>>Live from Stanford university on your host. Lisa Martin. My next guest joins me with many I, our corporate vice president at Microsoft, Rick Minnie. It's great to have you on the program. Thank you for having me. Tell me a little bit about your background. So you run Microsoft advertising, engineering organizations. You also manage a multi-billion dollar marketplace globally. Yes. Big responsibilities. >>A little bit >>About you and your role at Microsoft. >>So basically online advertising, you know, funds a lot of the consumer services like search, you know, feeds. And so I run all of the online advertising pieces. And so my team is a combination of machine learning in theory, software engineers, online services. So you think of you think of what needs to happen for running an online advertising ecosystem? That's billions of dollars. I have all these people on my team when I get to work with these fantastic people. So that's my >>Roles. We have a really diverse team. >>Yes. My background itself is in AI. So my PhD was in language modeling and natural language processing. That's how I got into the space. And then I did, you know, machine learning. Then I did some auctions and then I'd, you know, I basically have touched almost all pieces of the puzzle. So from, I appreciate what's required to run a business the size. And so from that perspective, you know, yeah, it is a lot of diverse people, but at the same time, I feel like I know what they do >>Right then interdisciplinary collaboration must be incredibly important and >>Powerful. It is. I mean, for machine learning engineer or machine learning scientists to be successful, when you're running a production system, they have to really appreciate what constraints are there, you know, required online. So you have to look at how much CPU you use, how much memory you need, how fast can your model inference run with your model. And so they have to work very closely with the soft, soft engineering field. But at the same time, the software engineering guys need to know that their job is not to constrain the machine learning scientists. So, you know, as the models get larger, they have to get more creative. Right. And if that balance is right, then you get a really ambitious product. If that balance is not right, then you end up with a very small micro micro system. And so my job is to really make sure that the team is really ambitious in their thinking, not always liking, pushing the borders of what can be done. >>I like that pushing the borders of what can be done. You know, we, we often, when we talk about roles in, in stammered technology, we've talked about the hard skills, but the soft skills you've mentioned creativity. I always think creativity and curiosity are two soft skills that are really important in data science and AI. Talk to me about what your thoughts are. There >>Definitely creativity, because a lot of the problems that you, you know, when you're in school, the problems you face are very theoretical problems. And when you go into the industry and you realize that you need to solve a problem using the theory you learned, then you have to either start making different kinds of assumptions or realize that some assumptions just can be made because life is messy and online. You know, users are messy. They don't all interact with your system the same way. So you get creative in what can be solved. And then what needs to be controlled and folks who can't figure that piece out, they try to solve everything using machine learning, and they become a perfectionist, but nothing ever gets done then. So you need this balance and, and creativity plays a huge role in that space. And collaboration is you're always working with a diverse group of people. So explaining the problem space to someone who's selling your product, say someone is, you know, you build this automated bidding engine and they have to take this full mouth full and sell it to a customer. You've got to give them the terminology to use, tell, explain to them what are the benefits if somebody uses that. So I, I feel people who can empathize with the fact that this has to be explained, do a lot better when they're working in a product system, you know, bringing machine learning to a production system. >>Right. There's a lot of enablement >>There. Yes, exactly. Yeah. Yeah. >>Were you always interested in, in stem and engineering and AIS from when you were small? >>Somewhat? I mean, I've been, I got to my college degree. I was very certain by that point I wanted to be an engineer and my path to AI was kind of weird because I didn't really want to do computer science. So I ended up doing electrical engineering, but in my last year I did a project on speech recognition and I got introduced to computer programming. That was my first introduction to computer programming at the end of it, I knew I was going to work in the space. And so I came to the U S with less than three or four months of a computer engineering background. You know, I barely knew how to code. I had done some statistics, but not nearly enough to be in machine learning. And, but I landed in a good place. And I came to be in Boston university and I landed in a great lab. And I learned everything on my feet in that lab. I do feel like from that point onwards, I have always been interested and I'm never satisfied with just being interested in what's hot right now. I really want to know what can be solved later in the future. So that combination, I think, you know, really keeps me always learning, growing, and I'm never happy with just what's being done. >>Right? Yeah. We here, we've been hearing a lot about that today at weds. Just the tremendous opportunities that are here, the opportunities for data science, for good drones, for good data science and AI in healthcare and in public transportation. For example, you've been involved in with winds from the beginning. So you've gotten to see this small movement grow into this global really kind of is a >>Phenomenon. It is, >>It's a movement. Yes. You talk to me about your involvement with winds from the beginning and some of the things that you're helping them do. And now, >>So I, I first met Karen and marble initially when I was trying to get students from ICME to apply for roles in Microsoft. I really thought they had the right mix of applied and research mindset and the skill sets that were coming out of ICME rock solid in their math and theoretical foundations. So that's how I got to know them. And then they were just thinking about bids at that point in time. And so I said, you know, how can I help? And so I think I've been a keynote speaker, Pam list run a workshop. And then I got involved with the woods high school volunteer effort. And I'd say, that's the most rewarding piece of my visit involvement. And so I've been with them every year. I never Ms. Woods. I'm always here. And I think it is, you know, Grace Hopper was the technology conference for women and, and it's, it's, it's an awesome conference. I mean, it's amazing to sit next to so many women engineers, but data science was a part of it, but not a critical part of it. And so having this conference, that's completely focused on data science and making it accessible. The talks are accessible, making it more personable to, to all the invitees here. I think it creates a great community. So for me, I think it's, I hope they can run this and grow this for >>Yeah. Over 200 online events this year in 60 countries, they're aiming to reach a hundred thousand people annually. It's, it's grown dramatically in a short time period. Yes, >>Absolutely. Yeah. It hasn't been that long. It hasn't been that long and every year they add something new to the table. So for this year, I mean last year I thought the high schoolers, they started bringing in the high schoolers and this year again, I thought the high school. >>Yeah, >>Exactly. And I think the mix of getting data science from across a diversity, because a lot of the conferences are very focused. Like, you know, they, they will be the focused on healthcare and data science or pure AI or pure machine learning. This conference has a mix of a lot of different elements. And so attendees get to see how it's something is being used in healthcare and how something is being used in recommendations. And I think that diversity is really valuable. >>Oh, it's hugely valuable that the thought diversity is this is probably the conference where I discovered what thought diversity was if only a few years ago and the power and the opportunities that it can unlock for people everywhere for businesses in any industry. Yes. >>I want to kind of play off one of the things you said before, you know, data science for good, the, the incredible part of data sciences, you can do good wherever you are with data science. So take online advertising, you know, we build products for all advertisers, but we quickly figured out that are really large advertisers. They have their own data science teams and they are optimizing and, you know, creating new ads and making sure the best ads are serving at all times. They have figured out, you know, they have machine learning pipelines, so they are really doing their best already. But then there's this whole tale of small advertisers who just don't have the wherewithal or the knowledge to do any of that. Now, can you make data, use data science and your machine learning models and make it accessible for that long table? Pretty much any product you build, you will have the symptom of heavy users and then the tail users. And can you create an experience that is as valuable for those tailored users as it is for the heavy users. So data science for good exists, whatever problem you're solving, basically, >>That's nice to hear. And so you're going to be participating in some of the closing remarks today. What are some of the pearls of wisdom that you're going to enlighten the audience with today? >>Well, I mean the first thing I, to tell this audiences that they need to participate, you know, in whatever they shaped form, they need to participate in this movement of getting more women into stem and into data science. And my reasoning is, you know, I joined the lab and my professor was a woman and she was very strong scientists, very strong engineer. And that one story was enough to convince me that I belong. And if you can imagine that we create thousands of these stories, this is how you create that feeling of inclusion, where people feel like they belong. Yeah. Look, just look at those other 50 people here, those other a hundred stories here. This is how you create that movement. And so the first thing I want the audience to do is participate, come back, volunteer, you know, submit papers for keynote speeches, you know, be a part of this movement. >>So that's one. And then the second is I want them to be ambitious. So I don't want them to just read a book and apply the theory. I really want them to think about what problem are they solving and could they have solved it in the, in the scale manner that it can be solved. So I'll give a few examples and problems and I'll throw them out there as well. So for instance, experimentation, one of the big breakthroughs that happened in a lot of these large companies in data science is experimentation. You can AB experiment pretty much anything. You know, we can, Google has this famous paper where they talk about how they experimented with thousands of different blues just to get the right blue. And so experimentation has been evolving and data scientists are figuring out that if they can figure out interactions between experiments, you can actually run multiple experiments on the same user. >>So at any given time, you may be subject to four or five different experiments. Now, can we now scale that to infinity so that you can actually run as many experiments as you want questions like these, you shouldn't stop with just saying, oh, I know how AB experimentation works. The question you should be asking is how many such experiments can I run? How do I scale the system? As one of the keynote speakers initially talked about the unasked questions. And I think that's what I want to leave this audience with that don't stop at, you know, answering the questions that you're asked or solving the problems. You know, of you think about the problems you haven't solved your blind spots, you know, those blind spots and that I think I want ambitious data scientists. And so that's the message I want to give this audience. >>I can feel your energy when you say that. And you're involved with, with, with Stanford program for middle school and high school girls. If we look at the data and we see, there's still only about a quarter of stem positions are filled by females, what do you see? Do you see an inspiring group of young women in those middle school and high school girls that, that you see we're, we're on trend to start increasing that percentage. >>So I had a high schooler who just went, you know, she, she, she just, she's at UCLA now shout out to her and she, but she just went through high school. And what I realized is it's the same problem of not having enough stories around you, not having enough people around you that are all echoing the sentiment for, Hey, I love math. A lot of girls just don't talk about us. Yeah. And so I think the reason I want to start in middle school and high school is I think the momentum needs to start there. Yes. Because they get to college. And actually you heard my story. I didn't know any programming until I came here and I had already finished my four years of college and I still figured it out. Right. But a lot of women lose confidence to change fields after four years of college. >>Yes. And so if you don't catch them in early and you're catching them late, then you need to give them this boost of confidence or give them that ramp up time to learn, to figure out, like, I have a few people who are joining me from pure math nowadays. And these kids, these kids come in and within six months they're off and running. So, you know, in the interview phase, people might say, oh, they don't have any coding skills. Six months later, if you interview them, they pick up coding skills. Yeah. And so if you can get them started early on, I think, you know, they don't have this crisis of confidence of moving, changing fields. That's why I feel, and I don't think we are there yet, to be honest, I don't think yet. I think >>You still think there are plenty of girls being told. Now you can't do computer science. No, you can't do physics. No, you can't do math. >>Actually. They are denying it to themselves in many cases because they say, Hey, I go to physics class and there are two boys, two girls out of 50 boys. And I don't think girls are in, you know, you get the stereotype that maybe girls are not interested in physics. And it's not about, Hey, as a girl, I'm doing really well in physics. Maybe I should take this as my career. So I do feel we need to create more resounding stories in the area. And then I think we'll drum up that momentum. That's >>A great point. More stories, more and names to success here so that she can be what she can see exactly what many it's been great having you on the program. Thank you for joining me and sharing your background and some of the pearls of wisdom that you're gonna be dropping on the audience shortly today. We appreciate your insights. Thank you. My pleasure. Who Rick, Minnie, I are. I'm Lisa Martin. You're watching the cubes coverage weds 2022. We'll be right back after a short break.

>> Livefrom London, England, it's theCUBE, covering .Next Conference Europe 2018. Brought to you by Nutanix. >> Welcome back to London, England. This is theCUBE's exclusive coverage of Nutanix .Next 2018 Europe. My name's Stu Miniman. My cohost for these two days of coverage has been Joep Piscaer. And happy to welcome to the program, two first (mumbles). We're gonna talk about culture and people. To my right is Rukmini Sivaraman, who is the vice president of business operations and chief of staff to the CEO. And sitting next to her is Prabha Krishna, who is the senior vice president of people and places, both of them with Nutanix. Ladies, thank you so much for joining us. >> Thank you. >> Thank you for having us. >> All right so, we've been covering Nutanix for a long time. I've been to every one of the shows. I start out, I guess... Dheeraj talked for a long time about the three Hs. It was humble, hungry, and honest, if I got those right. And more recently, it was with heart. Actually sitting not too far behind us, there's a big booth for heart. So, the culture of the company is something that is tied with the founders. We've watched that growth. I've watched the company go from about 35 people to over 3500 people. So, having those core principles is something that we look at in companies. Why don't we start? If you could both just give quick introduction, what brought you to Nutanix, and what your role is there. >> Sure, I've been at Nutanix a little over 18 months and I started out as an engineer, then went to finance and investment banking of all things, was at Goldman for almost a decade. And Nutanix is a client of Goldman's back form the IPO, and I had heard great things about the company, of course, but wasn't intending to leave Goldman Sachs. But when I got introduced to Dheeraj, there was so much that was compelling about the company, the disruption, the category-defining, category-creating kind of position that the company had. And more importantly, I think, where we were going, which was just phenomenal. it was ambitious, it was bold. And I think for me, it's always been about the people. We spend a lot of time at work and it's really important to feel that connection to the people. And that was really important 'cause I had to pick up and move from New York City to the Bay Area to make this move. And we can talk more about this, but to me the people were, like I said, ambitious, but they were also grounded. And I see it and after being at Nutanix now, it's phenomenal how truly humble the people are and that's always struck me as a great combination. You want ambition and challenging problems to solve, but you also want humility and people that you can relate to. So that's really what got me to Nutanix. >> Please. >> Yeah so, I've actually been following Nutanix for quite a while. It's a company that addresses a space that's very underserved and has created a suite of products that's nothing short of amazing for our customers, entirely focused on our customer base. But for me, the most interesting thing was, it's a company that is as right-brained as it is left-brained. I've actually spent 19 years of my career in engineering and made a career switch into the people side. And it's one of the few companies where that fit is almost perfect. And once I met our founder and our CEO, Dheeraj, this became even more obvious. So. I'm actually very happy to be here. I've been here for about four months now, and it's already very clearly the beginning of a very, very exciting journey. >> Yeah, interesting, both of you kind of making those shifts. Talk a little bit about that, talk about... People from outside of Silicon Valley, always, it's like, "Oh, there's the one where they have the playground "and free meals and free drinks." And it's like, "Yeah, that's because you do the analysis "and if they'll work 18 hours a day, "if we can keep them there, "maybe even put a cot in the office, that's good." I haven't seen cots in the office when I go to Nutanix, but hey are really nice offices. And even on the east coast, we're tartin' to change and see some of those things there. Maybe give us a little bit of insight as to that culture. And Nutanix is much more than just Silicon Valley based now. >> That's right. So we are truly a global organization. And we decided very early on that we wanted to be a global organization, but we're also thinking local. All right, so we do have multiple offices within the US, in Durham and Seattle and other places, but we're also truly global. Our Bangalore office, in India we have a big presence. And so for us what that means is there's people from different perspectives and background. But ultimately, it's our sort of, like you said, the four values, but also our culture principles that we've qualified fairly recently that bind us. And that really help us move forward in the same direction and pointing that same direction, and growing the same way. So that has been a phenomenal to see and it's one that I think we've very deliberately qualified more recently. It's sort of the how, how do we behave that embodies those four values that you talked about. >> So Prabha, so you're a new hire, right? >> Yes. >> You haven't been with Nutanix as much. So while we're talking on the subject, what's your personal experience coming into Nutanix? Is it true what you're talking about? How does it work in real life, in practice? >> No, absolutely. All companies state a culture. All companies, I think, in this day and age at least and definitely in Silicon Valley, are very clear about having a specific culture. But the key, as far as I'm concerned, and the strength of a company is how they live and breathe their culture every single day, in every decision, and every action, right. In every difficult balance that they need to meet, that's where the culture really shows up. And at Nutanix, it is... How shall I put it? It's really the core of every single thing we do. It's the core of how we interact. It's the core of how we grow. It's the core of how we recruit, how we define our organizations. And frankly, I have to say, I have been in a lot of organizations and a lot of organizations over time, actually, and particularly as they reach our size... We're a bit at sort of an inflection point, if you will, in terms of size. Our growth has definitely been very, very quick and continues to accelerate. Having that culture being something that we really live is the most important thing. And it is what will allow us to continue to innovate and continue to succeed all over the globe as Rukmini just explained. For me, it's quite extraordinary to see it in action. >> Yeah, that's really interesting because, one, our industry has some challenges hiring. It's finding the right skillset there. If you match that with a culture, what challenge are there? What are you looking for? What is the fit from the outside to match what you're looking for? >> Yeah, I'm happy to address a little bit. So recruiting for us is everything. We want to bring in the best. We wanna bring in the brightest and we wanna bring in folks who really value our culture and our values, who really understand them. And again, are willing to live them every single day. So we do look for great talent all over the planet because great talent exists all over the planet. This is absolutely fundamental to our growth. We are an infrastructure company and we offer, actually, very interesting work for anyone who is interested in the engineering side, who is interested in the sales side, who's interested in market. And for me, the most interesting part in the roles we have, and frankly the most unusual piece if you will, is we offer opportunities to build things from scratch. So, the creative side, the creative mind is really what we encourage. And it shows up in every single aspect of the way we're structured. So, the diversity of thought, the diversity of background, the diversity of... Whether it's gender or location, philosophies, and all of that, is really what we want to bring in and what will allow us to continue to create these products that are quite unique. >> If I may add to that, we talk internally a lot about the founder's mentality. It's a concept, a framework that was developed by Bain & Company and the gist of it is as follows: When you think about great disruptive startups, they're on this rocket ship, accelerating growth. And then they get to a certain size, so they become a little bigger. And they get enjoy the benefits of scale, economies of scale, and that's a good thing. But the best companies take that and then they enjoy those benefits, but they then also don't lose what got them there in the first place, which is the innovation, the ability to disrupt and look around corners, and all of that. So we want the best of both worlds. And in this framework, it's called a scaled insurgent. So you're scaled, but you're still an insurgency. And that is important to us. Folks that can sort of balance the two, really make sure that we are benefiting from one, but also not losing sight of the other. And it's a paradox in many ways and we believe in embracing those paradoxes. And folks who can sort of balance those two would be really a great fit. >> And so, if you're growing that fast, I can imagine that keeping the balance between culture and engineering, and you're growing, that's difficult. How does Nutanix handle that paradox? >> I think it goes back to what Prabha was saying. And for us, culture and the way we behave is like oxygen. So it almost fuels the fire as opposed to the other way around or having to do two things at once. And that's how we've thought about it. And the principles, when we thought about them and conceived them, it was the same idea, which is how can this just be the way we conduct ourselves we treat our customers, we treat each other, we treat our partners? How can it just become the way we do business? And so far, that's worked well for us. >> So one of my favorite culture principles, actually, is comfortable being uncomfortable. And there's a real reason that because given our scale, given the way we wanna grow, and given the fact that we want to preserve that innovative seed at every step, for us, every single day is about balancing opposing forces. Do we invest in the short term? Do we invest in the long term? Do we manage locally? Do we manage more globally? Do we centralize things, do we not? Do we distribute, right? Every single day is about balancing those kinds of things and it's that balance that encourages the creativity in every single one of us. So, the very fact that we've sort of embodied that in a culture principle, really is a very strong indication of what we look for and what we wanna be. >> Right, with the time that we have left, I wondering if you could talk about both at the show and beyond the show, what things Nutanix is doing. Think tech for good, think about the charitable things. Some of speakers I've seen at these shows... Mick Ebeling is one that stood out from a previous show. On talking about tech for good, Dr. Jane Goodall, who I know spoke at a women's lunch event and in the keynote here today, is just so inspiring. As someone that loves science and animals, it was very powerful. You've got the .heart initiatives here. Maybe help for those that don't know here and what else you're doing around the globe and around the year. >> Did you wanna go first? >> Yeah, so giving back is very important for us. It's very fundamental. Gratitude, understanding where we all came from, where we are, and where we wanna go, and not losing ourselves, that's really the key of, I think, any type of success, frankly. So we have an organization around that. It's a very active organization, we all participate. And the company is very much involved in as many different types of charities as possible. It also feeds into the kinds of sourcing that we do when every bring people in. We look for folks who care. We care very much about our people. The amount of attention and the amount of just knowledge and thought that goes into structuring our organization is very much reflective of that sense of giving back and gratitude as well. Our employees are everything and the folks around us who are in need are also everything. It sort of goes together, if you will. So basically to us, it's a hugely, hugely important effort and we'll continue investing in those kinds of things as we go forward. >> I think one thing I would add is as you saw at the end of the closing keynote, I think we announced or shared that thanks to everyone here, really all the folks here, our customers, partners, all of our participants, we were able to collect over 10,000 pounds for .heart and that is phenomenal. We're forever grateful to our community to be able to do things like that. We also partner with organizations like Girls in Tech, which is doing great work on making sure that we are bringing all kinds of talent, as Prabha said, to the table. We believe there's great people everywhere. And so, how do we harness the power of all of those initiatives? >> All right, those are some great examples. And Prabha, to your point, I think that that individual touch to your employees, that also translates to the customer side. Something I hear from Nutanix customers is despite the fact how large you've grown and how many customers you have, they feel that they get that individual attention. So thank you so much for sharing all of the updates. Wish you both the best of luck in your continued journey. And we wanna thank our community, of course, for tuning in to our coverage. It is truly our pleasure to help document what's happening out in the industry, hopefully be a surrogate for you, to ask the questions that you wanna hear and help you along your journeys. My name's Stu Miniman. My first European cohost who also did a segment in Dutch, Joep Piscaer, Can you goodbye in Dutch for us, Joep? >> (Dutch). >> All right, I'll have to learn that one some time because, unfortunately, my english and speaking numbers in a couple of different languages is where I'm a little bit limited. But once again, thanks for watching. Turn to thecube.net to catch all of the replays from this show as well as all the shows that we will be at. Including, next year, Nutanix will be at Anaheim and the spring and Copenhagen in the fall. And our team look forward to bringing you coverage from both of those. So once again, thank you for watching theCUBE. >> Thank you. (slick electronic music) >> Hi, I'm John Wallis. I've been with theCUBE for a couple years serving as a host here on our broadcast, our flagship broadcast on SiliconANGLE TV. I like to think about the hows and the whys, and the whats of technology. How's it work? Why does it matter? What is it doing for end users? 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