transactions. It was very cheap to get things done very fast. With a look at last summer that things went completely out of control. This is a big reason that unstoppable for a long time has been working on a layer two. And we've moved over to the polygon as our primary source of record, which is built on top of Ethereum. Of course, I think saved well over a hundred million in gas fees for our users. We're constantly keeping an eye on new technologies that are emerging, weighing how we can incorporate those things. And really where of this industry is going to take us. In many ways we are just as much passengers as the other people floating around the ecosystem as well. >> It's certainly getting faster every day, I'm seeing a huge uptake on Ethereum. I heard a stat that most people at the university of California, Berkeley, 30% of the computer science students are dropping out to join Web3 companies. This goes to show you this cultural shift and you're going to see a lot more companies getting involved. So I got to ask you Charlie, on the BizDev front, how are companies getting started? What's the playbook? Are they putting their toe in the water? They jumping in full throttle? What's the roadmap? What's the best practice for people to get started with unstoppable? >> Absolutely. We're lucky that we get a lot of inbound interest from companies Web2 and Web3, because they first want to secure their domains. And we do a ton of work on the back end to protect trademark domains. We want to avoid squatting as much as possible. We don't think that's the spirit of Web3 at all. And certainly not what the original tension of the internet was. So, fair amount of companies will reach out to us to get their domain. And then we can have a longer conversation about some of the other integrations and ways we can collaborate. So certainly visiting our website, unstoppabledomains.com is a great starting point. We have an app submission page where apps can reach out to us, even request a grant. We have a grant program to help developers get started, provide them some resources to work with us and integrate some of our technology. We have great documentation as well on the site. So you can read all about what it takes to resolve domains, if you're a wallet and an exchange, as well as what it takes to integrate login with unstoppable, which is actually a super easy integration as well, which we're really excited about. So yeah, I'd say check out the website, apply for a grant if you think you're a fit there, then of course, people can always reach out to me directly on Twitter, on Telegram, email. We're very reachable and we're always happy to chat with projects and learn more about what they're doing. >> What's the coolest thing you see going on Charlie, with your partners right now? What's the number one use case that's cool that people are jumping on right now to get in and get some success out of the gate? >> Maybe GameFi play to earn is huge. It's blowing up and the gaming community is really passionate, vibrant, just expanding like crazy. Same with DeFi, there's all this cool new stuff you can do with DeFi where no matter how big your portfolio is, you're able to stake and use all these interesting tools to grow your book. So it's super exciting to see and talk to all these projects. And, there's certainly an energy in the community where everyone wants to onboard the general public to Web3. So we're all working on these school projects, but we need everyone to come over from Web2, understand the advantages of DeFi, of GameFi of having an entity domain. So, I'm lucky that I'm one of the first layers there of meeting new projects and helping get access to more users so that they can grow along with us. >> I remember the early days of Bitcoin and Ethereum, we were giving it away. The community mantra was, give a Bitcoin to someone. That was like, >> Right. >> When you can actually give a Bitcoin to someone. What's the word of mouth or organic viral? I won't say growth hack 'cause that's got negative connotations. But what's the community's way of putting forth the mission for unstoppable? Is it just more domains? You guys have any programs got going on? Is it give it away? Obviously you can get domains on your site, but what's the way to get people ingratiated in and getting comfortable? >> So much of what we do is really to solve that question, answer that question. We spend a ton of time and energy just on education and whether that's specifically around domains or just general Web3. We have a podcast which is pretty exceptional, which talks to Web3 leaders from across the space and makes the project that they're working on more accessible. I think we passed over a hundred episodes, not too long ago. There's a ton of stuff that we do that other people do. If anyone has questions, I'm happy to talk about our resources, of course. >> The pod, I think you guys are up to 117, but that's a deep dive. You guys go deep on the podcast. So that's where you go in. What else is new on digital identity? Where do you guys see the future going? Now that you get the baseline identity with the NFT. Makes a lot of sense, create innovation. Good logic, makes sense. Solid technically, what's next? >> I think this really boils down to the way that the internet has grown. Doesn't really feel like the way that the internet should be. Like our data shouldn't live in these wild gardens, controlled by these large companies. Ultimately people should be responsible for their own identities. They should have control over of things that they do online. The data that's shared, the benefit of that data. It's about the world that we are working towards, is very much that. Where we are giving people the ability to be paid for sharing their data with companies. We're giving applications the ability to request information from the people that use those applications to improve their experience. We're really just trying to make connections across the ecosystem through these products, to enable a better experience for everyone. So whether that's the use cases that I mentioned already, or maybe viewing reviews on something like Yelp or Amazon, that just confirm that the person that you are you're looking at is actually a real person, not some bot that's been paid to load a review. The interesting thing about these products is they're so universally applicable. There are so many different ways that we can try to plug them in. So we are- >> A bots is a great example, double-edged sword. You can have a metaverse image and have pre-programmed conversations with liquid audio and the video application. Or it's a real person. How do you know the difference? These are going to be questions around who solves that problem. Now there's time for bots and there's a time not for bots. We all know what happens when you get into the game of manipulation, but also it can be helpful. This is where you got to be smart. And identity's critical in this future. Charlie, what's your reaction to the future of digital identity? So much to look at here on the trajectory. >> I think a big part of it is data portability. If you go to a site like Instagram, you're giving them all this content that's very personal to you, and you can't just pack up and leave Instagram. So we want a future where most of these apps are just a front end and you can navigate from one to the other and bring your data with you. And not be beholden to the companies that operate centralized servers. So, I think data portability is huge and it's going to open up a lot of doors. And just going back to that thought on cleaning up Web2 for a better web three. When I think about the Amazons, the Yelps of the world, there are all these bots, there are all these awful fake reviews. There's a lot of gamification happening that is really just creating a lot of noise. And I want to bring transparency back to the internet where when you see a review, you should know that that's a real human. And blockchain technology is enabling us to do that. And certainly FT domains are going to play a huge part of that. So I think that having an experience where you know and trust the people that you're interacting with is going to be really powerful and just a better experience for everyone. And there's a lot of ramifications with that. politically speaking, we've all seen all the issues with attacking communities and using bots and fake accounts to hit people's pain points, it's sad and certainly not something that we want to see continue happening. So, whatever we can do to give people their digital identity and help people understand that this is a real person on the other end, I think is huge for the future of the internet and really for society as well. >> That's a great call out there Charlie. Cleaning up the mess of Web 2.0, Web2, actually it was 2.0 technically, now Web3 is no point zero in it. But I saw on or listened to the podcast with Matt. This recent one, he had a great metaphor that went back to when I was growing up in the internet, you had IP addresses. And the mess there was, you couldn't find what you want to look. And no one could remember what to type in, 'cause you could type in IP address in the browser back then. And then DNS came out and then keywords that's web. Now that mess, now is fraud, misinformation, bot manipulation, deep fakes, many other kind of unwanted time to innovate. And every year, every time you had these inflection points, there'd be an abstraction on top of it. So, similar thing happening here, is that how you guys see it too? >> I think we're going back to some of the foundational architecture of the internet, DNS. And really bringing that forward about 30, 40 years in terms of technology. So loading in some more cryptography and some other fancy things to help patch some of those issues from the previous versions of the web. >> Awesome. Well guys, thanks so much for coming on and the spirit of TikTok, Emily summarizes asking, can you guys give us a quick TikTok moment, short comment on where this is all going, where is login, single sign-on mean and what should people do to steps to secure their digital identity? >> Sure, I'll jump in here. So, it's time for people to secure their digital identity. The great first step is going to sample domains and getting an NFT domain. You can control your data. You can do a lot of cool different things with your domain, including posting your own website that you will own forever, no one can take it away from you. I would certainly recommend that people join our Discord, Telegram communities, check out our podcasts. It's really great especially if you're new to crypto Web3. We do a great job of explaining all the basic concepts and expanding on them. So yeah, I would say, the time is now to get your digital identity and start embracing Web3 because it's really exploding right now. And there's just so many incredible advantages, especially for the user. >> Michael, what's your take? >> But not, have said it better myself. >> Like we always say, if you're not on the next wave, you're driftwood. And this is a big wave that's happening. It's pretty clear guys, it's there, it's happening now. And again, very pragmatic implementations of solving problems. The sign-on, the app integration. Congratulations and we got our CUBE domain too, by the way. So I think we're good. >> Excellent. >> So, we got to put it to use. Appreciate it, Charlie, Michael, thanks for coming on and sharing the update. >> It's pleasure. >> Welcome. >> Okay, this is theCUBE, with Unstoppable Domains Partner Showcase I'm John for your host, got a lot of other great interviews. Check them out. We're going to continue our coverage and continue on with this great showcase. Thanks for watching. (upbeat music)

(bright music) >> Hello, welcome to theCUBE's presentation of the Unstoppable Domains Partner Showcase. I'm John Furrier host of theCUBE. We're here talking about the metaverse and what it all means, what it brings to the table. We've got two pioneers here in the metaverse breaking it down, doing great stuff. Both co-founders of companies, Noah Gainer, co-founder and CEO Parcel. And CJ Hetherington Co-Founder of Atlantis World, digging deep and doing all the great stuff in the Midwest. Chill and thanks for coming on theCUBE. >> Thank you so much for having us. >> Thanks for having us. >> So, first of all, I want to say congratulations for the work you guys are doing. This is one of the biggest waves we've seen coming on. It's a changing user expectations, it's a changing architecture, it's real technology involved, there's a lot of action. 30% of people at University of California, Berkeley are dropping out of the Computer Science program to get into Web3. This is the biggest technological change, business model change, user experience change. And we've been seeing going back multiple inflection points. This is a big deal. So the metaverse is real. Some people say, "Well, you know, it's not com..." It's coming it's just a matter of time. So let's get into it. What are you guys doing? Tell us about your company's Parcel and Atlantis World. Noah, start with you. >> Sure, so Parcel is a marketplace for virtual real estate. So you can think of something like OpenSea, which everyone is familiar with, but we solely focus on virtual land and virtual real estate in a number of virtual world, maybe part of decent land or the sandbox. So we feature those on our platform and, you know, we take it the next level with the user experience. So we have fully interactive maps. We have price estimates. You can think of it like a estimate on Zillow and in general, we're building the fully verticalized solution for virtual real estate users. And that will extend into rentals, like Airbnbing out your virtual condo or getting a mortgage on your virtual home, as well as, you know, cultivating the community around it. And especially helping empower creators and architects and builders and getting them work and getting their work on display. >> I'm looking forward to digging into that, that sounds very cool. CJ what's Atlantis world doing? What do you got going on? >> Yeah, exactly. So at Atlantis world, we're building the Web3, social metaverse by connecting Web3 with social, gaming, and education in one light web virtual world, that's accessible to everybody. So by going with actually a light web first and a pixel approach so that you can play on mobile or a really old device, because the problem with existing metaverses is that they set an incredibly high cost barrier to entry and also tech isn't necessarily readily available globally in terms of things like VR headsets and gaming PCs. Like for example, when I was in Africa, I travel a lot. If my book would break, it's not even that I couldn't necessarily afford to buy anyone, it's actually not available there. So we're ruling out a lot of the global kind of population from a metaverse experience. And we're building something which is like 3D pixel and super light weight, to kind of bridge that gap and build something which is ready to be massive up till now and onboard billions of users into Web3. So they'll all basically be using Web3 applications in a gamified way and going really hard on connecting that with social features, like voice chat and talking, getting, and virtual events and vaulting and all of that stuff. >> You know, I love what you guys are doing, you're pioneering a whole another area, but what's great about the whole crypto area, is that, since you know, 2017 onwards you saw Ethereum set the developer market started coming in strong. So you start to see that development. And now we got the metaverse. So I got to ask you guys what's the current definition of the metaverse. I mean everyone's... I mean, since Facebook changed their name to Meta, it's been a hype cycle and everyone's like, "Woh..." First of all, you know why they did that. But they're actually putting a lot of DAO in this. This is a wave, we talked about that. But what is the metaverse? How do you describe it? Why is it relevant? Virtual real estate, that sounds cool. What does this all come together? Explain it for the people out there that might not be getting it right. >> Yeah, I feel like for me, the critical difference between an ordinary gamer, what one might think of as game and a metaverse is actually Web3. For me, Web3 is metaverse. And for me it's really because Web3 enables real world utility, but inside of a virtual environment. So for example, inside of Atlantis, you might run into a DeFi bank and understand by interacting with other game characters, which are programmed to teach you about DeFi and like, what is Avel, how to deposit. And so you're actually getting a real world utility out of doing something in a virtual environment. And for me, that's what really bridges the gap into metaverse. Yeah, I'm really kind of bullish on that. (chuckles) >> Noah, what's your take? Define the current state of the definition of the metaverse? What is the metaverse? >> Yeah, to me, it's the 3D internet. And I do agree with what CJ's saying, how, you know, what makes it the most compelling and will ultimately the most successful is that addition of a blockchain and essentialized, you know, tributed ledger technology. Because you can have the closed metaverse, which nobody wants that future. And I don't believe that will be the future. you know, versus the open metaverse, which is blockchain-based, the users are the owners of the assets and the land and everything around it. And it's really foreign by the people. But I see the metaverse as just an extension of the internet we're already using today but we're going to have hardware that makes it 3D and more immersive like AR and VR. >> Yeah, I think- >> Yeah, definitely- >> Go on CJ. >> Around kind of like eight or nine months ago when we started to build Atlantis, we decided that the metaverse was a virtual world where you could live, work, play, and earn, and that's what we've been building. It started off as like building the metaverse that has DeFi and over the kind of time it's gone on our community has grown, we've started to understand the future of our product and our mission and values. It started to become the Web3 metaverse, right? And then on top of that, the Web3 social metaverse, so it's a combination of what all these things. >> You know, it's interesting. And I'm a little bit older than you guys, I wish I was your age, but when the web came along, people were saying the same thing. That the web's terrible. It's a stupid thing. It's never going to be real. And yeah, there was problems. It was slow to dial up back in the day. But yeah, now with gaming, I got to say, I had to look at the gaming evolution being a gamer myself, old school, I guess, but the gaming culture is proxy to what I see kind of happening in the metaverse. And let me get your reaction to that. I'm not saying directly, but you saw what gaming did, right? In game currency, some, you know, pockets of the same kind of dynamic where a lot of value is happening, the expectations were different for users. So how does the metaverse... How does gaming cross over? What's the ecosystem of metaverse? Obviously it's a cultural shift, one. Infrastructure, two. But I can just see this new generation of thinking. It's a whole nother level. Can you guys share your thoughts on that riff? >> Absolutely. Yeah, absolutely. It's like for us, we really believe that we can enable a social revolution, where workers from impoverished and remote regions can actually be onboarded into these digital player to earn economies and also learn to earn economies. So it's about leveraging Web3 and blockchain gaming, whatever actually you want to call it, to enable this revolution and actually onboard new people into a completely new working and dynamic. One of the other things we envision for Atlantis, imagine like you run around this game world and you complete quests inside of the game. And these quests basically involve talking to the non-player characters, the NPCs, which are basically pre-programmed. I don't know if anyone's ever played an MMORPG before, but it can be super fun. And they'll actually teach you how to use different crypto applications. Whether that's a DeFi bank, NFT marketplace, kind of digital asset exchange. And once you all do that, the kind of end goal in vision is that you'll be rewarded with tokens. So users will earn crypto for learning about crypto. And if anybody wants to do that right now, they can actually go to rabbithole.gg. It's a different project to Atlantis, but they building learn to earn, and you go on you complete quests and interact with different crypto applications. And it's so crucial for onboarding. And yeah, it's going to be really powerful, the kind of revolution that play to earn and learn to earn will enable. >> I'll check out the rabbihole.gg sounds awesome. What's your take on the reaction to that riff on this convergence of culture tech, gaming, vibe that's kind of divine the metaverse what's your take on that, Noah? >> Yeah, I mean... I think gaming will be the on ramp for maybe the first billion people, you know, into blockchain. It's something people already do and are already paying for, and they now have the opportunity to get paid to play. So the incentives are extremely strong and I think that will be a great way to usher people in, teach 'em about blockchain without realizing that they're using blockchain. And then once they're already in it and have already used it, then it becomes much more natural to user than other applications. >> It's funny, people always talk about, "Oh, user experience!" You know, expectations drive experience, right? If you expect something and if they're used to gaming, I see the great, great call out there, good point. Well, let me ask you guys a question, 'cause I think this is comes out a lot in terms of like the market shifts and metaverse, as an old expression, "Great markets pull the products out of companies or out of the industry." What organic growth have you guys seen in the metaverse that's been either a surprise or a natural evolution of just success and just growth, because the market's hungry for this and it is relevant. It's new, what's pulling out? What's coming out of the organic aspect of the metaverse? >> I think a lot of art and architecture and design. And, you know, it's empowering a lot of independent creators and allowing 'em to stretch their skills in a way that they maybe couldn't do before, but now can do and get compensated for. Like, we see really see the rise of the creator coming in the next couple of years in the open metaverse and finally they will be the ruling class. They won't get the short end of the stick, which artists have for... I mean all the time. >> Yeah, some of the wall street bet skies in the same way, feel the same way. CJ, What's your take on... What's getting pulled out on the organic execution growth of the interactions and metaverse evolution? >> Of course, yeah. I would, first of all love to go back to the previous point on gaming and just kind of like, definitely agree with what Noah said. And the thing is that gaming is 3.4 billion user market, and they're typically an experimental by nature people and group of users, right? So it's definitely a huge onboarding opportunity for teaching users about Web3 and using Web3 in a gamified way and making that kind of inherently fun and engaging. And again, in terms of organic growth, Web3 is incredible for that. We place a huge emphasis on, I think, collaborate versus compete and try to enable network effects for everybody who is involved in Atlantis and becoming part of our fast growing ecosystem. Like we have eight blockchain, more than 10 DeFi apps, like Aave, Yearn, Balanced, 1inch, Perpetual. All of the DAOs like The Exile, MetaCartel, lobsterdao, PizzaDAO, all of the NFT communities. Like we're actually building a yacht for bought yacht club on the beach in Atlantis. So that's fun. But yeah, we grew our community. We're very early stage still. We've been building only for eight or nine months, but we grew our community to like 20 to 30,000 community members across social channels. And we recently raised over a million dollars from our community and we're fully bootstrapped and taken no private money. So the ability to actually do that and to coordinate both kind of community efforts and fundraising and resources is really testament to Web3 and what it's becoming in the community aspect of that. And also its future and the kind of dawn and domination of the Metaverse. >> Well, I got to say, I just got to give you props for that. I think that fundraising dynamic is a real entrepreneurial new thing, that's awesome. You've got active community vote with their contribution and whether it's money and or other value, right? You got social value. This is the whole thing about the metaverse, there's a new community culture going next level here. >> We believe in community and we believe in Web3. And we know we don't understand why most leading metaverses are focusing fully on huge IP and actually ignoring Web3. So we're actually trying to build the infrastructure layer for Web3 applications and for Web3 driven utility inside of the metaverse. And what we mean by that imagine that any developer or any project or any team or any company could occupy a plot for free inside of the metaverse, customize it by branding and then effectively set up shop, whether that's a Web3 integration, so it's a DeFi Bank, or it's an exchange. Or whether that's an NFT marketplace or a music venue or a coworking space. We're really excited about that. And we really believe we've designed the value capture mechanism for virtual land in the metaverse and we're approaching it in a different way to land in the real world. >> That's awesome. Well, let's get that infrastructure conversation, unstoppable domains obviously there having the partner showcase here. You guys are partners. This NFT kind of like access method is a huge... I love it by the way. I think it's phenomenal. I love the value there, but it's also digital identity and it's distributed naming. So you kind of got this enablement vibe, you got solve a problem. How is it working with you guys? Take us through what does unstoppable metaverse... Why does unstoppable matter to the metaverse? >> Yeah, unstoppable is very great mostly for identity and having a kind of crush chain identity inside of the metaverse and just kind of in Web3 in general. And unstoppable, we enable log in with unstoppable. So if you have, for example, an unstoppable domain which is like a human readable kind of crypto wallet address, but you can also do some incredible, stuff with it, and there is a lot of fun and exciting utility, effectively, like if you would have, I don't know, like unstoppable.dao you would be able to use that to log in to the Atlantis metaverse and it would represent some of your identity and social graph in game with your peers. >> Awesome, Noah, what's your take on the unstoppable angle on this? >> Yeah, I mean, it makes it social. So, instead of you can have a feed, you know, something we're thinking about at Parcel is like a feed of all the real estate transactions, and you could follow certain people, you can follow your friends and see a feed of everything that your friends are doing in English or human readable terms that are not just like a wallet address. So, that's obviously a big one and they're also giving people more options in terms of, naming and top level domains if you want to be something.wallet or .nft, or hopefully eventually .metaverse- >> John: Yes. >> Will help expand that ecosystem much more. In addition to like on our... Like backend being able to capture email when they login and to provide better marketing for our users. >> What would you guys say to other metaverse partners looking for work with unstoppable domains for their login and digital identity, what would you recommend? >> It doesn't make sense to- >> I believe- >> Connect with the best DAO and integrate that if you want to keep shipping stuff for your community and keeping it exciting and engaging and enabling user choice in how they choose to display their identity in virtual environments. >> Yeah, there's practically no downside and plenty of upside, again, having those users who are already using unstoppable domains quickly, you know, log into your site and plug in. >> All right. That's awesome. Good stuff with unstoppable. I got to ask you guys give an example of on your products, I love the metaverse progression. I love the pioneering work you guys are doing. And again, the funding things are different. The user expectations are different. The technology experience are different. Billions of people going to be in enabled for it. What are the cool things you guys got going on? CJ, we were talking before we came on camera about the tree thing you got going on. Take us through some of the things that are exciting that people may not know about or may know about. What should they pay attention to share, share some insight? >> Yeah, of course. So one of the fun things, actually that we're building on that on these sites together with our full team and also some outside contributors from the community and two kin protocol, which is a regenerative finance protocol. And I'll get into that a little bit in a minute. Effectively what we're actually doing is planting a carbon capturing virtual forest inside of the metaverse that will in future also be bio diverse. So how we're approaching that is imagine that you can plant NFT trees inside of the metaverse, providing that your will deposit X amount of kind of USD stablecoin or Ether or some digital asset. You can actually use that to deposit inside of the tree. And we will use some, probably something like super fluid, which is like a kind of smart projecting infrastructure platform. And we all essentially enable every single second funds being sent from the contract and actually purchasing real world carbon credits. So legitimate, you know, government bags to carbon credits from the voluntary kind of public market that have actually been bridged on chain, transformed into a crypto asset, and they will be locked away inside of these trees inside of game forever. And in future, we also hope to have like user on animals, roaming the great forest of Atlantis, which will have biodiversity and endangered species credit, locked inside. And we hope to support a variety of different kind of sustainable assets and things like that to really populate this ecosystem. >> So it's you're doing climate change good for real, as well as rendering it as an asset for everyone to see and enjoy. >> Absolutely. And for me, that's what makes the metaverse the metaverse, that's what I talked about. It's how Web3 enables the metaverse to cross over into our real world, ordinary life from URL to IRL and actually provide some incredible positive impact for all of humanity on the planet. >> And Noah, you have some action going on there. I mean, I would be like, "oh, virtual real estate, isn't it unlimited real estate?" But when you have users come together, this value, we've seen this in gaming, what are some of the cool things you got going on over there at Parcel? >> Yeah, I think one thing that stands out, which maybe not enough people are thinking about are AR virtual world. So, right now a lot of people are focused on the VR types, central and sandbox and, and Atlantis, but there very well may be a billion people using augmented reality before there are a billion using virtual reality just because of the nature of the hardware development and apple may come out with their AR headset by the end of the year. So there are a few projects there they've taken the real world to map and Parcel it out into hexagons, and you can actually buy that, and you own that, that piece and you can put your own custom content there. And on that social impact point, we have heard about a few projects that are trying to use it for good. And like one project is bought up some land in the Amazon rain forest and some of the proceeds go to conservation of the rain forest. So, you know, we're all about using blockchain for good and right, coming together as a globe. >> I can't wait to see the commercial real estate division of your group with all the work from, a remote coming on. Guys, great stuff you got going on, again, you guys are pioneering an area that is coming big. It's coming strong, its got a lot of... A momentum, vitality, and energy to it. Put a plug in for your companies. Noah, we'll start with you. What's going on with Parcel, share a plug for the company. What you're looking for, do some key highlights, news, take a minute to, to give a plug. >> Sure. Yeah, great. We are the destination for virtual real estate and that extends well beyond just the buyers and sellers. That's everyone across the whole chain with property managers and property developers, but then also the builders and creators and artists, and we are working right now on aggregating the best creator directory in the metaverse. So you can think of it as a place where artists can come showcase their work and get hired. As well as just generally like bridging this knowledge gap that is much wider than we even expected. So we have our Parcel learn product coming soon, which is a fully fledged, knowledge base with education, informational content and lots of rich data. >> Where can people get involved? What's the channels? Are all channels open? Where can we find you? >> Yeah, our websites Parcel.so on Twitter, you can find us at ParcelNFT and you can link to our discord from either one of those. It's the best way to get involved. >> All right, CJ, put a plug in for the last world, I know you got a lot of action to share. >> Yeah, of course. I would love to see everybody there. Thanks so much for having us. And thanks for listening. Like I said, at the start of the call, we're building the Web3 social metaverse and we're connecting Web3 with social gaming and education, in one light web virtual world that's accessible to everybody. We're also doing some crazy stuff like planting their cabin, capturing virtual forest and all of that, and trying to be the infrastructure layer for Web3 driven real world utility inside of the metaverse. And we believe that we have designed the critical value capture mechanism for virtual learn. I we'll be sharing more all of that very soon and continuing to integrate the best apps from across the Web3 ecosystem and showcasing them at the center of Atlantis. You can go to discord.gg/atlantisworld. If you would love to learn more about us, you can go to wiki.atlantis.world. And there is some documentation now, which includes back story and team and some of our milestones and achievements so far from winning hackathons to raising grants and launching our Alpha belt, soft launching it. And we all have the public free to play coming in March. And where most active, I would say on discord and Twitter. On Twitter you can find us atlantisOx, or just search Atlantis world. And it's the first one that come up. >> All right. CJ, thank you. Noah, thanks for coming out. I really appreciate you spending the time here, and unstoppable showcase and being a partner. Again they got the great digital identity, great plug there for them here. Thanks for sharing that and thanks for sharing the time. Appreciate you guys are pioneer of some good stuff. Appreciate it. >> Thanks so much man. >> I so appreciate that. >> All right, theCUBE's unstoppable domains partner showcase. Thanks for watching. (bright music)

>>Hey everyone. Welcome back to the cubes. Live coverage of women in data science, worldwide conference widths 2022. I'm Lisa Martin coming to you from Stanford university at the Arriaga alumni center. And I'm pleased to welcome my next guest. Hannah Sperling joins me business process intelligence or BPI, academic and research alliances at SAP HANA. Welcome to the program. >>Hi, thank you so much for having me. >>So you just flew in from Germany. >>I did last week. Yeah. Long way away. I'm very excited to be here. Uh, but before we get started, I would like to say that I feel very fortunate to be able to be here and that my heart and vicious still goes out to people that might be in more difficult situations right now. I agree >>Such a it's one of my favorite things about Wiz is the community that it's grown into. There's going to be about a 100,000 people that will be involved annually in woods, but you walk into the Arriaga alumni center and you feel this energy from all the women here, from what Margo and teams started seven years ago to what it has become. I was happened to be able to meet listening to one of the panels this morning, and they were talking about something that's just so important for everyone to hear, not just women, the importance of mentors and sponsors, and being able to kind of build your own personal board of directors. Talk to me about some of the mentors that you've had in the past and some of the ones that you have at SAP now. >>Yeah. Thank you. Um, that's actually a great starting point. So maybe talk a bit about how I got involved in tech. Yeah. So SAP is a global software company, but I actually studied business and I was hired directly from university, uh, around four years ago. And that was to join SAP's analytics department. And I've always had a weird thing for databases, even when I was in my undergrad. Um, I did enjoy working with data and so working in analytics with those teams and some people mentoring me, I got into database modeling and eventually ventured even further into development was working in analytics development for a couple of years. And yeah, still am with a global software provider now, which brought me to women and data science, because now I'm also involved in research again, because yeah, some reason couldn't couldn't get enough of that. Um, maybe learn about the stuff that I didn't do in my undergrad. >>And post-grad now, um, researching at university and, um, yeah, one big part in at least European data science efforts, um, is the topic of sensitive data and data privacy considerations. And this is, um, also topic very close to my heart because you can only manage what you measure, right. But if everybody is afraid to touch certain pieces of sensitive data, I think we might not get to where we want to be as fast as we possibly could be. And so I've been really getting into a data and anonymization procedures because I think if we could random a workforce data usable, especially when it comes to increasing diversity in stem or in technology jobs, we should really be, um, letting the data speak >>And letting the data speak. I like that. One of the things they were talking about this morning was the bias in data, the challenges that presents. And I've had some interesting conversations on the cube today, about data in health care data in transportation equity. Where do you, what do you think if we think of international women's day, which is tomorrow the breaking the bias is the theme. Where do you think we are from your perspective on breaking the bias that's across all these different data sets, >>Right. So I guess as somebody working with data on a daily basis, I'm sometimes amazed at how many people still seem to think that data can be unbiased. And this has actually touched upon also in the first keynote that I very much enjoyed, uh, talking about human centered data science people that believe that you can take the human factor out of any effort related to analysis, um, are definitely on the wrong path. So I feel like the sooner that we realize that we need to take into account certain bias sees that will definitely be there because data is humanly generated. Um, the closer we're going to get to something that represents reality better and might help us to change reality for the better as well, because we don't want to stick with the status quo. And any time you look at data, it's definitely gonna be a backward looking effort. So I think the first step is to be aware of that and not to strive for complete objectivity, but understanding and coming to terms with the fact just as it was mentioned in the equity panel, that that is logically impossible, right? >>That's an important, you bring up a really important point. It's important to understand that that is not possible, but what can we work with? What is possible? What can we get to, where do you think we are on the journey of being able to get there? >>I think that initiatives like widths of playing an important role in making that better and increasing that awareness there a big trend around explainability interpretability, um, an AI that you see, not just in Europe, but worldwide, because I think the awareness around those topics is increasing. And that will then, um, also show you the blind spots that you may still have, no matter how much you think about, um, uh, the context. Um, one thing that we still need to get a lot better at though, is including everybody in these types of projects, because otherwise you're always going to have a certain selection in terms of prospectus that you're getting it >>Right. That thought diversity there's so much value in thought diversity. That's something that I think I first started talking about thought diversity at a Wood's conference a few years ago, and really understanding the impact there that that can make to every industry. >>Totally. And I love this example of, I think it was a soap dispenser. I'm one of these really early examples of how technology, if you don't watch out for these, um, human centered considerations, how technology can, can go wrong and just, um, perpetuate bias. So a soap dispenser that would only recognize the hand, whether it was a certain, uh, light skin type that w you know, be placed underneath it. So it's simple examples like that, um, that I think beautifully illustrate what we need to watch out for when we design automatic decision aids, for example, because anywhere where you don't have a human checking, what's ultimately decided upon you end up, you might end up with much more grave examples, >>Right? No, it's, it's I agree. I, Cecilia Aragon gave the talk this morning on the human centered guy. I was able to interview her a couple of weeks ago for four winds and a very inspiring woman and another herself, but she brought up a great point about it's the humans and the AI working together. You can't ditch the humans completely to your point. There are things that will go wrong. I think that's a sends a good message that it's not going to be AI taking jobs, but we have to have those two components working better. >>Yeah. And maybe to also refer to the panel discussion we heard, um, on, on equity, um, I very much liked professor Bowles point. Um, I, and how she emphasized that we're never gonna get to this perfectly objective state. And then also during that panel, um, uh, data scientists said that 80% of her work is still cleaning the data most likely because I feel sometimes there is this, um, uh, almost mysticism around the role of a data scientist that sounds really catchy and cool, but, um, there's so many different aspects of work in data science that I feel it's hard to put that all in a nutshell narrowed down to one role. Um, I think in the end, if you enjoy working with data, and maybe you can even combine that with a certain domain that you're particularly interested in, be it sustainability, or, you know, urban planning, whatever that is the perfect match >>It is. And having that passion that goes along with that also can be very impactful. So you love data. You talked about that, you said you had a strange love for databases. Where do you, where do you want to go from where you are now? How much more deeply are you going to dive into the world of data? >>That's a good question because I would, at this point, definitely not consider myself a data scientist, but I feel like, you know, taking baby steps, I'm maybe on a path to becoming one in the future. Um, and so being at university, uh, again gives me, gives me the opportunity to dive back into certain courses and I've done, you know, smaller data science projects. Um, and I was actually amazed at, and this was touched on in a panel as well earlier. Um, how outdated, so many, um, really frequently used data sets are shown the realm of research, you know, AI machine learning, research, all these models that you feed with these super outdated data sets. And that's happened to me like something I can relate to. Um, and then when you go down that path, you come back to the sort of data engineering path that I really enjoy. So I could see myself, you know, keeping on working on that, the whole data, privacy and analytics, both topics that are very close to my heart, and I think can be combined. They're not opposites. That is something I would definitely stay true to >>Data. Privacy is a really interesting topic. We're seeing so many, you know, GDPR was how many years did a few years old that is now, and we've got other countries and states within the United States, for example, there's California has CCPA, which will become CPRA next year. And it's expanding the definition of what private sensitive data is. So we're companies have to be sensitive to that, but it's a huge challenge to do so because there's so much potential that can come from the data yet, we've got that personal aspect, that sensitive aspect that has to be aware of otherwise there's huge fines. Totally. Where do you think we are with that in terms of kind of compliance? >>So, um, I think in the past years we've seen quite a few, uh, rather shocking examples, um, in the United States, for instance, where, um, yeah, personal data was used or all proxies, um, that led to, uh, detrimental outcomes, um, in Europe, thanks to the strong data regulations. I think, um, we haven't had as many problems, but here the question remains, well, where do you draw the line? And, you know, how do you design this trade-off in between increasing efficiency, um, making business applications better, for example, in the case of SAP, um, while protecting the individual, uh, privacy rights of, of people. So, um, I guess in one way, SAP has a, as an easier position because we deal with business data. So anybody who doesn't want to care about the human element maybe would like to, you know, try building models and machine generated data first. >>I mean, at least I would feel much more comfortable because as soon as you look at personally identifiable data, you really need to watch out, um, there is however ways to make that happen. And I was touching upon these anonymization techniques that I think are going to be, um, more and more important in the, in the coming years, there is a proposed on the way by the European commission. And I was actually impressed by the sophisticated newness of legislation in, in that area. And the plan is for the future to tie the rules around the use of data science, to the specific objectives of the project. And I think that's the only way to go because of the data's out there it's going to be used. Right. We've sort of learned that and true anonymization might not even be possible because of the amount of data that's out there. So I think this approach of, um, trying to limit the, the projects in terms of, you know, um, looking at what do they want to achieve, not just for an individual company, but also for us as a society, think that needs to play a much bigger role in any data-related projects where >>You said getting true anonymization isn't really feasible. Where are we though on the anonymization pathway, >>If you will. I mean, it always, it's always the cost benefit trade off, right? Because if the question is not interesting enough, so if you're not going to allocate enough resources in trying to reverse engineer out an old, the tie to an individual, for example, sticking true to this, um, anonymization example, um, nobody's going to do it right. We live in a world where there's data everywhere. So I feel like that that's not going to be our problem. Um, and that is why this approach of trying to look at the objectives of a project come in, because, you know, um, sometimes maybe we're just lucky that it's not valuable enough to figure out certain details about our personal lives so that nobody will try, because I am sure that if people, data scientists tried hard enough, um, I wonder if there's challenges they wouldn't be able to solve. >>And there has been companies that have, you know, put out data sets that were supposedly anonymized. And then, um, it wasn't actually that hard to make interferences and in the, in the panel and equity one lab, one last thought about that. Um, we heard Jessica speak about, uh, construction and you know, how she would, um, she was trying to use, um, synthetic data because it's so hard to get the real data. Um, and the challenge of getting the synthetic data to, um, sort of, uh, um, mimic the true data. And the question came up of sensors in, in the household and so on. That is obviously a huge opportunity, but for me, it's somebody who's, um, very sensitive when it comes to privacy considerations straight away. I'm like, but what, you know, if we generate all this data, then somebody uses it for the wrong reasons, which might not be better urban planning for all different communities, but simple profit maximization. Right? So this is something that's also very dear to my heart, and I'm definitely going to go down that path further. >>Well, Hannah, it's been great having you on the program. Congratulations on being a Wood's ambassador. I'm sure there's going to be a lot of great lessons and experiences that you'll take back to Germany from here. Thank you so much. We appreciate your time for Hannah Sperling. I'm Lisa Martin. You're watching the QS live coverage of women in data science conference, 2020 to stick around. I'll be right back with my next guest.

(contemplative upbeat music) >> Hello and welcome to this CUBE Conversation. I'm John Furrier, your host of theCUBE, here in Palo Alto, California. Got a great topic on expanding capabilities for urgent computing. Dan Stanzione, he's Executive Director of TACC, the Texas Advanced Computing Center, and Rajesh Pohani, VP of PowerEdge, HPC Core Compute at Dell Technologies. Gentlemen, welcome to this CUBE Conversation. >> Thanks, John. >> Thanks, John, good to be here. >> Rajesh, you got a lot of computing in PowerEdge, HPC, Core Computing. I mean, I get a sense that you love compute, so we'll jump right into it. And of course, I got to love TACC, Texas Advanced Computing Center. I can imagine a lot of stuff going on there. Let's start with TACC. What is the Texas Advanced Computing Center? Tell us a little bit about that. >> Yeah, we're part of the University of Texas at Austin here, and we build large-scale supercomputers, data systems, AI systems, to support open science research. And we're mainly funded by the National Science Foundation, so we support research projects in all fields of science, all around the country and around the world. Actually, several thousand projects at the moment. >> But tied to the university, got a lot of gear, got a lot of compute, got a lot of cool stuff going on. What's the coolest thing you got going on right now? >> Well, for me, it's always the next machine, but I think science-wise, it's the machines we have. We just finished deploying Lonestar6, which is our latest supercomputer, in conjunction with Dell. A little over 600 nodes of those PowerEdge servers that Rajesh builds for us. Which makes more than 20,000 that we've had here over the years, of those boxes. But that one just went into production. We're designing new systems for a few years from now, where we'll be even larger. Our Frontera system was top five in the world two years ago, just fell out of the top 10. So we've got to fix that and build the new top-10 system sometime soon. We always have a ton going on in large-scale computing. >> Well, I want to get to the Lonestar6 in a minute, on the next talk track, but... What are some of the areas that you guys are working on that are making an impact? Take us through, and we talked before we came on camera about, obviously, the academic affiliation, but also there's a real societal impact of the work you're doing. What are some of the key areas that the TACC is making an impact? >> So there's really a huge range from new microprocessors, new materials design, photovoltaics, climate modeling, basic science and astrophysics, and quantum mechanics, and things like that. But I think the nearest-term impacts that people see are what we call urgent computing, which is one of the drivers around Lonestar and some other recent expansions that we've done. And that's things like, there's a hurricane coming, exactly where is it going to land? Can we refine the area where there's going to be either high winds or storm surge? Can we assess the damage from digital imagery afterwards? Can we direct first responders in the optimal routes? Similarly for earthquakes, and a lot recently, as you might imagine, around COVID. In 2020, we moved almost a third of our resources to doing COVID work, full-time. >> Rajesh, I want to get your thoughts on this, because Dave Vellante and I have been talking about this on theCUBE recently, a lot. Obviously, people see what cloud's, going on with the cloud technology, but compute and on-premises, private cloud's been growing. If you look at the hyperscale on-premises and the edge, if you include that in, you're seeing a lot more user consumption on-premises, and now, with 5G, you got edge, you mentioned first responders, Dan. This is now pointing to a new architectural shift. As the VP of PowerEdge and HPC and Core Compute, you got to look at this and go, "Hmm." If Compute's going to be everywhere, and in locations, you got to have that compute. How does that all work together? And how do you do advanced computing, when you have these urgent needs, as well as real-time in a new architecture? >> Yeah, John, I mean, it's a pretty interesting time when you think about some of the changing dynamics and how customers are utilizing Compute in the compute needs in the industry. Seeing a couple of big trends. One, the distribution of Compute outside of the data center, 5G is really accelerating that, and then you're generating so much data, whether what you do with it, the insights that come out of it, that we're seeing more and more push to AI, ML, inside the data center. Dan mentioned what he's doing at TACC with computational analysis and some of the work that they're doing. So what you're seeing is, now, this push that data in the data center and what you do with it, while data is being created out at the edge. And it's actually this interesting dichotomy that we're beginning to see. Dan mentioned some of the work that they're doing in medical and on COVID research. Even at Dell, we're making cycles available for COVID research using our Zenith cluster, that's located in our HPC and AI Innovation Lab. And we continue to partner with organizations like TACC and others on research activities to continue to learn about the virus, how it mutates, and then how you treat it. So if you think about all the things, and data that's getting created, you're seeing that distribution and it's really leading to some really cool innovations going forward. >> Yeah, I want to get to that COVID research, but first, you mentioned a few words I want to get out there. You mentioned Lonestar6. Okay, so first, what is Lonestar6, then we'll get into the system aspect of it. Take us through what that definition is, what is Lonestar6? >> Well, as Dan mentioned, Lonestar6 is a Dell technology system that we developed with TACC, it's located at the University of Texas at Austin. It consists of more than 800 Dell PowerEdge 6525 servers that are powered with 3rd Generation AMD EPYC processors. And just to give you an example of the scale of this cluster, it could perform roughly three quadrillion operations per second. That's three petaFLOPS, and to match what Lonestar6 can compute in one second, a person would have to do one calculation every second for a hundred million years. So it's quite a good-size system, and quite a powerful one as well. >> Dan, what's the role that the system plays, you've got petaFLOPS, what, three petaFLOPS, you mentioned? That's a lot of FLOPS! So obviously urgent computing, what's cranking through the system there? Take us through, what's it like? >> Sure, well, there there's a mix of workloads on it, and on all our systems. So there's the urgent computing work, right? Fast turnaround, near real-time, whether it's COVID research, or doing... Project now where we bring in MRI data and are doing sort of patient-specific dosing for radiation treatments and chemotherapy, tailored to your tumor, instead of just the sort of general for people your size. That all requires sort of real-time turnaround. There's a lot AI research going on now, we're incorporating AI in traditional science and engineering research. And that uses an awful lot of data, but also consumes a huge amount of cycles in training those models. And then there's all of our traditional, simulation-based workloads and materials and digital twins for aircraft and aircraft design, and more efficient combustion in more efficient photovoltaic materials, or photovoltaic materials without using as much lead, and things like that. And I'm sure I'm missing dozens of other topics, 'cause, like I said, that one really runs every field of science. We've really focused the Lonestar line of systems, and this is obviously the sixth one we built, around our sort of Texas-centric users. It's the UT Austin users, and then with contributions from Texas A&M , and Texas Tech and the University of Texas system, MD Anderson Healthcare Center, the University of North Texas. So users all around the state, and every research problem that you might imagine, those are into. We're just ramping up a project in disaster information systems, that's looking at the probabilities of flooding in coastal Texas and doing... Can we make building code changes to mitigate impact? Do we have to change the standard foundation heights for new construction, to mitigate the increasing storm surges from these sort of slow storms that sit there and rain, like hurricanes didn't used to, but seem to be doing more and more. All those problems will run on Lonestar, and on all the systems to come, yeah. >> It's interesting, you mentioned urgent computing, I love that term because it could be an event, it could be some slow kind of brewing event like that rain example you mentioned. It could also be, obviously, with the healthcare, and you mentioned COVID earlier. These are urgent, societal challenges, and having that available, the processing capability, the compute, the data. You mentioned digital twins. I can imagine all this new goodness coming from that. Compare that, where we were 10 years ago. I mean, just from a mind-blowing standpoint, you have, have come so far, take us through, try to give a context to the level of where we are now, to do this kind of work, and where we were years ago. Can you give us a feel for that? >> Sure, there's a lot of ways to look at that, and how the technology's changed, how we operate around those things, and then sort of what our capabilities are. I think one of the big, first, urgent computing things for us, where we sort of realized we had to adapt to this model of computing was about 15 years ago with the big BP Gulf Oil spill. And suddenly, we were dumping thousands of processors of load to figure out where that oil spill was going to go, and how to do mitigation, and what the potential impacts were, and where you need to put your containment, and things like that. And it was, well, at that point we thought of it as sort of a rare event. There was another one, that I think was the first real urgent computing one, where the space shuttle was in orbit, and they knew something had hit it during takeoff. And we were modeling, along with NASA and a bunch of supercomputers around the world, the heat shield and could they make reentry safely? You have until they come back to get that problem done, you don't have months or years to really investigate that. And so, what we've sort of learned through some of those, the Japanese tsunami was another one, there have been so many over the years, is that one, these sort of disasters are all the time, right? One thing or another, right? If we're not doing hurricanes, we're doing wildfires and drought threat, if it's not COVID. We got good and ready for COVID through SARS and through the swine flu and through HIV work, and things like that. So it's that we can do the computing very fast, but you need to know how to do the work, right? So we've spent a lot of time, not only being able to deliver the computing quickly, but having the data in place, and having the code in place, and having people who know the methods who know how to use big computers, right? That's been a lot of what the COVID Consortium, the White House COVID Consortium, has been about over the last few years. And we're actually trying to modify that nationally into a strategic computing reserve, where we're ready to go after these problems, where we've run drills, right? And if there's a, there's a train that derails, and there's a chemical spill, and it's near a major city, we have the tools and the data in place to do wind modeling, and we have the terrain ready to go. And all those sorts of things that you need to have to be ready. So we've really sort of changed our sort of preparedness and operational model around urgent computing in the last 10 years. Also, just the way we scheduled the system, the ability to sort of segregate between these long-running workflows for things that are really important, like we displaced a lot of cancer research to do COVID research. And cancer's still important, but it's less likely that we're going to make an impact in the next two months, right? So we have to shuffle how we operate things and then just, having all that additional capacity. And I think one of the things that's really changed in the models is our ability to use AI, to sort of adroitly steer our simulations, or prune the space when we're searching parameters for simulations. So we have the operational changes, the system changes, and then things like adding AI on the scientific side, since we have the capacity to do that kind of things now, all feed into our sort of preparedness for this kind of stuff. >> Dan, you got me sold, I want to come work with you. Come on, can I join the team over there? It sounds exciting. >> Come on down! We always need good folks around here, so. (laughs) >> Rajesh, when I- >> Almost 200 now, and we're always growing. >> Rajesh, when I hear the stories about kind of the evolution, kind of where the state of the art is, you almost see the innovation trajectory, right? The growth and the learning, adding machine learning only extends out more capabilities. But also, Dan's kind of pointing out this kind of response, rapid compute engine, that they could actually deploy with learnings, and then software, so is this a model where anyone can call up and get some cycles to, say, power an autonomous vehicle, or, hey, I want to point the machinery and the cycles at something? Is the service, do you guys see this going that direction, or... Because this sounds really, really good. >> Yeah, I mean, one thing that Dan talked about was, it's not just the compute, it's also having the right algorithms, the software, the code, right? The ability to learn. So I think when those are set up, yeah. I mean, the ability to digitally simulate in any number of industries and areas, advances the pace of innovation, reduces the time to market of whatever a customer is trying to do or research, or even vaccines or other healthcare things. If you can reduce that time through the leverage of compute on doing digital simulations, it just makes things better for society or for whatever it is that we're trying to do, in a particular industry. >> I think the idea of instrumenting stuff is here forever, and also simulations, whether it's digital twins, and doing these kinds of real-time models. Isn't really much of a guess, so I think this is a huge, historic moment. But you guys are pushing the envelope here, at University of Texas and at TACC. It's not just research, you guys got real examples. So where do you guys see this going next? I see space, big compute areas that might need some data to be cranked out. You got cybersecurity, you got healthcare, you mentioned oil spill, you got oil and gas, I mean, you got industry, you got climate change. I mean, there's so much to tackle. What's next? >> Absolutely, and I think, the appetite for computing cycles isn't going anywhere, right? And it's only going to, it's going to grow without bound, essentially. And AI, while in some ways it reduces the amount of computing we do, it's also brought this whole new domain of modeling to a bunch of fields that weren't traditionally computational, right? We used to just do engineering, physics, chemistry, were all super computational, but then we got into genome sequencers and imaging and a whole bunch of data, and that made biology computational. And with AI, now we're making things like the behavior of human society and things, computational problems, right? So there's this sort of growing amount of workload that is, in one way or another, computational, and getting bigger and bigger. So that's going to keep on growing. I think the trick is not only going to be growing the computation, but growing the software and the people along with it, because we have amazing capabilities that we can bring to bear. We don't have enough people to hit all of them at once. And so, that's probably going to be the next frontier in growing out both our AI and simulation capability, is the human element of it. >> It's interesting, when you think about society, right? If the things become too predictable, what does a democracy even look like? If you know the election's going to be over two years from now in the United States, or you look at these major, major waves >> Human companies don't know. >> of innovation, you say, "Hmm." So it's democracy, AI, maybe there's an algorithm for checking up on the AI 'cause biases... So, again, there's so many use cases that just come out of this. It's incredible. >> Yeah, and bias in AI is something that we worry about and we work on, and on task forces where we're working on that particular problem, because the AI is going to take... Is based on... Especially when you look at a deep learning model, it's 100% a product of the data you show it, right? So if you show it a biased data set, it's going to have biased results. And it's not anything intrinsic about the computer or the personality, the AI, it's just data mining, right? In essence, right, it's learning from data. And if you show it all images of one particular outcome, it's going to assume that's always the outcome, right? It just has no choice, but to see that. So how we deal with bias, how do we deal with confirmation, right? I mean, in addition, you have to recognize, if you haven't, if it gets data it's never seen before, how do you know it's not wrong, right? So there's about data quality and quality assurance and quality checking around AI. And that's where, especially in scientific research, we use what's starting to be called things like physics-informed or physics-constrained AI, where the neural net that you're using to design an aircraft still has to follow basic physical laws in its output, right? Or if you're doing some materials or astrophysics, you still have to obey conservation of mass, right? So I can't say, well, if you just apply negative mass on this other side and positive mass on this side, everything works out right for stable flight. 'Cause we can't do negative mass, right? So you have to constrain it in the real world. So this notion of how we bring in the laws of physics and constrain your AI to what's possible is also a big part of the sort of AI research going forward. >> You know, Dan, you just, to me just encapsulate the science that's still out there, that's needed. Computer science, social science, material science, kind of all converging right now. >> Yeah, engineering, yeah, >> Engineering, science, >> slipstreams, >> it's all there, >> physics, yeah, mmhmm. >> it's not just code. And, Rajesh, data. You mentioned data, the more data you have, the better the AI. We have a world what's going from silos to open control planes. We have to get to a world. This is a cultural shift we're seeing, what's your thoughts? >> Well, it is, in that, the ability to drive predictive analysis based on the data is going to drive different behaviors, right? Different social behaviors for cultural impacts. But I think the point that Dan made about bias, right, it's only as good as the code that's written and the way that the data is actually brought into the system. So making sure that that is done in a way that generates the right kind of outcome, that allows you to use that in a predictive manner, becomes critically important. If it is biased, you're going to lose credibility in a lot of that analysis that comes out of it. So I think that becomes critically important, but overall, I mean, if you think about the way compute is, it's becoming pervasive. It's not just in selected industries as damage, and it's now applying to everything that you do, right? Whether it is getting you more tailored recommendations for your purchasing, right? You have better options that way. You don't have to sift through a lot of different ideas that, as you scroll online. It's tailoring now to some of your habits and what you're looking for. So that becomes an incredible time-saver for people to be able to get what they want in a way that they want it. And then you look at the way it impacts other industries and development innovation, and it just continues to scale and scale and scale. >> Well, I think the work that you guys are doing together is scratching the surface of the future, which is digital business. It's about data, it's about out all these new things. It's about advanced computing meets the right algorithms for the right purpose. And it's a really amazing operation you guys got over there. Dan, great to hear the stories. It's very provocative, very enticing to just want to jump in and hang out. But I got to do theCUBE day job here, but congratulations on success. Rajesh, great to see you and thanks for coming on theCUBE. >> Thanks for having us, John. >> Okay. >> Thanks very much. >> Great conversation around urgent computing, as computing becomes so much more important, bigger problems and opportunities are around the corner. And this is theCUBE, we're documenting it all here. I'm John Furrier, your host. Thanks for watching. (contemplative music)

>>Hello, and welcome to the cube special presentation of unstoppable domains partner showcase. I'm John furrier, your host of the cube. We got a great conversation talking about the future of the infrastructure of web three, all around domains, non fungible tokens, and more two great guests. Charlie Brooks, with business development of ensemble domains, and Michael Williams, product leader and advisor with unstoppable doing gentlemen, thanks for coming on the cube partner showcase with unstoppable domains. >>Thanks John. Excited to be here. So >>I love what you guys are doing. Congratulations on all your success. You guys are on the leading edge of what is a major infrastructure shift. Web three is being called, but people who have been doing this for a while, know that you see the blockchain, you see decentralization, you see immutability, all these future smart contracts. All the decentralized applications are now hitting the scene and NFTs are super hot as, as, as you can imagine, you guys are in the middle of it. So you guys are in, in, in the sweet spot of what I call the pragmatic pioneers. You guys are to building solutions that are making a difference like single sign-on. You have the login product, let's get into it. What is the path to I digital identity beyond the web, because we know what web identity is, but now that the web is kind of being abstracted away by this new web three layer, what is digital identity? >>Yeah, I can take that one. So I think what we're really seeing is this transition away from a purely physical identity where your digital life or where your, your online identity is really just a reflection of the, the parts of your physical identity, where you live, where you go to school, all of these things. And we're really seeing this world emerge where your online identity becomes much more of a primary. So if you have a way that you represent yourself in the online world, whether that's an Instagram account or TechTalk or email address or username, all of these things together make up your digital identity. So congrats. If you have any of those things, you already have one. >>Yeah. And we see that all the time with link tree people put their link tree out there and it's got the zillion handles. You're right. We all get up to Instagram and everyone's got like zillion identities. Is that a problem or an opportunity? >>I think it's just a reality. The fact that as our identities are spread across all of these different services and platforms that we use, the problem with something like link tree is that it is owned by link tree. You know, if I won the lottery purchased link tree and decided I wanted to change your personal website, John, I could easily do that. Moving to the kind of architecture that we have. And then if T architecture changes that significantly, it puts a lot of power back in the hands of the people who actually own those identities. >>You know, I do a lot of cube showcases with folks rent on my machine, learning and AI, and the number one conversation that they bring up. The number one issue is data. And they say when data is siloed and, and protected and owned, it is not optimized for machine learning. So I can almost imagine, as you bring NFTs to the digital identity, you mentioned you don't own your identity. If someone else is managing the service like link tree, this is, this is a cultural shift. This is an infrastructure software shift at the same time. Can you guys expand more about what you guys are doing with the NFT and ensemble domains with respect to that digital identity, because is that power shifting to the users now? And how does that compare to what's out there today? >>Sure. I think so. Our domains are NFTs, so they are ERC 7 21 tokens. And if you think about the past kind of web two identities are controlled by the platforms that we use, Twitter, Facebook, whatnot. There's a really a lack of data portability there. Our accounts and data live on their servers. They can be deleted at any time. So using an NFT to anchor your digital identity really gives you full control over your identity. You can't, it can't be deleted. It can't be revoked or edited or changed without your permission. And really, even better than information you store on your entity domain can be plugged into the services you use so that you never have to enter the same data twice. So when you go from platform to platform, everything can be tied to your existing domain. You're not going to a new site, kind of entering their ecosystem and providing all this information time and time again, and not really having a clear understanding of how your data is being used and where it's being stored. >>So the innovation here is the NFT is your identity and, and a non fungible token NFT is different than say a fungible tokens. So for the folks out there, that's trying to follow the bouncing ball. Michael, what's the difference between an NFT and a fungible token. And how does, and why is that important for identity? >>Yeah. My favorite metaphor here is baseball cards versus like dollar bills. So a dollar bill is fungible. If I have a dollar and then you have a dollar, we can trade dollars. And none of us is richer or poorer. If I have a babe Ruth and you have a Hank Aaron, and we swap baseball cards, like we have, we have changed something fundamental. So the, the important thing about NFT is, is that they are non fungible. So if I have a domain and you have a domain, like I have that identity and you have that identity, they are unique. They're independent, they're owned by each one of us. And then we can kind of swap them interchangeably. >>And that's why you're seeing NFTs hot with art and artists, because it's like a property, it's a property issue, not so much absolutely changeable, a divisible kind of asset. >>It is a, it is ownership rights in digital >>Form. Yes. All right. So now let's get into what the, the identity piece. I think I find that interesting because if I have something that's an NFT, it's not fungible. It's unique to me. It's property, my property, my login, this sounds compelling. So how does log-in work with the NFT? Can you guys take us through that, that architecture, what does it do? How does it work? And what's the benefit? >>So the way our login product works is it effectively uses your NFT domain. So Michael dot crypto, for example, as the authentication piece of a, of a login session. So basically when I, when I go and I try to log in with my domain, I type in Michael dot crypto. I sign it with my wallet, which cryptographically proves that I am this human. This is me. I have the rights to log in. And then when I do so I have the ability to share certain parts of my identity information with the applications that I use. And so it really blends the best of the ease of use from web to have just a standard like login with Gmail SSL experience, with all of the security and privacy benefits of web three. >>How important is single sign-on because, I mean, right now people are used to like, seeing things like log with your kid hub handle or LinkedIn, or, you know, Google, apple. I mean, you're seeing people offering login. Okay. What's the difference here from those solutions and why is it make sense for the user? >>Sure. Yeah. The big differences, what we're building is really user first. So if you think about traditional SSOs, you are the product. When you use their product, they're selling your data and, you know, they're tracking everything you do logging in with unstoppable handles, not only authentication, but data sharing as well. So when you log in a domain or owner can choose to share aspects of their online identity, such as first name, preferred language profile, picture location. So this is a user controlled way of using a sign-on, where they are permissioning, these different pieces of their identity. And really apps can use this information to enable new experiences, such as for example, website might automatically enable high contrast mode for someone visually impaired. It could, pre-populate your friends from a decentralized social graph. So what we're doing is taking the best parts of web to SSL and combining them with the best parts of web three. >>So no more losing your password entering in the same data, hundreds of times, you know, depending on other services, keep your information safe. Logging with unstoppable really puts you in complete control of your data. And, you know, a big part of that is you're not going to have 80 plus usernames and passwords anymore. You know, we have these tools like password managers that exist to kind of put a bandaid on this issue, but it's not really a long-term solution. So we're, we're building is really seamless onboarding where everything can be tied to your domain so that you can navigate to different apps in a much more seamless way. >>Michael, I got to get your thoughts on this because on the product side, it's interesting. My mind's kind of connecting some dots if I have, first of all, great convenience to reduce all those logins, right? So, you know, check their little pain, pain reduction. But when you think about what's different, I can now broker my data as well as log in. So let's just say, hypothetically, I'm cruising around some D apps and, you know, doing things and earning reputation or attention or points or whatever, tokens utility tokens. There could be a way for me to control what I own. I'm the product I own the data. Is that kind of where this is going? >>I think it's definitely a direction. It could go say, for example, if I'm a e-commerce platform and I'm trying to figure out where I'm going to place a new billboard, you know, one of the things that I could request from a user is their address. I can figure out where they live, what city they're in that will help inform the, the decision that I need to make as a business. And in return, maybe I give that person a dollar off their purchase, right? Like we can, we can start to build a stronger relationship between the applications that people use and the people that use them and try to optimize that whole experience and try to just transfer information back and forth to make everyone's lives better. >>What's the roadmap on the business side, Charlie, when you see companies kind of adopting it, they're probably taking baby steps or crawling before they walk they're walking before they run. I mean, I can see decentralized applications in the future, whether it's FinTech or whatever, having new kinds of marketplaces that take advantage of the paradigm where the, the script flips to the user first. Okay. So I see that. How do people get started now? What are some of the success momentum points that you're seeing companies do now with unstoppable? >>Sure. So a lot of web three apps are very sensitive about respecting the, the information that their users are providing, right? So what we're doing is I'm offering different ways for apps can touch with their users in a way that is user controlled. So an example there is that a lot of web three companies will use wallet connect to allow users to log in using a wallet address, an issue. There is that one person can have hundreds of wallet addresses, and it's impossible for the app to understand that. So what we do is we use login, we attach an email address, some other pieces to a wallet address so that we can identify who a unique user is. And the app is able to collect that information. They don't have to deal with passwords or PII storage. They have access to a huge amount of new data for an improved UX. >>It's really simple to implement and maintain as well. So one example there is if you are a DFI platform and you want to reward your users for coming to their site for the first time, now that they can identify unique user, they can drop a token into that user's wallet all because they're able to identify that user as unique. So they have a better way of understanding their customers. They enable their customers to share data. A lot of these companies well ask users to follow them on Twitter or discord when they need to provide updates or, you know, bug bounties, all these different things and log in with unstoppable, lets them permission, email addresses so they can collect emails if they want to do a newsletter. And instead of sort of harvesting data from elsewhere and kind of forcing people to join this newsletter program, it's all user controlled. So each user saying, yes, you can use my email for your newsletter. You know, I'm supporting your project, want to be kept up to date with bugs or bounties or rewards programs. So really it's just kind of a, a better way for users to, to share the data that they're willing to with dApps and dabs can use it to create all sorts of incentives and really just kind of understand their users on a, on a different level. >>How has the development Michael going on the, on the smart contract side of the business, you know, theories has always been heralded as being very developer focused. There's been great innovations. Just, you still got, you know, gas fees out there. You still gotta do some things. How is the development environment, how are the applications coming? Cause I can see the really, I can see the flywheel kicking in as a developer, Frank gets more streamlined, more efficient, and now you've got the identity piece nailed down. I just see a lot of kind of dominoes falling at the same time. What's the status on the dev side? >>What's your tour? The fascinating thing about crypto is how quickly it changes. You know, when I, when I joined Ethereum was pretty reasonable still for transactions. It was very cheap to get things done very fast. We've looked at last summer that things went completely out of control. This is a big reason that unstoppable for a long time has been working on a layer two and we've moved over to the Pollyanna, our primary source of record, which is built on top of it. The area of course, I think saved well over a hundred million dollars in Gaspe is for our users that we're constantly keeping an eye on new technologies that are emerging, weighing how we can incorporate those things and really where this industry is going to take us. You know, in many ways we are, are just as much passengers as the other people floating around the ecosystem as well. >>Yeah, it's, it's certainly getting faster every day and seeing a huge uptake on a theorem. I heard a stat that most people at the university of California, Berkeley, 30% of the computer science students are dropping out to join web three companies just goes to show you this cultural shift and you can see a lot more companies getting involved. So I got to ask you Charlie, on the biz dev front, how are companies getting started? What's the playbook? Are they putting their toe in the water? Are they jumping in full throttle? What's, what's the, what's the roadmap. What's the best practice for people to get started with unstoppable? >>Absolutely. You know, we're lucky that we get a lot of inbound interest from companies web two and web three because they first want to secure their domains. And we do a ton of work on the backend to protect trademark domains. We want to avoid squatting as much as possible. You know, we don't think that's the spirit of, of weaponry at all. And certainly not what the original intention of the internet was. So fair amount of companies will reach out to, out to us to get their domain. And then we can have a longer conversation about some of the other integrations and ways we can collaborate. So certainly visiting our website and several domains.com is a great starting point. We have an app submission page where asking, reach out to us, even request a grant. We have a grant prop, a program to help developers get started, provide them some resources to, to work with us and integrate some of our technology. >>We have great documentation as well on the site. So you can read all about what it takes to resolve domains, if you're a water and an exchange, as well as what it takes to integrate login within softball, which is actually a super easy integration as well, which we're, we're really excited about. So yeah, I'd say check out the website apply for our grant. If you think you're a fit there, then of course, people can always reach out to me directly on Twitter, on telegram email. We're very reachable and, and we're always happy to chat with projects and, and learn more about what they're doing. >>What's the coolest thing you've seen going on trial with your partners right now. What's, what's the, what's the number one use case that's cool that people are jumping on right now to get in and get some, some, you know, some success out of the gate. >>Yeah. Maybe, maybe gamefied kind of played, earns huge. It's blowing up. And the gaming community is really passionate, vibrant, just expanding like crazy same with there's all this cool new stuff you can do with defy where no matter, you know, how many, how, how big your kind of portfolio is, you're you're able to stake and use all these interesting tools to kind of grow your book. So it's super exciting to see and talk to all these projects and, you know, there's certainly kind of an energy in the community where everyone wants to onboard the general public to web three, right? So we're all working on these school projects, but we need everyone to come over from web to kind of understand the advantages of defy of game fi of having an empty domain. So I'm lucky that I'm kind of one of the first layers there of, of meeting new projects and kind of helping them get access to more users so that they can grow along with. >>Yeah. I remember the early days of Bitcoin and Ethereum, we were giving it away to give the, the community manager was give a, give a Bitcoin to someone that was when it was, you can actually give a Bitcoin to someone what's the, what's the word of mouth or organic viral. I won't say growth hack because that's got negative connotations, but what's the community's way of putting forth the mission for unstoppable. Is it just more domains you guys have any programs got going on? Is it give it away? I'll see you, you can get domains on your site, but what's the, what's the way to get people in gray shaded in and getting comfortable. >>Yeah. So much of what we do is really just all of that, to all that question, to answer that question, we spent a ton of time and energy just on education and whether that's specifically around domains or just general led three, we have a podcast which is pretty exceptional, which talks to what three leaders from across the space and makes the projects that they're working on more accessible. I think we passed over a hundred episodes, not too long ago. There's a ton of stuff that we do that other people do. If anyone has questions, I'm happy to talk about resources. >>Yeah. The part I think you guys are up to one 17, but that's a deep dive that you guys go deep on the podcast. So that's, you know, where you go in, what else is new on digital identity? Where do you guys see the future going now that you get the baseline identity with the NFT? It makes a lot of sense. Create innovation. Good logic makes sense. Solid. Technically what's next. >>Yeah. I think that's really boils down to the way that the internet has grown. Doesn't really feel like the way that the internet should be like our data shouldn't live in these walled gardens controlled by these large companies. Like ultimately people should be responsible for their own identity it's they should have control over the things that they do online, the data that's shared or the benefit of that data. And so the world that we are working towards is very much that where we are giving people the ability to be paid for sharing their data with companies, we're giving applications, the ability to request information from the people that use those applications to improve their experience. We're really just trying to make connections across the ecosystem, through these products to enable a better experience for everyone. So whether that's the, the use cases that I mentioned already, or maybe viewing reviews on something like Yelp or Amazon that just confirmed that the person that you are looking at is actually a real person, not some bot that's been paid to to the loader review. Like the, the interesting thing about these products is they're so universally applicable, applicable. There are so many different games that we can try to plug them in. So have >>It's a great example. It's double-edged sword. You can have a, a metaverse image and have pre-programmed conversations with, with, you know, liquid audio and the video application, you know, or it's a real person. How do you know the difference? You, these are going to be questions, you know, around, around who solves that problem. Now this is time for bots and is it time not for bots? We all know what happens when you get into the, you know, the game of manipulation, but also it can be helpful. This is where you gotta be smart and identity is critical in this future. Charlie, what's your reaction to the future of digital identity? I mean so much to look at here on the trajectory. >>Yeah. You know, I think a big part of it is data portability, right? If you go to a site like Instagram, you're giving them all this content that's very personal to you and you can't just pack up and leave Instagram. So we want a future where most of these apps are just kind of a front end and you can navigate from one to the other and bring your data with you and not be beholden to the companies that operate centralized servers. So I think data portability is huge and it's going to open up a lot of doors. And, and just going back to that thought on kind of cleaning up web two for a better web three. When I think about the Amazons, the Alps, the Yelps of the world, they're all these bots are all these awful fake reviews. There's a lot of gamification happening that is really just creating a lot of noise. >>And I want to bring kind of transparency back to the internet, where when you see a review, you should know that that's a real human and blockchain technology is enabling us to do that. And certainly enough, two domains are going to play a huge part of that. So I think that having an experience where, you know, and trust the people that you're interacting with is going to be really powerful and just a better experience for everyone. And there's a lot of ramifications with that. You know, politically speaking, we've, we've all seen all the issues with kind of attacking communities and using bots and fake accounts to kind of hit people's pain points is it's kind of sad and, and certainly not something that we want to see continue happening. So whatever we can do to kind of give people their digital identity and help people understand that this is a real person on the other end, I think is huge for, for the future of the internet and really for society as well. >>That's a great call out there. Charlie cleaning up the mess of web 2.0 web two. Well, actually I was, it was 2.0 technically now web three is no nos 0.0 in it, but, but I saw on our listen to the podcast with Matt, this recent one, and he had a great metaphor that went back to when I was growing up in the internet, you got IP addresses, right? And the mess there was, it was, you couldn't find what you want to look and no one could remember what to type in. Cause you can type in IP addresses in the browser back then. And then DNS came out and then keywords that's web. Okay. Now that mess now is fraud. Misinformation, bot manipulation, deep fakes, many other kind of unwanted kind of time to innovate. And every year, every time you had these inflection points, there'd be an abstraction on top of it. So similar thing happening here is that you guys see it too. >>Yeah. I think we're going back to some of the foundational architecture of the internet DNS and really bringing that forward about 30, 40 years in terms of technology. So loading in some work cryptography and some other fancy things to help patch some of those issues from the previous versions of the web. >>Yeah. Awesome. Well guys, thanks so much for coming on and the spirit of our tick talk, you know, I'm only summarize this. Can you guys give us a quick tick tock moment, short comment on, you know, where this is all going, whereas log-in single sign on mean and what should people do to take steps to secure their digital identity? >>Sure. I'll jump in here. So it's time for people to secure their digital identity. That great first step has gone on several domains and getting an entity domain. You know, you can control your data. You can do a lot of cool different things with your domain, including posting your own website that you own forever. And no one can take it away from you. I would certainly recommend the people join. Our discord, telegram community is check out our podcasts. It's really great. Especially if you're new to crypto web three, you know, we do a great job of sort of explaining all the basic concepts and expanding on them. So yeah, I'd say, you know, the time is now, so to get your digital identity and start embracing web three, because it's really exploding right now. And there's just so many incredible advantages, especially for the user, >>Michael, what's your take? >>I mean, I put not, I've said it better myself. >>Like we always say, if you're not on the next wave, your driftwood, and this is a big wave it's happening. It's pretty clear guys. It's it's there, it's happening now. And again, very pragmatic implementations of solving problems. The sign-on the app integration. Congratulations. And we've got our cube domain too, by the way. So we're we're I think we're good. You know, so we've got to put it to you. It's appreciate it, Charlie, Michael, thanks for coming on and sharing the update. Okay. This is the cube with unstoppable domains partner showcase, shout for your hosts. Got a lot of other great interviews. Check them out. We're going to continue our coverage and continue on with this great showcase. Thanks for watching.

>>Yeah. >>Hello. Welcome to the Special Cube conversation here in Palo Alto, California. I'm John for a host of the Cube. We have a conversation around a I for the enterprise. What this means I got two great guests. John Finelli, Vice President, virtual GPU at NVIDIA and Maurizio D V D C T o University of Pisa in Italy. Uh, Practitioner, customer partner, um, got VM world coming up. A lot of action happening in the enterprise. John. Great to see you. Nice to meet you. Remotely coming in from Italy for this remote. >>John. Thanks for having us on again. >>Yeah. Nice to meet >>you. I wish we could be in person face to face, but that's coming soon. Hopefully, John, you were talking. We were just talking about before we came on camera about AI for the enterprise. And the last time I saw you in person was in Cuba interview. We were talking about some of the work you guys were doing in AI. It's gotten so much stronger and broader and the execution of an video, the success you're having set the table for us. What is the ai for the enterprise conversation frame? >>Sure. So, um, we, uh we've been working with enterprises today on how they can deliver a I or explore AI or get involved in a I, um uh, in a standard way in the way that they're used to managing and operating their data centre. Um, writing on top of you know, they're Dell servers with B M or V sphere. Um, so that AI feels like a standard workload that night organisation can deliver to their engineers and data scientists. And then the flip side of that, of course, is ensuring that engineers and data scientists get the workloads position to them or have access to them in the way that they need them. So it's no longer a trouble ticket that you have to submit to, I t and you know, count the hours or days or weeks until you you can get new hardware, right By being able to pull it into the mainstream data centre. I can enable self service provisioning for those folks. So we actually we make a I more consumable or easier to manage for I t administrators and then for the engineers and the data scientists, etcetera. We make it easy for them to get access to those resources so they can get to their work right away. >>Quite progress in the past two years. Congratulations on that and looking. It's only the beginning is Day one Mercy. I want to ask you about what's going on as the CTO University piece of what's happening down there. Tell us a little bit about what's going on. You have the centre of excellence there. What does that mean? What does that include? >>Uh, you know, uh, University of Peace. Are you one of one of the biggest and oldest in Italy? Uh, if you have to give you some numbers is around 50 K students and 3000 staff between, uh, professors resurgence and that cabinet receive staff. So I we are looking into data operation of the centres and especially supports for scientific computing. And, uh, this is our our daily work. Let's say this, uh, taking us a lot of times, but, you know, we are able to, uh, reserve a merchant percentage of our time, Uh, for r and D, And this is where the centre of excellence is, Uh, is coming out. Uh, so we are always looking into new kinds of technologies that we can put together to build new solutions to do next generation computing gas. We always say we are looking for the right partners to do things together. And at the end of the day is the work that is good for us is good for our partners and typically, uh, ends in a production system for our university. So is the evolution of the scientific computing environment that we have. >>Yeah. And you guys have a great track record and reputation of, you know, R and D, testing software, hardware combinations and sharing those best practises, you know, with covid impact in the world. Certainly we see it on the supply chain side. Uh, and John, we heard Jensen, your CEO and video talk multiple keynotes. Now about software, uh, and video being a software company. Dell, you mentioned Dale and VM Ware. You know, Covid has brought this virtualisation world back. And now hybrid. Those are words that we used basically in the text industry. Now it's you're hearing hybrid and virtualisation kicked around in real world. So it's ironic that vm ware and El, uh, and the Cube eventually all of us together doing more virtual stuff. So with covid impacting the world, how does that change you guys? Because software is more important. You gotta leverage the hardware you got, Whether it's Dell or in the cloud, this is a huge change. >>Yeah. So, uh, as you mentioned organisations and enterprises, you know, they're looking at things differently now, Um, you know, the idea of hybrid. You know, when you talk to tech folks and we think about hybrid, we always think about you know, how the different technology works. Um, what we're hearing from customers is hybrid, you know, effectively translates into, you know, two days in the office, three days remote, you know, in the future when they actually start going back to the office. So hybrid work is actually driving the need for hybrid I t. Or or the ability to share resources more effectively. Um, And to think about having resources wherever you are, whether you're working from home or you're in the office that day, you need to have access to the same resources. And that's where you know the the ability to virtualize those resources and provide that access makes that hybrid part seamless >>mercy What's your world has really changed. You have students and faculty. You know, Things used to be easy in the old days. Physical in this network. That network now virtual there. You must really be having him having impact. >>Yeah, we have. We have. Of course. As you can imagine, a big impact, Uh, in any kind of the i t offering, uh, from, uh, design new networking technologies, deploying new networking technologies, uh, new kind of operation we find. We found it at them. We were not able anymore to do burr metal operations directly, but, uh, from the i t point of view, uh, we were how can I say prepared in the sense that, uh, we ran from three or four years parallel, uh, environment. We have bare metal and virtual. So as you can imagine, traditional bare metal HPC cluster D g d g X machines, uh, multi GPU s and so on. But in parallel, we have developed, uh, visual environment that at the beginning was, as you can imagine, used, uh, for traditional enterprise application, or VD. I, uh, we have a significant significant arise on a farm with the grid for remote desktop remote pull station that we are using for, for example, uh, developing a virtual classroom or visual go stations. And so this is was typical the typical operation that we did the individual world. But in the same infrastructure, we were able to develop first HPC individual borders of utilisation of the HPC resources for our researchers and, uh, at the end, ai ai offering and ai, uh, software for our for our researchers, you can imagine our vehicle infrastructure as a sort of white board where we are able to design new solution, uh, in a fast way without losing too much performance. And in the case of the AI, we will see that we the performance are almost the same at the bare metal. But with all the flexibility that we needed in the covid 19 world and in the future world, too. >>So a couple things that I want to get John's thoughts as well performance you mentioned you mentioned hybrid virtual. How does VM Ware and NVIDIA fit into all this as you put this together, okay, because you bring up performance. That's now table stakes. He's leading scale and performance are really on the table. everyone's looking at it. How does VM ware an NVIDIA John fit in with the university's work? >>Sure. So, um, I think you're right when it comes to, uh, you know, enterprises or mainstream enterprises beginning their initial foray into into a I, um there are, of course, as performance in scale and also kind of ease of use and familiarity are all kind of things that come into play in terms of when an enterprise starts to think about it. And, um, we have a history with VM Ware working on this technology. So in 2019, we introduced our virtual compute server with VM Ware, which allowed us to effectively virtual is the Cuda Compute driver at last year's VM World in 2020 the CEOs of both companies got together and made an announcement that we were going to bring a I R entire video AI platform to the Enterprise on top of the sphere. And we did that, Um, starting in March this year, we we we finalise that with the introduction of GM wears V, Sphere seven, update two and the early access at the time of NVIDIA ai Enterprise. And, um, we have now gone to production with both of those products. And so customers, Um, like the University of Pisa are now using our production capabilities. And, um, whenever you virtualize in particular and in something like a I where performances is really important. Um, the first question that comes up is, uh doesn't work and And how quickly does it work Or or, you know, from an I t audience? A lot of times you get the How much did it slow down? And and and so we We've worked really closely from an NVIDIA software perspective and a bm wear perspective. And we really talk about in media enterprise with these fair seven as optimist, certified and supported. And the net of that is, we've been able to run the standard industry benchmarks for single node as well as multi note performance, with about maybe potentially a 2% degradation in performance, depending on the workload. Of course, it's very different, but but effectively being able to trade that performance for the accessibility, the ease of use, um, and even using things like we realise, automation for self service for the data scientists, Um and so that's kind of how we've been pulling it together for the market. >>Great stuff. Well, I got to ask you. I mean, people have that reaction of about the performance. I think you're being polite. Um, around how you said that shows the expectation. It's kind of sceptical, uh, and so I got to ask you, the impact of this is pretty significant. What is it now that customers can do that? They couldn't or couldn't feel they had before? Because if the expectations as well as it worked well, I mean, there's a fast means. It works, but like performance is always concerned. What's different now? What what's the bottom line impact on what country do now that they couldn't do before. >>So the bottom line impact is that AI is now accessible for the enterprise across there. Called their mainstream data centre, enterprises typically use consistent building blocks like the Dell VX rail products, right where they have to use servers that are common standard across the data centre. And now, with NVIDIA Enterprise and B M R V sphere, they're able to manage their AI in the same way that they're used to managing their data centre today. So there's no retraining. There's no separate clusters. There isn't like a shadow I t. So this really allows an enterprise to efficiently deploy um, and cost effectively Deploy it, uh, it without because there's no performance degradation without compromising what their their their data scientists and researchers are looking for. And then the flip side is for the data science and researcher, um, using some of the self service automation that I spoke about earlier, they're able to get a virtual machine today that maybe as a half a GPU as their models grow, they do more exploring. They might get a full GPU or or to GPS in a virtual machine. And their environment doesn't change because it's all connected to the back end storage. And so for the for the developer and the researcher, um, it makes it seamless. So it's really kind of a win for both Nike and for the user. And again, University of Pisa is doing some amazing things in terms of the workloads that they're doing, Um, and, uh and, uh, and are validating that performance. >>Weigh in on this. Share your opinion on or your reaction to that, What you can do now that you couldn't do before. Could you share your experience? >>Our experience is, uh, of course, if you if you go to your, uh, data scientists or researchers, the idea of, uh, sacrificing four months to flexibility at the beginning is not so well accepted. It's okay for, uh, for the Eid management, As John was saying, you have people that is know how to deal with the virtual infrastructure, so nothing changed for them. But at the end of the day, we were able to, uh, uh, test with our data. Scientists are researchers veteran The performance of us almost similar around really 95% of the performance for the internal developer developer to our work clothes. So we are not dealing with benchmarks. We have some, uh, work clothes that are internally developed and apply to healthcare music generator or some other strange project that we have inside and were able to show that the performance on the beautiful and their metal world were almost the same. We, the addition that individual world, you are much more flexible. You are able to reconfigure every finger very fast. You are able to design solution for your researcher, uh, in a more flexible way. An effective way we are. We were able to use the latest technologies from Dell Technologies and Vidia. You can imagine from the latest power edge the latest cuts from NVIDIA. The latest network cards from NVIDIA, like the blue Field to the latest, uh, switches to set up an infrastructure that at the end of the day is our winning platform for our that aside, >>a great collaboration. Congratulations. Exciting. Um, get the latest and greatest and and get the new benchmarks out their new playbooks. New best practises. I do have to ask you marriage, if you don't mind me asking why Look at virtualizing ai workloads. What's the motivation? Why did you look at virtualizing ai work clothes? >>Oh, for the sake of flexibility Because, you know, uh, in the latest couple of years, the ai resources are never enough. So we are. If you go after the bare metal, uh, installation, you are going into, uh, a world that is developing very fastly. But of course, you can afford all the bare metal, uh, infrastructure that your data scientists are asking for. So, uh, we decided to integrate our view. Dual infrastructure with AI, uh, resources in order to be able to, uh, use in different ways in a more flexible way. Of course. Uh, we have a We have a two parallels world. We still have a bare metal infrastructure. We are growing the bare metal infrastructure. But at the same time, we are growing our vehicle infrastructure because it's flexible, because we because our our stuff, people are happy about how the platform behaviour and they know how to deal them so they don't have to learn anything new. So it's a sort of comfort zone for everybody. >>I mean, no one ever got hurt virtualizing things that makes it makes things go better faster building on on that workloads. John, I gotta ask you, you're on the end video side. You You see this real up close than video? Why do people look at virtualizing ai workloads is the unification benefit. I mean, ai implies a lot of things, implies you have access to data. It implies that silos don't exist. I mean, that doesn't mean that's hard. I mean, is this real people actually looking at this? How is it working? >>Yeah. So? So again, um you know for all the benefits and activity today AI brings a I can be pretty complex, right? It's complex software to set up and to manage. And, um, within the day I enterprise, we're really focusing in on ensuring that it's easier for organisations to use. For example Um, you know, I mentioned you know, we we had introduced a virtual compute server bcs, um uh, two years ago and and that that has seen some some really interesting adoption. Some, uh, enterprise use cases. But what we found is that at the driver level, um, it still wasn't accessible for the majority of enterprises. And so what we've done is we've built upon that with NVIDIA Enterprise and we're bringing in pre built containers that remove some of the complexities. You know, AI has a lot of open source components and trying to ensure that all the open source dependencies are resolved so you can get the AI developers and researchers and data scientists. Actually doing their work can be complex. And so what we've done is we've brought these pre built containers that allow you to do everything from your initial data preparation data science, using things like video rapids, um, to do your training, using pytorch and tensorflow to optimise those models using tensor rt and then to deploy them using what we call in video Triton Server Inference in server. Really helping that ai loop become accessible, that ai workflow as something that an enterprise can manage as part of their common core infrastructure >>having the performance and the tools available? It's just a huge godsend people love. That only makes them more productive and again scales of existing stuff. Okay, great stuff. Great insight. I have to ask, What's next one's collaboration? This is one of those better together situations. It's working. Um, Mauricio, what's next for your collaboration with Dell VM Ware and video? >>We will not be for sure. We will not stop here. Uh, we are just starting working on new things, looking for new development, uh, looking for the next beast. Come, uh, you know, the digital world is something that is moving very fast. Uh, and we are We will not We will not stop here because because they, um the outcome of this work has been a very big for for our research group. And what John was saying This the fact that all the software stock for AI are simplified is something that has been, uh, accepted. Very well, of course you can imagine researching is developing new things. But for people that needs, uh, integrated workflow. The work that NVIDIA has done in the development of software package in developing containers, that gives the end user, uh, the capabilities of running their workloads is really something that some years ago it was unbelievable. Now, everything is really is really easy to manage. >>John mentioned open source, obviously a big part of this. What are you going to? Quick, Quick follow if you don't mind. Are you going to share your results so people can can look at this so they can have an easier path to AI? >>Oh, yes, of course. All the all the work, The work that is done at an ideal level from University of Visa is here to be shared. So we we as, uh, as much as we have time to write down we are. We are trying to find a way to share the results of the work that we're doing with our partner, Dell and NVIDIA. So for sure will be shared >>well, except we'll get that link in the comments, John, your thoughts. Final thoughts on the on the on the collaboration, uh, with the University of Pisa and Delvian, where in the video is is all go next? >>Sure. So So with University of Pisa, We're you know, we're absolutely, uh, you know, grateful to Morocco and his team for the work they're doing and the feedback they're sharing with us. Um, we're learning a lot from them in terms of things we can do better and things that we can add to the product. So that's a fantastic collaboration. Um, I believe that Mauricio has a session at the M World. So if you want to actually learn about some of the workloads, um, you know, they're doing, like, music generation. They're doing, you know, covid 19 research. They're doing deep, multi level, uh, deep learning training. So there's some really interesting work there, and so we want to continue that partnership. University of Pisa, um, again, across all four of us, uh, university, NVIDIA, Dell and VM Ware. And then on the tech side, you know, for our enterprise customers, um, you know, one of the things that we actually didn't speak much about was, um I mentioned that the product is optimised certified and supported, and I think that support cannot be understated. Right? So as enterprises start to move into these new areas, they want to know that they can pick up the phone and call in video or VM ware. Adele, and they're going to get support for these new workloads as they're running them. Um, we were also continuing, uh, you know, to to think about we spent a lot of time today on, like, the developer side of things and developing ai. But the flip side of that, of course, is that when those ai apps are available or ai enhanced apps, right, Pretty much every enterprise app today is adding a I capabilities all of our partners in the enterprise software space and so you can think of a beady eye enterprises having a runtime component so that as you deploy your applications into the data centre, they're going to be automatically take advantage of the GPS that you have there. And so we're seeing this, uh, future as you're talking about the collaboration going forward, where the standard data centre building block still maintains and is going to be something like a VX rail two U server. But instead of just being CPU storage and RAM, they're all going to go with CPU, GPU, storage and RAM. And that's going to be the norm. And every enterprise application is going to be infused with AI and be able to take advantage of GPS in that scenario. >>Great stuff, ai for the enterprise. This is a great QB conversation. Just the beginning. We'll be having more of these virtualizing ai workloads is real impacts data scientists impacts that compute the edge, all aspects of the new environment we're all living in. John. Great to see you, Maurizio here to meet you and all the way in Italy looking for the meeting in person and good luck in your session. I just got a note here on the session. It's at VM World. Uh, it's session 22 63 I believe, um And so if anyone's watching, Want to check that out? Um, love to hear more. Thanks for coming on. Appreciate it. >>Thanks for having us. Thanks to >>its acute conversation. I'm John for your host. Thanks for watching. We'll talk to you soon. Yeah,

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel AWS and our community partners. Welcome to the cubes Coverage of AWS reinvent 2020. The digital version I'm Lisa Martin and I'm joined by a couple of guests from Unisys. Please welcome unprompted high BP and Cloud CTO on income. Great to have you on the program. Thanks for joining me today. >>Great to be here leader >>and a new pre or a new Ram Raj, VP of Cloud Services. A new welcome. Great to have you on a swell. Great >>to be here in this virtual AWS being that great. >>Thank you. Very socially Distance We're following all the guidelines here. A new Let's start with you. I'd love to get just kind of Ah, you know, a vision of the AWS Unisys partnership. I know you guys are advanced consulting partner MSP. Tell me about that partnership. >>Absolutely. Lisa, we see our clients on a cloud journey which we accelerate with Unisys Cloud Services and AWS partnership is a big piece of that again. Way thorough. We have bean rated in aws MSP partner Come out very, very highly from those msb audited our, uh and we're investing in multiple competencies across the boat as well. So and we work very closely with AWS in terms off innovating in sharing our platform cloud 44 world map In looking at what our customers looking around the corner, what services could be co developed. So we're looking at some potential I o T engagements to jointly with AWS is, well, eso you're always co inventing and it's a great partnership with a W s >>excellent. And you let's stick with you Following on hybrid Cloud Journey you mentioned the Cloud Forte platform. I wanted to understand what that platform is, how your co developing that with AWS and how your customers are benefiting >>absolutely s. Um, every year Unisys does a cloud barometer study across thousands of our clients and and we got some interesting takeaways from that. Essentially two thirds of her clients that have started this cloud journey believe they don't really realize the benefits out of that and up thio 53% off. The the respondents said they needed some help with cloud security. And this is where I believe that Unisys Cloud Services has a strong viewpoint and can find their AWS, um, journey, no matter where, what challenges they're facing, whether it's budgetary challenges on optimizing AWS and whether it's getting I t operations right when you move your applications to AWS. Um, and is it is it getting the that I have seen cops models established? So no matter where clients are in the A journey, we look to accelerate with our set of solutions and services, and we're very proud about the fact that we respond very me to make sure our clients can innovate and achieve the business outcomes that they need. For example, with California Stink City, we were able to work with them on the AWS. John Pretty set up a native other lake and analytics on top of it so we could actually predict and influence graduation rates with students. Our scores are higher than any off are coming because of the outcomes that we deliver for our clients. And it's really about business outcomes and 40 platform, which helps us drive those outcomes. I mean, probably do you want to add on without cloud 40 platform? >>Sure, I know eso, as as I knew was saying cloud for the platform provides AH set off capabilities that allows us to create an offer highly differentiated services with Unisys Pipe and, as was mentioned earlier, our cloud solutions are are able to help customers no matter where they are in their car, in their cloud journeys, whether it's ah Greenfield opportunity, where they where the customers are intending to move to the cloud, or if it's a brownfield opportunity where they already have adopted the cloud and are looking to manage and operate and optimize their deployments. Cloud Forte Platform and our Cloud Solutions are able to provide, uh, customized solution for that customer context to really deliver the solution that addresses some of the pain points that you talked about. The keeping points really relate to security to get secured. It also relates to cost optimization and then optimizing the cloud purse, a cloud deployment hybrid cloud deployment of the key requirement. So our cloud 40 platform health drives the key use cases. The key pain points that our customers are looking for through a combination off accelerators, the number of cloud photo accelerators that enable customers to rapidly prove it provisioned customers and to rapidly migrate to the cloud with God rails so that they're the secure, their compliant. And then we've got the the Cloud Cloud 40 Cloud management platform for ensuring provisioning onda management and operations, along with cost optimization capabilities and the eyelid operations. So it's a comprehensive suite off services and solutions that addresses the key business outcomes. There are customers are are looking for >>outcomes. Focused is absolutely critical, especially these days. I knew I wanted to go back to you for a second. You talked about the Unisys Barometer study, and I like the name of that. When was that done? And I'm just wondering if there are certain things that you saw this year from a customer. Cloud journey. Need perspective because of the pandemic that have really influenced that barometer >>Wait Question. Hey said and development is study. The last version of it was done late last year, and we're still waiting on the ones from this year. So, but we're starting to see some of the trends that were influenced by the pandemic. We saw rush to cloud when the pandemic hit because business adopt to to remote workers to do more digital selling and then seeing our CEO is kind of struggle with optimizing and maximizing the results off their cloud. Spend right, So So that's a unique challenge that that we're seeing based on our tryingto interaction. So the rush to the cloud and the ask for more spend optimization and in terms of spend optimization, that's an interesting facet because, uh, it cuts through my multiple angles. It's it's cuts through having the platforms around, being able to dio right predictions on where you spend is going, and then it also it's across collaborative effort. Finn ops. As we see it, we call it as a synopsis of is that we bring to our clients it's passing with multiple organizations, including finance, to sometimes figure out. Where will this business be? Where should you spend be? What should be the reserved instance buys right. So combining cloud knowledge with financial knowledge and organizational and business knowledge. And that's the service that we bring to our clients with our phenoms services. At least a great question about how how is I kind of making the current business climate affecting our operating models? Um, like we said, there's increased ask for Finn ops is an increase. Ask for security ops because security threats have only amplified. And then the entire cloud ups model. I think hybrid cloud operations its's prompted us to rethink a lot off. How do we do? I t operations and and we're investing a lot in terms of automation and then underpinning that by ai led operation. So, um, you talked about the client management platform making sure we've got the best automation and processes which are repeatable around all the way from just doing provisioning to data operations to optimization. Just making all of that robust and repeatable um, is such a value. Add to clients because then they can see SOS can sleep at night knowing that everything is taken care off and, uh, the CIA, the CEOs can be rest assured that hey, they're not going to get that AWS bill that's going to make them hit the roof. So making sure we've got the right checks and balances and approval flow is all a part of our child management platform. And at that point, I know you really passionate AI and the role that it plays in operations and the entire cloud management platform and cloud for day platform So your thoughts in the poem? >>Yes, sir. No, thank you. But so yeah, yeah, I led operations is really part off the bigger question and the pain point that customers are faced with, which is I've reached the cloud. Now, how do I optimized and get benefits from the cloud on the benefits is around. You know, uh, utility for on demand access to resource is, uh, this cost optimization potential and the security, uh, cloud security potential that, if not managed properly, can really blow up in the face. And unfortunately, you know that in the case on the AI ops led Operation Side, that's again a huge foretell area where Unisys Investor is investing a lot off a lot off i p and creating a lot of differentiation. And the objective there is to ask Customers adopt cloud for day as they adopt Unisys Cloud services. They're able to take advantage off cost optimization capabilities, which essentially looks at historical usage on predicts future usage, based on a number off a I artificial intelligence and machine learning technologies that that is able to give you predictions that otherwise very hard to hard to get and, uh, in the cloud environment because of the sheer velocity volume and variety of the data. Doing that in a manual fashion is very, very hard. So automated machine learning driven approach is very productive is very effective on, you know, some of the outcomes that we've achieved is is just amazing. We've been able to save up to 25% off infrastructure costs through the island operations. About 40% off infrastructure incidents have bean reduced due to root cause analysis. Eso onda up to 35% off meantime, to resolution improvements in time. So huge customer benefits driven by e I led operations. The I am a approaches to following the problem. >>Let me see him If I could stick with you for a second big numbers that you just talked about and we talked a few minutes ago about outcomes. It's all about outcomes right now with this rush to cloud as as a new set. And we talked about this on the Cuba all the time. We've seen that the last eight months there is an acceleration of this digital transformation. I'm just curious una come from your perspective as the VP and CTO cloud how are you? What are some of the things that you advise customers to do if they need to rush to the cloud 21 just, you know, move their business quickly and not have the stay on life support. What are some of the things that you advise them to do when they're in this? Maybe a few months ago, when they were in the beginning of this? >>Yeah, that's that's a very interesting question, and lot off our clients are faced with that question as they either they're already in the cloud or the deciding to migrate to the cloud on the whole journey. Customer journeys for either stepping on the cloud or managing and operating the optimizing the cloud deployments is very key. So if you look at the market research that's out there and what we hear from our customers, the key challenges are really, really around. How do I migrate to the cloud without facing a lot of bottlenecks and challenges, and how do I overcome them? So that's the keeping pain point and again cloud for the advisory services and the cloud services that we offer allows customers to take up uh, toe work with us, and we work with the customer to ensure that they're able to do that on and then rapidly migrating to the cloud, managing and operating their operations. The hybrid cloud operations in optimized fashion is a huge challenge. How do they migrate? How do they migrate with security and compliance not being compromised once they're in the cloud, ensuring cloud security is and compliance is is maintained. Ensuring that the cost structure is is optimized so that they're not being mawr wants to move to the cloud compared to on premises and and then taking advantage of the whole cloud. Deployments to ensure you're looking at data are nothing the data to derive meaningful business outcomes. So if the entire end to end customer journey that needs to be looked at optimized. And that's where Unisys comes in with a cloud for the platform where we work with the customers to enhance the journeys. And in this case I want to mention CSU, which is, uh, the California State University, where the approach Unisys to really work with them to deliver uh, cloud services by enhancing the the objective was to enhance the student learning experience to enable adoption off off the technology by the students but also to achieve better performance, better adoption cost savings on we were able to deliver about 30% better performance help realize about 30 33% savings on 40% plus growth in adoption. On this was for about half a million student bodies. The 50,000 plus faculty staff spread across 23 campuses. So deploying, optimizing on and managing the infrastructure is something that Unisys does. Does that. And this is an example of that. I know you want to add anything to that. >>Absolutely Any Permanente's really well and, >>uh, >>it Z also securing, making sure securities with the >>journey >>it Z O Keefe or hybrid cloud. Um, uh, at least I'm sure you're aware of the Unisys tagline is securing tomorrow. So who better s so we really, really take that really, really seriously in terms of making sure we seek clients cloud journeys, and >>you >>probably heard the statistic from her. About 80% off cloud breaches are due to mis configuration, and this could have bean prevented. And and it doesn't. There's an element of the human angle in there. You believe strongly that can automate using our platform. So we've got 2000 plus security policies, which makes sure which again enables our clients to be compliant as well. So no matter what compliant standards, we've got several off our clients, for example, in the financial sector that are hosted on AWS and that we managed and they have to, especially the US They have to comply with Y de f s, the New York Department of Financial Services and making sure that they compliant with all the standards out there, which is next plus plus in this case. So that's part of what we do and enabling those journeys and then just keeping up with the rate of change like on different was talking about the variety and velocity of the data and and the rate of change of the applications out there, especially as businesses react to the pandemic and have to cope with the changing business paradigms out there. They have to be quick. Um, so we've got a drugmaker, one of the most premium drug makers in the US, who is who is against it on AWS, and, uh, they're racing for the cure and they are always looking at How do they get drugs quicker to the market? And that means accelerating applications. And we know that based on research by the Dora study, that if you adopt develops paradigms, you can accelerate 200 times faster than if you didn't. But then you have to underpin backward security as well. So really helping this adopt deaths are cops in all their deployments to AWS so that they can really race for the cure. That's the kind of business outcomes that we really, uh, are really, really proud to drive for our clients. >>Excellent on a pound. Let's wrap this up with you. We've just got about 30 seconds left sticking on the security front. It's such a huge topic right now. It has been for a long time, but even more so during these unprecedented times when you're talking with customers, what makes Unisys unique from a security perspective? >>So first thing is to understand what it takes to solve the hybrid cloud security problem. Like you said earlier, that's the biggest pain point that we hear from customers from our clients on. It's all over the market research all the breaches that have happened, like the zoom breach that happened that compromised about half a million, you know, user log ins. And then there was also the the Marriott breach, where about half a billion users names and credential for legal legal. So it Zaveri easy for customers, potential customers to become like a headline. And our our job really are the companies to make sure that they're not the next capital one or the next Marriott, uh, showing up in the newspaper. So we kind of look at their customer deployments situation on. We put together a comprehensive into an hybrid cloud solution, hybrid cloud security and compliance solution that includes look, securing their cloud infrastructure, their cloud workloads in terms of applications that they might have secured, and also to look at securing their applications, which may or may not be running on the cloud. So we kind of take a very holistic approach, using our homegrown solutions and partner solutions to create a comprehensive, robust hybrid cloud solution that really fits the customer context and and so we we are essentially a trusted adviser for our for our clients to create the solution, which again, at the cloud 40 ashore, which is a cloud security posture management solution. We have a cloud worker protection solution on then stealth, which is a full stack security solution if combined together with the other cloud Forte platform components on. We wrap this up in a matter of security services offering that allows US customers to have complete peace of mind as we take care off assessment remediation monitoring on, then continues Posture, posture, management. I know. Do you want to add anything to that? >>If I'm think in terms of closing, I think like you covered it well, we've got platform competence and services that run the gamut off the off the life cycle from migrations to two transformations. And one thing that I think in terms of outcomes of these, uh, when the service built around it have really helped us. Dr is, um is kind of responding especially to our public sector clients, very passionate about enabling cloud journeys for our public sector clients. And we'll take the example of Georgia Technology s So this is the G t A. Is the technology agency for all services are 14 of the agencies in Georgia and many of these public sector agencies had to quickly adopt cloud to deal with the report workers. Whether it was v D I whether it was chatbots on cloud, um, it was it was, ah, brand new world out there, the new normal. And it was just using the cloud management platform that anyone was refering to. We were able to kind of take them from taking three months. Plus to be able to provision workloads Thio thio less than 30 minutes to provision workloads. And this is this is across hybrid cloud. So and this is >>a big outcome, especially in this time where things were changing so quickly. Well, I wish we had more time, guys because I could tell you have a lot more that you can share. You're just gonna have to come back. And I like that. The tagline securing tomorrow. Adding on to what Anu Pump said So your customers don't become the next headline. I think they would all appreciate that. Thank you both. So much for joining me on the Cube today and sharing what's the latest with Unisys. We appreciate your time. Thank you. Thank >>you for having us >>aren't my pleasure for my guests. I'm Lisa Martin. And you're watching the Cube? Yeah,