(soft music) >> Hello, fellow hardware nerds and welcome back to Dallas Texas where we're reporting live from Supercomputing 2022. My name is Savannah Peterson, joined with the John Furrier on my left. >> Looking good today. >> Thank you, John, so are you. It's been a great show so far. >> We've had more hosts, more guests coming than ever before. >> I know. >> Amazing, super- >> We've got a whole thing going on. >> It's been a super computing performance. >> It, wow. And, we'll see how many times we can say super on this segment. Speaking of super things, I am in a very unique position right now. I am a flanked on both sides by people who have been doing content on theCUBE for 12 years. Yes, you heard me right, our next guest was on theCUBE 12 years ago, the third event, was that right, John? >> Man: First ever VM World. >> Yeah, the first ever VM World, third event theCUBE ever did. We are about to have a lot of fun. Please join me in welcoming Justin Emerson of Pure Storage. Justin, welcome back. >> It's a pleasure to be here. It's been too long, you never call, you don't write. (Savannah laughs) >> Great to see you. >> Yeah, likewise. >> How fun is this? Has the set evolved? Is everything looking good? >> I mean, I can barely remember what happened last week, so. (everyone laughs) >> Well, I remember lot's changed that VM world. You know, Paul Moritz was the CEO if you remember at that time. His actual vision actually happened but not the way, for VMware, but the industry, the cloud, he called the software mainframe. We were kind of riffing- >> It was quite the decade. >> Unbelievable where we are now, how we got here, but not where we're going to be. And you're with Pure Storage now which we've been, as you know, covering as well. Where's the connection into the supercomputing? Obviously storage performance, big part of this show. >> Right, right. >> What's the take? >> Well, I think, first of all it's great to be back at events in person. We were talking before we went on, and it's been so great to be back at live events now. It's been such a drought over the last several years, but yeah, yeah. So I'm very glad that we're doing in person events again. For Pure, this is an incredibly important show. You know, the product that I work with, with FlashBlade is you know, one of our key areas is specifically in this high performance computing, AI machine learning kind of space. And so we're really glad to be here. We've met a lot of customers, met a lot of other folks, had a lot of really great conversations. So it's been a really great show for me. And also just seeing all the really amazing stuff that's around here, I mean, if you want to find, you know, see what all the most cutting edge data center stuff that's going to be coming down the pipe, this is the place to do it. >> So one of the big themes of the show for us and probably, well, big theme of your life, is balancing power efficiency. You have a product in this category, Direct Flash. Can you tell us a little bit more about that? >> Yeah, so Pure as a storage company, right, what do we do differently from everybody else? And if I had to pick one thing, right, I would talk about, it's, you know, as the name implies, we're an all, we're purely flash, we're an all flash company. We've always been, don't plan to be anything else. And part of that innovation with Direct Flash is the idea of rather than treating a solid state disc as like a hard drive, right? Treat it as it actually is, treat it like who it really is and that's a very different kind of thing. And so Direct Flash is all about bringing native Flash interfaces to our product portfolio. And what's really exciting for me as a FlashBlade person, is now that's also part of our FlashBlade S portfolio, which just launched in June. And so the benefits of that are our myriad. But, you know, talking about efficiency, the biggest difference is that, you know, we can use like 90% less DRAM in our drives, which you know, everything uses, everything that you put in a drive uses power, it adds cost and all those things and so that really gives us an efficiency edge over everybody else and at a show like this, where, I mean, you walk the aisles and there's there's people doing liquid cooling and so much immersion stuff, and the reason they're doing that is because power is just increasing everywhere, right? So if you can figure out how do we use less power in some areas means you can shift that budget to other places. So if you can talk to a customer and say, well, if I could shrink your power budget for storage by two thirds or even, save you two-thirds of power, how many more accelerators, how many more CPUs, how much more work could you actually get done? So really exciting. >> I mean, less power consumption, more power and compute. >> Right. >> Kind of power center. So talk about the AI implications, where the use cases are. What are you seeing here? A lot of simulations, a lot of students, again, dorm room to the boardroom we've been saying here on theCUBE this is a great broad area, where's the action in the ML and the AI for you guys? >> So I think, not necessarily storage related but I think that right now there's this enormous explosion of custom silicon around AI machine learning which I as a, you said welcome hardware nerds at the beginning and I was like, ah, my people. >> We're all here, we're all here in Dallas. >> So wonderful. You know, as a hardware nerd we're talking about conferences, right? Who has ever attended hot chips and there's so much really amazing engineering work going on in the silicon space. It's probably the most exciting time for, CPU and accelerator, just innovation in, since the days before X 86 was the defacto standard, right? And you could go out and buy a different workstation with 16 different ISAs. That's really the most exciting thing, I walked past so many different places where you know, our booth is right next to Havana Labs with their gout accelerator, and they're doing this cute thing with one of the AI image generators in their booth, which is really cute. >> Woman: We're going to have to go check that out. >> Yeah, but that to me is like one of the more exciting things around like innovation at a, especially at a show like this where it's all about how do we move forward, the state of the art. >> What's different now than just a few years ago in terms of what's opening up the creativity for people to look at things that they could do with some of the scale that's different now. >> Yeah well, I mean, every time the state of the art moves forward what it means is, is that the entry level gets better, right? So if the high end is going faster, that means that the mid-range is going faster, and that means the entry level is going faster. So every time it pushes the boundary forward, it's a rising tide that floats all boats. And so now, the kind of stuff that's possible to do, if you're a student in a dorm room or if you're an enterprise, the world, the possible just keeps expanding dramatically and expanding almost, you know, geometrically like the amount of data that we are, that we have, as a storage guy, I was coming back to data but the amount of data that we have and the amount of of compute that we have, and it's not just about the raw compute, but also the advances in all sorts of other things in terms of algorithms and transfer learning and all these other things. There's so much amazing work going on in this area and it's just kind of this Kay Green explosion of innovation in the area. >> I love that you touched on the user experience for the community, no matter the level that you're at. >> Yeah. >> And I, it's been something that's come up a lot here. Everyone wants to do more faster, always, but it's not just that, it's about making the experience and the point of entry into this industry more approachable and digestible for folks who may not be familiar, I mean we have every end of the ecosystem here, on the show floor, where does Pure Storage sit in the whole game? >> Right, so as a storage company, right? What AI is all about deriving insights from data, right? And so everyone remembers that magazine cover data's the new oil, right? And it's kind of like, okay, so what do you do with it? Well, how do you derive value from all of that data? And AI machine learning and all of this supercomputing stuff is about how do we take all this data? How do we innovate with it? And so if you want data to innovate with, you need storage. And so, you know, our philosophy is that how do we make the best storage platforms that we can using the best technology for our customers that enable them to do really amazing things with AI machine learning and we've got different products, but, you know at the show here, what we're specifically showing off is our new flashlight S product, which, you know, I know we've had Pure folks on theCUBE before talking about FlashBlade, but for viewers out there, FlashBlade is our our scale out unstructured data platform and AI and machine learning and supercomputing is all about unstructured data. It's about sensor data, it's about imaging, it's about, you know, photogrammetry, all this other kinds of amazing stuff. But, you got to land all that somewhere. You got to process that all somewhere. And so really high performance, high throughput, highly scalable storage solutions are really essential. It's an enabler for all of the amazing other kinds of engineering work that goes on at a place like Supercomputing. >> It's interesting you mentioned data's oil. Remember in 2010, that year, our first year of theCUBE, Hadoop World, Hadoop just started to come on the scene, which became, you know kind of went away and, but now you got, Spark and Databricks and Snowflake- >> Justin: And it didn't go away, it just changed, right? >> It just got refactored and right size, I think for what the people wanted it to be easy to use but there's more data coming. How is data driving innovation as you bring, as people see clearly the more data's coming? How is data driving innovation as you guys look at your products, your roadmap and your customer base? How is data driving innovation for your customers? >> Well, I think every customer who has been, you know collecting all of this data, right? Is trying to figure out, now what do I do with it? And a lot of times people collect data and then it will end up on, you know, lower slower tiers and then suddenly they want to do something with it. And it's like, well now what do I do, right? And so there's all these people that are reevaluating you know, we, when we developed FlashBlade we sort of made this bet that unstructured data was going to become the new tier one data. It used to be that we thought unstructured data, it was emails and home directories and all that stuff the kind of stuff that you didn't really need a really good DR plan on. It's like, ah, we could, now of course, as soon as email goes down, you realize how important email is. But, the perspectives that people had on- >> Yeah, exactly. (all laughing) >> The perspectives that people had on unstructured data and it's value to the business was very different and so now- >> Good bet, by the way. >> Yeah, thank you. So now unstructured data is considered, you know, where companies are going to derive their value from. So it's whether they use the data that they have to build better products whether it's they use the data they have to develop you know, improvements in processes. All those kinds of things are data driven. And so all of the new big advancements in industry and in business are all about how do I derive insights from data? And so machine learning and AI has something to do with that, but also, you know, it all comes back to having data that's available. And so, we're working very hard on building platforms that customers can use to enable all of this really- >> Yeah, it's interesting, Savannah, you know, the top three areas we're covering for reinventing all the hyperscale events is data. How does it drive innovation and then specialized solutions to make customers lives easier? >> Yeah. >> It's become a big category. How do you compose stuff and then obviously compute, more and more compute and services to make the performance goes. So those seem to be the three hot areas. So, okay, data's the new oil refineries. You've got good solutions. What specialized solutions do you see coming out because once people have all this data, they might have either large scale, maybe some edge use cases. Do you see specialized solutions emerging? I mean, obviously it's got DPU emerging which is great, but like, do you see anything else coming out at that people are- >> Like from a hardware standpoint. >> Or from a customer standpoint, making the customer's lives easier? So, I got a lot of data flowing in. >> Yeah. >> It's never stopping, it keeps powering in. >> Yeah. >> Are there things coming out that makes their life easier? Have you seen anything coming out? >> Yeah, I think where we are as an industry right now with all of this new technology is, we're really in this phase of the standards aren't quite there yet. Everybody is sort of like figuring out what works and what doesn't. You know, there was this big revolution in sort of software development, right? Where moving towards agile development and all that kind of stuff, right? The way people build software change fundamentally this is kind of like another wave like that. I like to tell people that AI and machine learning is just a different way of writing software. What is the output of a training scenario, right? It's a model and a model is just code. And so I think that as all of these different, parts of the business figure out how do we leverage these technologies, what it is, is it's a different way of writing software and it's not necessarily going to replace traditional software development, but it's going to augment it, it's going to let you do other interesting things and so, where are things going? I think we're going to continue to start coalescing around what are the right ways to do things. Right now we talk about, you know, ML Ops and how development and the frameworks and all of this innovation. There's so much innovation, which means that the industry is moving so quickly that it's hard to settle on things like standards and, or at least best practices you know, at the very least. And that the best practices are changing every three months. Are they really best practices right? So I think, right, I think that as we progress and coalesce around kind of what are the right ways to do things that's really going to make customers' lives easier. Because, you know, today, if you're a software developer you know, we build a lot of software at Pure Storage right? And if you have people and developers who are familiar with how the process, how the factory functions, then their skills become portable and it becomes easier to onboard people and AI is still nothing like that right now. It's just so, so fast moving and it's so- >> Wild West kind of. >> It's not standardized. It's not industrialized, right? And so the next big frontier in all of this amazing stuff is how do we industrialize this and really make it easy to implement for organizations? >> Oil refineries, industrial Revolution. I mean, it's on that same trajectory. >> Yeah. >> Yeah, absolutely. >> Or industrial revolution. (John laughs) >> Well, we've talked a lot about the chaos and sort of we are very much at this early stage stepping way back and this can be your personal not Pure Storage opinion if you want. >> Okay. >> What in HPC or AIML I guess it all falls under the same umbrella, has you most excited? >> Ooh. >> So I feel like you're someone who sees a lot of different things. You've got a lot of customers, you're out talking to people. >> I think that there is a lot of advancement in the area of natural language processing and I think that, you know, we're starting to take things just like natural language processing and then turning them into vision processing and all these other, you know, I think the, the most exciting thing for me about AI is that there are a lot of people who are, you are looking to use these kinds of technologies to make technology more inclusive. And so- >> I love it. >> You know the ability for us to do things like automate captioning or the ability to automate descriptive, audio descriptions of video streams or things like that. I think that those are really,, I think they're really great in terms of bringing the benefits of technology to more people in an automated way because the challenge has always been bandwidth of how much a human can do. And because they were so difficult to automate and what AI's really allowing us to do is build systems whether that's text to speech or whether that's translation, or whether that's captioning or all these other things. I think the way that AI interfaces with humans is really the most interesting part. And I think the benefits that it can bring there because there's a lot of talk about all of the things that it does that people don't like or that they, that people are concerned about. But I think it's important to think about all the really great things that maybe don't necessarily personally impact you, but to the person who's not cited or to the person who you know is hearing impaired. You know, that's an enormously valuable thing. And the fact that those are becoming easier to do they're becoming better, the quality is getting better. I think those are really important for everybody. >> I love that you brought that up. I think it's a really important note to close on and you know, there's always the kind of terminator, dark side that we obsess over but that's actually not the truth. I mean, when we think about even just captioning it's a tool we use on theCUBE. It's, you know, we see it on our Instagram stories and everything else that opens the door for so many more people to be able to learn. >> Right? >> And the more we all learn, like you said the water level rises together and everything is magical. Justin, it has been a pleasure to have you on board. Last question, any more bourbon tasting today? >> Not that I'm aware of, but if you want to come by I'm sure we can find something somewhere. (all laughing) >> That's the spirit, that is the spirit of an innovator right there. Justin, thank you so much for joining us from Pure Storage. John Furrier, always a pleasure to interview with you. >> I'm glad I can contribute. >> Hey, hey, that's the understatement of the century. >> It's good to be back. >> Yeah. >> Hopefully I'll see you guys in, I'll see you guys in 2034. >> No. (all laughing) No, you've got the Pure Accelerate conference. We'll be there. >> That's right. >> We'll be there. >> Yeah, we have our Pure Accelerate conference next year and- >> Great. >> Yeah. >> I love that, I mean, feel free to, you know, hype that. That's awesome. >> Great company, great runs, stayed true to the mission from day one, all Flash, continue to innovate congratulations. >> Yep, thank you so much, it's pleasure being here. >> It's a fun ride, you are a joy to talk to and it's clear you're just as excited as we are about hardware, so thanks a lot Justin. >> My pleasure. >> And thank all of you for tuning in to this wonderfully nerdy hardware edition of theCUBE live from Dallas, Texas, where we're at, Supercomputing, my name's Savannah Peterson and I hope you have a wonderful night. (soft music)

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. Welcome back to the Cubes Coverage of 80 Bus Reinvent 2020. This is the Cube virtual. I'm your host, John Ferrier normally were there in person, a lot of great face to face, but not this year with the pandemic. We're doing a lot of remote, and he's got a great great content guest here. Rebecca Weekly, who's the senior director and senior principal engineer at for Intel's hyper scale strategy and execution. Rebecca. Thanks for coming on. A lot of great news going on around Intel on AWS. Thanks for coming on. >>Thanks for having me done. >>So Tell us first, what's your role in Intel? Because obviously compute being reimagined. It's going to the next level, and we're seeing the sea change that with Cove in 19, it's putting a lot of pressure on faster, smaller, cheaper. This is the cadence of Moore's law. This is kind of what we need. More horsepower. This is big theme of the event. What's what's your role in intel? >>Oh, well, my team looks after a joint development for product and service offerings with Intel and A W s. So we've been working with AWS for more than 14 years. Um, various projects collaborations that deliver a steady beat of infrastructure service offerings for cloud applications. So Data Analytics, ai ml high performance computing, Internet of things, you name it. We've had a project or partnership, several in those the main faces on thanks to that relationship. You know, today, customers Committee choose from over 220 different instance types on AWS global footprint. So those feature Intel processors S, P. J s ai accelerators and more, and it's been incredibly rewarding an incredibly rewarding partnership. >>You know, we've been covering Intel since silicon angle in the Cube was formed 10 years ago, and this is what we've been to every reinvent since the first one was kind of a smaller one. Intel's always had a big presence. You've always been a big partner, and we really appreciate the contribution of the industry. Um, you've been there with with Amazon. From the beginning, you've seen it grow. You've seen Amazon Web services become, ah, big important player in the enterprise. What's different this year from your perspective. >>Well, 2020 has been a challenging here for sure. I was deeply moved by the kinds of partnership that we were able to join forces on within telling a W s, uh, to really help those communities across the globe and to address all the different crisis is because it it hasn't just been one. This has been, ah, year of of multiple. Um, sometimes it feels like rolling crisis is So When the pandemic broke out in India in March of this year, there were schools that were forced to close, obviously to slow the spread of the disease. And with very little warning, a bunch of students had to find themselves in remote school out of school. Uh, so the Department of Education in India engaged career launcher, which is a partner program that we also sponsor and partner with, and it really they had to come up with a distance learning solutions very quickly, uh, that, you know, really would provide Children access to quality education while they were remote. For a long as they needed to be so Korean launcher turned to intel and to a W s. We helped design infrastructure solution to meet this challenge and really, you know, within the first, the first week, more than 100 teachers were instructing classes using that online portal, and today it serves more than 165,000 students, and it's going to accommodate more than a million over the fear. Um, to me, that's just a perfect example of how Cove it comes together with technology, Thio rapidly address a major shift in how we're approaching education in the times of the pandemic. Um, we also, you know, saw kind of a climate change set of challenges with the wildfires that occurred this year in 2020. So we worked with a partner, Roman, as well as a partner who is a partner with AWS end until and used the EEC Thio C five instances that have the second Gen Beyond available processors. And we use them to be able to help the Australian researchers who were dealing with that wildfire increase over 60 fold the number of parallel wildfire simulations that they could perform so they could do better forecasting of who needed to leave their homes how they could manage those scenarios. Um, and we also were able toe work with them on a project to actually thwart the extinction of the Tasmanian Devils. Uh, in also in Australia. So again, that was, you know, an HPC application. And basically, by moving that to the AWS cloud and leveraging those e c two instances, we were able to take their analysis time from 10 days to six hours. And that's the kind of thing that makes the cloud amazing, right? We work on technology. We hope that we get thio, empower people through that technology. But when you can deploy that technology a cloud scale and watch the world's solve problems faster, that has made, I would say 2020 unique in the positivity, right? >>Yeah. You don't wanna wish this on anyone, but that's a real upside for societal change. I mean, I love your passion on that. I think this is a super important worth calling out that the cloud and the cloud scale With that kind of compute power and differentiation, you gets faster speed to value not just horsepower, but speed to value. This is really important. And it saved lives that changes lives. You know, this is classic change. The world kind of stuff, and it really is on center stage on full display with Cove. I really appreciate, uh, you making that point? It's awesome. Now with that, I gotta ask you, as the strategist for hyper scale intel, um, this is your wheelhouse. You get the fashion for the cloud. What kind of investments are you making at Intel To make more advancements in the clock? You take a minute, Thio, share your vision and what intel is working on? >>Sure. I mean, obviously were known more for our semiconductor set of investments. But there's so much that we actually do kind of across the cloud innovation landscape, both in standards, open standards and bodies to enable people to work together across solutions across the world. But really, I mean, even with what we do with Intel Capital, right, we're investing. We've invested in a bunch of born in the cloud start up, many of whom are on top of AWS infrastructure. Uh, and I have found that to be a great source of insights, partnerships, you know, again how we can move the needle together, Thio go forward. So, in the space of autonomous learning and adopt is one of the start ups we invested in. And they've really worked to use methodologies to improve European Health Co network monitoring. So they were actually getting a ton of false positive running in their previous infrastructure, and they were able to take it down from 50 k False positive the day to 50 using again a I on top of AWS in the public cloud. Um, using obviously and a dog, you know, technology in the space of a I, um we've also seen Capsule eight, which is an amazing company that's enabling enterprisers enterprises to modernize and migrate their workloads without compromising security again, Fully born in the cloud able to run on AWS and help those customers migrate to the public cloud with security, we have found them to be an incredible partner. Um, using simple voice commands on your on your smartphone hypersonic is another one of the companies that we've invested in that lets business decision makers quickly visualized insects insight from their disparate data sources. So really large unstructured data, which is the vast majority of data stored in the world that is exploding. Being able to quickly discern what should we do with this. How should we change something about our company using the power of the public cloud? I'm one of the last ones that I absolutely love to cover kind of the wide scope of the waves. That cloud is changing the innovation landscape, Um, Model mine, which is basically a company that allows people thio take decades of insights out of the mainframe data and do something with it. They actually use Amazon's cloud Service, the cloud storage service. So they were able Teoh Teik again. Mainframe data used that and be able to use Amazon's capabilities. Thio actually create, you know, meaningful insights for business users. So all of those again are really exciting. There's a bunch of information on the Intel sponsor channel with demos and videos with those customer stories and many, many, many more. Using Amazon instances built on Intel technology, >>you know that Amazon has always been in about startup born in the cloud. You mentioned that Intel has always been investing with Intel Capital, um, generations of great investments. Great call out there. Can you tell us more about what, uh, Amazon technology about the new offerings and Amazon has that's built on Intel because, as you mentioned at the top of the interview, there's been a long, long standing partnership since inception, and it continues. Can you take a minute to explain some of the offerings built on the Intel technology that Amazon's offering? >>Well, I've always happened to talk about Amazon offerings on Intel products. That's my day job. You know, really, we've spent a lot of time this year listening to our customer feedback and working with Amazon to make sure that we are delivering instances that are optimized for fastest compute, uh, better virtual memory, greater storage access, and that's really being driven by a couple of very specific workloads. So one of the first that we are introducing here it reinvents is the n five the n instant, and that's really ah, high frequency, high speed, low Leighton see network variants of what was, you know, the traditional Amazon E. C two and five. Um, it's powered by a second Gen Intel scalable processors, The Cascade late processors and really these have the highest all court turbo CPU performance from the on scalable processors in the club, with a frequency up to 4.5 gigahertz. That is really exciting for HPC work clothes, uh, for gaining for financial applications. Simulation modeling applications thes are ones where you know, automation, Um, in the automotive space in the aerospace industries, energy, Telkom, all of them can really benefit from that super low late and see high frequency. So that's really what the M five man is all about, um, on the br to others that we've introduced here today and that they are five beats and that is that can utilize up thio 60 gigabits per second of Amazon elastic block storage and really again that bandwidth and the 260 I ops that it can deliver is great for large relational databases. So the database file systems kind of workload. This is really where we are super excited. And again, this is built on Cascade Lake. The 2nd 10. Yeah, and it takes It takes advantage of many different aspects of how we're optimizing in that processor. So we were excited to partner with customers again using E. B s as well as various other solutions to ensure that data ingestion times for applications are reduced and they can see the delivery to what you were mentioning before right time to results. It's all about time to results on the last one is t three e. N. 33 e n is really the new D three instant. It's again on the Alexa Cascade Lake. We offer those for high density with high density local hard drive storage so very cost optimized but really allowing you to have significantly higher network speed and disk throughput. So very cost optimized for storage applications that seven x more storage capacity, 80% lower costs given terabytes of storage compared to the previous B two instances. So we will really find that that would be ideal for workloads in distributed and clustered file system, Big data and analytics. Of course, you need a lot of capacity on high capacity data lakes. You know, normally you want to optimize a day late for performance, but if you need tons of capacity, you need to walk that line. And I think the three and really will help you do that. And and of course, I would be absolutely remiss to not mention that last month we announced the Amazon Web Services Partnership with us on an Intel select solution, which is the first, you know, cloud Service provider to really launching until select solution there. Um, and it's an HPC space, So this is really about in high performance computing. Developers can spend weeks for months researching, you know, to manage compute storage network software configuration options. It's not a field that has gone fully cloud native by default, and those recipes air still coming together. So this is where the AWS parallel cluster solution using. It's an Intel Select solution for simulation and modeling on top of AWS. We're really excited about how it's going to make it easier for scientists and researchers like the ones I mentioned before, but also I t administrators to deploy and manage and just automatically scale those high performance computing clusters in Aws Cloud. >>Wow, that's a lot. A lot of purpose built e mean, no, you guys were really nailing. I mean, low late and see you got stories, you got density. I mean, these air use cases where there's riel workloads that require that kind of specialty and or e means beyond general purpose. Now, you're kind of the general purpose of the of the use case. This is what cloud does this is amazing. Um, final comments this year. I want to get your thoughts because you mentioned Cloud Service provider. You meant to the select program, which is an elite thing, right? Okay, we're anticipating Mawr Cloud service providers. We're expecting Mawr innovation around chips and silicon and software. This is just getting going. It feels like to me, it's just the pulse is different this year. It's faster. The cadence has changed. As a strategist, What's your final comments? Where is this all going? Because this is pretty different. Its's not what it was pre code, but I feel like this is going to continue transforming and being faster. What's your thoughts? >>Absolutely. I mean, the cloud has been one of the biggest winners in a time of, you know, incredible crisis for our world. I don't think anybody has come out of this time without understanding remote work, you know, uh, remote retail, and certainly a business transformation is inevitable and required thio deliver in a disaster recovery kind of business continuity environment. So the cloud will absolutely continue on continue to grow as we enable more and more people to come to it. Um, I personally, I couldn't be more excited than to be able Thio leverage a long term partnership, incredible strength of that insulin AWS partnership and these partnerships with key customers across the ecosystem. We do so much with SVS Os Vives s eyes MSP, you know, name your favorite flavor of acronym, uh, to help end users experience that digital transformation effectively, whatever it might be. And as we learn, we try and take those learnings into any environment. We don't care where workloads run. We care that they run best on our architecture. Er and that's really what we're designing. Thio. And when we partner between the software, the algorithm on the hardware, that's really where we enable the best and user demand and the end use their time to incite and use your time to market >>best. >>Um, so that's really what I'm most excited about. That's obviously what my team does every day. So that's of course, what I'm gonna be most excited about. Um, but that's certainly that's that's the future that you see. And I think it is a bright and rosy one. Um, you know, I I won't say things I'm not supposed to say, but certainly do be sure to tune into the Cube interview with It's on. And you know, also Chatan, who's the CEO of Havana and obviously shaken, is here at A W s, a Z. They talk about some exciting new projects in the AI face because I think that is when we talk about the software, the algorithms and the hardware coming together, the specialization of compute where it needs to go to help us move forward. But also, the complexity of managing that heterogeneity at scale on what that will take and how much more we need to do is an industry and as partners to make that happen. Um, that is the next five years of managing. You know how we are exploding and specialized hardware. I'm excited about that, >>Rebecca. Thank you for your great insight there and thanks for mentioning the Cube interviews. And we've got some great news coming. We'll be breaking that as it gets announced. The chips in the Havana labs will be great stuff. I wouldn't be remiss if I didn't call out the intel. Um, work hard, play hard philosophy. Amazon has a similar approach. You guys do sponsor the party every year replay party, which is not gonna be this year. So we're gonna miss that. I think they gonna have some goodies, as Andy Jassy says, Plan. But, um, you guys have done a great job with the chips and the performance in the cloud. And and I know you guys have a great partner. Concerts provide a customer in Amazon. It's great showcase. Congratulations. >>Thank you so much. I hope you all enjoy olive reinvents even as you adapt to New time. >>Rebecca Weekly here, senior director and senior principal engineer. Intel's hyper scale strategy and execution here in the queue breaking down the Intel partnership with a W s. Ah, lot of good stuff happening under the covers and compute. I'm John for your host of the Cube. We are the Cube. Virtual Thanks for watching

>>from around the globe. It's the Cube with digital coverage of AWS >>reinvent 2020 sponsored >>by Intel, AWS and our community partners. Welcome back to the cubes. Virtual coverage of AWS reinvent 2020. It's virtual this year. We're not in person, so we're doing remote interviews. Part of the three weeks we'll be covering wall to wall a lot of great conversations. News to cover and joining me today Off Fresh off the news off Andy Jackson's keynote, We have two great guests here. Jason Kapoor, senior product manager for Accelerated Computing at A. W S and eight time Medina Chief business officer, Havana Labs, which was recently acquired by Intel Folks. Thanks for coming on, gentlemen. Thank you for spending the time for coming on the key. Appreciate it. >>Thanks for having us. >>J Town. So talk about the news, actually. Uh, computers changing. It's being reinvented. That's the theme from Andy's keynote. What did Andy announced? Could you take a minute to explain the announcement? What services? What ap What's gonna be supported? What's this about? Take a minute to explain. >>Yeah, absolutely. Yeah. So today >>we >>announced our plans to launch and easy to instance based on hardware accelerators from Havana labs. We expect these businesses to be available in the first time from next year. And these air custom designed for accelerating training off deep learning models, a zoo we all know like training of deep learning models is a really competition. Aly extensive task. Oftentimes it takes too long and cost too much. And we're really excited about getting these instances out of the market as we expect for them to provide up to 40% better price performance. Thani on top of the line GPU instances, >>a lot of improvements. Why did anybody do this? Why heaven or what's the what the working backwards document tell you? What is it customers looking for here is or specific use case? >>Yeah, absolutely. So, you know, over the years, uh, the use of machine learning and deep learning has, like, really skyrocketed, right? So we're seeing companies from all the way like 14, 500 to like start ups just reinventing their business models and use using deep learning more pervasively. Right. So we have companies like Pinterest, you know, you'd use deep learning for content recommendations and object detection to Toyota Research Institute that are advancing the science behind autonomous vehicles. And there's a consistent cream from a lot of these customers that are, you know, innovating in the deep learning space that you know the cost it takes to experiment, train and optimize the deep learning models. It's too high. And, you know, they're looking at us as one of their partners to help them optimize their costs, you know, bring them as well as possible while giving them really performing products and enable them to actually bring their markets, their innovations to market as soon as possible. Right? S o. Do you answer your questions straight on your wants? The working backwards. It's a feedback from customers that they want choice on. They want our help Thio lower. Uh, the amount of compute resources and the cost it takes to train the new planning models. >>Hey, Tom, why don't you weigh in here on Havana and now part of intel? What trends are driving this? What's the motivation? Were you guys fit in? What's your view on this? >>Yeah, So Havana was founded in 2016 to deliver a I processors for the data center and cloud for training and inference deep learning models. So while building chips is hard, building, the software and ecosystem is even harder. So joining forces with intel simply helps us connect the dots. Ever since the acquisition last year, we were able to significantly boost our armed. The resource is, and now we're leveraging inter scale in number of customers and ecosystem and partner support. >>So what's the name of the product? Is there a chip name got? Was it Gowdy is the name? >>Yes, the product is man angle. >>Okay. And so it's gonna be hardware. So it's the hardware software. What's involved? Take us through the product. >>Yes. So Gandhi was designed from the ground up to do one task which is training deep learning models. To do that well, we focus the architectural to aspect efficiency and scalability. The computer architectures is a combination of fully programmable TPC tensile process, of course, and a central g M n G. These DPC course are programmable Villa W seen the machines that we designed with custom instruction, set architecture, er and special functions that will developed specifically for a I. The Gandhi cheap integrates also 32 gigabyte off H B M to memory which makes it easy to port to. For GPU developers, Gandhi is unique in integrating 10 parts of 100 gigabit Internet rocky on cheap. And this is opposed to other architectural, which use proprietary interfaces. So overall, improving the cost performance is achieved through efficiency, namely higher utilization off the computer and memory resource is on cheap and the native integration off the rocky interfaces >>J Town. This is actually interesting, as this is the theme for reinvent. We're seeing it right on stage today. Play out again another command performance by Andy Jassy. Slew of announcements. How does Gowdy fit into the AI portfolio or Amazon strategy? Because what a town saying is it sounds like he's doing the heavy lifting on all this training stuff when people want to just get to the outcome. I mean, the theme has been, just let the product do what they do kind of put stuff under the covers and just let it scale. Is that the theme here is this. >>What does this >>all fit in? Take us through how this fits into the A, I strategy for Amazon and also what what what is Havana Intel bring to the table? >>Absolutely. Yeah. So with respect to our overall strategy and portfolio units, it's relatively straightforward, right? So we're laser focused on making sure we have the broadest and deepest portfolio off services for machine learning, right? So these range from infrastructure services specifically compute networking and storage all the way up to, like, managed and all services, which come with pre trained models and customers can simply invoke them using an A P. I call right eso. So from a strategy perspective, you want to make sure that we provide a customer to a choice, uh, enable them to pick the right platform for the right use case, help them get to the Khan structure they actually want, right eso with Havana. And you know, their acquisition with Intel, we finally have access to hardware software and the ability to kind of build out a ecosystem beyond what you know judicially is being used. Which is was a GP used right eso. So the engagement with with Havana, you know, allows us to take their products and capabilities, wrap it around, and easy to instance, which is what customers will be able to launch right on doing so. We're enabling them to tap into the innovation that Teton the rest of the Havana team are working on while having a solution that is integrated with the full AWS stack. Right? So you don't you don't have to rack in stock hard. Bring your data center thes. They're gonna be available standard. Easy to instances. You can just click and launch them. Get access to software that's already pre integrated and big den and ready to go right. Eso so it actually comes down to taking their innovations, coupling it with an AWS solution and making it too easy for customers together. I've been running with the respective training the deepened models. >>Well, here is the question that I want to get to. I think everyone's on everyone's mind is how is it Gowdy different or similar than other GPU? Specifically, you mentioned the software stack on the AWS What you get the software stack inside the chip. How is this different or similar? Two other GP use. And what's the difference between the software stack versus a traditional libraries? >>So from day one, we were focused on the software experience and we were mindful in the need to make it easy for developers to use the innovations we have in the hardware. Most developers, if not all of them, are using deep learning frameworks such as tensile flowing pytorch for building their deep learning models. So God is synapse AI software suite comes integrated and optimized for tensorflow and pilotage, so we expect most developers to be able to take their existing models and with minor changes to the training strips to be able to run them on Gowdy based instances. In addition, expert developers that are familiar with writing their own kernels will be provided with food too sweet for writing their own TPC kernels that can augment the Havana provided library. >>So that's the user experience for the developers, right? That's what you're saying >>exactly, exactly, and we will provide detailed guides for developers. In doing that, Havana will provide open access to documentation library software models and left toe Havana's kita and bi directional communication with the Havana developer community. All these resources will be available concurrently with the AWS Instances launch. >>Okay, so I'm a developer. How did I get involved? It's software on git hub I use the hardware is on Amazon, obviously, in their instances. It's a new instance. Take me through the workflow develop. I'm into this. I wanna I wanna get involved. What I what am I doing? Take me >>through? Yes, I think it s so If the developer is accustomed to using GPS for training the deep learning models three experience is gonna be practically the same, right? So they'll have multiple options to get started. One of them would be, for example, to take our deep learning, Um, it's or Amazon machine images that will come integrated with software from Havana labs. Right. So customers will take the deep Learning Army and launch it on an easy to instance, featuring the gaudy accelerators. Right? So when with that, they'll have, you know, the baseline construct off software and hardware available to get up and running with right, we'll support, you know, all different types of work flows. So if customers want to use containerized solutions, thes instances will be supported R E C s and E s services. Eso using containerized kubernetes you know, thes the solution will just work on. Lastly, we also intend to support these instances through sage maker eso. Just a quick recap on stage maker. That's a manage service that does end to end that provides end to end capabilities for training, debugging, building and deploying machine learning applications. Eso these instances will also be supporting sage maker. So if you're fiddling with sage maker, you can get up and running with this. This is fairly quickly. >>It sounds like it's gonna enable a lot of action and sage maker level. Then can that layer on the use cases? I gotta ask you guys quickly, What's the low hanging fruit use case applications for this product thing? This partnership, Because you know that's gonna be the first Traction said, What are some of these applications gonna be used for? What can we expect to see? >>So typical applications would be image classifications, object detection, natural language processing, the recommendation systems. You'll find reference models in our get up for that and will be growing at least a Z you can imagine. >>Okay, where can people find more info? Give us the data. Take him in to explain. Put a plug in for how What's all the coordinates? U r l sites support how people create, Um, how people get involved. The community. >>Yeah, so customers will be able to access information on AWS websites and also on Havana Labs website. So you will be kicking off a preview early next year. Eso I would highly recommend for customers to find our product pages and signed up for already access and previous information. Utah. >>Yes, and you'll find more information on Havana. A swell a Savannah's get up over time. >>Great announcement. Congratulations. Thanks for sharing the news and some commentary on it. This is really the big theme. You know what Cove in 19 and this pandemic has shown is massive acceleration of digital transformation and having the software and hardware out there that accelerates the heavy lifting and creates value around the data. Super valuable. Thanks for for doing that. Appreciate taking the time. Thank >>you so much. >>Yeah. Thanks for having >>us. Okay, this is the cubes coverage at 80. Best reinvent next three weeks. We're here on the ground. Will remote. We're live inside the studio. We wish we could be there in person, but it's remote this year. But stay tuned. Check out silicon angle dot com. Exclusive interviews with Andy Jassy and Amazon executives and the big news covering. They're all there in one spot. Check it out. We'll be back with more coverage after this break. Thanks for watching. Yeah.

>> Live, from San Francisco, it's The Cube! Covering DockerCon '18. Brought to you by Docker and its ecosystem partners. >> Hey, welcome back to The Cube. We are live at DockerCon 2018 on a beautiful day in San Francisco. We're glad you're not playing hooky though if you're in the city because it's important to be here watching John Troyer and myself, Lisa Martin, talk to some awesome, inspiring guests. We're excited to welcome two Docker captains, that's right, to The Cube. We've got Nirmal Mehta, you are the chief technologist of Booz Allen. Welcome back to The Cube. And, we've got Bret Fisher, the author of Docker Mastery. Both of you, Docker captains. Can't wait to dig into that. But you're both speakers here at the fifth annual DockerCon. So Bret, let's talk, you just came off the stage basically. So, thank you for carving out some time for us. Talk to us about your session. What did you talk about? What was some of the interaction with the attendees? >> Well the focus is on Docker Swarm and I'm a assist admin at heart so I focus on ops more than developer but I spend my life helping developers get their stuff into production. And so, that talk centers around the challenges of going in and doing real work that's for a business with containers and how do you get what seems like an incredible amount of new stuff into production all at the same time on a container ecosystem. So, kind of helping them build the tools they need, and what we call a stack, a stack of tools, that ultimately create a full production solution. >> What were some of the commentary you heard from attendees in terms of... Were these mostly community members, were there users of container technology, what was sort of the dynamic like? >> Well you have, there's all sorts of dynamics, right? I mean you have startups, I think I took a survey in the room because it was packed and like 20% of the people in the room about were a solo DevOps admin. So they were the only person responsible for their infrastructure and their needs are way different than a team that has 20 or 30 people all serving that responsibility. So, the talk was a little bit about how do they handle their job and do this stuff. You know, all this latest technology without being overwhelmed and, then, how does it grow in complexity to a larger team and how do they sustain that. So, yeah. >> Bret, it's nice that the technology is mature enough now that people are in production, but what are some of the barriers that people hit when they try to go into production the first time? >> Yeah, great question. I think the biggest barrier is trying to do too much new at the same time. And, I don't know why we keep relearning this lesson in IT, right? We've had that problem for decades of projects being over cost, over budget, over timed, and I think with so much exciting new stuff in containers it's susceptible to that level of, we need all these new things, but you actually don't, right? You can actually get by with very small amounts of change, incrementally. So, we try to teach that pattern of growing over time, and, yeah. >> You mentioned like the one person team versus the multi-person team kind of DevOps organization. Does that same problem of boiling the ocean, do you see that in both groups? >> Yeah, I mean you have fundamentally the same needs, the same problem that you have to solve, but different levels of complexity is really all it has to do with and different levels of budget, obviously, right? So, usually the solo admin doesn't have the million dollar budget for all the tools and bells and whistles, so they might have to do more on their own, but, then, they also have less time so it's a tough row to hoe, you know, to deal with, because you've got those two different fundamental problems of time and money and people are using the most expensive thing. So, no matter what the tool is you're trying to buy, it's usually your time that's the most valuable thing. So how do we get more of our time back? And that's really what containers were all about originally was just getting more of our time back out of it and so we can put back into the business instead of focusing on the tech itself. >> Nirmal, your talk tomorrow is on empathy. >> Yes. >> Very provocative, dig into that for us. >> Sure, so it was actually inspired by a conversation I had with John a couple years ago on Geek Whisperers podcast and he asked the folks on that show, yourself included, asked if there was an event in my past that I kind of regret or taught me a lot. And it was about basically neglecting someone on my team and just kind of shoving them away. And, that moment was a big change in how I felt about the IT industry. And, what I had done was pushed someone who probably needed that help and built up a lot of courage to talk to me and I kind of just dismissed him too quickly. And, from there, I was thinking more and more about game theory and behavioral economics and seeing a lot of our clients and organizations struggle to go through a digital transformation, a DevOps transformation, a cultural transformation. So, to me, culture is kind of the core of what's happening in the industry. And so, the idea of my talk is a little bit of behavioral economics, a little bit of game theory, to kind of set the stage for where your IT organization is probably kind of is right now and how to use empathy to get your organization to that DevOps and to a more efficient place and resolve those conflicts that happen inherently. And, somehow tie that all together with Docker. So, that's kind of what my talk is all about. >> Nice, I mean what's interesting to me, Lisa, is that we do Cubes and there are many Cubes actually all across the country during conference season, right? And we talk to CEOs and VPs of very large companies and even today, at DockerCon, the word 'culture' and the talking about culture and process and people has come up every single interview. So, it's not just from the techies up that this conversation is going... this DevOps and empathy conversation is going on, it seems to be from the top down as well. Everyone seems to recognize that, if you really are going to get this productivity gain, it's not just about the tech, you gotta have culture. >> Absolutely, a successful transformation of an organization is both grassroots and top down. Can't have it without either. And, I think we inherently want to have a... Like, we want to take a pill to solve that problem and there's lots of pills: Docker or cloud or CICD or something. But, those tools are the foundational safety net for a cultural transformation, that's all that it is. So, if you're implementing Docker or Jenkins or some CICD pipeline or automation, that's a safety blanket for providing trust in an organization to allow that change in the culture to happen. But, you still need that cultural change. Just adopting Docker isn't going to make you automatically a more effective organization. Sorry, but it's just one piece and it's an important piece but you have to have that top down understanding of where you are now as an organization and where you want to be in the future. And understanding that this kind of legacy, siloed team mindset is no longer how you can achieve that. >> You talked about trust earlier from a thematic perspective as something that comes up. You know we were at SAP Sapphire last week and trust came up a lot as really paramount. And that was in the context of a vendor/customer relationship. But, to your point, it's imperative that it's actually coming from within organizations. We talk a lot about, well stuff today: multi-cloud--multi-cloud, silos-- but, there's also silos with people and without that cultural shift and probably that empathy, how successful, how big of an impact can a technology make? Are you talking with folks that are at the executive level as well as the developer level in terms of how they each have a stake and need to contribute to this empathy? >> Yeah, absolutely. So, the talk I'm doing is basically the ammunition a lower level person would need to go up to management and say, hey, you know this is where the organization is, this is what the IT department kind of looks like, these are the conflicts, and we have to change in order to succeed. And a lot of folks don't. They see the technology changes that they need. You know, adopting the new javascript framework or the new UX pattern. But, they might not have the ammunition to understand the business strategy, the organizational issues. But, they still need that evidence to actually convince a CTO or a CEO or a COO for the need to change. So, I've talked to both groups. From the C-level side, I think it comes from the inherent speed of the industry, the competitive landscape, those are all the pressures that they see and the disruptions that they are tackling. Maybe it's incumbent disruption or new startups that they may have to compete with in the future. The need for constant innovation is kind of the driver. And, IT is kind of where all that is, these days. >> That's great. Building on the concept of trust and this morning at the keynote, Matt Mckesson where they talked about trusting Docker, trusting Docker the company, trusting Docker the technology. Almost the very first words out of Steve Singh's mouth this morning were about community. And, I think community is one of the big reasons people do trust Docker and one of the things that brings them along. You guys are both Docker captains, part of a program of advocacy, community programs. I don't know, Bret, can you tell us a little bit about the program and what's involved in it? >> Yeah, sure. So, it's been around over two years now and it actually spawned out of Docker's pre-existing programs were focusing on speakers and bloggers and supporting them as well as community leaders that run meetups. And they kind of figured out that a key set of people were kind of doing two or three of those things all at once. And so, they were sort of deciding how do we make like super-groups of these people and they came up with the term Docker captain It really just means you know something about Docker, you share it constantly, something about a Docker toolset, something about the container tools. And that you're sort of... And you don't work for Docker. You're a community person that is, maybe you're working for someone that is a partner of Docker or maybe you're just a meetup volunteer that also blogs a lot about patterns and practices of Docker or new Docker features. And so, they kind of use the engineering teams at Docker to kind of pick through people on the internet and the people they see in the community that are sort of rising out of all the noise out there. And they ask them to be a part of the program and then, of course, we get nice jackets and lots of training. And, it's really just a great group of people, we're about 70 people now around the world. >> And yeah, this is global as well, right? >> Oh yeah, yep. It's one of my favorite aspects is the international aspect. I work for Booz Allen which is a more US government focused and I don't get to interact with the global community much. But, through the Docker captain program got friendships and connections almost on every continent and a lot of locations. I just saw a post of a Docker meetup in like, I think it was like Tunisia. Very, very out there kind of places. There was a Cuban one, recently, in Havana. The best connections to a global community that I've ever seen. I think one of the biggest drivers is the rapid adoption and kind of industry trend of containerization and the Docker brand and what it is basically gave rise to a ton of folks just beginners, just wanting to know what it's all about. And, we've been identified as folks that are approachable and have kind of a mandate to be people that can help answer those initial questions, help align folks that have questions with the right resources, and also just make it like a soft, warm, fuzzy kind of introduction to the community. And engage on all kinds of levels, advanced to beginner levels. >> It was interesting, again, this morning, I think about half the people raised their hands to the question, "is it their first year?" So, it still seems like the Docker, the inbound people interested in Docker is still growing and millions of developers all over the world, right? I don't know, Bret, you have a course, Docker Mastery, you also do meetups, and so I'm curious like what is the common pathway or drivers for new folks coming in, that you see and talk with? >> Yeah, what's the pathways? >> Yeah, the pathway, what's driving them? What are they trying to do? Again, are they these solo folks? >> Yeah, it's sort of a little bit of everything. We're very lucky in the course. We actually just crossed 55,000 students worldwide, 161 countries on a course that is only a year old. So, it kind of speaks to the volume of people around the world that really want to learn containers and all the tools around them. I think that the common theme there is I think we had the early adopters, right, and that was the first three or four years of Docker was people that were Silicon Valley, startups, people who were already on the bleeding edge of technology, whether it was hobbyist or enterprise. It was all people, but it was sort of the Linux people. Now, what we're getting is the true enterprise admins and developers, right. And that means, Microsoft, IBM mainframes, .Net, Java, you're getting all of these sort of traditional enterprise technologies but they all have the same passion, they're just coming in a few years later. So, what's funny is, you're meetups don't really change. They're just growing. Like what you see worldwide, the trend is we're still on the up-climb of all the groups, we have over 200 meetups worldwide now that meet once a month about Docker. It's just a crazy time right now. Everything's growing and it's like you wonder if it's ever going to stop, right How big are we gonna get, gonna take over the world with containers? >> Yeah, about 60% or more of all our meetups are completely new to Docker. And, it ranges from, you know, my boss told me about it so I gotta learn it or I found it and I want to convince other people in my organization to use it so I need to learn it more so I can make that case or, it's immediately solving a problem but I don't know how to take it to the next level, don't know where it's going, all that. It's a lot of new people. >> I get students a lot, college students that want to be more aggressive when they get in the marketplace and they hear the word 'DevOps' a lot and they think DevOps is a thing I need to learn in order to get a job. They don't really know what that is. And, of course, we don't even. At this point, it's so watered down, I don't know if anyone really knows what it is. But eventually, they search that and they come up with sort of key terms and I think one of those the come up right away is Docker. And they don't know what that is. But, I get asked the question a lot, If I go to this workshop or if I go the meetup or whatever, can I put that on my resume so I can get my first job out of school? They're always looking for something else beyond their schooling to make them a better first resume. So, it's cool to see even the people just stepping into the job market getting their feet wet with Docker even when they don't even know why they need it. >> It sounds like a symbiotic thought leadership community that you guys are part of and it sounds like the momentum we heard this morning in the general session is really carried out through the Docker captains and the communities. So, Nirmal, Bret, thanks so much for stopping by bringing your snazzy sweatshirts and sharing what you guys are doing as Docker captains. We appreciate your time. >> Thank you. >> Thank you. >> We want to thank you for watching The Cube. I'm Lisa Martin with John Troyer. We're live at DockerCon 2018. Stick around, John and I will be right back with our next guest.