>>Yeah. Hello and welcome to the Cubes Presentation of Women in Tech Global Event Celebrating International Women's Day I'm John for a host of the Cube. We had a great guest in Cuba. Alumni Veranda re vice president. Commercial sales for Europe, Middle East and Africa. EMEA at AWS Amazon Web service to great to see you. Thank you for coming in all the way across the pond and the US to Palo Alto from London. >>Thank you, John. Great to see you again. I'm super excited to be part of this particularly special event. >>Well, this is a celebration of International Women's Day. It's gonna continue throughout the rest of the year, and every day is International Women's Day. But you're actually international. Your women in Tech had a great career. We talk that reinvent. Let's step back and walk through your career. Highlights to date. What have been some of the key things in your career history that you can share? >>Uh, thanks, John. It's always nice to reflect on this, you know? Look, I the way I would classify my career. First of all, it's very it's been very international. I was born and raised in India I went to study in the US It was always a dream to go do that. I did my masters in Boston University. I then worked in the U S. For a good 17 years across A number of tech, uh, tech companies in particular, started my career at McKinsey in the very early days and then moved on to work for E M. C. You'll you'll probably remember them, John. Very well, of course, There now, Del um And then I moved over to Europe. So I've spent the last 18 years here in Europe. Um, and that's been across a couple of different things. I I always classify. Half my career has been strategy, transformation, consulting, and the other half of my career is doing the real job of actually running operations. And I've been, you know, 12 15 years in the tech and telecom sector had the excitement of running Schneider Electric's business in the UK Denniston and Private Equity went back to McKinsey Boomerang, and then a W s called me, and how could I possibly refuse that? So it's been really exciting, I think the one big take away when I reflect on my career is. I've always had this Northstar about leading a business someday, and then I've sort of through my career master set of skills to be able to do that. And I think that's probably what you see. Very eclectic, very mobile, very international and cross industry. Uh, in particular. >>I love the strategy and operations comment because they're both fun, but they're different ones. Very execution, tactical operating. The business strategy is kind of figuring out the future of the 20 mile stare. You know, playing that chess match, so to speak, all great skills and impressive. But I have to ask you, what got you in the tech sector? Why technology? >>Well, so you know, in some ways I kind of fell into it, John, right? Because when I was growing up, my father was always in the tech space, so he had a business and fax machines and he was a reseller of cannon. If you remember Cannon, um, and microfilm equipment and I grew up around him, and he was a real entrepreneur. I mean, always super visionary about new things that were coming out. And so as I followed him around, I said, I kind of wanna be him. And it's a little bit about that sort of role model right early in your career. And then when I moved to the U. S. To study again, it wasn't like I thought I was gonna go to attack. I mean, I wasn't an engineer, you know. I grew up in India with economics degree. That's when women went into We didn't necessarily go into science. But when I joined McKinsey in the early days, I ended up working with, you know, the big companies of the days. You know, the IBMs, the E M. C. Is the Microsoft the oracles, etcetera. So I just then began to love, love the innovation, always being on the sort of bleeding edge. Um, and I guess it was a little bit just fascinating for me not being an engineer to learn how technology had all these applications in terms of how businesses advanced. So I guess, Yeah, that's kind of why I still think it around with it. It's interesting >>how you mentioned how you at that time you pipeline into economics, which is math. Of course. Uh, math is needed for economics, but also the big picture and This is one of the conversation we're having, Uh, this year, the breaking down the barriers for women in tech. Now there's more jobs you don't You don't need to have one pathway into into science or, you know, we're talking stem versus steam arts are super important, being creative. So the barriers to get in are being removed. I mean, if you think about the surface area for technology. So I got to ask you, what barriers do you think Stop girls and young women the most in considering a career in Tech? >>I've got to start with role models, John. Right? Because I think a number of us grew up, by the way, being the only not having the allies in the business, right? All of us, all the all the managers and hiring people are males rather than females. And the fact of the matter is, we didn't have this sort of he for she movement. And I think that's the biggest barrier is not having enough role models and positive role models in the business. I can tell you that research shows that actually, when you have female role models, you tend to hire more and actually what employees say is they feel more supportive when they have actually female managers. So I think there are lots of goodness, but we just need to accelerate how many role models we have. I think the other things I will say to you as well is, if you look at just the curriculum and the ability to get women into stem, right, I mean, we need to have colleges, universities, schools also encouraging women into stem. And you've probably heard about our programme. You know, it's something we do to encourage girls into stem. I think it's really important that teachers and others are actually encouraging girls to do math, for example, right? It's not just about science. Math is great. Logic is great, by the way. Philosophy is great. I just love what you said. I think increasingly, the EQ and EQ parts have to come together, and I think that's what women excel at. Um, so I think that's another very, very big carrier, and then the only other thing I will say is we're gonna watch the language we use, like when I think about job descriptions, they tend to be very male oriented languages we look at CVS now, if you haven't been a female in tech for a long time, your CV isn't going to show a lot of tech, is it? So for recruiters out there, look for competencies. Look for capabilities. You mentioned strategy and arts earlier. We have this leadership principles, As you know, John, really well, think big and dive deep, right? That strategy and operations. And so I think we we need to recruit for that. And we need to recruit for culture. And we need to recruit for people with ambition, an aspiration and not always Just look at 20 years of experience because you're not gonna find it. So I think those are some of the big barriers. Um, that I that I at least think, is stopping women from getting into town. But the biggest one is not enough women at the top hiring women. >>I think people want to see themselves, or at least an aspirational version of what they could be. And I think that's only gonna get better. Lots changed. A lot has happened over the years, but now, with technology in everyone's life, covid pulled forward a lot of realities. You know, the current situation in Europe where you're you are now has pulled forward a lot of realities around community, cyber, digital, our lives. And I think this opens up new positions, clearly cybersecurity. And I'm sure the job boards in every company is hiring people that didn't exist years ago, but also this new problems to solve. So the younger generation coming up, um, is gonna work on these problems, and they need to have role models. So what's your reaction to that? You know, new problems are opportunities their new so usually solved by probably the next generation. Uh, they need mentors. All this kind of works together. What's your reaction? >>Yeah, and, you know, let me pick up on something we're doing that I think is really important. I think you have to address age on the pipeline problem, you know, because they're just is a pipeline problem, you know, at the end of the day, And by that, what I mean is, we need to have more and more people with the and I'm not gonna use the word engineering or science. I'm going to use the word digital skills, right? And I think what we've we've committed to doing, John, you know, I'm very proud of this is we said we're gonna train 29 people 29 million people around this world on digital skills for free by 2025. Right, That's gonna help us get that pipeline going. The other thing we do is something called Restart where we actually do 12 weeks of training for the under, employed and under served right and underrepresented communities. And that means in 12 weeks we can get someone. And you know, this case I talk to you about this before I love it. Fast food operator to cloud, right? I mean, that's that's what I call changing the game on pipeline. But But here's the other stand. Even if the pipeline is good and we often see that the pipeline can be as much as 50% at the very early career women, by the time you get into the C suite, you're not a 50 anymore. You're less than 20%. So the other big thing John there, and this comes back to the types of roles you have an opportunities you create. We've got to pull women through the pipeline. We've really got to encourage that there are sponsors and not just mentors. I think women are sorry to say this over mentored and under sponsored. We need more people say I'm gonna open the door for you and create the opportunity I had that advantage. I hit people through my career. By the way, they were all men, right? Who actually stood out there and bang on the door and said, Okay, Tunisia is gonna go do this. And my first break I remember was having done strategy all my life when the CEO come into the room and you said, You're gonna better locks and you're gonna go run the P and L in Benelux and I almost fainted because I thought, Oh, my God, I've never run a PNR before But it's that type of risk taking that's going to be critical. And I think we've got to train our leaders and our managers to have those conversations be the sponsors, get that unconscious bias training. We all have it. Every single one of us has it. I think those are the combinations of things that are going to actually help open the door and make a see that Actually, it's not just about coding. It's actually about sales. It's about marketing. It's about product management. It's about strategy. It's about sales operations. It's about really, really thinking differently about your customers, right? And that's the thing that I think is attractive about technology. And you know what? Maybe that leads you to eventually become a coder. Or maybe not. Maybe you enter from coding, but those are all the range is available to you in technology, which is not good at advertising, >>that there's more applications than ever before. But I love your comment about over mentoring and under sponsored. Can you quickly just define the difference between those two support elements sponsoring versus, uh, mentoring sponsoring >>So mentors And by the way they can range from my son is my mentor, you know, is a great reverse mentor. By the way, I really encourage you to have the reverse mentoring going. So many mentors are people from all walks of your life, right? And you should have, you know, half a dozen of those. At least I think right who are going to be able to help you deal with situations, help coach you give you feedback respond to concerns You're having find ways for you to navigate all the stuff you need, by the way. Right? And feedback the gift we need that sponsors. It's not about the feedback. Necessarily. It's people who literally will create opportunities for you. Mentors don't necessarily do that. Sponsors will say you You know what? We got the phone. Call John and say, John, I've got the perfect person for you. You need to go speak to her. That's the big difference. John and a couple of sponsors. It's not about many, >>and that's where the change happens. I love that comment. Good call. I'm glad I could double down on that. Now that you have the environment, pipeline and working, you have the people themselves in the environment getting better sponsors and mentors, hopefully working more and more together. But once they're in the environment, they still got to be part of it. So as girls and young women and to the working sector for tech, what advice would you give them? Because now they're in the game there in the arena. So what advice would you give them? Because the environments they are now >>yeah, yeah. I mean, Gosh, John, it's you know, you've lived your career in this space. It's an exciting place to be right. Um, it's a growth opportunity. And I think that's a really important point because the more you enter sectors where there's a lot of growth and I would say hyper right growth, that's just gonna open the doors to so many more things. If you're in a place where it's all about cost cutting and restructuring, do you know what? It's super hard to really compete and have fun, right? And as we say, make history. So it's an exciting place. Today's world transformation equals digital transformation, right? So tech is the place to be, because tech is about transformation, Right? So coming in here, the one advice I would give you is Just do it because believe me, there's so much you can do, like take the risk, find someone is going to give you that entree point and get in the door right? And look, you know what's the worst that could happen? The worst that could happen is you don't like it. Fine. There's lots of other things than to go to. So my advice is, you know, don't take the mm. The really bad tips I've received in my career, right? Don't let people tell you you can't do it. You're not good enough. You don't have the experience, right? It's a male's world. You're a woman. It's all about you and not about EQ. Because that's just rubbish, Frankly, right. The top tip I was ever given was actually to take the risk and go for it. And that was my father. And then all these other sponsors I've had around the way. So that's that's the one thing I would say. The other thing I will say to you is the reason I advise it and the reason you should go for it. It's purposeful. Technology is changing our lives, you know, And we will all live to be no longer. 87 I think 100 right? And so you have the opportunity to change the course of the world by coming to technology. The vaccine deployment John was a great example, right? Without cloud, we couldn't have launch these vaccines as fast as we did. Right? Um, so I think there's a tonne of purpose. You've got to get in and then you've got to find. As I said, those sponsors, you've got to find those mentors. You've got to not worry about vertical opportunities and getting promoted. You gotta worry about horizontal opportunities, right? And doing the things that I needed to get the skills that you require, right? I also say one thing. Um, don't Don't let people tell you not to speak up, not to express your opinion. Do all of the above be authentic, Be authentic style. You will see more role models. Many, many more role models are gonna come out in tech that are going to be female role models. And actually, the men are really stepping up to the role models. And so we will be better together. And here's the big thing. We need you. We can do this without women. There's no possible way that we will be able to deliver on the absolute incredible transformation we have ahead of us without you. >>Inclusion, Diversity equity. These are force multipliers for companies. If applied properly, it's competitive advantage. And so breaking the bias. The theme this year is super super important. It sounds like common sense, but the reality is you break the bias It's not just women as men, as all of us. What can we do? Better to bring that force multiplier capabilities and competitive advantage of inclusion, diversity, equity to business. >>So the first thing I would say and my doctor used to always tell me this if it hurts, don't do it right. I would say to you just do it. Get diverse teams in place because if you have diverse teams, you have diversity of thought. You don't have to worry as much about bias because, you know, you've got the people around the table who actually represent the world. We also do something really cool. We have something called biassed busters. And so in meetings we have bias borders. People are going to, like, raise their hand and say, I'm not sure that that was really meant the way it was supposed to be, So I think that's just a nice little mechanism that we have here, Um, in a W s that helps. The other thing I would say to you is being your authentic self. You can't be a man and mentioned be women, and you're not gonna replicate somebody else because you're never gonna succeed if you do that, you know? So I would say be your authentic self all of the time, You know, we know. We know that women are sometimes labelled as aggressive when they're really not. Don't worry about it. It's not personal. I think the main thing you have to do is and I advise women all the time Is calibrate the feedback you're getting okay? Don't catastrophizing it right. Calibrate it. Taken in, you don't have to react to every feedback in the world, right? And make sure that you're also conscious of your own biases, right? So I think those are my Those are my two cents John for what they were for breaking device. I love the thing. >>Be yourself, You know, Don't take it too personal. Have some fun. That's life. That's a life lesson. Um, Final question, while I got you here, you're a great inspiration, and you're a great role model. You're running a very big business for Amazon web services. Europe, Middle East and Africa is a huge territory. It's its own thing. It's It's like you're bigger than some companies out there. Your role in your organisation. What's the hot area out there you were talking before camera. That's emerging areas that you're focused on. People are watching this young women, young ladies around the world. We're gonna look at this and say, What wave should I jump on? What's the hot things happening in in Europe? Middle Eastern Africa? >>I think the three things I would mention and I'm sure there's I'm sure, John, as we've spoken to my peers across the other gos, right, there are some similarities. The very, very hot thing right now is sustainability. Um, and you know, people are really building sustainability into their strategy. It's no longer sort of just an E S G goal in itself. It's actually very much part of changing the way they do business. So I think that's the hard part. And that's why again, I think it's a phenomenal place to be. I think the other big thing that we're absolutely talking about a lot is, and you know, this is getting even more complicated right now is just around security and cyber security and where that's going and how can we be really thinking about how we address some of these concerns that are coming out and I think there's There's something. There's a lot to be said about the way we build our infrastructure in terms of that context. So I think that's the second one. I think the third one is. People are really looking at technology to change the way businesses operate. So how does HR operate? How do you improve your employee value proposition? How do you do marketing in the next generation? How do you do finance in the next generation? So across the business is no longer the place of I t. It really is about changing the way we are as businesses and all of us becoming tech companies at the core. So the big thing there, John, is data data at the heart of everything we do data not because it's there in front of you, but data because you can actually make decisions on the back of it. So those are the things, Um, I seem to come across a lot more than anything else. >>It's always great to talk to you, your senior leader at AWS, um, inspirational to many. And thank you for taking the time to speak with us here on this great event. Women in text. Global Celebration of International Women's Day. Thank you so much for your time. >>Thank you, John. Always great to talk to you. >>We will definitely be keeping in touch More storeys to be had and we're gonna bring it to you. This is the cubes continuing presentation of women in tech. A global event celebrating International Women's Day. I'm John for your host. Thanks for watching. Yeah.

>> live from Boston, Massachusetts. It's the you covering your red hat. Some twenty nineteen rots. You buy bread hat. >> Well, good afternoon. Welcome back here on the Cube as we continue our coverage of the Red Hat Summit and you know, every once in a while you come across one of these fascinating topics. It's what's doing I get so excited about when we do the Cube interviews is that you never know where >> you're >> going to go, the direction you're going to take. And I think this next interview has been a fit into one of those wow interviews for you at home. Along was to minimum. I am John Walls, and we're joined by Dr Ellen Grant, who was the director of the fetal neo NATO Neuroimaging and Developmental Science Center of Boston Children's Hospital. So far, so good, right? And the professor, Radiology and pediatrics at the Harvard Medical School's Dr Grant. Thank you for joining us here on the Cube and Dr Rudolph Pienaar, who is the technical director at the F n N D. S. C. And an instructor of radiology at the Harvard Medical School. So Dr Rudolph Pienaar, thank you for joining us as well. Thank you very much. All right. Good. So we're talking about what? The Chris Project, which was technically based. Project Boston Children's Hospital. I'm going to let you take from their doctor Grant. If you would just talk about the genesis of this program, the project, what its goal, wass And now how it's been carried out. And then we'LL bring in Dr PNR after that. So if you would place >> sure, it's so The goal of the Chris Project was to bring innovated imaging, announces to the bedside to the front end where clinicians are not like high are working all the time but aren't sophisticated enough or don't have enough memory to remember how to do, you know, line code in Lenox. So this is where initially started when I was reading clinical studies and I wanted to run a complex analysis, but there was no way to do it easily. I'd have tio call up someone to log into a different computer, bring the images over again lots of conflict steps to run that analysis, and even to do any of these analysis, you have to download the program set up your environment again. Many many steps, said someone. As a physician, I would rather deal with the interpretation and understanding the meaning of those images. Then all that infrastructure steps to bring it together. So that was the genesis of Chris's trying to have a simple Windows point and click way for a physician such as myself, to be able to rapidly do something interesting and then able to show it to a clinician in a conference or in the at the bedside >> and who's working on it, then, I mean, who was supplying what kind of manpower, If you will root off of the project >> kind of in the beginning, I would say maybe one way to characterize it is that we wanted to bring this research software, which lives mostly online, ex onto a Windows world, right? So the people developing that software researchers or computational researchers who do a lot of amazing stuff with image processing. But those tools just never make it really from the research lab outside of that. And one of the reasons is because someone like Ellen might not ever want to fire paternal and typing these commands. So people working on it are all this huge population of researchers making these tools on what we try to do. What I try to help with, How do we get those tools really easily usable in excess of one and, you know, to make a difference? Obviously. So that was a genesis. I was kind of need that we had in the beginning, so it started out, really, as a bunch of scrips, shell scripts, you slight a type of couple stuff, but not so many things on gradually, with time, we try to move to the Web, and then it began to grow and then kind of from the Web stretching to the cloud. And that's kind of the trajectory in the natural. As each step moved along, more and more people kind of came in to play. >> Dr Grant, I think back, you know, I work for a very large storage company and member object storage was going to transform because we have the giant files. We need to be able to store them and manage them and hold them up. But let's talk about the patient side of things. What does this really mean? You know, we had a talk about order of magnitude that cloud can make things faster and easier. But what? What does this mean to patient care? Quality service? >> Well, I think what it means or the goal for patient care is really getting to specialized medicine or individualized medicine on to be able to not just rely on my memory as to what a normal or abnormal images or the patients I may have seen just in my institution. But can we pull together all the knowledge across multiple institutions throughout the country and use more rigorous data announces to support my memory? So I want to have these big bridal in front lobes that air there, the cloud that helped me remember things into tidies connections and not have to remind just rely on my visual gestalt memory, which is obviously going to have some flaws in it. So and if I've never seen a specific disorder, say, for example, at my institution, if they've seen it at other institutions who run these comparisons all of sudden, I made be aware of a new treatment that otherwise I may not have known about >> All right, so one of my understanding is this is tied into the mass open cloud which I've had the pleasure of talking on the program at another show back here in Boston. Talk about a little bit about you know how this is enable I mean massive amounts of data you need to make sure you get that. You know the right data and it's valuable information and to the right people, and it gets updated all the time, so give us a little bit of the inner workings. >> Exactly. So thie inner workings, That's it can be a pretty big story, but kind of the short >> story time Theo Short >> story is that if we can get data in one place, and not just from one institution, from many places, that we can start to do things that are not really possible otherwise so, that's kind of the grand vision. So we're moving along those steps on the mass Open cloud for us makes perfect sense because it's there's a academic linked to Boston University. And then there's thie, Red Hat, being one of the academic sponsors as well in that for this kind of synergy that came together really almost perfectly at the right time, as the cloud was developing as where that was moving in it as we were trying to move to the cloud. It just began to link all together. And that's very much how we got there at the moment on what we're trying to do, which is get data so that we can cause medicine. Really, it's amazing to me. In some ways there's all these amazing devices, but computational e medicine lag so far behind the rest of the industry. There's so little integration. There's so little advanced processing going on. There's so much you can do with so little effort, you could do so much. So that's part of the >> vision as well. So help me out here a little bit, Yeah, I mean, maybe it before and after. Let's look at the situation may be clinically speaking here, where a finding or a revelation that you developed is now possible where it wasn't before and kind of what those consequences might have been. And then maybe, how the result has changed now. So maybe that would help paint up a practical picture of what we're talking about. >> I could use one example we're working on, but we haven't got fully to the clouds. All of these things are in their infancy because we still have to deal with the encryption part, which is a work in progress. But for example, we have mind our clinical databases to get examples of normal images and using that I can run comparisons of a case. It comes up to say whether this looks normal or abnormal sweat flags. The condition is to whether it's normal or abnormal, and that helps when there's trainees are people, not is experienced in reading those kinds of images. So again we're at the very beginnings of this. It's one set of pictures. There's many sets of pictures that we get, so there's a long road to get to fully female type are characterized anyone brain. But we're starting at the beginning those steps to very to digitally characterize each brain so we can then start to run. Comparisons against large libraries of other normals are large libraries of genetic disorders and start to match them up. And >> this is insecure. You working in fetal neural imaging as well. So you're saying you could take a an image of ah baby in a mother's womb and many hundreds thousands, whatever it is and you developed this basically a catalogue of what a healthy brain might look like. And now you're offering an opportunity to take a image here on early May of twenty nineteen. And compared to that catalogue, look and determine whether might be anabel normality that otherwise could have been spotted before. >> Correct and put a number to that in terms of a similarity value our probability values so that it's not just Mia's a collision, say Well, I think it's a little abnormal because it is hard to interpret that in terms of how severe is the spectrum of normal. How how? Sure you. So we put all these dated together. We can start to get more predictive value because we couldn't follow more kids and understand if it's that a a sima that too similar what's most likely disorder? What's the best treatment? So it gives you better FINA typing of the disorders that appear early and fetal life, some of which are linked to we think he treated, say, for example, with upcoming gene therapies and other nutritional intervention so we could do this characterization early on. We hope we can identify early therapies that our target to targeted to the abnormalities we detect. >> So intervene well ahead of time. Absolutely. >> I don't know. The other thing is, I mean Ellen has often times said how many images she looks at in the day on other radiologist, and it's it's amazing. It's she said, the number hundred thousand one point so you can imagine the human fatigue, right? So it Matt, imagine if you could do a quick pre processing on just flag ones that really are abnormal by you know they could be grossly abnormal. But at least let's get those on the top of the queue when you can look at it when you are much more able to, you know, think, think, think these things through. So there's one good reason of having these things sitting on an automated system. Stay out of the cloud over it might be >> Where are we with the roll out of this? This and kind of expansion toe, maybe other partners. >> So a lot of stuff has been happening over the last year. I mean, the the entire platform is still, I would say, somewhat prototypical, but we have a ll the pipelines kind of connected, so data can flow from a place like the hospital flowed to the cloud. Of course, this is all you know, protected and encrypted on the cloud weaken Do kind of weaken. Do any analysis we want to do Provided the analysis already exists, we can get the results back. Two definition we have the interface is the weapon to faces built their growing. So you can at this point, almost run the entire system without ever touching a command line. A year ago, it was partially there. A year ago, you had to use a command line. Now you don't have to. Next year will be even more streamlined. So this is the way it's moving right now and was great for me personally. About the cloud as well is that it's not just here in Boston where you, Khun benefit from using these technologies, you know, for the price of a cellphone on DH cell signal. You can use this kind of technology anywhere. You could be in the bush in Africa for argument's sake, and you can have access to these libraries of databases imaging that might exist. You, khun compare Images are collected wherever it might be just for the price of connecting to the Internet. >> You just need a broadband connection >> just right. Just exactly. >> Sometimes when you think about again about you know, we've talked about mobile technology five g coming on as it is here in the U. S. Rural health care leveling that and Third World, I was thinking more along the lines of here in the States and with some memories that just don't have access to the kind of, like, obviously platinum carry you get here in the Boston area. But all those possibilities would exist or could exist based on the findings that you're getting right now with Chris Project. So >> where does the Chris project go from here? >> Well, what we'd like to do is get more hospitals on board, uh, thinking pediatrics, we have a lot of challenge because there are so many different rare disorders that it's hard to study any one of them from one hospital. So we have to work together. There's been some effort to bring together some genetic databases, but we really need to being also the imaging bait databases together. So hopefully we can start to get a consortium of some of the pediatric hospitals working together. We need that also because normal for normal, you need to know the gender, the age, the thie ethnicity. You know, so many demographics that are nice to characterize what normal is. So if we all work together, we can also get a better idea of what is normal. What is normal variants. And there's a lot of other projects that are funded by N. H. Building up some of those databases as well, too. But we could put him into all into one place where we can actually now query on that. Then we could start to really do precision medicine. >> And the other thing, which we definitely are working on and I want to do, is build a community of developers around this platform because, you know, there's no way our team can write all of these tools. No, no, no, we want to. But we want everyone else who wants to make these tools very easily hop onto this platform. And that's very important to us because it's so much easier to develop to christen it just about the Amazon. There's almost no comparison. How much easier >> we'Ll Definitely theme, we hear echoing throughout Red Hat summit here is that Does that tie into, like, the open shift community? Or, you know, what is the intersection with red hat? >> It definitely does, because this is kind of the age of continue ization, which makes so many things so much easier on DH. This platform that we've developed is all about container ization. So we want to have medical by medical or any kind of scientific developers get onto that container ization idea because when they do that and it's not that hard to do. But when you do that, then suddenly you can have your your analysis run almost anywhere. >> And that's an important part in medicine, because I run the same analysis on different computers, get different results. So the container ization concept, I think, is something that we've been after, which is a reproduce ability that anybody can run it along there, use the same container we know we're going. Same result. And that is >> critical. Yes, especially with what you're doing right, you have to have that one hundred percent certainty. Yep. Standardisation goes along, Ray. Sort of fascinating stuff. Thank you both for joining us. And good luck. You're an exciting phase, that's for sure. And we wish you all the best going forward here. Thank you so much. Thank you both. Back with more from Boston. You're watching Red Hat Summit coverage live here on the Q t.