>> From Seattle Washington, it's theCUBE, covering AWS Imagine, nonprofit. Brought to you by Amazon Web Services. >> Hey welcome back everybody, Jeff Frick here with theCUBE. We're actually on the waterfront in Seattle at the AWS Imagine nonprofit event. We were here a couple weeks ago for the AWS Imagine education event. This is really about nonprofits and solving big, big problems. So Dave Levy and team have you know dedicated to some of these big problems. And one of the big problems in the world is human trafficking, and problems that people are encountering and all kinds of nasty situations all over the world. And we're really excited to have someone who's tackling that problem, and really trying to bring a voice to those people that wouldn't otherwise have a voice. And she's Hend Alhinnawai, she's the CEO of Humanitarian Tracker. Hend, good to see you. >> Thank you Jeff, good to be here. >> Absolutely. So before we jump into it, impressions on this event? >> Wonderful event bringing together technologists, people in nonprofits, really creating synergies for people to collaborate and talk to each other and network and learn how they can advance their organizations. >> Such important work. >> Yes. >> So give us kind of the background on what you're up to, what Humanitarian Tracker's all about. >> So Humanitarian Tracker's a nonprofit forum. It was created to connect and empower citizens using innovation and technology, but specifically for humanitarian events. We were among the first to combine crowdsourced reports with data mining and artificial intelligence and apply them to humanitarian disasters, conflicts, human rights violations, disease outbreak. All the way to tracking the UN's Sustainable Development Goals. Really giving a holistic view of what's happening. >> It's interesting, you know, it's probably like the middle eastern spring, I can't remember the exact term that people use, where it was kind of the first use of regular people using their mobile phones to kind of grab a ground swell of action. You're not looking at the politics specifically, you're looking more at humanitarian disasters. But pretty amazing kind of what a connected phone represents to anyone anywhere in the world now to communicate what's happening to them. To share that story. We really didn't have anything like that before. To get that personal event on the ground. >> No it's really a new way of consuming, creating and consuming information. So the cell phone has really given people on the ground a chance to tell their own story. But it's not enough. If you have an event that happens to you. Something happens to you. And you record it, it stops there. But the unique thing with Humanitarian Tracker is it gives people that forum to show the world and tell them what's happening to and around them. >> Right, but it's not just about the individual. And what you guys are doing is using cutting edge technology, obviously you're here as part of the AWS event. In terms of machine-learning and big data to grab a large number of these reported events and distill it into more of an overarching view of what is actually happening on the ground. How did you do that, where did you get that vision, how are you executing that? >> Well, we're all about empowering the citizen. And in our line of work we deal with a lot of data, a lot of information, most of it is unstructured, most of it is crowdsourced. So we use machine-learning to help us extract important details. Information on time. Event location, what is happening. And at the same time we really cared that this reporter, stays anonymous for their own safety. We, privacy and security is utmost importance to us. So that's always our focus. So in that space, we de-identify them. We take out any information that could be identifiable, that could lead to their arrest, or could lead to someone identifying that it was them that reported. >> And how do you get this information to the people that are suffering this activity ground? How do they know about you, how do they know that you are anonymizing their information so there's not going to be repercussions if they report. You know, how do, kind of I guess your go-to-market, to steal a business terms, in making sure that people know this tool's available for help? >> It depends on the situation. For example in the conflict situation, we rolled it out, and we kept it low key for awhile. Because we didn't want government attacks, we didn't want people to be arrested, or to be tried. So we rolled it out. And it was word of mouth that spreads. And people started submitting supports. Actually the first project we did with conflict, we weren't sure if we were going to get one report, zero reports. The first week we got nothing. And then slowly as people learned about it they started submitting their reports. And we see our job as really elevating the otherwise marginalized voice. So you submit a report to us, we then take it. We verify it. We make it public. And that, we welcome, we encourage, we want people to consume it. Whether you're a student, whether you're a journalist, whether you're a government, whether you work in a nonprofit, the UN. It's been used to address human rights violations, it's been used to identify humanitarian hotspots. The data's phenomenal, and what you get from it. It's not just collecting data. We're not just about collecting the data. We want to make sure it's meaningful, and we want to derive insights. So we want to know what is the data actually telling us? >> Right, right. So just to be clear for people that don't know, so you're making that data available, you're cleansing the data, you're running some AI on it to try to get a bigger picture, and anyone with a login, any kind of journalist can now access that data in support of whatever issue or topic or story they're chasing? >> That's it Jeff. >> That's phenomenal. And just kind of size and scope. You've been at this I think you said since 2011. You know kind of how many active, activities, crisis, I don't know, what the definition is of a bucket of these problems. Are you tracking historically at a given point in time? Give us some kind of basic sizing type of dimensions. >> It really ranges, because it could, when we were tracking conflict for example, we were really focused on one area, and the surrounding countries. Because you had refugee population, you had displacement, you had all sorts of issues. But it could be anywhere from five projects, it just depends. And we want to make sure that each project we're taking on we're giving it our full attention, full scope. And I like to run the organization like a two-team pizza team. And so I don't take on more than I could handle. >> Right, right. So then how did it morph from the conflict to the Global Sustainability Goal? So we've worked with Western Digital, they're doing a lot of work, ASP's doing a lot of work on kind of these global sustainability goals. How did you get involved in that, and how did the two kind of dovetail together? >> So the elasticity of the cloud has helped our operation scale tremendously. And in 2016 we were selected as a top 10 global innovation, that could be applied to the Sustainable Development Goals, and-- >> So they found you, the UN find you, or did you get nominated? How did that happen? >> We were nominated, and from over 1,000 solutions we were chosen. >> Congratulations. >> Thank you. And we were showcased at the Solutions Summit which is hosted at the United Nations. And just based on that experience of meeting people that were doing really cool things in their respective communities, we launched the Global Action Mosaic. Because we wanted to create one place where people that are doing projects in their communities could submit it, and have it showcased. And the goals are not only to crowdsource the SGD's, but to also be a part of the effort to track what's happening. Who's doing what where, make it easy for people to search say, Jeff you decided to get involved in a project with education. You can go onto our Global Action Mosaic, search projects on education in your community or in other parts of the world and then get involved in it. So it's really creating a centralized place where people can get information on the global goals. >> Awesome. So that's pretty much the Global Action Mosaic. It's pretty much focused on the UN global goals versus your core efforts around the Humanitarian Tracker. >> Yes. >> That's great. So we're here at AWS. Have you always been on AWS? Is this something new? How does being on kind of the AWS infrastructure help you do your mission better? >> We are, we've been partners in running AWS since we actually started. >> Since the beginning. >> Yes we have Yusheheedi as one of our partners, development partners, AWS. And because one of the core, one of the most important things to us is privacy and security, we want to make sure that whatever data is being handled and received is stored securely. >> Right, right. >> And that information transmitted, handled is also being done so in a secure way. Like I mentioned, the elasticity of the cloud has helped us scale our mission tremendously. It's affordable, we've been able to us it, we've learned their machine-learning stock to de-identify some of the data that comes in. So we're firm believers that AWS is essential to how we run our operation. >> Because do the individual conflicts kind of grow and shrink over time? Do you see it's really a collection of kind of firing up hotspots and then turning down versus one long, sustained, relatively flat, from kind of a utilization and capacity point of view? >> Yeah, no it definitely, it flares up and you'll have like a year, months, weeks sometimes where it's just focused on one area. But one of the things we focus on, it's not just. So what is the data actually telling us? So say you're focusing on point A. But just down the street in location B there is a dire humanitarian emergency that needs to be addressed. The crowdsourced reports, combined with the data mining and the AI, helps us identify those hotspots. So everybody could be focused here, but there could be an emergency down the street that needs to be addressed as well. It just depends. >> And do you have your own data scientists or do you, do other people take your data and run it through their own processes to try to find some of these insights? >> We have both. >> You have both. >> Yeah. >> So what's been the biggest surprise when you anonymize and aggregate the data around some of these hotspots? Is there a particular pattern that you see over and over? Is there some insight, that now that you've seen so much of it, from kind of the (muffled speaking) that you can share and reflect on? >> I think it' very unique to each project to do. But there is one thing that I strongly support, that I don't see enough of, and that's the sharing of data within the organizations. And so, for example just getting to that culture where sharing your data between organizations is encouraged and actually done. Could help create a, create a pool of knowledge. So, for example we worked with 13 different organizations that were all tackling humanitarian events. The same one, in Syria. And the 13 did not share data and did not talk to each other. And so we found that for example, they were all focused on one area. When just a few miles down, there was a need that wasn't being addressed. But because they don't share information, they had no idea. >> Right. >> It was only when we were able to take a look at it, kind of from the, from an overarching view, looking all their data, we were able to say you know, it would be helpful, it would actually, you could save on resources, and less time, and less effort, and you guys are tackling a small funding pool to begin with. If you shared information and tackled different things, instead of focusing on one area, because you don't know what the other guys doing. >> And were they using crowdsource data, is there source data, or were they just trying to collect their own from the field? >> They were collecting their own. >> So I assume that the depth, and the richness, and the broadness of data is nothing like you're collecting. >> Well you get a different kind of, you get different kind of information when the individuals actually telling you what's happening versus you asking a very direct question like, "Are you healthy? Yes or No?". Whereas you give them the chance, they might tell you that they haven't eaten, and their diabetic and you know, give you other pieces of information. Where they're living, are they refugees? Are they healthy? Are they not healthy? Do they go to school? Do their kids go to school? How many kids they have? Are they a female-run household? All this information could help guide development in the proper way. >> Right, right. All right. So give you the final word, how should people get involved if they want to help? >> You can go to humanitariantracker.org if you want to volunteer with us. And if you're doing a project that is related to the UN's Sustainable Development Goals, I would like you to go to globalactionmosaic.org, and map it there, and be part of our community. >> So Hend, thank you for taking a few minutes to share your story, and for all the good work that you're doing out there. >> Thank you Jeff it was a pleasure. >> All right, she's Hend, I'm Jeff, you're watching theCUBE, we're at AWS Imagine nonprofit. Thanks for watching we'll see you next time. (techno music)

>> Live from San Francisco, it's the Cube, covering Google Cloud Next 2018. Brought to you by Google Cloud and its ecosystem partners. >> Hello and welcome back to The Cube coverage here live in San Francisco for Google Cloud's conference Next 2018, #GoogleNext18. I'm John Furrier with Jeff Frick, my cohost all week. Third day of three days of wall to wall live coverage. Our next guest, Carol Carpenter, Vice President of Product Marketing for Google Cloud. And Ayin Vala, Chief Data Science Foundation for Precision Medicine. Welcome to The Cube, thanks for joining us. >> Thank you for having us. >> So congratulations, VP of Product Marketing. Great job getting all these announcements out, all these different products. Open source, big query machine learning, Istio, One dot, I mean, all this, tons of products, congratulations. >> Thank you, thank you. It was a tremendous amount of work. Great team. >> So you guys are starting to show real progress in customer traction, customer scale. Google's always had great technology. Consumption side of it, you guys have made progress. Diane Green mentioned on stage, on day one, she mentioned health care. She mentioned how you guys are organizing around these verticals. Health care is one of the big areas. Precision Medicine, AI usage, tell us about your story. >> Yes, so we are a very small non-profit. And we are at the intersection of data science and medical science and we work on projects that have non-profits impact and social impact. And we work on driving and developing projects that have social impact and in personalized medicine. >> So I think it's amazing. I always think with medicine, right, you look back five years wherever you are and you look back five years and think, oh my god, that was completely barbaric, right. They used to bleed people out and here, today, we still help cancer patients by basically poisoning them until they almost die and hopefully it kills the cancer first. You guys are looking at medicine in a very different way and the future medicine is so different than what it is today. And talk about, what is Presicion Medicine? Just the descriptor, it's a very different approach to kind of some of the treatments that we still use today in 2018. It's crazy. >> Yes, so Presicion Medicine has the meaning of personalized medicine. Meaning that we hone it into smaller population of people to trying to see what is the driving factors, individually customized to those populations and find out the different variables that are important for that population of people for detection of the disease, you know, cancer, Alzheimer's, those things. >> Okay, talk about the news. Okay, go ahead. >> Oh, oh, I was just going to say. And to be able to do what he's doing requires a lot of computational power to be able to actually get that precise. >> Right. Talk about the relationship and the news you guys have here. Some interesting stuff. Non-profits, they need compute power, they need, just like an eneterprise. You guys are bringing some change. What's the relationship between you guys? How are you working together? >> So one of our key messages here at this event is really around making computing available for everyone. Making data and analytics and machine learning available for everyone. This whole idea of human-centered AI. And what we've realized is, you know, data is the new natural resource. >> Yeah. >> In the world these days. And companies that know how to take advantage and actually mine insights from the data to solve problems like what they're solving at Precision Medicine. That is really where the new breakthroughs are going to come. So we announced a program here at the event, It's called Data Solutions for Change. It's from Google Cloud and it's a program in addition to our other non-profit programs. So we actually have other programs like Google Earth for non-profits. G Suite for non-profits. This one is very much focused on harnessing and helping non-profits extract insights from data. >> And is it a funding program, is it technology transfer Can you talk about, just a little detail on how it actually works. >> It's actually a combination of three things. One is funding, it's credits for up to $5,000 a month for up to six months. As well as customer support. One thing we've all talked about is the technology is amazing. You often also need to be able to apply some business logic around it and data scientists are somewhat of a challenge to hire these days. >> Yeah. >> So we're also proving free customer support, as well as online learning. >> Talk about an impact of the Cloud technology for the non-proit because6 I, you know, I'm seeing so much activity, certainly in Washington D.C. and around the world, where, you know, since the Jobs Act, fundings have changed. You got great things happening. You can have funding on mission-based funding. And also, the legacy of brand's are changing and open source changes So faster time to value. (laughs) >> Right. >> And without all the, you know, expertise it's an issue. How is Cloud helping you be better at what you do? Can you give some examples? >> Yes, so we had two different problems early on, as a small non-profit. First of all, we needed to scale up computationally. We had in-house servers. We needed a HIPAA complaint way to put our data up. So that's one of the reasons we were able to even use Google Cloud in the beginning. And now, we are able to run our models or entire data sets. Before that, we were only using a small population. And in Presicion Medicine, that's very important 'cause you want to get% entire population. That makes your models much more accurate. The second things was, we wanted to collaborate with people with clinical research backgrounds. And we need to provide a platform for them to be able to use, have the data on there, visualize, do computations, anything they want to do. And being on a Cloud really helped us to collaborate much more smoothly and you know, we only need their Gmail access, you know to Gmail to give them access and things. >> Yeah. >> And we could do it very, very quickly. Whereas before, it would take us months to transfer data. >> Yeah, it's a huge savings. Talk about the machine learning, AutoML's hot at the show, obviously, hot trend. You start to see AI ops coming in and disrupt more of the enterprise side but as data scientists, as you look at some of these machine learnings, I mean, you must get pretty excited. What are you thinking? What's your vision and how you going to use, like BigQuery's got ML built in now. This is like not new, it's Google's been using it for awhile. Are you tapping some of that? And what's your team doing with ML? >> Absolutely. We use BigQuery ML. We were able to use a few months in advance. It's great 'cause our data scientists like to work in BigQuery. They used to see, you know, you query the data right there. You can actually do the machine learning on there too. And you don't have to send it to different part of the platform for that. And it gives you sort of a proof of concept right away. For doing deep learning and those things, we use Cloud ML still, but for early on, you want to see if there is potential in a data. And you're able to do that very quickly with BigQuery ML right there. We also use AutoML Vision. We had access to about a thousand patients for MRI images and we wanted to see if we can detect Alzheimer's based on those. And we used AutoML for that. Actually works well. >> Some of the relationships with doctors, they're not always seen as the most tech savvy. So now they are getting more. As you do all this high-end, geeky stuff, you got to push it out to an interface. Google's really user-centric philosophy with user interfaces has always been kind of known for. Is that in Sheets, is that G Suite? How will you extend out the analysis and the interactions. How do you integrate into the edge work flow? You know? (laughs) >> So one thing I really appreciated for Google Cloud was that it was, seems to me it's built from the ground up for everyone to use. And it was the ease of access was very, was very important to us, like I said. We have data scientisits and statisticians and computer scientists onboard. But we needed a method and a platform that everybody can use. And through this program, they actually.. You guys provide what's called Qwiklab, which is, you know, screenshot of how to spin up a virtual machine and things like that. That, you know, a couple of years ago you have to run, you know, few command lines, too many command lines, to get that. Now it's just a push of a button. So that's just... Makes it much easier to work with people with background and domain knowledge and take away that 80% of the work, that's just a data engineering work that they don't want to do. >> That's awesome stuff. Well congratulations. Carol, a question to you is How does someone get involved in the Data Solutions for Change? An application? Online? Referral? I mean, how do these work? >> All of the above. (John laughs) We do have an online application and we welcome all non-profits to apply if they have a clear objective data problem that they want to solve. We would love to be able to help them. >> Does scope matter, big size, is it more mission? What's the mission criteria? Is there a certain bar to reach, so to speak, or-- >> Yeah, I mean we're most focused on... there really is not size, in terms of size of the non-profit or the breadth. It's much more around, do you have a problem that data and analytics can actually address. >> Yeah. >> So really working on problems that matter. And in addition, we actually announced this week that we are partnering with United Nations on a contest. It's called Sustainable.. It's for Visualize 2030 >> Yeah. >> So there are 17 sustainable development goals. >> Right, righr. >> And so, that's aimed at college students and storytelling to actually address one of these 17 areas. >> We'd love to follow up after the show, talk about some of the projects. since you have a lot of things going on. >> Yeah. >> Use of technology for good really is important right now, that people see that. People want to work for mission-driven organizations. >> Absolutely >> This becomes a clear citeria. Thanks for coming on. Appreciate it. Thanks for coming on today. Acute coverage here at Google Could Next 18 I'm John Furrier with Jeff Fricks. Stay with us. More coverage after this short break. (upbeat music)