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AI, Azure and the future of healthcare with Dr. Peter Lee – Microsoft Research

headshot of Peter Lee for the Microsoft Research Podcast

Episode 109 | March 4, 2020

Over the past decade, the healthcare industry has undergone a series of technological changes in an effort to modernize it and bring it into the digital world, but the call for innovation persists. One person answering that call is Dr. Peter Lee, Corporate Vice President of Microsoft Healthcare, a new organization dedicated to accelerating healthcare innovation through AI and cloud computing.

Today, Dr. Lee talks about how MSR’s advances in healthcare technology are impacting the business of Microsoft Healthcare. He also explains how promising innovations like precision medicine, conversational chatbots and Azure’s API for data interoperability may make healthcare better and more efficient in the future.

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Transcript

Peter Lee: In tech industry terms, you know, if the last decade was about digitizing healthcare, the next decade is about making all that digital data good for something, and that good for something is going to depend on data flowing where it needs to flow at the right time.

Host: You’re listening to the Microsoft Research Podcast, a show that brings you closer to the cutting-edge of technology research and the scientists behind it. I’m your host, Gretchen Huizinga.

Host: Over the past decade, the healthcare industry has undergone a series of technological changes in an effort to modernize it and bring it into the digital world, but the call for innovation persists. One person answering that call is Dr. Peter Lee, Corporate Vice President of Microsoft Healthcare, a new organization dedicated to accelerating healthcare innovation through AI and cloud computing.

Today, Dr. Lee talks about how MSR’s advances in healthcare technology are impacting the business of Microsoft Healthcare. He also explains how promising innovations like precision medicine, conversational chatbots and Azure’s API for data interoperability may make healthcare better and more efficient in the future. That and much more on this episode of the Microsoft Research Podcast.

(music plays)

Host: Peter Lee, welcome to the podcast!

Peter Lee: Thank you. It’s great to be here.

Host: So you’re a Microsoft Corporate Vice President and head of a relatively new organization here called Microsoft Healthcare. Let’s start by situating that within the larger scope of Microsoft Research and Microsoft writ large. What is Microsoft Healthcare, why was it formed, and what do you hope to do with it?

Peter Lee: It’s such a great question because when, we were first asked to take this on, it was confusing to me! Healthcare is such a gigantic business in Microsoft. You know, the number that really gets me is, Microsoft has commercial contracts with almost 169,000 healthcare organizations around the world.

Host: Wow.

Peter Lee: I mean, it’s just massive. Basically, anything from a one-nurse clinic in Nairobi, Kenya, to Kaiser Permanente or United Healthcare, and everything in-between. And so it was confusing to try to understand, what is Satya Nadella thinking to ask a “research-y” organization to take this on? But, you know, the future of healthcare is so vibrant and dynamic right now, and is so dependent on AI, on Cloud computing, big data, I think he was really wanting us to think about that future.

Host: Let’s situate you.

Peter Lee: Okay.

Host: You cross a lot of boundaries from pure to applied research, computer science to medicine. You’ve been head of Carnegie Mellon University’s computer science department, but you were also an office director at DARPA, which is the poster child for applied research. You’re an ACM fellow and on the board of directors of the Allen Institute for AI, but you’re also a member of the National Academy of Medicine, fairly newly minted as I understand?

Peter Lee: Right, just this year.

Host: And on the board of Kaiser Permanente’s School of Medicine. So, I’d ask you what gets you up in the morning, but it seems like you never go to bed So instead, describe what you do for a living, Peter! How you choose what hat to wear in the morning and what’s a typical day in your life look like?

Peter Lee: Well, you know, this was never my plan. I just love research, and thinking hard about problems, being around other smart people and thinking hard about problems, getting real depth of understanding. That’s what gets me up. But I think the world today, what’s so exciting about it for anyone with the research gene, is that research, in a variety of areas, has become so important to practical, everyday life. It’s become important to Microsoft’s business. Not just Microsoft, but all of our competitors. And so I just feel like I’m in a lucky position, as well as a lot of my colleagues, I don’t think any of us started with that idea. We just wanted to do research and now we’re finding ourselves sort of in the middle of things.

Host: Right. Well, talk a little bit more about computer science and medicine. How have you moved from one to the other, and how do you kind of envision yourself in this arena?

Peter Lee: Well, my joke here is, these were changes that, actually, Satya Nadella forced me to make! And it’s a little bit of a joke because I was actually honored that he would think of me this way, but it was also painful because I was in a comfort zone just doing my own research, leading research teams, and then, you know, Satya Nadella becomes the CEO, Harry Shum comes on board to drive innovation, and I get asked to think about new ways to take research ideas and get them out into the world. And then, three years after that, I get asked to think about the same thing for healthcare. And each one of those, to my mind, are examples of this concept that Satya Nadella likes to talk about, “growth mindset.” I joke that growth mindset is actually a euphemism because each time you’re asked to make these changes, you just get this feeling of dread. You might have a minute where you’re feeling honored that someone would ask you something, but then…

Host: Oh, no! I’ve got to do it now!

Peter Lee: …and boy, I was, you know, on a roll in what I was doing before, and you do spend some time feeling sorry for yourself… but when you work through those moments, you find that you do have those periods in your life where you grow a lot. And my immersion with so many great people in healthcare over the last three or four years has been one of those big growth periods. And to be recognized, then, let’s say, by the National Academies is sort of validation of that.

Host: All right, so rewind just a little bit and talk about that space you were in just before you got into the healthcare situation. You were doing Microsoft Research. Where, on the spectrum from pure, like your Carnegie Mellon roots, to applied, like your DARPA roots, did that land? There’s an organization called NeXT here I think, yeah?

Peter Lee: That’s right. You know, when I was in academia, academia really knows how to do research.

Host: Yeah.

Peter Lee: And they really put the creatives, the graduate students and the faculty, at the top of the pyramid, socially, in the university. It’s just a great setup. And it’s organized into departments, which are each named after a research area or a discipline and within the departments there are groups of people organized by sub-discipline or area, and so it’s an organizing principle that’s tried and true. When I went to DARPA, it was completely different. The departments aren’t organized by research area, they’re organized by mission, some easily assessable goal or objective. You can always answer the question, have we accomplished it yet or not?

Host: Right.

Peter Lee: And so research at DARPA is organized around those missions and that was a big learning experience for me. It’s not like saying we’re going to do computer vision research. We’ll be doing that for the next fifty years. It’s, can we eliminate the language barrier for all internet-connected people? That’s a mission. You can answer the question, you know, how close are we?

Host: Right.

Peter Lee: And so the mix between those two modes of research, from academia to DARPA, is something that I took with me when I joined Microsoft Research and, you know, Microsoft Research has some mix, but I thought the balance could be slightly different. And then, when Satya Nadella became the CEO and Harry Shum took over our division, they challenged me to go bigger on that idea and that’s how NeXT started. NeXT tried to organize itself by missions and it tried to take passionate people and brilliant ideas and grow them into new lines of business, new engineering capabilities for Microsoft, and along the way, create new CVPs and TFs for our company. There’s a tension here because one of the things that’s so important for great research is stability. And so when you organize things like you do in academia, and in large parts of Microsoft Research, you get that stability by having groups of people devoted to an area. We have, for example, say, computer networking research groups that are best in the world.

Host: Right.

Peter Lee: And they’ve been stable for a long time and, you know, they just create more and more knowledge and depth, and that stability is just so important. You feel like you can take big risks when you have that stability. When you are mission-oriented, like in NeXT, these missions are coming and going all the time. So that has to be managed carefully, but the other benefit of that, management-wise, is more people get a chance to step up and express their leadership. So it’s not that either model is superior to the other, but it’s good to have both. And when you’re in a company with all the resources that Microsoft has, we really should have both.

Host: Well, let’s zoom out and talk, somewhat generally, about the promise of AI because that’s where we’re going to land on some of the more specific things we’ll talk about in a bit, but Microsoft has several initiatives under a larger umbrella called AI for Good and the aim is to bring the power of AI to societal-scale problems in things like agriculture, broadband accessibility, education, environment and, of course, medicine. So AI for Health is one of these initiatives, but it’s not the same thing as Microsoft Healthcare, right?

Peter Lee: Well, the whole AI for Good program is so exciting and I’m just so proud to be in a company that makes this kind of commitment. You can think of it as a philanthropic grants program and it is, in fact, in all of these areas, providing funding and technical support to really worthy teams, passionate people, really trying to bring AI to bear for the greater good.

Host: Mm-hmm.

Peter Lee: But it’s also the case that we devote our own research resources to these things. So it’s not just giving out grants, but it’s actually getting into collaborations. What’s interesting about AI for Health is that it’s the first pillar in the AI for Good program that actually overlaps with a business at Microsoft and that’s Microsoft Healthcare. One way that I think about it is, it’s an outlet for researchers to think about, what could AI do to advance medicine? When you talk to a lot of researchers in computer science departments, or across Microsoft research labs, increasingly you’ll see more and more of them getting interested in healthcare and medicine and the first things that they tend to think about, if they’re new to the field, are diagnostic and therapeutic applications. Can we come up with something that will detect ovarian cancer earlier? Can we come up with new imaging techniques that will help radiologists do a better job? Those sorts of diagnostic and therapeutic applications, I think, are incredibly important for the world, but they are not Microsoft businesses. So the AI for Health program can provide an outlet for those types of research passions. And then there are also, as a secondary element, four billion people on this planet today that have no reasonable access to healthcare. AI and technology have to be part of the solution to creating that more equitable access and so that’s another element that, again, doesn’t directly touch Microsoft’s business today in Microsoft Healthcare, but is so important we have a lot to offer so AI for Health is just, I think, an incredibly visionary and wonderful program for that.

Host: Well, let’s zoom back out… um, no, let’s zoom back in. I’ve lost track of the camera. I don’t know where it is! Let’s talk about the idea of precision medicine, or precision healthcare, and the dream of improving those diagnostic and therapeutic interventions with AI. Tell us what precision medicine is and how that plays out and how are the two rather culturally diverse fields of computer science and medicine coming together to solve for X here?

Peter Lee: Yeah, I think one of the things that is sometimes underappreciated is, over the past ten to twenty years, there’s been a massive digitization of healthcare and medicine. After the 2008 economic collapse, in 2009, there was the ARA… there was a piece of legislation attached to that called the HITECH Act, and HITECH actually required healthcare organizations to digitize health records. And so for the past ten years, we’ve gone from something like 15% of health records being in digital form, to today, now over 98% of health records are in digital form. And along with that, medical devices that measure you have gone digital, our ability to sequence and analyze your genome, your proteome, have gone digital and now the question is, what can we do with all the digital information? And on top of that, we have social information.

Host: Yeah.

Peter Lee: People are carrying mobile devices, people talk to computers at home, people go to their Walgreens to get their flu shots.

Host: Yeah.

Peter Lee: And all of this is in digital form and so the question is, can we take all of that digital data and use it to provide highly personalized and precisely targeted diagnostics and therapeutics to people.

Host: Mm-hmm.

Peter Lee: Can we get a holistic, kind of, 360-degree view of you, specifically, of what’s going on with you right now, and what might go on over the next several years, and target your wellness? Can we advance from sick care, which is really what we have today…

Host: Right.

Peter Lee: …to healthcare.

Host: When a big tech company like Microsoft throws its hat in the healthcare ring and publicly says that it has the goal of “transforming how healthcare is experienced and delivered,” I immediately think of the word disruption, but you’ve said healthcare isn’t something you disrupt. What do you mean by that, and if disruption isn’t the goal, what is?

Peter Lee: Right. You know, healthcare is not a normal business. Worldwide, it’s actually a $7.5 trillion dollar business. And for Microsoft, it’s incredibly important because, as we were discussing, it’s gone digital, and increasingly, that digital data, and the services and AI and computation to make good use of the data, is moving to the cloud. So it has to be something that we pay very close attention to and we have a business priority to support that.

Host: Right.

Peter Lee: But, you know, it’s not a normal business in many, many different senses. As a patient, people don’t shop, at least not on price, for their healthcare. They might go on a website to look at ratings of primary care physicians, but certainly, if you’re in a car accident, you’re unconscious. You’re not shopping.

Host: No.

Peter Lee: You’re just looking for the best possible care. And similarly, there’s a massive shift for healthcare providers away from what’s called fee-for-service, and toward something called value-based care where doctors and clinics are being reimbursed based on the quality of the outcomes. What you’re trying to do is create success for those people and organizations that, let’s face it, they’ve devoted their lives to helping people be healthier. And so it really is almost the purest expression of Microsoft’s mission of empowerment. It’s not, how do we create a disruption that allows us to make more money, but instead, you know, how do we empower people and organizations to deliver better – and receive better – healthcare? Today in the US, a primary care doctor spends almost twice as much time entering clinical documentation as they do actually taking care of patients. Some of the doctors we work with here at Microsoft call this “pajama time,” because you spend your day working with patients and then, at home, when you crawl into bed, you have to finish up your documentation. That’s a big source of burn out.

Host: Oh, yeah.

Peter Lee: And so, what can we do, using speech recognition technologies, natural language processing, diarization, to enable that clinical note-taking to be dramatically reduced? You know, how would that help doctors pay more attention to their patients? There is something called revenue-cycle management, and it’s sort of sometimes viewed as a kind of evil way to maximize revenues in a clinic or hospital system, but it is also a place where you can really try to eliminate waste. Today, in the US market, most estimates say that about a trillion dollars every year is just gone to waste in the US healthcare system. And so these are sort of data analysis problems, in this highly complex system, that really require the kind of AI and machine learning that we develop.

Host: And those are the kinds of disruptions we’d like to see, right?

Peter Lee: That’s right. Yeah.

Host: We’ll call them successes, as you did.

Peter Lee: Well, and they are disruptions though, they’re disruptions that help today’s working doctors and nurses. They help today’s hospital administrators.

(music plays)

Host: Let’s talk about several innovations that you’ve actually made to help support the healthcare industry’s transformation. Last year – year ago – at the HIMSS conference, you talked about tools that would improve communication, the healthcare experience and interoperability and data sharing in the cloud. Tell us about these innovations. What did you envision then, and now, a year later, how are they working out?

Peter Lee: Yeah. Maybe the one I like to start with is about interoperability. I sometimes have joked that it’s the least sexy topic, but it’s the one that is, I think, the most important to us. In tech industry terms, you know, if the last decade was about digitizing healthcare, the next decade is about making all that digital data good for something and that good for something is going to depend on data flowing where it needs to flow…

Host: Right.

Peter Lee: …at the right time. And doing that in a way that protects people’s privacy because health data is very, very personal. And so a fundamental issue there is interoperability. Today, while we have all this digital data, it’s really locked into thousands of different incompatible data formats. It doesn’t get exposed through modern APIs or microservices. It’s oftentimes siloed for business reasons, and so unlocking that is important. One way that we look at it here at Microsoft is, we are seeing a rising tidal wave of healthcare organizations starting to move to the cloud. Probably ten years from now, almost all healthcare organizations will be in the cloud. And so, with that historic shift that will happen only once, ever, in human history, what can we do today to ensure that we end up in a better place ten years from now than we are now? And interoperability is one of the keys there. And that’s something that’s been recognized by multiple governments. The US government, through the Centers for Medicare and Medicaid Services, has proposed new regulations that require the use of specific interoperable data standards and API frameworks. And I’m very proud that Microsoft has participated in helping endorse and guide the specific technical choices in those new rules.

Host: So what is the API that Microsoft has?

Peter Lee: So the data standard that we’ve put a lot of effort behind is something called FHIR. F-H-I-R, Fast Healthcare Interoperability Resources. And for anyone that’s used to working in the web, you can look at FHIR and you’ll see something very familiar. It’s a modern data standard, it’s extensible, because medical science is advancing all the time, and it’s highly susceptible to analysis through machine learning.

Host: Okay.

Peter Lee: And so it’s utterly modern and standardized, and I think FHIR can be a lingua franca for all healthcare data everywhere. And so, for Microsoft, we’ve integrated FHIR as a first-class data type in our cloud, in Azure.

Host: Oh, okay.

Peter Lee: We’ve enabled FHIR in Office. So the Teams application, for example, it can connect to health data for doctors and nurses. And there’s integration going on into Dynamics. And so it’s a way to convert everything that we do here at Microsoft into great healthcare-capable tools. And once you have FHIR in the cloud, then you also, suddenly, unlock all of the AI tools that we have to just enable all that precision medicine down the line.

Host: That’s such a Biblical reference right then! The cloud and the FHIR.

Peter Lee: You know, there are – there’s an endless supply of bad puns around FHIR. So thank you for contributing to that.

Host: Well, it makes me think about the Fyre Festival, which was spelt F-Y-R-E, which was just the biggest debacle in festival history

Peter Lee: I should say, by the way, another thing that everyone connected to Microsoft should be proud of is, we have really been one of the chief architects for this new future. One of the most important people in the FHIR development community is Josh Mandel, who works with us here at Microsoft Healthcare, and he has the title Chief Architect, but it’s not Chief Architect for Microsoft, it’s Chief Architect for the cloud.

Host: Oh, my gosh.

Peter Lee: So he spends time talking to the folks at Google, at AWS, at Salesforce and so on.

Host: Right.

Peter Lee: Because we’re trying to bring the entire cloud ecosystem along to this new future.

Host: Tell me a little bit about what role bots might play in this arena?

Peter Lee: Bots are really interesting because, how many listeners have received a lab test result and have no idea what it means? How many people have received some weird piece of paper or bill in the mail from their insurance company? It’s not just medical advice, you know, where you have a scratch in your throat and you’re worried about what you should do. That’s important too, but the idea of bots in healthcare really span all these other things. One of the most touching, in a project led by Hadas Bitran and her team, has been in the area of clinical trials. So there’s a website called clinicaltrials.gov and it contains a registry describing every registered clinical trial going on. So now, if you are desperate for more experimental care, or you’re a doctor treating someone and you’re desperate for this, you know, how do you find, out of thousands of documents, and they’re complicated…

Host: Right.

Peter Lee: …technical, medical, science things.

Host: Jargon-y.

Peter Lee: Yeah, and it’s difficult. If you go to clinicaltrials.gov and type into the search box ‘breast cancer’ you get hundreds of results. So the cool project that Hadas and her team led was to use machine reading from Microsoft Research out of Hoifung Poon’s team, to read all of those clinical trials documents and create a knowledge graph and use that knowledge graph then to drive a conversational chatbot so that you can engage in a conversation. So you can say, you know, “I have breast cancer. I’m looking for a clinical trial,” and the chatbot will start to ask you questions in order to narrow down, eventually, to the one or two or three clinical trials that might be just right for you. And so this is something that we just think has a lot of potential.

Host: Yeah.

Peter Lee: And business-wise, there are more mundane, but also important things. Just call centers. Boy, those nurses are busy. What would happen if we had a bot that would triage and tee up some of those things and really give superpowers to those call center nurses. And so it’s that type of thing that I think is very exciting about conversational tech in general. And of course, Microsoft Research and NeXT should be really proud of really pioneering a lot of this bot technology.

Host: Right. So if I employed a bot to narrow down the clinical trials, could I get myself into one? Is that what you’re explaining here?

Peter Lee: Yeah, in fact, the idea here is that this would help, tremendously, the connection between perspective patients and clinical trials. It’s so important because pharmaceutical companies, in clinics that are setting up clinical trials, more than 50% of them fail to recruit enough participants. They just never get off the ground because they don’t get enough. The recruitment problem is so difficult.

Host: Wow.

Peter Lee: And so this is something that can really help on both ends.

Host: I didn’t even think about it from the other angle. Like, getting people in. I always just assumed, well, a clinical trial, no biggie.

Peter Lee: It’s such a sad thing that most clinical trials fail. And fail because of the recruitment problem.

Host: Huh. Well, let’s talk a little bit more about some of the really interesting projects that are going on across the labs here at Microsoft Research. So what are some of the projects and who are some of the people that are working to improve healthcare in technology research?

Peter Lee: Yeah. I think pretty much every MSR lab is doing interesting things. There’s some wonderful work going on in the Cambridge UK lab, in Chris Bishop’s lab there, in a group being led by Aditya Nori. One of the things there has been a set of projects in collaboration with Novartis really looking at new ideas about AI-powered molecule design for cellular therapies, as well as very precise dosing of therapies for things like macular degeneration and so these are, sort of, bringing the very best machine learning and AI researchers shoulder-to-shoulder with the best researchers and scientists at Novartis to really kind of innovate and invent the future. In the MSR India lab, Sriram Rajamani’s team, they’ve been standing up a really impressive set of technologies and projects that have to do with global access to healthcare and this is something that I think is just incredibly, incredibly important. You know, we really could enable, through more intelligent medical devices for example, much less well-trained technicians and clinicians to be able to deliver healthcare at a distance. The other thing that is very exciting to me there is just looking at data. You know, how do we normalize data from lots of different sources?

Host: Right.

Peter Lee: And then MSR Asia in Beijing, they’ve increasingly been redirecting some of the amazing advances that that lab is famous for in computer vision to the medical imaging space. And there are just amazing possibilities in taking images that might not be high resolution enough for a precise diagnosis and using AI to, kind of, magically improve the resolution. And so just across board, you go from, kind of, lab to lab you just see some really inspiring work going on.

Host: Yeah, some of the researchers have been on the podcast. Antonio Criminisi with InnerEye, umm…  haven’t had Ethan Jackson from Premonition yet

Peter Lee: No, Premonition… Well, Antonio Criminisi and the work that he led on InnerEye, you know, we actually went all the way to an FDA 510(k) approval on the tumor segmentations…

Host: Wow.

Peter Lee: …and the components of that now are going into our cloud. Really amazing stuff.

Host: Yeah.

Peter Lee: And then Premonition, this is one of these things that is, in the age of coronavirus…

Host: Right?

Peter Lee: …is very topical.

Host: I was just going to refer to that, but I thought maybe I shouldn’t…

Peter Lee: The thing that is so important is, we talked of precision medicine before…

Host: Yeah.

Peter Lee: …but there is also an emerging science of precision population health. And in fact, the National Academy of Medicine just recently codified that as an official part of medical research and it’s bringing some of the same sort of precision medicine ideas, but to population health applications and studies. And so when you look at Premonition, and the ability to look at a whole community and get a genetically precise diagnosis of what is going on in that community, it is something that could really be a game-changer, especially in an era where we are seeing more challenging infectious disease outbreaks.

Host: I think a lot of people would say, can we speed that one up a little? I want you to talk for a minute about the broader tech and healthcare ecosystem and what it takes to be a leader, both thought and otherwise, in the field. So you’ve noted that we’re in the middle of a big transformation that’s only going to happen once in history and because of that, you have a question that you ask yourself and everyone who reports to you. So what’s the question that you ask, and how does the answer impact Microsoft’s position as a leader?

Peter Lee: Right. You know, healthcare, in most parts of the world, is really facing some big challenges. It’s at a financial breaking point in almost all developed countries. The spread of the latest access to good medical practice has been slowing in the developing world and as you, kind of, look at, you know, how to break out of these cycles, increasingly, people turn to technology. And the kind of shining beacon of hope is this mountain of digital data that’s being produced every single day and so how can we convert that into what’s called the triple aim of better outcomes, lower costs and better experiences? So then, when you come to Microsoft, you have to wonder, well, if we’re going to try to make a contribution, how do you do it? When Satya Nadella asked us to take this on, we told ourselves a joke that he was throwing us into the middle of the Pacific Ocean and asking us to find land, because it’s such a big complex space, you know, where do you go? And, we had more jokes about this because you start swimming for a while and you start meeting lots of other people who are just as lost and you actually feel a little ashamed to feel good about seeing other people drowning. But it fundamentally it doesn’t help you to figure out what to work on, and so we started to ask ourselves the question, if Microsoft were to disappear today, in what ways would healthcare be harmed or held back tomorrow and into the future? If our hyperscale cloud were to disappear today, in what ways would that matter to healthcare? If all of the AI capabilities that we can deploy so cheaply on that cloud were to disappear, how would that matter? And then, since we’re coming out of Microsoft Research, if Microsoft Research were to disappear today, in what ways would that matter? And asking ourselves that question has sort of helped us focus on the areas where we think we have a right to play. And I think the wonderful thing about Microsoft today is, we have a business model that makes it easy to align those things to our business priorities. And so it’s really a special time right now.

(music plays)

Host: Well, this is – not to change tone really quickly – but this is the part of the podcast where I ask what could possibly go wrong? And since we’ve actually just used a drowning in the sea metaphor, it’s probably apropos… but when you bring nascent AI technologies, and I say nascent because most people have said, even though it’s been going on for a long time, we’re still in an infancy phase of these technologies. When you bring that to healthcare, and you’re literally dealing with lifeanddeath consequences, there’s not any margin for error. So… I realize that the answer to this question could be too long for the podcast, but I have to ask, what keeps you up at night, and how are you and your colleagues addressing potential negative consequences at the outset rather than waiting for the problems to appear downstream?

Peter Lee: That’s such an important question and it actually has multiple answers. Maybe the one that I think would be most obvious to the listeners of this podcast has to do with patient safety. Medical practice and medical science has really advanced on the idea of prospective studies and clinical validation, but that’s not how computer science, broadly speaking, works. In fact, when we’re talking about machine learning it’s really based on retrospective studies. You know, we take data that was generated in the past and we try to extract a model through machine learning from it. And what the world has learned, in the last few years, is that those retrospective studies don’t necessarily hold up very well, prospectively. And so that gap is very dangerous. It can lead to new therapies and diagnoses that go wrong in unpredictable ways, and there’s sort of an over-exuberance on both sides. As technologists, we’re pretty confident about what we do and we see lots of problems that we can solve, and the healthcare community is sometimes dazzled by all of the magical machine learning we do and so there can be over-confidence on both sides. That’s one thing that I worry about a lot because, you know, all over our field, not just all over Microsoft, but across all the other major tech companies and universities, there are just great technologists that are doing some wonderful things and are very well-intentioned, but aren’t necessarily validated in the right way. And so that’s something that, really, is worrisome. Going along with safety is privacy of people’s health data. And while I think most people would be glad to donate their health data for scientific progress, no one wants to be exploited. Exploited for money, or worse, you know, denied, for example, insurance.

Host: Right.

Peter Lee: And you know, these two things can really lead to outcomes, over the next decade, that could really damage our ability to make good progress in the future.

Host: So that said, we’re pretty good at identifying the problem. We may be able to start a good conversation, air quotes, on that, but this is, for me, like, what are you doing?

Peter Lee: Yeah.

Host: Because this is a huge thing, and

Peter Lee: I really think, for real progress and real transformation, that the foundations have to be right and those foundations do start with this idea of interoperability. So the good thing is that major governments, including the US government, are seeing this and they are making very definitive moves to foster this interoperable future. And so now, our role in that is to provide the technical guidance and technologies so that that’s done in the right way. And so everything that we at Microsoft are doing around interoperability, around security, around identity management, differential privacy, all of the work that came out of Microsoft Research in confidential computing…

Host: Yeah.

Peter Lee: …all of those things are likely to be part of this future. As important as confidential computing has been as a product of Microsoft Research, it’s going to be way, way more important in this healthcare future. And so it’s really up to us to make sure that regulators and lawmakers and clinicians are aware and smart about these things. And we can provide that technical guidance.

Host: What about the other companies that you mentioned? I mean, you’re not in this alone and it’s not just companies, it’s nations, and, I dare say, rogue actors, that are skilled in this arena. How do you get, sort of, agreement and compliance?

Peter Lee: I would say that Microsoft is in a good position because it has a clear business model. If someone is asking us, well what are you going to with our data? We have a very clear business model that says that we don’t monetize on your data.

Host: Right.

Peter Lee: But everyone is going to have to figure that out. Also, when you are getting into a new area like healthcare, every tech company is a big, complicated place with lots of stakeholders, lots of competing internal interests, lots of politics.

Host: Right.

Peter Lee: And so Microsoft, I think, is in a very good position that way too. We’re all operating as one Microsoft. But it’s so important that we all find ways to work together. One point of contact has been engineered by the White House in something called the Blue Button Developers Conference. So that’s where I’m literally holding hands with my counterparts at Google, at Salesforce, at Amazon, at IBM, making certain pledges there. And so the convening power of governments is pretty powerful.

Host: It’s story time. We’ve talked a little about your academic and professional life. Give us a short personal history. Where did it all start for Peter Lee and how did he end up where he is today?

Peter Lee: Oh, my.

Host: Has to be short.

Peter Lee: Well, let’s see, so uh, I’m Korean by heritage. I was born in Ohio, but Korean by heritage and my parents immigrated from Korea. My dad was a physics professor. He’s long retired now and my mother a chemistry professor.

Host: Wow.

Peter Lee: And she passed away some years ago. But I guess as an Asian kid growing up in a physical science household, I was destined to become a scientist myself. And in fact, they never said it out loud, but I think it was a disappointment to them when I went to college to study math! And then maybe an even the bigger disappointment when I went from math to computer science in grad school. Of course they’re very proud of me now.

Host: Of course! Where’d you go to school?

Peter Lee: I went to the University of Michigan. I was there as an undergrad and then I was planning to go work after that. I actually interviewed at a little, tiny company in the Pacific Northwest called Microsoft…

Host: Back then!

Peter Lee: … and …but I was wooed by my senior research advisor at Michigan to stay on for my PhD and so I stayed and then went from grad school right to Carnegie Mellon University as a professor.

Host: And then worked your way up to leading the department…

Peter Lee: Yeah. So I was there for twenty four years. They were wonderful years. Carnegie Mellon University is just a wonderful, wonderful place. And um..

Host: It’s almost like there’s a pipeline from Microsoft Research to Carnegie Mellon. Everyone is CMU this, CMU that!

Peter Lee: Well, I remember, as an assistant professor, when Rick Rashid came to my office to tell me that he was leaving to start this thing called Microsoft Research and I was really sad and shocked by that. Now here I am!

Host: Right. Well, tell us, um, if you can, one interesting thing about you that people might not know.

Peter Lee: I don’t know if people know this or not, but I have always had an interest in cars, in fast cars. I spent some time, when I was young, racing in something called shifter karts and then later in open wheel Formula Ford, and then, when I got my first real job at Carnegie Mellon, I had enough money that I spent quite a bit of it trying to get a sponsored ride with a semi-pro team. I never managed to make it. It’s hard to kind of split being an assistant professor and trying to follow that passion. You know, I don’t do that too much anymore. Once you are married and have a child, the annoyance factor gets a little high, but it’s something that I still really love and there’s a community of people, of course, at a place like Microsoft, that’s really passionate about cars as well.

Host: As we close, Peter, I’d like you to leave our listeners with some parting advice. Many of them are computer science people who may want to apply their skills in the world of healthcare, but are not sure how to get there from here. Where, in the vast sea of technology and healthcare research possibilities, should emerging researchers set their sights and where should they begin their swim?

Peter Lee: You know, I think it’s all about data and how to make something good out of data. And today, especially, you know, we are in that big sea of data silos. Every one of them has different formats, different rules, most of them don’t have modern APIs. And so things that can help evolve that system to a true ocean of data, I think anything to that extent will be great. And it is not just tinkering around with interfaces. It’s actually AI. To, say, normalize the schemas of two different data sets, intelligently, is something that we will need to do using the, kind of, latest machine learning, latest program synthesis, the kind of, latest data science techniques that we have on offer.

Host: Who do you want on your team in the coming years?

Peter Lee: The thing that I think I find so exciting about great researchers today is their intellectual flexibility to start looking at an idea and getting more and more depth of understanding, but then evolve as a person to understanding, you know, what is the value of this in the world, and understanding that that is a competitive world. And so, how willing are you to compete in that competitive marketplace to make the best stuff? And that evolution that we are seeing over and over again with people out of Microsoft Research is just incredibly exciting. When you see someone like a Galen Hunt or a Doug Burger or a Lili Cheng come out of Microsoft Research and then evolve into these world leaders in their respective fields, not just in research, but spanning research to really competing in a highly competitive marketplace, that is the future.

Host: Peter Lee, thank you for joining us on the podcast today. It’s been an absolute delight.

Peter Lee: Thank you for having me. It’s been fun.

(music plays)

To learn more about Dr. Peter Lee and how Microsoft is working to empower healthcare professionals around the world, visit Microsoft.com/research

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Author: Microsoft News Center

How to Use ASR and Hyper-V Replica with Failover Clusters

In the third and final post of this blog series, we will evaluate Microsoft’s replication solutions for multi-site clusters and how to integrate basic backup/DR with them. This includes Hyper-V Replica, Azure Site Recovery, and DFS Replication. In the first part of the series, you learned about setting up failover clusters to work with DR solutions and in the last post, you learned about disk replication considerations from third-party storage vendors. The challenge with the solutions that we previously discussed is that they typically require third-party hardware or software. Let’s look at the basic technologies provided by Microsoft to reduce these upfront fixed costs.

Note: The features talked about in this article are native Microsoft features with a baseline level of functionality. Should you require over and above what is required here you should look at a third-party backup/replication product such as Altaro VM Backup.

Multi-Site Disaster Recovery with Windows Server DFS Replication (DFSR)

DFS Replication (DFSR) is a Windows Server role service that has been around for many releases. Although DFSR is built into Windows Server and is easy to configure, it is not supported for multi-site clustering. This is because the replication of files only happens when a file is closed, so it works great for file servers hosting documents. However, it is not designed to work with application workloads where the file is kept open, such as SQL databases or Hyper-V VMs. Since these file types will only close during a planned failover or unplanned crash, it is hard to keep the data consistent at both sites. This means that if your first site crashes, the data will not be available at the second site, so DFSR should not be considered as a possible solution.

Multi-Site Disaster Recovery with Hyper-V Replica

The most popular Microsoft DR solution is Hyper-V Replica which is a built-in Hyper-V feature and available to Windows Server customers at no additional cost. It copies the virtual hard disk (VHD) file of a running virtual machine from one host to a second host in a different location. This is an excellent low-cost solution to replicate your data between your primary and secondary sites and even allows you to do extended (“chained”) replication to a third location. However, it is limited in that is only replicates Hyper-V virtual machines (VMs) so it cannot be used for any other application unless they are virtualized and running inside a VM. The way it works is that any changes to the VHD file are tracked by a log file, which is copied to an offline VM/VHD in the secondary site. This also means that replication is also asynchronous, allowing copies to be sent every 30 seconds, 5 minutes or 15 minutes. While this means that there is no distance limitation between the sites, there could be some data loss if any in-memory data has not been written to the disk or if there is a crash between replication cycles.

Two Clusters Replicate Data between Sites with Hyper-V Replica

Figure 1 – Two Clusters Replicate Data between Sites with Hyper-V Replica

Hyper-V Replica allows for replication between standalone Hyper-V hosts or between separate clusters, or any combination.  This means that instead of stretching a single cluster across two sites, you will set up two independent clusters. This also allows for a more affordable solution by letting businesses set up a cluster in their primary site and a single host in their secondary site that will be used only for mission-critical applications. If the Hyper-V Replica is deployed on a failover cluster, a new clustered workload type is created, known as the Hyper-V Replica Broker. This basically makes the replication service highly-available, so that if a node crashes, the replication engine will failover to a different node and continue to copy logs to the secondary site, providing greater resiliency.

Another powerful feature of Hyper-V Replica is its built-in testing, allowing you to simulate both planned and unplanned failures to the secondary site.  While this solution will meet the needs of most virtualized datacenters, it is also important to remember that there are no integrity checks in the data which is being copied between the VMs. This means that if a VM becomes corrupted or is infected with a virus, that same fault will be sent to its replica. For this reason, backups of the virtual machine are still a critical part of standard operating procedure. Additionally, this Altaro blog notes that Hyper-V Replica has other limitations compared to backups when it comes to retention, file space management, keeping separate copies, using multiple storage locations, replication frequency and may have a higher total cost of ownership. If you are using a multi-site DR solution which uses two clusters, then make sure that you are taking and storing backups in both sites, so that you can recover your data at either location. Also make sure that your backup provider supports clusters, CSV disks, and Hyper-V replica, however, this is now standard in the industry.

Multi-Site Disaster Recovery with Azure Site Recovery (ASR)

All of the aforementioned solutions require you to have a second datacenter, which simply is not possible for some businesses.  While you could rent rack space from a cohosting facility, the economics just may not make sense. Fortunately, the Microsoft Azure public cloud can now be used as your disaster recovery site using Azure Site Recovery (ASR). This technology works with Hyper-V Replica, but instead of copying your VMs to a secondary site, you are pushing them to a nearby Microsoft datacenter. This technology still has the same limitations of Hyper-V Replica, including the replication frequency, and furthermore you do not have access to the physical infrastructure of your DR site in Azure. The replicated VM can run on the native Azure infrastructure, or you can even build a virtualized guest cluster, and replicate to this highly-available infrastructure.

While ASR is a significantly cheaper solution than maintaining your own hardware in the secondary site, it is not free. You have to pay for the service, the storage of your virtual hard disks (VHDs) in the cloud, and if you turn on any of those VMs, you will pay for standard Azure VM operating costs.

If you are using ASR, you should follow the same backup best practices as mentioned in the earlier Hyper-V Replica section. The main difference will be that you should use an Azure-native backup solution to protect your replicated VHDs in Azure, in case you switch over the Azure VMs for any extended period of time.

Conclusion

From reviewing this blog series, you should be equipped to make the right decisions when planning your disaster recovery solution using multi-site clustering.  Start by understanding your site restrictions and from there you can plan your hardware needs and storage replication solution.  There are a variety of options that have tradeoffs between a higher price with more features to cost-effective solutions using Microsoft Azure, but have limited control. Even after you have deployed this resilient infrastructure, keep in mind that there are still three main reasons why disaster recovery plans fail:

  • The detection of the outage failed, so the failover to the secondary datacenter never happens.
  • One component in the DR failover process does not work, which is usually due to poor or infrequent testing.
  • There was no automation or some dependency on humans during the process, which failed as humans create a bottleneck and are unreliable during a disaster.

This means that whichever solution you choose, make sure that it is well tested with quick failure detection and try to eliminate all dependencies on humans! Good luck with your deployment and please post any questions that you have in the comments section of this blog.


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Author: Symon Perriman

Clumio extends support to AWS EBS with $135M funding bump

Clumio plans to use its $135M Series C funding to expand its data protection scope.

The backup-as-a-service startup came out of stealth in August with protection for VMware on premises, VMware Cloud on AWS and native AWS services. Clumio this week disclosed its latest funding round. Clumio’s Series A and B rounds raised $11M and $40M, respectively, so the latest $135M injection marks a substantial funding boost for the company. Sutter Hill Ventures and Altimeter Capital led the new funding round.

Clumio CEO Poojan Kumar said the data protection vendor will build out its services platform eventually to cover every data source, starting with Amazon Elastic Block Store (EBS). The Amazon EBS support was rolled out in beta this week, and Clumio is working on support for Microsoft Azure and Google Cloud Platform.

Clumio’s Amazon EBS support is expected to become generally available before the end of 2019.

Clumio’s mission statement is to do with backup what Salesforce has done with customer relationship management (CRM) by delivering backup as a service entirely through the cloud. All processes involved with backup such as deduplication, access management, encryption, backup scheduling and resource allotment would be handled through the service.

Kumar said as customers’ infrastructures expand beyond their data centers, keeping their data protected has grown more complicated. Clumio is targeting customers who don’t want to devote IT resources to keeping up with that complexity.

“Customers are saying, ‘I want to stop the business of doing this myself,'” Kumar said.

Kumar said this is especially true with cloud-native data. He said customers have told him that data generated from a cloud application shouldn’t then be replicated to a data center in order to back it up. He said most customers want to lower or remove their data center footprint.

screenshot of Clumio EBS backup
Clumio now protects AWS EBS data in addition to VMware Cloud on AWS.

Investor interest in backup

This has been a banner year for funding for backup vendors, with four vendors alone pulling in more than $1 billion. Veeam received $500 million and Rubrik pulled in $261M in January, and Druva rose $130M in June.  

Christophe Bertrand, senior analyst at IT analysis firm Enterprise Strategy Group, said Clumio nearly tripled its previous funding, although it competes in a crowded backup market, because of its “born-in-the-cloud-ness.” Cloud-native service offerings, subscription pricing and the lack of on-premises investment are all seen as the direction of where backup is currently headed, so investors are buying in now.

“Investors are looking at this as where the market is going,” Bertrand said. “Winning Best of Show at VMworld probably helped, too.”

Bertrand was quick to note that Clumio faces a tough competitive field, however.  Druva and Carbonite — now  part of OpenText — have provided cloud-based backup for years, and long-time backup vendor Commvault added its Metallic SaaS backup service in October. Most of the other large backup vendors can also protect data in the cloud.

Bertrand expects Clumio to invest in extending its geographical reach and bolstering its partner ecosystem. As for product development, he expects Clumio to support more applications, hypervisors besides VMware vSphere and even use cases beyond backup.

Kumar said the Clumio roadmap calls for adding features such as security, container support, customer access keys and bandwidth throttling. He said Clumio will also develop support for new workloads, expand its channel strategy and add to its engineering team.

“They have to do these things quickly to gain traction,” Bertrand said. “It’s going to become a very contested space.”

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Addressing the coming IoT talent shortage – Microsoft Industry Blogs

This blog is the third in a series highlighting our newest research, IoT Signals. Each week will feature a new top-of-mind topic to provide insights into the current state of IoT adoption across industries, how business leaders can develop their own IoT strategies, and why companies should use IoT to improve service to partners and customers.

As companies survey the possibilities of the Internet of Things (IoT), one of the challenges they face is a significant growing talent shortage. Recent research from Microsoft, IoT Signals, drills down into senior leaders’ concerns and plans. Microsoft surveyed 3,000 decision-makers at companies across China, France, Germany, Japan, the United States, and the United Kingdom who are involved in IoT.

Exploring IoT skills needs at enterprises today

Most IoT challenges today relate to staffing and skills. Our research finds that only 33 percent of companies adopting IoT say they have enough workers and resources, 32 percent lack enough workers and resources, and 35 percent reported mixed results or didn’t know their resourcing issues. Worldwide, talent shortages are most acute in the United States (37 percent) and China (35 percent).

Of the top challenges that impede the 32 percent of companies struggling with IoT skills shortages, respondents cited a lack of knowledge (40 percent), technical challenges (39 percent), lack of budget (38 percent), an inability to find the right solutions (28 percent), and security (19 percent).

a close up of a logo graph of tech assessment

a close up of a logo graph of tech assessment

Companies will need to decide which capabilities they should buy, in the form of hiring new talent; build, in the form of developing staff competencies; or outsource, in the form of developing strategic partnerships. For example, most companies evaluating the IoT space aren’t software development or con­nectivity experts and will likely turn to partners for these services.

Adequate resourcing is a game-changer for IoT companies

Our research found that having the right team and talent was critical to IoT success on a number of measures. First, those with sufficient resources were more likely to say that IoT was very critical to their company’s future success: 51 percent versus 39 percent. Hardship created more ambivalence, with only 41 percent of IoT high performers saying IoT was somewhat critical to future success, whereas 48 percent of lower-performing companies agreed.

Similarly, companies with strong IoT teams viewed IoT as a more successful investment, attributing 28 percent of current ROI to IoT (inclusive of cost savings and efficiencies) versus 20 percent at less enabled companies. That’s likely why 89 percent of those who have the right team is planning to use IoT more in the future versus 75 percent of those who lack adequate resources.

IoT talent shortage may cause higher failure rate

Getting IoT off the ground can be a challenge for any company, given its high learning curve, long-term commitment, and significant investment. It’s doubly so for companies that lack talent and resources. IoT Signals found that companies who lack adequate talent and resources have a higher failure rate in the proof of concept phase: 30 percent versus 25 percent for those with the right team. At companies with high IoT success, the initiative is led by a staffer in an IT role, such as a director of IT, a chief technology officer, or a chief information officer. With leadership support, a defined structure, and budget, these all-in IoT organizations are able to reach the production stage on an average of nine months, while those who lack skilled workers and resources take 12 months on average.

Despite initial challenges, company leaders are unlikely to call it quits. Business and technology executives realize that IoT is a strategic business imperative and will be increasingly required to compete in the marketplace. Setting up the right team, tools, and resources now can help prevent team frustration, business burnout, and leadership commitment issues.

Overcoming the skills issues with simpler platforms

Fortunately, industry trends like fully hosted SaaS platforms are reducing the complexity of building IoT programs: from connecting and managing devices to providing integrated tooling and security, to enabling analytics.

Azure IoT Central, a fully managed IoT platform, is designed to let anyone build an IoT initiative within hours, empowering business teams and other non-technical individuals to easily gain mastery and contribute. Azure includes IoT Plug and Play, which provides an open modeling language to connect IoT devices to the cloud seamlessly.

Additionally, Microsoft is working with its partner ecosystem to create industry-specific solutions to help companies overcome core IoT adoption blockers and investing in training tools like IoT School and AI Business School. Microsoft has one of the largest and fastest-growing partner ecosystems. Our more than 10,000 IoT partners provide domain expertise across industries and help address connectivity, security infrastructure, and application infrastructure requirements, allowing companies to drive to value faster. 

Learn more about how global companies are using IoT to drive value by downloading the IoT Signals report and reading our Transform Blog on IoT projects companies such as ThyssenKrupp, Bühler, Chevron, and Toyota Material Handling Group are driving.

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Author: Microsoft News Center

Equip Yourself for Battle with the Xbox Wireless Controller – Midnight Forces II Special Edition – Xbox Wire

In 2014, we introduced the fan-favorite military-inspired Forces series for the Xbox Wireless Controller. Today, we’re introducing a new take on one of the most popular designs from the series – the new Xbox Wireless Controller – Midnight Forces II Special Edition. The Xbox Wireless Controller – Midnight Forces II Special Edition features the modern blue camouflage-pattern you love plus textured grip to help you stay on target in the heat of the battle and a 3.5mm stereo headset jack to plug in for a fully immersive gaming experience. Like all Xbox Wireless Controllers, the Xbox Wireless Controller – Midnight Forces II Special Edition comes with Bluetooth technology for gaming on Windows 10 devices or Samsung Gear VR and custom button mapping through the Xbox Accessories app to customize your controller just the way you like it.

Make your camo-inspired gaming set complete with the officially licensed Midnight Forces II Special Edition Xbox Pro Charging Stand by Controller Gear. This charging stand is built with the same high-quality materials as Xbox Wireless Controllers so it’s always an exact match, while the magnetic contact system ensures a perfect fit and secure charge every time. Each Xbox Pro Charging Stand comes with a premium charging stand, battery cover, rechargeable battery and 6-foot power cord.

The Midnight Forces II Special Edition Xbox Pro Charging Stand and the Xbox Wireless Controller – Midnight Forces II Special Edition are available today at Microsoft Store in the U.S., Canada and Mexico. The controller is also available online through Wal-Mart in U.S. and Canada starting today and coming to their physical stores beginning mid-October.

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Author: Microsoft News Center

Tune-In Tomorrow to the ELEAGUE Gears Summer Series: The Bonds and Betrayals of Brotherhood Finale – Xbox Wire

Tomorrow night, ELEAGUE Gears Summer Series: The Bonds and Betrayals of Brotherhood concludes on TBS with the sixth and final episode of the docu series focused on the stories and players behind the world of Gears Esports. If you’d like to catch up with the entire series of The Bonds and Betrayals of Brotherhood ahead of the finale, you can watch all five aired episodes through VOD on the Gears Esports website.

Stemming from Xbox’s partnership with ELEAGUE, the six-part docu series focused on the stories and players behind the world of Gears Esports on TBS, the ELEAGUE Gears Summer Invitational was held three weeks ago, crowning Tox Gaming as the inaugural champions of the first Gears 5 esports event. In addition to a thrilling weekend of competition, we announced the first details of the Gears Esports 2019-2020 season, including a partnership with PGL to create a new Pro League.

To continue the Gears Esports journey, be sure to tune-in to the sixth and final episode of The Bonds & Betrayals of Brotherhood airing on TBS tomorrow, Friday, August 2, at 11 pm ET/8 pm PT. The docu series will continue to explore each player’s intense connection to the game and each other as they navigate to become the best players in the world on Gears 5 Esports.

Episode 6 of The Bonds & Betrayals of Brotherhood highlights pro player Justin “Kenny” Kenny’s career in Gears Esports – spanning across numerous titles, teams, and organizations over the years. Kenny reflects upon how the Gears Esports scene has both itself grown and allowed him to grow along with it.

The final episode also provides an exclusive behind-the-scenes look at the recent ELEAGUE Gears 5 Invitational event and allows each of the six featured series pro players to reflect upon on their performance competing in the unreleased title. Through the eyes of these players, viewers will get the chance to experience the Gears 5 esports mode, Escalation, and prepare for the upcoming Gears 5 Esports season.

To stay updated, follow @EsportsGears on Twitter and visit Gears.gg. Be sure to also check out ELEAGUE’s channels; @ELEAGUETV and www.ELEAGUE.com.

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Author: Microsoft News Center

Mini XL+, Mini E added to iXsystems FreeNAS Mini series

Open source hardware provider iXsystems introduced two new models to its FreeNAS Mini series storage system lineup: FreeNAS Mini XL+ and FreeNAS Mini E. The vendor also introduced tighter integration with TrueNAS and cloud services.

Designed for small offices, iXsystems’ FreeNAS Mini series models are compact, low-power and quiet. Joining the FreeNAS Mini and Mini XL, the FreeNAS Mini XL+ is intended for professional workgroups, while the FreeNAS Mini E is a low-cost option for small home offices.

The FreeNAS Mini XL+ is a 10-bay platform — eight 3.5-inch and one 2.5-inch hot-swappable bays and one 2.5-inch internal bay — and iXsystem’s highest-end Mini model. The Mini XL+ provides dual 10 Gigabit Ethernet (GbE) ports, eight CPU cores and 32 GB RAM for high-performance workloads. For demanding applications, such as hosting virtual machines or multimedia editing, the Mini XL+ scales beyond 100 TB.

For lower-intensity workloads, the FreeNAS Mini E is ideal for file sharing, streaming and transcoding video up to 1080p. The FreeNAS Mini E features four bays with quad GbE ports and 8 GB RAM, configured with 8 TB capacity.

The full iXsystems FreeNAS Mini series supports error correction RAM and Z File System with data checksumming, unlimited snapshots and replication. IT operations can remotely manage systems via Intelligent Platform Management Interface and, dependent on needs, can be built has hybrid or all-flash storage.

FreeNAS provides traditional NAS and delivers network application services via plugin applications, featuring both open source and commercial applications to extend usability to entertainment, collaboration, security and backup. IXsystems’ FreeNAS 11.2 provides a web interface and encrypted cloud sync to major cloud services, such as Amazon S3, Microsoft Azure, Google Drive and Backblaze B2.

At Gartner’s 2018 IT Infrastructure, Operations & Cloud Strategies Conference, ubiquity of IT infrastructure was a main theme, and FreeNAS was named an option for file, block, object and hyper-converged software-defined storage. According to iXsystems, FreeNAS and TrueNAS are leading platforms for video, telemetry and other data processing in the cloud or a colocation facility.

New FreeNAS Mini models were introduced to iXsystems' lineup for open source storage.
IXsystems’ FreeNAS Mini lineup now includes the high-end FreeNAS Mini XL+ and entry-level FreeNAS Mini E.

With the upgrade, the FreeNAS Mini series can be managed by iXsystems’ unified management system, TrueCommand, which enables admins to monitor all TrueNAS and FreeNAS systems from a single UI and share access to alerts, reports and control of storage systems. A TrueCommand license is free for FreeNAS deployments of fewer than 50 drives.

According to iXsystems, FreeNAS Mini products reduce TCO by combining enterprise-class data management and open source economics. The FreeNAS Mini XL+ ranges from $1,499 to $4,299 and the FreeNAS Mini E from $749 to $999.

FreeNAS version 11.3 is available in beta, and the vendor anticipates a 12.0 release that will bring more efficiency to its line of FreeNAS Minis.

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How government is transforming with AI – part 3

In our last two blogs in this series, we discussed how governments are using digital assistants—often with cognitive services such as language translation built in—to engage their community in more accessible ways and support their teams.

Another way that governments are using emerging technologies such as artificial intelligence (AI) and the Internet of Things (IoT) is to help them predict needs and anticipate issues so they can prepare accordingly.

For example, to keep Alaska’s highways open and safe during severe winter weather, the Alaska Department of Transportation and Public Facilities uses the Fathym WeatherCloud solution and Microsoft Azure IoT technologies to make better, hyper-local decisions about deploying road crews. Being able to make more informed decisions with better data is helping Alaska save lives and significantly reduce road maintenance costs.

“The information we get from WeatherCloud puts us miles ahead in creating accurate forecasts,” says Daniel Schacher, Maintenance Superintendent at the Alaska Department of Transportation and Public Facilities, in this article. “We’ve become much more proactive in our responses.”

Read How Alaska outsmarts Mother Nature in the cloud” to learn about what led Alaska to deploy the system, how it works, and the way it’s helping the state keep residents safer and save hundreds of thousands of dollars each year in resource usage.

Another example of keeping vital infrastructures up and running with insight from AI and IoT solutions comes from our partner eSmart Systems. With its Connected Drone portfolio, utilities can send smart drones out on beyond-line-of-sight missions to inspect power lines and pinpoint faults and weaknesses.

Utilities are using Connected Drones to stay ahead of power grid maintenance issues and help them prevent or reduce blackouts in the communities they serve. And by using drones to inspect lines, which can be dangerous for personnel, they can keep their teams safer.

Utilities are also using Connected Drones to get power back up and running after a disaster, as was the case in Florida after Hurricane Irma. Watch this video to see how the drones helped to assess the damage quickly—inspecting hazardous areas so human inspectors wouldn’t have to be put in harm’s way. With insight from the Connected Drones, the utility company was able to know not only precisely where repairs were required, but also which crew and equipment were needed to get power restored as quickly as possible in the affected communities.

Those are just a few examples of how governments can gain insight with AI and IoT that can help them keep the infrastructures their citizens rely on up and running. To learn about more vertical and horizontal areas where your government agency can benefit from AI, read the Gartner report: “Where you should use artificial intelligence—and why.” It provides research on the potential of various use cases and offers recommendations on the most effective strategies for applying AI.

For Sale – i3 4160 3.6ghz ; 8gb HyperX fury DDR3

Memory details: Kingston Fury Hyper X Black Series 8 GB PC3-12800 (DDR3-1600) HX316C10FB/8
cpu details: Intel Core i3-4160 4160 Haswell Processor 3.6GHz 5.0GT/s 3MB LGA 1150 CPU

Both working perfectly.

£38 each including postage

Price and currency: 38 each
Delivery: Delivery cost is included within my country
Payment method: ppal preferred
Location: stevenage
Advertised elsewhere?: Not advertised elsewhere
Prefer goods collected?: I have no preference

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DO NOT proceed with a deal until you are completely satisfied with all details being correct. It’s in your best interest to check out these details yourself.

For Sale – i3 4160 3.6ghz ; 8gb HyperX fury DDR3

Memory details: Kingston Fury Hyper X Black Series 8 GB PC3-12800 (DDR3-1600) HX316C10FB/8
cpu details: Intel Core i3-4160 4160 Haswell Processor 3.6GHz 5.0GT/s 3MB LGA 1150 CPU

Both working perfectly.

£38 each including postage

Price and currency: 38 each
Delivery: Delivery cost is included within my country
Payment method: ppal preferred
Location: stevenage
Advertised elsewhere?: Not advertised elsewhere
Prefer goods collected?: I have no preference

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Please be advised, all buyers and sellers should satisfy themselves that the other party is genuine by providing the following via private conversation to each other after negotiations are complete and prior to dispatching goods and making payment:

  • Landline telephone number. Make a call to check out the area code and number are correct, too
  • Name and address including postcode
  • Valid e-mail address

DO NOT proceed with a deal until you are completely satisfied with all details being correct. It’s in your best interest to check out these details yourself.