>>From around the globe, it's the cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. >>Oh, welcome back to the cube. As we continue our coverage of AWS reinvent 2020, you know, I know you're familiar with Moneyball, the movie, Brad Pitt, starting as Billy Bean, the Oakland A's general manager, where the A's were all over data, right. With the Billy Bean approach, it was a very, uh, data driven approach to building his team and a very successful team. Well, AWS is taking that to an extraordinary level and with us to talk about that as Matt Hearst, who was the head of global sports marketing and communications at AWS and Matt, thanks for joining us here on the queue. >>John is my pleasure. Thanks so much for having me. You >>Bet. Um, now we've already heard from a couple of folks, NFL folks, uh, at re-invent, uh, about the virtual draft. Um, but for those of our viewers who maybe aren't up to speed on that, or having a chance to see, uh, what those folks had to say, uh, let's just talk about that as an opener, um, about your involvement with the NFL and particularly with, with the draft and, and what that announcement was all about. >>Sure. We, we saw, we've seen a great evolution with our work with the NFL over the past few years. And you mentioned during the infrastructure keynote where Michelle McKenna who's, the CIO for the NFL talks about how they were able to stage the 2020 virtual draft, which was the NFL is much most watched ever, uh, you know, over 55 million viewers over three days and how they were unable to do it without the help and the power of AWS, you know, utilizing AWS is reliability, scalability, security, and network connectivity, where they were able to manage thousands of live feeds to flow to the internet and go to ESPN, to airline. Um, but additionally, Jennifer LinkedIn, who's the SVP of player health and innovation at the NFL spoke during the machine learning keynote during reinvent. And she talked about how we're working with the NFL, uh, to co-develop the digital athlete, which is a computer simulation model of a football player that can replicate infinite scenarios in a game environment to help better foster and understanding of how to treat and rehabilitate injuries in the short term and in the long-term in the future, ultimately prevent, prevent and predict injuries. >>And they're using machine learning to be able to do that. So there's, those are just a couple of examples of, uh, what the NFL talked about during re-invent at a couple of keynotes, but we've seen this work with the NFL really evolve over the past few years, you know, starting with next gen stats. Those are the advanced statistics that, uh, brings a new level of entertainment to football fans. And what we really like to do, uh, with the NFL is to excite, educate, and innovate. And those stats really bring fans closer to the game to allow the broadcasters to go a little bit deeper, to educate the fans better. And we've seen some of those come to life through some of our ads, uh, featuring Deshaun Watson, Christian McCaffrey, um, these visually compelling statistics that, that come to life on screen. Um, and it's not just the NFL. AWS is doing this with some of the top sports leagues around the world, you know, powering F1 insights, Buddhist league, and match facts, six nations, rugby match stats, all of which utilize AWS technology to uncover advanced stats and really help educate and engage fans around the world in the sports that they love. >>Let's talk about that engagement with your different partners then, because you just touched on it. This is a wide array of avenues that you're exploring. You're in football, you're in soccer, you're in sailing, uh, you're uh, racing formula one and NASCAR, for example, all very different animals, right? In terms of their statistics and their data and of their fan interest, what fans ultimately want. So, um, maybe on a holistic basis first, how are you, uh, kind of filtering through your partner's needs and their fans needs and your capabilities and providing that kind of merger of capabilities with desires >>Sports, uh, for AWS and for Amazon are no different than any other industry. And we work backwards from the customer and what their needs are. You know, when we look at the sports partners and customers that we work with and why they're looking to AWS to help innovate and transform their sports, it's really the innovative technologies like machine learning, artificial intelligence, high performance computing, internet of things, for example, that are really transforming the sports world and some of the best teams and leagues that we've talked about, that you touched on, you know, formula one, NASCAR, NFL, Buena, Sligo, six nations, rugby, and so on and so forth are using AWS to really improve the athlete and the team performance transform how fans view and engage with sports and deliver these real-time advanced statistics to give fans, uh, more of that excitement that we're talking about. >>Let me give you a couple of examples on some of these innovative technologies that our customers are using. So the Seattle Seahawks, I built a data Lake on AWS to use it for talent, evaluation and acquisition to improve player health and recovery times, and also for their game planning. And another example is, you know, formula and we talk about the F1 insights, those advanced statistics, but they're also using AWS high-performance computing that helped develop the next generation race car, which will be introduced in the 2022 season. And by using AWS F1 was able to reduce the average time to run simulations by 70% to improve the car's aerodynamics, reducing the downforce loss and create more wheel to wheel racing, to bring about more excitement on the track. And a third example, similar to, uh, F1 using HPC is any of those team UK. So they compete in the America's cup, which is the oldest trophy in international sports. And endosteum UK is using an HPC environment running on Amazon, easy to spot instances to design its boat for the upcoming competition. And they're depending on this computational power on AWS needing 2000 to 3000 simulations to design the dimension of just a single boat. Um, and so the power of the cloud and the power of the AWS innovative technologies are really helping, uh, these teams and leagues and sports organizations around the world transform their sport. >>Well, let's go back. Uh, you mentioned the Seahawks, um, just as, uh, an example of maybe, uh, the kind of insights that that you're providing. Uh, let's pretend I'm there, there's an outstanding running back and his name's Matt Hearst and, uh, and he's at a, you know, a college let's just pretend in California someplace. Um, what kind of inputs, uh, are you now helping them? Uh, and what kind of insights are you trying to, are you helping them glean from those inputs that maybe they didn't have before? And how are they actually applying that then in terms of their player acquisition and thinking about draft, right player development, deciding whether Matt Hertz is a good fit for them, maybe John Wallace is a good fit for them. Um, but what are the kinds of, of, uh, what's that process look like? >>So the way that the Seahawks have built the data Lake, they built it on AWFs to really, as you talk about this talent, evaluation and acquisition, to understand how a player, you know, for example, a John Walls could fit into their scheme, you know, that, that taking this data and putting it in the data Lake and figuring out how it fits into their schemes is really important because you could find out that maybe you played, uh, two different positions in high school or college, and then that could transform into, into the schematics that they're running. Um, and try to find, I don't want to say a diamond in the rough, but maybe somebody that could fit better into their scheme than, uh, maybe the analysts or others could figure out. And that's all based on the power of data that they're using, not only for the talent evaluation and acquisition, but for game planning as well. >>And so the Seahawks building that data Lake is just one of those examples. Um, you know, when, when you talk about a player, health and safety, as well, just using the NFL as the example, too, with that digital athlete, working with them to co-develop that for that composite NFL player, um, where they're able to run those infinite scenarios to ultimately predict and prevent injury and using Amazon SageMaker and AWS machine learning to do so, it's super important, obviously with the Seahawks, for the future of that organization and the success that they, that they see and continue to see, and also for the future of football with the NFL, >>You know, um, Roger Goodell talks about innovation in the national football league. We hear other commissioners talking about the same thing. It's kind of a very popular buzz word right now is, is leagues look to, uh, ways to broaden their, their technological footprint in innovative ways. Again, popular to say, how exactly though, do you see AWS role in that with the national football league, for example, again, or maybe any other league in terms of inspiring innovation and getting them to perhaps look at things differently through different prisms than they might have before? >>I think, again, it's, it's working backwards from the customer and understanding their needs, right? We couldn't have predicted at the beginning of 2020, uh, that, you know, the NFL draft will be virtual. And so working closely with the NFL, how do we bring that to life? How do we make that successful, um, you know, working backwards from the NFL saying, Hey, we'd love to utilize your technology to improve Clare health and safety. How are we able to do that? Right. And using machine learning to do so. So the pace of innovation, these innovative technologies are very important, not only for us, but also for these, uh, leagues and teams that we work with, you know, using F1 is another example. Um, we talked about HPC and how they were able to, uh, run these simulations in the cloud to improve, uh, the race car and redesign the race car for the upcoming seasons. >>But, uh, F1 is also using Amazon SageMaker, um, to develop new F1 insights, to bring fans closer to the action on the track, and really understand through technology, these split-second decisions that these drivers are taking in every lap, every turn, when to pit, when not to pit things of that nature and using the power of the cloud and machine learning to really bring that to life. And one example of that, that we introduced this year with, with F1 was, um, the fastest driver insight and working F1, worked with the Amazon machine learning solutions lab to bring that to life and use a data-driven approach to determine the fastest driver, uh, over the last 40 years, relying on the years of historical data that they store in S3 and the ML algorithms that, that built between AWS and F1 data scientists to produce this result. So John, you and I could sit here and argue, you know, like, like two guys that really love F1 and say, I think Michael Schumacher is the fastest drivers. It's Lewis, Hamilton. Who's great. Well, it turned out it was a arts incentive, you know, and Schumacher was second. And, um, Hamilton's third and it's the power of this data and the technology that brings this to life. So we could still have a fun argument as fans around this, but we actually have a data-driven results through that to say, Hey, this is actually how it, how it ranked based on how everything works. >>You know, this being such a strange year, right? With COVID, uh, being rampant and, and the major influence that it has been in every walk of global life, but certainly in the American sports. Um, how has that factored into, in terms of the kinds of services that you're looking to provide or to help your partners provide in order to increase that fan engagement? Because as you've pointed out, ultimately at the end of the day, it's, it's about the consumer, right? The fan, and giving them info, they need at the time they want it, that they find useful. Um, but has this year been, um, put a different point on that for you? Just because so many eyeballs have been on the screen and not necessarily in person >>Yeah. T 20, 20 as, you know, a year, unlike any other, um, you know, in our lifetimes and hopefully going forward, you know, it's, it's not like that. Um, but we're able to understand that we can still bring fans closer to the sports that they love and working with, uh, these leagues, you know, we talk about NFL draft, but with formula one, we, uh, in the month of may developed the F1 Pro-Am deep racer event that featured F1 driver, uh, Daniel Ricardo, and test driver TA Sianna Calderon in this deep racer league and deep racers, a one 18th scale, fully autonomous car, um, that uses reinforcement learning, learning a type of machine learning. And so we had actual F1 driver and test driver racing against developers from all over the world. And technology is really playing a role in that evolution of F1. Um, but also giving fans a chance to go head to head against the Daniel Ricardo, which I don't know that anyone else could ever say that. >>Yeah, I raced against an F1 driver for head to head, you know, and doing that in the month of may really brought forth, not only an appreciation, I think for the drivers that were involved on the machine learning and the technology involved, but also for the developers on these split second decisions, these drivers have to make through an event like that. You know, it was, it was great and well received. And the drivers had a lot of fun there. Um, you know, and that is the national basketball association. The NBA played in the bubble, uh, down in Orlando, Florida, and we work with second spectrum. They run on AWS. And second spectrum is the official optical provider of the NBA and they provide Clippers court vision. So, uh, it's a mobile live streaming experience for LA Clippers fans that uses artificial intelligence and machine learning to visualize data through on-screen graphic overlays. >>And second spectrum was able to rely on, uh, AWS is reliability, connectivity, scalability, and move all of their equipment to the bubble in Orlando and still produce a great experience for the fans, um, by reducing any latency tied to video and data processing, um, they needed that low latency to encode and compress the media to transfer an edit with the overlays in seconds without losing quality. And they were able to rely on AWS to do that. So a couple of examples that even though 2020 was, uh, was a little different than we all expected it to be, um, of how we worked closely with our sports partners to still deliver, uh, an exceptional fan experience. >>So, um, I mean, first off you have probably the coolest job at AWS. I think it's so, uh, congratulations. I mean, it's just, it's fascinating. What's on your want to do less than in terms of 20, 21 and beyond and about what you don't do now, or, or what you would like to do better down the road, any one area in particular that you're looking at, >>You know, our, our strategy in sports is no different than any other industry. We want to work backwards from our customers to help solve business problems through innovation. Um, and I know we've talked about the NFL a few times, but taking them for, for another example, with the NFL draft, improving player health and safety, working closely with them, we're able to help the NFL advance the game both on and off the field. And that's how we look at doing that with all of our sports partners and really helping them transform their sport, uh, through our innovative technologies. And we're doing this in a variety of ways, uh, with a bunch of engaging content that people can really enjoy with the sports that they love, whether it's, you know, quick explainer videos, um, that are short two minute or less videos explaining what these insights are, these advanced stats. >>So when you see them on the screening and say, Oh yeah, I understand what that is at a, at a conceptual level or having blog posts from a will, Carlin who, uh, has a long storied history in six nations and in rugby or Rob Smedley, along story history and F1 writing blog posts to give fans deeper perspective as subject matter experts, or even for those that want to go deeper under the hood. We've worked with our teams to take a deeper look@howsomeofthesecometolifedetailingthetechnologyjourneyoftheseadvancedstatsthroughsomedeepdiveblogsandallofthiscanbefoundataws.com slash sports. So a lot of great rich content for, uh, for people to dig into >>Great stuff, indeed. Um, congratulations to you and your team, because you really are enriching the fan experience, which I am. One of, you know, hundreds of millions are enjoying that. So thanks for that great work. And we wish you all the continued success down the road here in 2021 and beyond. Thanks, Matt. Thanks so much, Sean.

>>from around the >>globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. Yeah, >>Hi. We are the Cube live covering AWS reinvent 2020. I'm Lisa Martin, and I've got one of our cube alumni back with me. Mike Miller is here. General manager of A W s AI Devices at AWS. Mike, welcome back to the Cube. >>Hi, Lisa. Thank you so much for having me. It's really great to join you all again at this virtual reinvent. >>Yes, I think last year you were on set. We have always had to. That's at reinvent. And you you had the deep race, your car, and so we're obviously socially distance here. But talk to me about deepracer. What's going on? Some of the things that have gone on the last year that you're excited >>about. Yeah, I'd love to tell. Tell you a little bit about what's been happening. We've had a tremendous year. Obviously, Cove. It has restricted our ability to have our in person races. Eso we've really gone gone gangbusters with our virtual league. So we have monthly races for competitors that culminate in the championship. Um, at reinvent. So this year we've got over 100 competitors who have qualified and who are racing virtually with us this year at reinvent. They're participating in a series of knockout rounds that are being broadcast live on twitch over the next week. That will whittle the group down to AH Group of 32 which will have a Siris of single elimination brackets leading to eight finalists who will race Grand Prix style five laps, eight cars on the track at the same time and will crown the champion at the closing keynote on December 15th this year. >>Exciting? So you're bringing a reinforcement, learning together with with sports that so many of us have been missing during the pandemic. We talked to me a little bit about some of the things that air that you've improved with Deep Racer and some of the things that are coming next year. Yeah, >>absolutely so, First of all, Deep Racer not only has been interesting for individuals to participate in the league, but we continue to see great traction and adoption amongst big customers on dare, using Deep Racer for hands on learning for machine learning, and many of them are turning to Deep Racer to train their workforce in machine learning. So over 150 customers from the likes of Capital One Moody's, Accenture, DBS Bank, JPMorgan Chase, BMW and Toyota have held Deep Racer events for their workforces. And in fact, three of those customers Accenture, DBS Bank and J. P. Morgan Chase have each trained over 1000 employees in their organization because they're just super excited. And they find that deep racers away to drive that excitement and engagement across their customers. We even have Capital one expanded this to their families, so Capital One ran a deep raise. Their Kids Cup, a family friendly virtual competition this past year were over. 250 Children and 200 families got to get hands on with machine learning. >>So I envisioned some. You know, this being a big facilitator during the pandemic when there's been this massive shift to remote work has have you seen an uptick in it for companies that talking about training need to be ableto higher? Many, many more people remotely but also train them? Is deep Racer facilitator of that? Yeah, >>absolutely. Deep Racer has ah core component of the experience, which is all virtualized. So we have, ah, console and integration with other AWS services so that racers can participate using a three d racing simulator. They can actually see their car driving around a track in a three D world simulation. Um, we're also selling the physical devices. So you know, if participants want to get the one of those devices and translate what they've done in the virtual world to the real world, they can start doing that. And in fact, just this past year, we made our deep race or car available for purchase internationally through the Amazon Com website to help facilitate that. >>So how maney deep racers air out there? I'm just curious. >>Oh, thousands. Um, you know, And there what? What we've seen is some companies will purchase you, know them in bulk and use them for their internal leagues. Just like you know, JP Morgan Chase on DBS Bank. These folks have their own kind of tracks and racers that they'll use to facilitate both in person as well as the virtual racing. >>I'm curious with this shift to remote that we mentioned a minute ago. How are you seeing deepracer as a facilitator of engagement. You mentioned engagement. And that's one of the biggest challenges that so Maney teams develops. Processes have without being co located with each other deep Brister help with that. I mean, from an engagement perspective, I think >>so. What we've seen is that Deep Racer is just fun to get your hands on. And we really lower the learning curve for machine learning. And in particular, this branch called reinforcement Learning, which is where you train this agent through trial and error toe, learn how to do a new, complex task. Um, and what we've seen is that customers who have introduced Deep Racer, um, as an event for their employees have seen ah, very wide variety of employees. Skill sets, um, kind of get engaged. So you've got not just the hardcore deep data scientists or the M L engineers. You've got Web front end programmers. You even have some non technical folks who want to get their hands dirty. Onda learn about machine learning and Deep Racer really is a nice, gradual introduction to doing that. You can get engaged with it with very little kind of coding knowledge at all. >>So talk to me about some of the new services. And let's look at some specific use case customer use cases with each service. Yeah, >>absolutely. So just to set the context. You know, Amazon's got hundreds. A ws has hundreds of thousands of customers doing machine learning on AWS. No customers of all sizes are embedding machine learning into their no core business processes. And one of the things that we always do it Amazon is We're listening to customers. You know, 90 to 95% of our road maps are driven by customer feedback. And so, as we've been talking to these industrial manufacturing customers, they've been telling us, Hey, we've got data. We've got these processes that are happening in our industrial sites. Um, and we just need some help connecting the dots like, how do we really most effectively use machine learning to improve our processes in these industrial and manufacturing sites? And so we've come up with these five services. They're focused on industrial manufacturing customers, uh, two of the services air focused around, um, predictive maintenance and, uh, the other three services air focused on computer vision. Um, and so let's start with the predictive maintenance side. So we announced Amazon Monitor On and Amazon look out for equipment. So these services both enable predictive maintenance powered by machine learning in a way that doesn't require the customer to have any machine learning expertise. So Mono Tron is an end to end machine learning system with sensors, gateway and an ML service that can detect anomalies and predict when industrial equipment will require maintenance. I've actually got a couple examples here of the sensors in the gateway, so this is Amazon monitor on these little sensors. This little guy is a vibration and temperature sensor that's battery operated, and wireless connects to the gateway, which then transfers the data up to the M L Service in the cloud. And what happens is, um, the sensors can be connected to any rotating machinery like pump. Pour a fan or a compressor, and they will send data up to the machine learning cloud service, which will detect anomalies or sort of irregular kind of sensor readings and then alert via a mobile app. Just a tech or a maintenance technician at an industrial site to go have a look at their equipment and do some preventative maintenance. So um, it's super extreme line to end to end and easy for, you know, a company that has no machine learning expertise to take advantage of >>really helping them get on board quite quickly. Yeah, >>absolutely. It's simple tea set up. There's really very little configuration. It's just a matter of placing the sensors, pairing them up with the mobile app and you're off and running. >>Excellent. I like easy. So some of the other use cases? Yeah, absolutely. >>So So we've seen. So Amazon fulfillment centers actually have, um, enormous amounts of equipment you can imagine, you know, the size of an Amazon fulfillment center. 28 football fields, long miles of conveyor belts and Amazon fulfillment centers have started to use Amazon monitor on, uh, to monitor some of their conveyor belts. And we've got a filament center in Germany that has started using these 1000 sensors, and they've already been able to, you know, do predictive maintenance and prevent downtime, which is super costly, you know, for businesses, we've also got customers like Fender, you know, who makes guitars and amplifiers and musical equipment. Here in the US, they're adopting Amazon monitor on for their industrial machinery, um, to help prevent downtime, which again can cost them a great deal as they kind of hand manufacture these high end guitars. Then there's Amazon. Look out for equipment, which is one step further from Amazon monitor on Amazon. Look out for equipment. Um provides a way for customers to send their own sensor data to AWS in order to build and train a model that returns predictions for detecting abnormal equipment behavior. So here we have a customer, for example, like GP uh, E P s in South Korea, or I'm sorry, g S E P s in South Korea there in industrial conglomerate, and they've been collecting their own data. So they have their own sensors from industrial equipment for a decade. And they've been using just kind of rule basic rules based systems to try to gain insight into that data. Well, now they're using Amazon, look out for equipment to take all of their existing sensor data, have Amazon for equipment, automatically generate machine learning models on, then process the sensor data to know when they're abnormalities or when some predictive maintenance needs to occur. >>So you've got the capabilities of working with with customers and industry that that don't have any ML training to those that do have been using sensors. So really, everybody has an opportunity here to leverage this new Amazon technology, not only for predicted, but one of the things I'm hearing is contact list, being able to understand what's going on without having to have someone physically there unless there is an issue in contact. This is not one of the words of 2020 but I think it probably should be. >>Yeah, absolutely. And in fact, that that was some of the genesis of some of the next industrial services that we announced that are based on computer vision. What we saw on what we heard when talking to these customers is they have what we call human inspection processes or manual inspection processes that are required today for everything from, you know, monitoring you like workplace safety, too, you know, quality of goods coming off of a machinery line or monitoring their yard and sort of their, you know, truck entry and exit on their looking for computer vision toe automate a lot of these tasks. And so we just announced a couple new services that use computer vision to do that to automate these once previously manual inspection tasks. So let's start with a W A. W s Panorama uses computer vision toe improve those operations and workplace safety. AWS Panorama is, uh, comes in two flavors. There's an appliance, which is, ah, box like this. Um, it basically can go get installed on your network, and it will automatically discover and start processing the video feeds from existing cameras. So there's no additional capital expense to take a W s panorama and have it apply computer vision to the cameras that you've already got deployed, you know, So customers are are seeing that, um, you know, computer vision is valuable, but the reason they want to do this at the edge and put this computer vision on site is because sometimes they need to make very low Leighton see decisions where if you have, like a fast moving industrial process, you can use computer vision. But I don't really want to incur the cost of sending data to the cloud and back. I need to make a split second decision, so we need machine learning that happens on premise. Sometimes they don't want to stream high bandwidth video. Or they just don't have the bandwidth to get this video back to the cloud and sometimes their data governance or privacy restrictions that restrict the company's ability to send images or video from their site, um, off site to the cloud. And so this is why Panorama takes this machine learning and makes it happen right here on the edge for customers. So we've got customers like Cargill who uses or who is going to use Panorama to improve their yard management. They wanna use computer vision to detect the size of trucks that drive into their granaries and then automatically assign them to an appropriately sized loading dock. You've got a customer like Siemens Mobility who you know, works with municipalities on, you know, traffic on by other transport solutions. They're going to use AWS Panorama to take advantage of those existing kind of traffic cameras and build machine learning models that can, you know, improve congestion, allocate curbside space, optimize parking. We've also got retail customers. For instance, Parkland is a Canadian fuel station, um, and retailer, you know, like a little quick stop, and they want to use Panorama to do things like count the people coming in and out of their stores and do heat maps like, Where are people visiting my store so I can optimize retail promotions and product placement? >>That's fantastic. The number of use cases is just, I imagine if we had more time like you could keep going and going. But thank you so much for not only sharing what's going on with Deep Racer and the innovations, but also for show until even though we weren't in person at reinvent this year, Great to have you back on the Cube. Mike. We appreciate your time. Yeah, thanks, Lisa, for having me. I appreciate it for Mike Miller. I'm Lisa Martin. You're watching the cubes Live coverage of aws reinvent 2020.

>>law from Las Vegas. It's the two covering a ws re invent 2019. Brought to you by Amazon Web service is and in along with its ecosystem partners, >>everyone welcome to the Cubes Live coverage in Las Vegas For AWS Reinvent 2019 starts Seventh year of the Cube coverage. Watching the big wave of Amazon continue to pound the pound the beach with more announcements. I'm John Ferrier instructing the seal for the new ways with my partner, David Dante, our next guest. Brian Hall, vice president. Product market for all of AWS >>Brian. Thanks for coming on. The Cube is >>really a pleasure to be here. We've had ready, eh? We've >>had many conversations off camera around opportunities, innovation and watching Andy Jackson Kino, which is a marathon. Three hours, 30 announcements. He's hit his mark. Live music, well done. But he got a ton of stuff in there. Let's unpack the key points. Tell us what you think people should pay attention to. Of all the announcements, one of the three major or one of the major areas that are that stand out that are most notable that you wanna highlight. >>Okay, I'll give you I'll give you four areas that I think are most notable from the keynote. First is we continue to be very focused on how do we give the deepest and broadest platform for all the different things people want to be able to do with computing. And we had a big announcements around new instance instances of easy to that air based on custom design silicon that that we built one of them is called IMF one. These are instances that are focused on machine learning inference. Where it turns out, up to 90% of the cost for machine learning often is. And so we have. We have a brand new set of instances reduce costs by up to 90% for people doing inference in the cloud. We also last year announced a armed chip that we developed called Graviton, and we announced today grab it on two and that their new instances that are running on gravity on thio, including our general purpose computer instances, are compute intensive instances and high memory instances, and people will get up to 40% price performance improvement by using the instances that are based on the >>method of the messages faster more inexpensive. But also there's an architectural shift going on with Compute Way. Heard that with the I. O. T. And the Outpost stuff where computer is moving to the data because moving around is well recognized and now affirmed its expensive. Yeah, this is a big part of it. You got local zone. What's that local zone? Was it a local >>s? So they're kind of two ways that we're addressing that the first is but making it so that our infrastructure is closer to customers. We have outposts for customers that want to run a WS in their own environments. We announced today local zones which are essentially taking the computer storage database capabilities and putting it closer to metro areas where people want to have a single digit Leighton see for applications when going to the clouds over video rendering for gaming and like, that's gonna be very helpful. Is >>that gonna be like a regional point of presence was gonna be installed, Eleni, on any premise anyone wants, I could put my >>outpost can be put in any environment where you have the right power network infrastructure. Local zones are managed by Amazon, so I don't have to have it. I don't have to manage any data center. Anything. I could just choose to deploy to an environment that is geographically very >>smaller than a region. >>Small isn't an ability. Oh, yeah, >>Right. Okay. That's like a mini zone. Yeah, and and so what about the the availability component? It's sort of up to the customer to figure that out There >>it is connected to a region. So, for instance, we're releasing in Los Angeles with availability now, and that's connected to the US West region. So all of the data backup redundancy application duplication of people want to be able to do could do be done, do the region. >>All right, So graviton processor got onto those early press reports that leaked out prior to reinvent. I noticed that didn't match kind of what was announced. Just clarify what the grab it on ship is doing. What was the key? Grab it on a piece of the news here >>s O gravitas to is a arm based process lor designed and built by a W s. It is powering three different instance. Types are for those who know the types the see instances am instances and are instances on dhe available starting today with M six, which is one of our general purpose computing platforms. And so it gives up to 40% better price performance. And there's a whole ecosystem of platforms and APS Little run unarmed today. >>Are you pushing the envelope on computer? Which is great you continue to do That's the core of jewels of AWS, which we love and storage and everything else. Warm story. I get that a second, but I want your thoughts on the stage maker. A lot of time was spent on stage maker kind of levels of the stack infrastructure, machine, learning stage maker and tools. And a I service is. But the big announcement was this new I d frame environments, not a framework. You're taking an environment like an i d for all the different frameworks. Where did this come from? How I mean so obvious. Now, looking back that no one has this this was a big party announcement. You explain this. >>Yeah. So what you're referring to is sage Makers studio. One of the things that people have really liked about sage maker is it takes the whole process of building a model training a model ended up deploying a model and gives you the steps to do it, but there it hasn't been brought together into one environment before. And so sage maker Studio is a integrated development environment for machine learning that lets you spin up. No books. Run experiments test how your models performing. Deploy your model of detective. Your model is drifting all from one place, which gives me essentially a single dashboard for my whole machine learning work. Look, what do >>you think the impact's gonna be on this? Because if I'm just looking at that obvious awesomeness, it's like, OK, that means anyone can get start using machine learning, you know, be a guru or a total math. >>That's that's fundamentally a lot of what we're doing is trying to reduce the barrier for developers or anyone who has who has a desire to start using machine learning to be able to do that and say, you maker studios just another way that we're doing it. Another one we announced on Monday or on Sunday night, of course, a machine learning powered musical keyboard. Everyone knew that was coming right? That's that's just a example like Deep Racer, where we're taking machine learning. We're making it immediately practical and even fun. And then giving people a way to start experimenting does that they'll eventually become developers who are using machine learning for much >>things. Have a question. As you simplify machine learning, people are concerned about explain ability. You guys, I think, have some ways of helping people understand what's going on inside the algorithm. So that's not a pure black box. Is that correct interpretation? >>It is. It is way announced. Today s age maker experiments, which is one of the one of the things about machine learning, is your kind of constantly tuning the different variables that you're using in your model tow. Understand what works? What doesn't. That's all black box. It's really hard to tell with sage major studio and experiments in particular. Now I can see how models perform differently based on tweaking variables, which starts making it much easier to explain what's happening. >>I think you guys got it right, and he laid out the databases. Multiple databases pick your database. It's okay that multiple databases just create some abstracted layers on top. I totally agree with that philosophy and I think that's gonna be a nice haven for opportunity. We agree. >>Used to be that because so much of running a database was all of the operational expertise it took that you wouldn't wanna have too many databases because that's that many database administrators and people doing the undifferentiated heavy lifting now with the cloud. If you have a data set that's better suited for something like a uh uh, workload in Cassandra, we announced the Manage Cassandra service today. You can just been up that service, load your data and start going. And so it creates a lot more opportunity >>talk about quantum because I know you guys yesterday, which is always a signal from Amazon and didn't make the keynote cut, but a ray relevant quantum announcement, the joke was, is gonna be a quantum supremacy messaging. But no, is more of a humble approach from you guys is more. Hey, we're gonna put some quantum out there setting expectations on the horizon, not over playing your hand on that. But you also have an institute with Caltech humble academic thing going on. What's the quantum inside Inside conversation like an Amazon? What's the what's going on with you. What can we expect? >>We're really excited about what quantum computing's going to be able to do for customers, and we say a lot of Amazon on many things. It's date one, which means it's really early. When we look at Quantum somewhere between zero and one, we're not quite sure where. So just live saying it's really early days. And so what we're doing is providing a platform, a partnership with Caltech, to advance the state of the art and then also a Quantum Solutions lab to help customers start to experiment. To figure out how might. This enabled me to solve problems that I couldn't do before >>you? No one can ask. So Andy talked in a keynote about most of the spend is still on. So the early days of cloud were about, you know, infrastructures of service, storage, computer networking, and it seems like we're entering This era of this data is really sort of the driver where you're applying analytics and machine learning. Data's everywhere, and it seems to be driving sort of new forms of compute. It's not just in this sort of stovepipe anymore. You see that you see that sort of new emergence of new compute were close. >>Yeah. Yeah, we definitely do. And in particular, the way that people are starting to use data lakes, which is essentially a way of saying, Hey, I have my data and one place in a bunch of different formats. And I want different analytical tools, different machine learning tools, different applications toe all be able to build on that same data. And once you do that, you start unlocking opportunities for different application developers, different lines of business to take advantage of it. Brian, >>Thanks for coming on The Cube. Really appreciate your VP of all product. Mark. You get the keys to the kingdom, you kind of see what's going on. Take us home and finish the exit interview out by by talking about the best. Now that Jesse Safer last. The best for last was the outpost G A and the five G wavelength with CEO of Arise on. Yeah, I mean, that's gonna bring five G to stadiums for drones, immersive experiences. I mean, that's a big vision. Yeah, I think it's home >>people. People are rightfully excited about five G for having faster connections, but the thing that we're also very excited about is the fact that all these devices will have much lower laden see and the ability to run interactive applications that having a W s with AWS wavelength hosted with the five G providers is gonna give developers chances to melt. >>Brian Hall with With AWS I'm John David Lot. They were here on the Cube studios, sponsored by Intel's Our Signature sponsors of the Intel's Cube Studios. When it's to a shoutout for Intel to them for supporting our mission, bringing the best content from events and extracting the signal from the noise will be back with more after this short break.

>> from Seattle WASHINGTON. It's the Q covering AWS Imagine brought to you by Amazon Web service is >> Hey, welcome back, You're ready. Geoffrey here with the Cube were in Seattle, >> Washington downtown, right next to the convention center for the AWS. Imagine e d. You show. It's a second year of the show found by Andrew Cohen. His crew, part of Theresa's public sector group, really focused on education. Education means everything from K through 12 higher education and community college education, getting out of the military and retraining education. It's ah, it's a really huge category, and it's everything from, you know, getting the colleges to do a better job by being on cloud infrastructure, innovating and really thinking outside the box are really excited to have the man who's doing a lot of the work on the curriculum development in the education is Ken Eisner is the director of worldwide education programs for AWS. Educate can great to see you. Thank you so much for having absolutely nice shot out this morning by Theresa, she said. She just keeps asking you for more. So >> you want to deliver for Theresa? Carl says she is. She is a dynamo and she drives us >> all she does. So let's dive into it a little bit. So, you know, there was, Ah, great line that they played in the keynote with Andy talking about, You know, we cannot be protecting old institutions. We need to think about the kids is a story I hear all the time where somebody came from a time machine from 17 76 and landed here today. It wouldn't recognize how we talk, how we get around, but they would recognize one thing, and unfortunately, that's the school house down at the end of the block. So you guys are trying to change that. You're really trying to revolutionize what's happening in education, give us a little bit of background on some of the specific things that you're working on today. >> Yeah, I I think Andy, one of the things that he mentioned at that time was that education is really in a crisis on. We need to be inventing at a rapid rate. We need to show that invented simplify inside that occassion. Andi, he's incredibly, he's correct. The students are our customers, and we've got to be changing things for them. What we've been really excited to see is that with this giant growth in cloud computing A W S. It was the fastest I T vendor to ever hit $10,000,000,000 a year. The run rate We're now growing at a 42% or 41% year over year growth Ray and $31,000,000,000 a year Lee company. It's creating this giant cloud computing opportunity cloud computing in the number one Lincoln Skill for the past four years in Rome, when we look at that software development to cloud architecture to the data science and artificial intelligence and data analytics and cyber security rules. But we're not preparing kids for this. Market Gallop ran a study that that showed about 11% of business executives thought that students were prepared for their jobs. It's not working, It's gotta change. And the exciting thing that's happening right now is workforce development. Governments are really pushing for change in education, and it's starting to happen >> right? It's pretty amazing were here last year. The team last year was very much round the community college releases and the certification of the associate programs and trial down in Southern California, and this year. I've been surprised. We've had two guests on where it's the state governor has pushed these initiatives not at the district level, the city level, but from the state winning both Louisiana as well as Virginia. That's pretty amazing support to move in such an aggressive direction and really a new area. >> Yeah, I was actually just moderating a panel where we had Virginia, Louisiana, in California, all sitting down talking about that scaling statewide strategy. We had announcements from the entire CUNY and Sunni or City University of New York and State University of New York system to do both two and four year programs in Cloud Computing. And Louisiana announced it with their K 12 system, their community college system and their four year with Governor John Bel Edwards making the announcement two months ago. So right we are seeing this scaling consortium, a play where institutions are collaborating across themselves. They're collaborating vertically with your higher ed and K 12 and yet direct to the workforce because we need to be hiring people at such a rapid ray that we we need to be also putting a lot of skin in the game and that story that happened so again, I agree with Andy said. Education is at a crisis. But now we're starting to see change makers inside of education, making that move right. It's interesting. I wonder, >> you know, is it? Is it? I don't want to say second tier, that's the wrong word, but kind of what I'm thinking, you know, kind of these other institutions that the schools that don't necessarily have the super top in cachet, you know who are forced to be innovative, right? We're number two. We try harder. As they used to say in the in the Hertz commercial. Um, really a lot of creativity coming out of again the community colleges last year in L. A. Which I was, I was blown away, that kind of understand cause that specifically to skill people up to get a job. But now you're hearing it in much more kind of traditional institutions and doing really innovative things like the thing with the the Marines teaching active duty Marines about data science. >> Yeah, who came up with that idea that phenomenal Well, you know, data permeates every threat. It's not just impure data science, jobs and machine learning jobs. There's air brilliantly important, but it's also in marketing jobs and business jobs. And so on. Dad Analytics, that intelligence, security, cybersecurity so important that you think, God, you Northern Virginia Community College in U. S. Marine Corps are working for to make these programs available to their veterans and active military. The other thing is, they're sharing it with the rest of the student by. So that's I think another thing that's happening is this sharing this ability, all of for this cloud degree program that AWS educate is running. All these institutions are sharing their curricula. So the stuff that was done in Los Angeles is being learned in Virginia is the stuff that the U. S Marine Corps is doing is being available to students. Who are you not in military occupations? I think that collaboration mode is is amazing. The thing they say about community colleges and just this new locus of control for education on dhe. Why it's changing community colleges. You're right there. They're moving fast. These institutions have a bias for action. They know they have to. You change the r A. Y right? It's about preventing students for this work for, but they also serve as a flywheel to those four year institutions back to the 12 into the into the workforce and they hit you underserved audience. Is that the rest? So that you were not all picking from the same crew? You cannot keep going to just your lead institutions and recruit. We have to grow that pipeline. So you thank thank these places for moving quick brand operating for their student, right? >> Right, And and And that's where the innovation happens, right? I mean, that's that's, uh, that that's goodness. And the other thing that that was pretty interesting was, um, you know, obviously Skilling people up to get jobs. You need to hire him. That's pretty. That's pretty obvious and simple, but really bringing kind of big data attitude analytics attitude into the universities across into the research departments and the medical schools. And you think at first well, of course, researchers are data centric, right? They've been doing it that way for a long time, but they haven't been doing it and kind of the modern big, big data, real time analytics, you know, streaming data, not sampling data, all the data. So so even bringing that type of point of view, I don't know mindset to the academic institutions outside of what they're doing for the students. >> Absolutely. The machine learning is really changing the game. This notion of big data, the way that costs have gone down in terms of storing and utilizing data and right, it's streaming data. It's non Columbia or down, as opposed to yeah, the old pure sequel set up right that that is a game changer. No longer can you make just can you make a theory and tested out theories air coming streaming by looking at that data and letting it do some work for you, which is kind of machine learning, artificial intelligence path, and it's all becoming democratized. So, yes, researchers need to need learn these new past two to make sense and tow leverage. This with that big data on the medical center site, there are cures that can be discerned again. Some of our most pressing diseases by leveraging data way gonna change. And we, by the way, we gotta change that mindset, not just yeah, the phD level, but actually at the K 12 levels. Are kids learning the right skills to prepare them for you this new big data world once they get into higher ed, right? And then the last piece, which again we've seen >> on the Enterprise. You've kind of seen the movie on the enterprise side in terms of of cloud adoption. What AWS has done is at first it's a better, more efficient way to run your infrastructure. It's, you know, there's a whole bunch of good things that come from running a cloud infrastructure, but >> that's not. But that's not the end, right? The answer to the question >> is the innovation right? It's It's the speed of change, of speed development and some of the things that we're seeing here around the competitive nature of higher education, trying to appeal to the younger kids because you're competing for their time and attention in there. And they're dollar really interesting stuff with Alexa and some of these other kind of innovation, which is where the goodness really starts to pay off on a cloud investment. >> Yeah, without a doubt, Alexa Week AWS came up with robo maker and Deep Racer on our last reinvent, and there's there's organizations at the K 12 level like First Robotics and Project lead. The way they're doing really cool stuff by making this this relevant it you education becomes more relevant when kids get to do hands on stuff. A W S lowers the price for failure lowers the ability you can just open a browser and do real world hands on bay hands on stuff robotics, a rvr that all of these things again are game changers inside the classroom. But you also have to connect it to jobs at the end, right? And if your educational institutions can become more relevant to their students in terms of preparing them for jobs like they've done in Santa Monica College and like they're doing in Northern Virginia Community College across the state of Louisiana and by May putting the real world stuff in the hands of their kids, they will then start to attract assumes. We saw this happen in Santa Monica. They opened up one class, a classroom of 35 students that sold out in a day. They opened another co ward of 35 sold out in another day or two. The name went from 70 students. Last year, about 325 they opened up this California cloud workforce project where they now have 825 students of five. These Northern Virginia Community College. They're they're cloud associate degree that they ran into tandem with AWS Educate grew from 30 students at the start of the year to well over 100. Now the's programs will drive students to them, right and students will get a job at the end. >> Right? Right, well and can. And can the school support the demand? I mean, that's That's a problem we see with CS, right? Everyone says, Tell your kids to take CS. They want to take CS. Guess what? There's no sections, hope in C. S. So you know, thinking of it in a different way, a little bit more innovative way providing that infrastructure kind of ready to go in a cloud based way. Now we'll hopefully enable them to get more kids and really fulfill the demand. >> Absolutely. There's another thing with professional development. I think you're hitting on, so we definitely have a shortage in terms of teachers who are capable to teach about software development and cloud architecture and data sciences and cybersecurity. So we're putting AWS educators putting a specific focus on professional development. We also want to bring Amazonian, Tze and our customers and partners into the classroom to help with that, because the work based learning and the focus on subject matter expert experts is also important. But we really need to have programs both from industry as well as government out support new teachers coming into this field and in service training for existing teachers to make sure, because yes, we launch those programs and students will come. We have to make sure that were adequately preparing teachers. It's not it's not. It's not easy, but again, we're seeing whether it's Koda Cole out of yeah out of, uh, Roosevelt High School. Are the people that were working with George Mason University and so on were seeing such an appetite for making change for their students? And so they're putting in those extra hours they're getting that AWS certification, and they're getting stronger, prepared to teach inside the clients. >> That's amazing, cause right. Teachers have so many conflict ing draws on their time, many of which have nothing to do with teaching right whether it's regulations. And there's just so many things the teachers have to deal with. So you know the fact that they're encouraged. The fact that they want t to spend and invest in this is really a good sign and really a nice kind of indicator to you and the team that, you know, you guys were hitting something really, really positive. >> Yeah, I think we've had its this foam oh fear of missing out opportunity. There's the excitement of the cloud. There's the excitement of watching your kids. You're really transformed their lives. And it could be Alfredo Cologne who came over from Puerto Rico after Hurricane Maria. You wiped out his economic potential and started taking AWS educate. And you're learning some of these pathways and then landing a job as the Dev Ops engineered. When you see the transformation in your students, no matter what their background is, it is. It is a game changer. This has got to be you. Listen, I love watching that women's team when I win the World Cup, and that the excitement cloud is like the new sport. Robotics is the new sport for these kids. They'll bring them on >> pathways to career, right. We'll take for taking a few minutes in The passion comes through, Andrew Koza big passion guy. And we know Teresa is a CZ Well, so it shines through and keep doing good work. >> Thank you so much for the time. Alright, he's can on Jeff. You're watching the cube. We're in downtown Seattle. A aws. Imagine e d. Thanks for watching. >> We'll see you next time.

live from Las Vegas it's the cube covering AWS reinvent 2018 brought to you by Amazon Web Services Intel and their ecosystem partners okay welcome back and we're live here in Las Vegas day three last interview of the day three days of wall-to-wall coverage two sets here at AWS reinvent 2018 our sixth year we've been at every reinvent except for the first one and it's been great to watch the rise I'm Jeff we're with Dean Volante we're here with Andy Jesse the CEO of AWS started this as it working backwards document years ago twelve years ago 12 half year zine years ago was when the document was written and we've launched 12 and a half years ago great to see you thanks for spending time I know you're super busy congratulations we met last week you couldn't really talk about it but boy there was so much more payload in the announcements than they were before are you happy with the results certainly three our keynote was taxing what's good impression when the keynote was over but ya know we're thrilled with it and most importantly the reason we're thrilled is because our customers are thrilled I think they just couldn't believe how much we delivered this week you know well over 100 capabilities and they were super excited about you know the storage announced was the thing is when you have millions of customers any announcement you make is going to be popular with thousands of customers so some people walked up to me and said oh I know it's not sexy but I love the storage announcements I needed the file systems I wanted that glacier deep archive some customers love the database releases with lots of customers that were excited about the machine learning piece and you know the another unsexy one where the enterprise abstractions just to make it so much easier for that type of builder who wants more prescriptive guidance to be able to get started quicker and then you know people are pretty excited that outpost too so it has you a question I'll talk Amazon speak now what what areas of the show do you feel you raise the bar this year on what was that what would you point to bar raising moments announcements well you know I think each year one of the things I like about reinvent and that we work hard on is we'd like to have we don't really want it to be a corporate event we wanted to be quirky and we want it to be authentic and we want you know we want our community to fit to have fun here while they also learn so you know Midnight Madness is for instance something we do every you know we've done the last couple years and we try radically different things and so I thought that Tatanka eating contest raised the bar is again this year was the second year in a row that we said again as political World Records and you know I thought I really liked Peter De Santis --is and Myrna Vogel's keynotes on Monday and today respectively I thought they both were fantastic and you know keep raising the bar are you over a year and you know so they're you know we're hoping I too will be something that people feel like raise the bar year over year what the house band synchronicity was quite good too you know yeah I tell you that that fan is terrific and you know and I think that again all those things I mentioned are part of what we you know think makes the event fun and quirky and different but the most important thing by far is the learning of the education and then our customers excited about not just the platform but we launched so many things do they feel like it helps them do their job better well while we're on the raising bar we've got a prop here this is the the deep racer deep the deep racer machine learning it's a toy for testing and the question comes up how old do you have to be to use this and I said hey if your kid can code machine learning good for them but talk about this because this is kind of interesting because it's fun but where'd this come from you know it came from last year when we release sage maker and we were making machine learning so much easier for everyday developers of scientists we said what can we do to give people hands-on experience because you learn things better if you actually try it and so we tried to help developers get more experience to computer vision by having a deep lens you know video camera and that was wildly popular and so as we were thinking about this year making reinforcement learning available as easily as we are in sage maker which we think is a huge potential game-changer grant Forsman learning the team kept thinking about it's great but nobody knows enforcement learning and nobody has experienced with it how can we give them experience what are ways they can get hands-on experience and that's how the deep racer car came up which is really making it simple where they can just give us a reward function with a line of Python strip and then Sage Maker will automatically train an RL algorithm and then they get to play it to the car and then race against one another and when we watched how competitive it was getting inside our own house on these RL infused cars racing each other we figured other people might find a compelling as well and I couldn't believe how many people participate yesterday yeah and then I don't know if you saw it three burners right before burners keynote the finals were really exciting to like the fact that there were some imperfections were actually made it more compelling to watch and so we had a racer Cup coming up - I met play 19 competitive yes that's going to happen yeah today was the accelerated version of the first ever deep racer League championship Cup but next year will be a full season at our 20 AWS summits the top winners in the in the deep racers you see bracer League races at each of those summits plus the top 10 vote getters in points from those summits will come here and compete for the championship Cup now you and I talked about a new persona last week when we met but now the announcements pretty clear now why this points to a whole new persona developer you got eSports on the twitch side booming heat sports is changing the game and in the whole digital sports category robotics space you got a satellite announcement this is a genre changed in digital culture and you see the AI stuff and machine learning how does the web services stack play in this new world where AI is now a service it's a whole nother paradigm shift what's your thoughts on all that well you know I mean all those areas that were continuing to expand into our areas that our customers are asking us to help them with and where there are huge opportunities for customers but where it's hard I mean if you look at space as an example if you've to interact with a satellite it's it's expensive to have to have all those satellites set up you know and those drown ground antennas set up and then you have to program them and then and you actually have to pay this fixed price instead of on-demand customers so why can't you give us access those satellites the way we consume AWS and then if you can have the ground antennas where when the data comes down from the satellite it's basically on the same premises as your AWS region so we can store the data and process the data analyze it and take action that is very compelling so that that just felt like a natural fit you know and the same thing with robotics I think that robotics is one of the most underrated areas of Technology I think robots will do all kinds of things for us at work and in a home and the tools out there to make it easy to build robotic applications and to do the simulation to deploy them and then have them work with the rest of your applications and infrastructure have been pretty primitive and so robot maker is I agree with you I think you look at the younger generation too even at the high school elementary level people are gravitating towards robotics robotics clubs are booming that maker culture goes through a whole nother level with robotic congratulation you know it's funny we had the youngest person to ever pass the AWS certification exam is a kid named Karthik nine years old passed and he was here this week actually and I got a chance to meet with him today and I said well after the certification what are you doing he said well I'm building a robot you know I'm feeling Ruben he said now with your launch of deep racer I want to try and find a way to to have the deep racer car be the eyes and the camera and the reinforcement learning for my robot nine years old yes it's gonna be a different generation with what they build John and I were talking this morning Andy at our open about you're making it harder for the critics used to be self-service only it criticized your open source contributions the hybrid strategy your turn a tick in the box is on all those outpost was I think surprised a lot of people it didn't so much surprise us that you were moving in that direction but I wonder if you could sort of talk about some of those key initiatives I know it's customer driven but wow the the TAM expansion the the customer value that you're bringing it's like a whole new era that you're entering yeah you know everything we build is you guys know we talk about all the time it's just it's driven by what customers want and so we just started over the last six months you know and really by virtue of having this partnership with VMware where we have a lot of enterprise engagement as they're moving to the cloud using VMware cloud and AWS we had a bunch of customers say it's really great I'm moving most my application of the cloud but there's some that aren't moving for a while because they got to be close to selling on-premises and I want to use AWS for this I don't want a different environment can you just find a way to put some services like compute and storage on-premises and hardware but I want to actually use the same control plan I'm going to use for the rest of AWS and I wanted to easily connect with the rest of my applications in AWS and we had you know we didn't like as you and I talked about a week or two ago we just have not like the model that's been out there so far to do this because it's you know the control plane is different the api's are different the tools are different the hardware is different the functionality is different and customers don't like it's why it's not getting much traction and we didn't want to pursue it if we didn't think it was going to be useful but we had this concept we were working on with a couple customers where they wanted compute and storage on-premises but they wanted to have that connect with all the other applications in the AWS cloud and so we have this idea that maybe this local set of compute and storage would be like a far zone from an availability zone they were using and we started thinking about that and we thought there was much more generalized idea which became outposts and so the thing that I think people are gonna love about that is for the applications that can't move easily because they need to be close slang on-premises you get AWS like real AWS compute real AWS Storage Analytics database sage maker will be in there as well but it's the same api's same control playing the same tools the same hardware we use in our data centers and it will easily connect through the same control plane to the rest of AWS the rest of the services and the rest of their applications there so and it provides a platform for a whole host of new services down I mean every customer meeting I've had in the last we made the announcement people are excited about I want to ask you guys are talking about all the innovation and new areas and we're seeing an expansion of the AWS distinct brand and things like TV advertising statcast I wonder what's behind that can you address that yeah it's a good question I mean there's kind of two different types of I'll call it TV advert Swartz we're doing one is straight-up advertising one is less so which is you know the one that less so is that a number of the sports leagues are really interested in and actually pretty sophisticated in using cloud computing and analytics and machine learning if you look at Major League Baseball now NFL and Formula One and they want to make the user experience and the viewer experience so much better and so they're building on top of AWS and then we like the ability of helping them showcase the capabilities that they're you know both the customer experience and the ml and AI capabilities then there's just a straight-up advertising them that we've been trying we tried a little bit of it last q4 and you know it's always very difficult to quantitatively measure tvf but we have a lot of ways that we try to triangulate that and we were really surprised and what looked like the positive numbers we saw for both TV as well as the outdoor media and things like in the airports and things like that and so we decided we would try it again this q4 and you know I think I would call us right now still experimenting yeah and it's very much kind of what Amazon does which is we try different things to see what resonates the see Whitefield says so so far so good and we expect to keep experimenting I I think that's a good call because the brand lift is probably there I'll see impressions get reach vehicle but you guys are in a rising tide market we're hearing co-creation VMware co-creating deep meaningful partnerships you always talk about that so it's kind of this success model of innovation to reimagine the satellite Lockheed Martin a partnership this seems to be a new way to do business in this rising tide how are you guys getting the word out education people want to know more this is a big kind of movement yeah well you know I think that if you looked at the first several years of AWS I was always surprised when I would go see enterprises and they would have no idea that Amazon was doing anything in the cloud even though we had the only cloud offering at the time so I think if you compare where we were a few years ago to today there's you know gigantic awareness relatively speaking but I still think that there are so many majority of workloads still live on premises I mean we have a twenty seven billion dollar revenue run rate business it's growing forty six percent year-over-year and yet we're still at the early stages of the meet of enterprise of public sector adoption in the u.s. you go outside the US where there twelve to thirty six months behind depending on the country in the industry and sometimes it feels like you know like Groundhog's Day well you guys are doing regions out there Italy as was announced yeah you're expanding very fast globally can you talk about that real quick yeah it's it's a you know we've had customers from 192 countries using AWS for many many years but they've been using AWS in regions outside of their country usually because there are a lot of workloads that could stand that latency and where the data doesn't have to be on natural soil but increasingly if you want to help customers get done what they want to and serve the broader array of their applications you have to have regions in their country both so that they have lower latency to their end users and because the data sovereignty laws which are getting really more rigid rather than more flexible let me ask you a question about competition you you said I can't members on the cube or in person there's no compression reach out gorilla for experience and time elastic economies with scale when you have copycat people trying to copy Amazon how do you talk about some of those things that are those diseconomies of scale what are the points that customers should look at when they say okay I got someone else is talking cloud Amazon's got years of experience ahead of the competition more services what do you talk about what do you point to you it's not about slimming the competition but what is the diseconomy of scale to try to match the trajectory of Amazon yeah it's it's a bunch of things you know first of all it's operational performance you know a lot of the hardest lessons you learn and operating of scale only happen when you get to that level of scale and you know there's some events that we see sometimes elsewhere we look at that and then we read the post-mortem we say oh yeah 2011 you know we remember they went through that I don't wish it on anybody but when you have a business at several times larger than the next or providers combined you just said a different level of scale and you've learned lessons earlier I also think that the reason that we continue to have both so much more functionality and innovate at a faster clip and seem to get capabilities that customers want is because we have so many more customers than anybody else you know a lot of times and this is happening all week to where customers will say to me I can't believe that you knew that I wanted that and I always say it's because you told us yeah it's not like we're Nostradamus you've told us that and so when you have so many more customers and when they feel free to give you feedback and when you've built good mechanisms like we have to get that feedback from the field to the product builders it means there's this real flywheel of getting you know getting more customers leads to more feedback leads to more features leads to better functionality where there's a network effect from being on the platform with all those other customers and all those industries I wonder if you could add some color to a premise that we've put forth on your edge strategy so what you guys you know we do a lot of these shows and a lot of the IOT and edge strategies that we've seen from traditional IT players what you call the old guard have fallen flat in our opinion because it's a top-down approach it reminds us of the Windows Phone it just didn't work and it's not going to work as their operations technologies people we see what you've announced here as a Bottoms Up approach you developing an application platform to build secure and manage apps for those folks right at the edge I wonder if you could add some color to that and some thoughts on your edge strategy yeah I mean again for us if we don't have some top-down strategy that you know that I think is grandiose it's just what customers want and so we have so many customers who have all these devices at the edge and all these assets at the edge and they said to us well the first problem I have I want to get this data into the cloud and then I want to do analytics item we say ok well how can we help they say well the first thing is I don't even know how to translate this data from the device protocol to just being able to operate in the cloud so that's the first problem we go solve well then people say ok now I can get it in but I actually I need security like you know if you look at the amount of security options for these edge devices it's a new field you know let that dine attack that took a lot of the internet down a couple years ago came from you know a device on the edge and so that's why you know we built you know a security capability and people say well okay now you've made it so I can run devices but if I'm gonna run thousands of devices I need a way to manage all those devices of scale and we build telling to manage two devices and people say well ok it's great that I can do it and device is big enough that have a CPU but what about when they don't have a CPU you know they have just a microcontroller and that's why we built the our toss piece and you know the list kind of keeps going people so this is great now that I get all this data in the cloud I can take all these analytics actions but on my device sometimes I don't want to make the round trip to the cloud so can you give me a way to use the same programming model and and pick which triggers I want to take action with cloud versus those that want to take on the device itself which was what green grass was so all of those pieces is not some kind of top-down master plan as much as we know that customers have all these devices the edge that they want to use that data analyze that data take action on that data and send it back in multiple ways and you have you have the cloud platform to give them the services to make the tools the right tools for the right job yeah that's the main team yeah so I got to ask you about one of the big controversies that we don't think that's that controversial but the chips that you announced new Amazon Web Services front microprocessors the chips yeah do two of them talk about them and Intel's also a partner a lot of people are talking about this in the press yeah Intel Amazon chips well that annapurna acquisition is Norton they bear fruit was 2015 I think yeah early it really the annapurna team is fantastic and they've added a huge amount of value to AWS and Amazon as a whole you know the first thing I would say is that Intel is a very deep partner of AWS and will be for a long time I mean that that's not changing and we've been a long thought that they were gonna be lots of different processors out there and and different ones that did different things at different price points and so like a lot of other companies we've been interested in arm for a long time and for a while it wasn't mature enough and the technology is matured and we found a way in in building our own ARM chip with graviton where we think we can allow customers to run a lot of their scale out generalize were close but up to 45 percent less expensively and so when you find a value proposition that compelling for customers you need to do it and you know as I mentioned in the keynote yesterday when we were talking about inference we feel like a lot of the world has been solvent for training and not solvent as much for inference yet and we've made training so much easier with the things that we've built in AWS over the last couple years but inferences where most of the cost is gonna be and so elastic inference we think it you know will allow people to be much more efficient in how they use them for use and how they spend money but when you've got the type of workloads at scale and productions that use whole GPUs or that need that low latency where you need it on the hardware of a chip that's optimized for inference they is faster that's more cost effective that's high throughput we can get hundreds of tops on it and thousands to you ban them together he's gonna totally change the game for imprison and so that was something that wasn't easy for us to find elsewhere and when we have team fortunately they could build it and it's the combination of the elastic service of inference with the chip that makes the difference it specialism there so it's not like I mean you can use each on their own and we expect they'll be a bunch of customers who will use each on their own but there will be an opportunity to use those in combination that will be very powerful it comes down to really deeply understanding the customer problem again at night training versus inference and everybody talks about the training right the the technical challenge you got a child is the internet and tells gonna make a lot of money as it stands expanding market banding so they'll get their share the chips get taped out their con a couple year to three year life cycles and everything starts anew every time somebody's building a new chip so I think it's actually great for customers of all sorts that there's multiple processors that are possible but we will have a deep relationship with Intel forever I think so I want to talk about one of the cool demos you did on stage not a lot you did customer did f1 that was a super cool I love that imagery because it said an analogy of high performance competitive racing that can be applied to this play sports anything and the level of accuracy that they need in the real time time series kind of encapsulates a lot of the cloud value talk about the f1 analytic thing are you guys gonna sponsor these events there's a relationship there give us what the picture of what's going on there you have a deep relationship with Formula One where they're using our platform to to do their all their digital properties as well as their analytics and machine learning and it was super cool to see Ross demo the way that they're changing the user experience for for viewers and you know it's it's it's an amazing sport you know it's not watched as much maybe in the US but outside the US that is the motorsport and the way that they're changing the experience the way that they're able to assess what's happening with drivers and with cars and then predict what's actually happening and make the viewer feel like they're actually either in the cockpit or actually in the pit itself with it with the crew is it's really exciting and it's non err to be a partner so you do some events they'll get the cube they're these these big time again there's a tech angle now and everything it's a plug for you to be at the they have one event cloud demócrata you're hitting now new industries I mean this is the thing right I mean it's disrupting every industry I mean what aren't you disrupting I mean what areas do you see that yet aren't coming online to the cloud I don't see industry segments at this point that aren't moving to the cloud I would have told you 18 to 24 months ago that I felt like financial services was moving a lot more slowly than then I thought they should or you know probably healthcare also was a little bit slower but both of those industry segments are moving very aggressively well it's taking longer they're high-risk industries and the digital transformation has it occurred fast enough but it's coming and there's regulatory pieces that they legitimately have to sort through and you know we have just if you look at financial services as an example we have a pretty significant team that does nothing but work with our partners to help them with the regulatory bodies because what we find is when we go with a customer to a regulator and show them a real use case and then how it will be done in a DOP is the regulator says oh well that's more secure that you do on-premises and so it's just an education process and you know I think that's been helpful in it and I'll get final questions for you what have you observed here at reinvent Houston glad people talking so you get a lot of feedback actually to clopped two-part question because I was asked the final final question so I'll just get it out front what are people missing of all the announcements you've had a lot of signal in there a lot of a lot of announcements what are what is something that you've observed that you think should be amplified that people might have not overlooked but like you feel like it's more important to sign the light on we'll start with that one well you know it's a little hard for me to tell this moment just because there have been so many in such a short amount of time and and if we just look a little bit at the coverage it seems and if I take just as inputs they comments and and the questions from customers it's been pretty broadly understood and people are pretty excited and as I said different segments have kind of their favorite areas but I feel like people are pretty excited by the breadth of capabilities you know I think that if I pick two in particular I would say that people are still in the machine learning space people are blown away by how much we provided are all three layers of the stack I think people are still getting their heads around which layer of the stack am I gonna participate at you know I mean the one that probably has the most potential for most companies is that middle layer because most companies have gobs of data and there are jewels in that data and if you can enable their developers their everyday developers to be able to build models and get at the predictive value and add value that has huge impact for companies moving forward but most modern companies with technology functions will use all three layers of the stack and so just getting their arms around which layers of the stack they should take advantage of first and having the personnel to be able to do it and we're making that much easier with things like sage maker and then you know I think if you look at the blockchain space I think that that is just one of those spaces that has a huge amount of buzz people talk a lot about it exactly sure sometimes what they're gonna do but but I also think that a lot of people said to us that breaking those into those two real customer jobs to be done and then having a great solution that does each of those jobs really well is not only something that AWS does all the time that makes it easier for them but it also made it easier for a lot of them to understand that a lot of customers said to us you know that qld be that ledger database with a single trust of central authority for my supply chain that's what I need for my supply chain I don't need all the complexity of a blockchain framework and then there were a lot of other people said oh yeah that is what I want I wanted to decentralize trust between peers but I just needed a way easier way to manage hyper ledger fabric and etherium so I think those are two that people like are so interested and still figuring out how to use as expansively as I think they hope they will Andy thanks so much for your time and I want to just say watching you guys in the past six years has been a fun journey together but watching the execution you guys have done an amazing job of keeping your eye on the ball and being humble but being proud and loud at the same time so congratulations and you know guns blaring in 2019 what's your top pray all right besides listening to the customers what's your top 20 19 we know you listen to cut oh my gosh we have so many things that we're doing in 2019 but you know we have a lot of delivery in front and in front of us I mean as much as we launched 140 unique things over the last six to eight business days and yet I tell you to stay tuned the rest of 2018 we have more coming and then in nineteen you'll you should expect to see more few capabilities more database capabilities more machine learning capabilities more analytics capability look a lot I could spend all night John we don't need it we don't need a post reinvent post you know traumatic announcements syndrome because just to digest it all yeah it's a lot of work looking forward to seeing how enterprises continue to make to to kind of manage their hybrid approach as they're as they're making this trend transition from on-premises to the cloud how many continue to jump on to VMware cloud an AWS how many jump onto outpost so I think that that transition and helping customers do that easily is something on here of course we'll be commentating and pontificating on that for the next year thanks for your time I really should have me and I appreciate that you guys come at regular pay our pleasure okay winding down that's the last interview here wall to wall covers two cents 110 interviews in the books we'll have 500 video assets total blog post on Sylvia angle calm that's reinvent closing down 2018 thanks for watching [Music]

(upbeat music) >> Live from Las Vegas, it's theCUBE covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, and their ecosystem partners. >> Okay, welcome back everyone. Live coverage here in Las Vegas for Amazon re:Invent 2018. Day three, we're winding down over 150 videos. We'll have over 500 clips. Losing the voice. Dave Vellante, my co-host. Suzi analyst tech that we're going to extract theCUBE insights, James Kobielus. David Floyer from Wikibon. Jim you've been prolific on the blogs, Siliconangle.com, great stories. David you've got some research. What's your take? Jim, you're all over what's going on in the news. What's the impact? >> Well I think what this years re:Invent shows is that AWS is doubling down on A.I. If you look at the sheer range of innovative A.I. capabilities they've introduced into their portfolio, in terms of their announcements, it's really significant. A. They have optimized tense or flow for their cloud. B. They now have an automated labeling, called Ground Truth, labeling capability that leverages mechanical turf, which has been an Amazon capability for a while. They've also got now the industries first, what's called reinforcement learning plug-in to their data science tool chain, in this case Sage Maker, reinforcement learning is becoming so important for robotics, and gaming, and lots of other applications of A.I., and I'm just scratching the surface. So they've announced a lot of things, and David can discuss other things, but I'm seeing the depth of A.I. Their investment in it shows that they've really got their fingers on what enterprises are doing, and will be doing to differentiate themselves with this technology over the next five to ten years. >> What's an area that you see that people are getting? Clearly A.I. What areas are people missing that's compelling that you've observed here? >> When you say people are missing, you mean the general...? >> Journalists. >> Oh. >> Audience. There's so much news. >> Yeah. Yeah. >> Where are the nuggets that are hidden in the news? (laughing) What are you seeing that people might not see that's different? >> Getting back to the point I was raising, which is that robotics is becoming a predominant application realm for A.I. Robotics, outside the laboratory, or outside of the industrial I.O.T., robots are coming into everything, and there's a special type of A.I. you build into robots, re-enforcement learning is a big part of it. So I think the general, if you look at the journalists, they've missed the fact that I've seen in the past couple of years, robotics and re-enforcement learning are almost on the verge of being mainstream in the space, and AWS gets it. Just the depth of their investments. Like Deep Racer, that cute little autonomous vehicle that they rolled out here at this event, that just shows that they totally get it. That will be a huge growth sector. >> David Floyer, outpost is their on premises cloud. You've been calling this for I don't know how many years, >> (laughing) Three years. >> Three years? >> Yeah. What's the impact? >> And people said, no way Foyer's wrong (laughing). >> So you get vindication but... >> And people, in particular in AWS. (laughing) >> So you're right. So you're right, but is it going to be out in a year? >> Yeah, next in 2019. >> Will this thing actually make it to the market? And if it does what is the impact? Who wins and who loses? >> Well let's start with will it get to the market? Absolutely. It is outposts, AWS Outposts, is the name. It is taking AWS in the cloud and putting it on premise. The same API's. The same services. It'll be eventually identical between the two. And that has enormous increase in the range, and the reach that AWS and the time that AWS can go after. It is a major, major impact on the marketplace, puts pressure on a whole number of people, the traditional vendors who are supplying that marketplace of the moment, and in my opinion it's going to be wildly successful. People have been waiting that, wanting that, particularly in the enterprise market. They reasons for it are simple. Latency, low latency, you've got to have the data and the compute very close together. Moving data is very, very expensive over long distances, and the third one is many people want, or need to have the data in certain places. So the combination is meeting the requirements, they've taken a long time to get there. I think it's going to be, however wildly successful. It's going to be coming out in 2019. They'll have their alpha, their betas in the beginning of it. They'll have some announcements, probably about mid 2019. >> Who's threatened by this? Everybody? Cisco? HP? Dell? >> The integration of everything, storage, networking, compute, all in the same box is obviously a threat to all suppliers within that. And their going to have to adapt to that pretty strongly. It's going to be a declining market. Declining markets are good if you adapt properly. A lot of people make a lot of money from, like IBM, from mainframe. >> It's a huge threat to IBM. >> You're playing it safe. You're not naming names. (laughing) Okay, I'll rephrase. What's your prediction? >> What's my prediction on? >> Of the landscape after this is wildly successful. >> The landscape is that the alternatives is going to be a much, much smaller pie, and only those that have volume, and only those that can adapt to that environment are going to survive. >> Well, and let's name names. So who's threatened by this? Clearly Dell, EMC, is threatened by this. >> HP. >> HP, New Tanix, the VX rat guys, Lenovo is in there. Are they wiped out? No, but they have to respond. How do they respond? >> They have to respond, yeah. They have to have self service. They have to have utility pricing. They have to connect to the cloud. So either they go hard after AWS, connecting AWS, or they belly up to Microsoft >> With Azure Stack, >> Microsoft Azure. that's clearly going to be their fallback place, so in a way, Microsoft with Azure Stack is also threatened by this, but in a way it's goodness for them because the ecosystem is going to evolve to that. So listen, these guys don't just give up. >> No, no I know. >> They're hard competitors, they're fighters. It's also to me a confirmation of Oracle's same same strategy. On paper Oracle's got that down, they're executing on that, even though it's in a narrow Oracle world. So I think it does sort of indicate that that iPhone for the enterprise strategy is actually quite viable. If I may jump in here, four things stood out to me. The satellite as a service, was to me amazing. What's next? Amazon with scale, there's just so many opportunities for them. The Edge, if we have time. >> I was going to talk about the Edge. >> Love to talk about the Edge. The hybrid evolution, and Open Source. Amazon use to make it easy for the enterprise players to complete. They had limited sales and service capabilities, they had no Open Source give back, they were hybrid deniers. Everything's going to go into the public cloud. That's all changed. They're making it much, much more difficult, for what they call the old guard, to compete. >> So that same way the objection? >> Yeah, they're removing those barriers, those objections. >> Awesome. Edge. >> Yeah, and to comment on one of the things you were talking about, which is the Edge, they have completely changed their approach to the Edge. They have put in Neo as part of Sage Maker, which allows them to push out inference code, and they themselves are pointing out that inference code is 90% of all the compute, into... >> Not the training. >> Not the training, but the inference code after that, that's 90% of the compute. They're pushing that into the devices at the Edge, all sorts of architectures. That's a major shift in mindset about that. >> Yeah, and in fact I was really impressed by Elastic Inference for the same reasons, because it very much is a validation of a trend I've been seeing in the A.I. space for the last several years, which is, you can increasingly build A.I. in your preferred visual, declarative environment with Python code, and then the abstraction layers of the A.I. Ecosystem have developed to a point where, the ecosystem increasingly will auto-compile to TensorFlow, or MXNet, or PyTorch, and then from there further auto-compile your deployed trained model to the most efficient format for the Edge device, for the GP, or whatever. Where ever it's going to be executed, that's already a well established trend. The fact that AWS has productized that, with this Elastic Inference in their cloud, shows that not only do they get that trend, they're just going to push really hard. I'm making sure that AWS, it becomes in many ways, the hub of efficient inferencing for everybody. >> One more quick point on the Edge, if I may. What's going on on the Edge reminds me of the days when Microsoft was trying to take Windows and stick it on mobile. Right, the windows phone. Top down, I.T. guys coming at it, >> Oh that's right. >> and that's what a lot of people are doing today in IT. It's not going to work. What Amazon is doing see, we're going to build an environment that you can build applications on, that are secure, you can manage them from a bottoms up approach. >> Yeah. Absolutely. >> Identifying what the operations technology developers want. Giving them the tools to do that. That's a winning strategy. >> And focusing on them producing the devices, not themselves. >> Right. >> And not declaring where the boundaries are. >> Spot on. >> Very very important. >> Yep. >> And they're obviously inferencing, you get most value out of the data if you put that inferencing as close as you possibly can to that data, within a camera, is in the camera itself. >> And I eluded to it earlier, another key announcement from AWS here is, first of all the investment in Sage Maker itself is super impressive. In the year since they've introduced it, look at they've already added, they have that slide with all the feature enhancements, and new modules. Sage Maker Ground Truth, really important, the fully managed service for automating labeling of training datasets, using Mechanical Turk . The vast majority of the costs in a lot of A.I. initiatives involves human annotators of training data, and without human annotated training data you can't do supervised learning, which is the magic on a lot of A.I, AWS gets the fact that their customers want to automate that to the nth degree. Now they got that. >> We sound like Fam boys (laughing). >> That's going to be wildly popular. >> As we say, clean data makes good M.L., and good M.L. makes great A.I. >> Yeah. (laughing) >> So you don't want any dirty data out there. Cube, more coverage here. Cube insights panel, here in theCUBE at re:Invent. Stay with us for more after this short break. (upbeat music)