>>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.

>> Announcer: Live from Las Vegas, it's theCUBE covering AWS re:Invent 2019. Brought to you by Amazon Web Services and Intel along with its ecosystem partners. >> Okay, welcome back to theCUBE, everyone. We're live in Las Vegas for AWS exclusive coverage of Amazon Web Services re:Invent 2019. I'm John Furrier with Stuart Miniman. Want to thank Intel for sponsoring our two sets. Shout-out to them for the sponsorship bringing great content to you from SiliconANGLE. Our next guest is with the NFL, and Andy Jassy just consummated a deal here in Las Vegas with Roger Goodell, the commissioner of the National Football League, on a new strategic initiative to use next gen stats, Amazon cloud, that whole data infrastructure with the NFL to change the profile and posture for safety and for all the athletes. And the guest here, we have Dr. Jeff Crandall, who's the chairman of the NFL Engineering Committee. Thanks for coming on. >> Thanks for having me. >> So I saw your guys' speech up there as part of the announcement with Dr. Matt Wood and a fellow NFL executive. This is a really cool initiative, because the NFL, you guys have a lot of data geeks there. You have an enormous amount of data. We see stat tasks and next gen stats from Amazon on TV. There's been a lot of advertising dollars doing that. Pretty cool. You're taking it to a next level. Explain the program you're doing. It's got $300 million in funding behind it. You started three years ago. Take a minute to explain. >> Sure, I think one of the things, it's $100 million, but-- >> Okay. >> Not quite $300 million yet. But if you look at it, it was part of an initiative the league developed to say what could they do about safety. I think part of the thing that not everyone recognizes is what the NFL does for safety and innovation, how much effort they put into that. So I'm part of an engineering effort called the engineering road map, and really what we want to do there is we thought there was an opportunity to transform the space for head protection by us putting our understanding in, creating tools, we could help those in the market develop better equipment and better protect our players. >> And so one of the things I'm learning is that you guys have tons of data, and I learned a fun stat that the fastest runner this year was running at, what, 22 miles an hour. >> Jeff: Yeah. >> But you guys are collecting a lot of data from the equipment, surface, everything. Can you explain some of the insight into the data collection, specifically the amount and diverse types. >> Yeah, that's one of the things that we've learned is in order to make effective interventions, you really have to have a handle on the breadth of what's going on on field, and in order to do that, it's a very fast, dynamic game, so you'd have to have a number of data sources coming in. You need to know about the game itself, the plays, the position, the particular play types. You need to know about the players. What speed, what's their position, what orientations, what routes. And then their environment, the surfaces, the equipment. What helmets are they wearing, what shoes. So we're trying to say what we have for extrinsic factors, what's in the environment, and then the intrinsic factors, what do the players themselves experience for factors. >> We know that data can be a differentiator, but it sounds like data like this will help the entire ecosystem. Can you speak a little bit to the medical community, the equipment manufacturers, the teams that have to build new stadiums. We've interviewed some of the architects that put a lot of technology into the stadiums themselves. So how does that data flow happen? >> Yeah, that's one of the things. We have so much data that we're able to create sort of an evaluation of what's happening to the players and what they're experiencing. And I think very few other sports, even, or very few other applications have that level of quantification. And so what we're looking at is how do each of those factors contribute to how players train, how players perform, how players are injured. And so by having that, we can come up with something we've called the digital athlete, which is essentially a virtual representation. And through that virtual representation, we start to understand how any of these factors influence the dimensions of performance and injury. It scales broadly to anything where the body would be stressed or loaded or trained. Any of those applications could benefit from what we're doing. >> So your simulation, that's a digital twin in parlance of IT nerds here. >> Sure. >> But this is a really killer idea because you can do many simulations that the cloud will provide, right? >> Jeff: Sure. >> I mean, and you got video to match it. So talk about that dynamic. 'Cause you got video and you got data points. >> Jeff: Yeah. >> They're kind of working together. >> Exactly. And so I think if you want to take the digital twin analog, I mean, one of the unique things about that is that you can have this virtual representation and you get this continuous input of feeds from sensors, from video, and you start to refine what that digital twin looks like, whether it's a player or whether it's a mechanical device. And the more feeds and the more data you have and the more time goes on, the better represented that is. And so that's really what we're gearing towards. >> Yeah, one of the things I abstracted out of the presentation was honestly, the head injuries, helmet, that's clear. That's got to get done. You're working hard around that. But there was a mention of lower body injuries, as well. So it's not just head. There's other things you guys are thinking about. Can you expand on what that might look like and how you guys are thinking about it? >> Sure, I mean, obviously we want to make sure whole body, head to toe, we're protecting the players the best we can. I think if you look from an injury frequency or an injury burden standpoint, time lost for players, lower limb is one of the major injuries in that calculation. And so what we're doing is we've been working on concussions and helmets for the last three or four years. We've been working on cleats and turf for a long time. We're starting to curate that data, and that will go into our digital twin, digital athlete platform. >> It's like they're having LIDAR. It's like when my car backs up and stops, maybe when there's a rollover coming over, an alert kicks the leg around the right spot. But this is what, the kind of thing you guys are thinking about, the rule changes and the innovation and safety is, you can actually make direct impact. So there was a rule change on kickoffs. >> Jeff: Sure. >> Talk about that dynamic, 'cause this is kind of a teaser of where things might go, right? >> Yeah, exactly. I think if you look at injury prevention, they obviously talk about where can you change? You can do it with engineering, you can do it with education, or you can do it with enforcement or rules. And what we've learned is that we can take the data we're gathering and do data-driven initiatives on any of those. We've done a kickoff rule that was informed by data. We've done a use of helmet, leading with the helmet rule. So I think the same underlying data leads to any of these application areas. >> And the results just on the numbers. You guys quoted some stats. What was the reduction in concussions last year? >> Last year there was a reduction in games of 29% for concussions. >> Awesome. >> That's great. I've been watching a lot of the 100-year football anniversary here, and it's evident how much technology has been having an impact. Gives us a little bit of how the AWS and NFL, where we'll see that going in the coming decades and beyond. >> So I think historically, we've had very strong medical, we've had very strong engineering. What we've been seeing, though, is we've been doing a lot of stuff manually. It's been very labor-intensive. We've had some wins and successes, as you just heard from last year, but now we're looking to scale and accelerate that. So building on what AWS brings to the table in terms of their data analytics, their cloud computing. We believe we can do a better job understanding what's happening on field and lead to interventions and innovations much more quickly, much more broadly than currently exist. >> For the folks watching, we're here at an IT show or cloud show. You guys are immersed in data, so you're leaning on AWS for a lot of the expertise on scale, machine learning. They got a lot of goodness in their portfolio, but you guys have the data. So for other companies that are looking at this transformation with the top-down leadership model that you guys have, what have you learned? What is some of the scar tissue you might have from the process you've been through? Any observations or learnings you could share around the order of magnitude, approaches. Is there some paths that you'd recommend? >> Well, I think one of the things we've learned is there's a hard way and there's a more efficient way. We've had as many as 17 people looking at videos, and it led us to believe, we've looked at more than 100,000 helmet impacts manually. There's got to be a better way. And so we actually spent two years talking with tech companies, exploring what was out there, before we came to this AWS partnership. So I think when we look at the future and look at the opportunities, I would say where we were bounded previously and we were looking at maybe an immediate horizon, now what we've said is let's wipe the slate clean. Let's see where we want to end up far into the future. Let's look at what we would build, something to be scalable that we could leverage. >> And this is a pretty significant announcement, 'cause Roger Goodell was here with Andy Jassy. So it's not just a tech deal. This is a bigger play here. >> Jeff: Yeah. >> Can you give some insight into the strategic impact of the AWS-NFL piece? >> So AWS has had a relationship with the league, and one of the primary things they've done is the next gen sport, the next gen stats, rather, tracking player motion on field. You know, you've seen a lot of the stats that come up in games. And so there was an idea how we could take data, leverage it. That was more for fan engagement. But that very same information, we've looked at collisions. We take next gen stats data with two players coming together. What's the closing velocity? What are the closing angles? And so I think what you've seen is how you can take this wealth of data in the NFL and by taking those that are sort of best in class and innovators with the data analytics and machine learning, what else can you extract from the data that may not have been evident without sort of a broader computing platform. >> You know, a lot of people look at the NFL. They see the big networks who cover the sport for the fan experience. There's kind of a nerd culture going on with NFL and the fan base. We've been hearing feedback all the time about theCUBE becoming a broadcaster for NFL. Has that been kicked around at Roger's level yet? (Jeff laughs) Has it gotten there? >> Well, I was thinking of doing digital twins of you guys. (John laughs) I was just sizing it up. But I'm not sure we're quite there yet. >> Dr. Crandall, thank you so much for coming on. Congratulations. What a great initiative. You guys are being transparent, forthright with your research. It's open. Congratulations. It's a good step. >> Great. My pleasure. Appreciate it. >> Thanks for coming on. I'm John Furrier, Stuart Miniman, with the NFL here as part of the big announcement on Thursday with Andy Jassy and the commissioner of the NFL, Roger Goodell, it's theCUBE getting you all the action here at re:Invent. We'll be right back with more after this short break. 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la from Las Vegas it's the cube covering AWS reinvent 2019 brought to you by Amazon Web Services and in care along with its ecosystem partners hey welcome back everyone cubes live coverage of eight of us reinvent 2019 this is the cube seventh year covering Amazon reinvent it's their eighth year of the conference and want to just shout out to Intel for their sponsorship for these two amazing sets without their support we would be able to bring our mission of great content to you I'm John Force to many men we're here with the chief of AWS the chief executive officer Andy chassis tech athlete and himself three our keynotes welcome to the cube again great to see you great to be here thanks for having me guys congratulations on a great show a lot of great buzz thank you a lot of good stuff your keynote was phenomenal you get right into you giddy up right into as you say three hours 30 announcements you guys do a lot but what I liked the new addition in the last year and this year is the band house man yeah they're pretty good they hit the Queen note so that keeps it balanced so we're going to work on getting a band for the cube awesome so if I have to ask you what's your walk-up song what would it be there's so many choices depends what kind of mood I'm in but maybe times like these by the Foo Fighters these are unusual times right now Foo Fighters playing at the Amazon intersect show they are Gandy well congratulations on the intersect you got a lot going on intersect is the music festival I'll get that in a second but I think the big news for me is two things obviously we had a one-on-one exclusive interview and you laid out essentially what looks like was gonna be your keynote it was transformation key for the practice I'm glad to practice use me anytime yeah and I like to appreciate the comments on Jedi on the record that was great but I think the transformation story is a very real one but the NFL news you guys just announced to me was so much fun and relevant you had the Commissioner of NFL on stage with you talking about a strategic partnership that is as top-down aggressive goals you could get yeah I have Roger Goodell fly to a tech conference to sit with you and then bring his team talk about the deal well you know we've been partners with the NFL for a while with the next-gen stats are they using all their telecasts and one of the things I really like about Roger is that he's very curious and very interested in technology in the first couple times I spoke with him he asked me so many questions about ways the NFL might be able to use the cloud and digital transformation to transform their various experiences and he's always said if you have a creative idea or something you think that could change the world for us just call me is it or text me or email me and I'll call you back within 24 hours and so we've spent the better part of the last year talking about a lot of really interesting strategic ways that they can evolve their experience both for fans as well as their players and the player health and safe safety initiative it's so important in sports and particularly important with the NFL given the nature of the sport and they've always had a focus on it but what you can do with computer vision and machine learning algorithms and then building a digital athlete which is really like a digital twin of each athlete so you understand what does it look like when they're healthy what and compare that when it looks like they may not be healthy and be able to simulate all kinds of different combinations of player hits and angles and different plays so that you can try to predict injuries and predict the right equipment you need before there's a problem can be really transformational so it was super excited about it did you guys come up with the idea it was the collaboration between there's really a collaboration I mean they look they are very focused on player's safety and health and it's it's a big deal for their you know they have two main constituents that the players and fans and they care deeply about the players and it's a it's a hard problem in a sport like football but you watch it yeah I gotta say it does point out the use cases of what you guys are promoting heavily at the show here of the stage maker studio which is a big part of your keynote where they have all this data right and they're dated hoarders they've the hoard data but they're the manual process of going through the data it was a killer problem this is consistent with a lot of the enterprises that are out there they have more data than they even know so this seems to be a big part of the strategy how do you get the customers to actually a wake up to the fact that they got data and how do you tie that together I think in almost every company they know they have a lot of data and there are always pockets of people who want to do something with it but when you're gonna make these really big leaps forward these transformations so things like Volkswagen is doing with they're reinventing their factories in their manufacturing process or the NFL where they're gonna radically transform how they do players health and safety it starts top-down and if they if the senior leader isn't convicted about wanting to take that leap forward and trying something different and organizing the data differently and organizing the team differently and using machine learning and getting help from us and building algorithms and building some muscle inside the company it just doesn't happen because it's not in the normal machinery of what most companies do and so it all wait almost always starts top-down sometimes it can be the commissioner or the CEO sometimes it can be the CIO but it has to be senior level conviction or it does get off the ground and the business model impact has to be real for NFL they know concussions hurting their youth pipelining this is a huge issue for them is their business model they they lose even more players to lower extremity injuries and so just the notion of trying to be able to predict injuries and you know the impact it can have on rules the impact it can have on the equipment they use it's a huge game changer when they look at the next 10 to 20 years all right love geeking out on the NFL but no more do you know off camera a 10 man is here defeated season so everybody's a Patriots fan now it's fascinating to watch you and your three-hour keynote Vernor in his you know architectural discussion really showed how AWS is really extending its reach you know it's not just a place for a few years people have been talking about you know cloud as an operation operational model it's not a destination or a location but I felt that really was laid out is you talked about breadth and depth and Verna really talked about you know architectural differentiation people talk about cloud but there are very there are a lot of differences between the vision for where things are going help us understand and why I mean Amazon's vision is still a bit different from what other people talk about where this whole cloud expansion journey but put over what tagger label you want on it but you know the control plane and the technology that you're building and where you see that going well I think that we've talked about this a couple times we we have two macro types of customers we have those that really want to get at the load level building blocks and stitch them together creatively and however they see fit to create whatever is in there in their heads and then we have this second segment of customers who say look I'm willing to give up some of that flexibility in exchange for getting 80% of the way they're much faster in an abstraction that's different from those low level building blocks in both segments of builders we want to serve and serve well and so we built very significant offerings in both areas I think when you look at micro services you know some of it has to do with the fact that we have this very strongly held belief born out of several years at Amazon where you know the first seven or eight years of Amazon's consumer business we basically jumbled together all of the parts of our technology and moving really quickly and when we wanted to move quickly where you had to impact multiple internal development teams it was so long because it was this big ball this big monolithic piece and we got religion about that and trying to move faster in the consumer business and having to tease those pieces apart and it really was a lot of the impetus behind conceiving AWS where it was these low-level very flexible building blocks that don't try and make all the decisions for customers they get to make them themselves and some of the micro services that you saw Verner talking about just you know for instance what we what we did with nitro or even what we do with firecracker those are very much about us relentlessly working to continue to to tease apart the different components and even things that look like low-level building blocks over time you build more and more features and all of a sudden you realize they have a lot of things that are they were combined together that you wished weren't that slowed you down and so nitro was a completely reimagining of our hypervisor and virtualization layer to allow us both to let customers have better performance but also to let us move faster and have a better security story for our customers I got to ask you the question around transformation because I think it all points to that all the data points you got all the references goldman-sachs on stage at the keynote Cerner and the healthcare just an amazing example because I mean this demonstrating real value there there's no excuse I talked to someone who wouldn't be named last night and then around the area said the CIA has a cost bar like this cost up on a budget like this but the demand for mission based apps is going up exponentially so there's need for the cloud and so seeing more and more of that what is your top-down aggressive goals to fill that solution base because you're also very transformational thinker what is your what is your aggressive top-down goals for your organization because you're serving a market with trillions of dollars of span that's shifting that's on the table a lot of competition now sees it too they're gonna go after it but at the end of the day you have customers that have that demand for things apps yeah and not a lot of budget increase at the same time this is a huge dynamic what's your goals you know I think that at a high level are top-down aggressive goals so that we want every single customer who uses our platform to have an outstanding customer experience and we want that outstanding customer experience in part is that their operational performance and their security are outstanding but also that it allows them to build and it build projects and initiatives that change their customer experience and allow them to be a sustainable successful business over a long period of time and then we also really want to be the technology infrastructure platform under all the applications that people build and they were realistic we know that that you know the market segments we address with infrastructure software hardware and data center services globally are trillions of dollars in the long term it won't only be us but we have that goal of wanting to serve every application and that requires not just the security operational performance but also a lot of functionality a lot of capability we have by far the most amount of capability out there and yet I would tell you we have three to five years of items on our roadmap that customers want us to add and that's just what we know today well and any underneath the covers you've been going through some transformation when we talked a couple years ago about how serverless is impacting things I've heard that that's actually in many ways glue behind the two pizza teams to work between organizations talk about how the internal transformations are happening how that impacts your discussions with customers that are going through that transformation well I mean there's a lot of a lot of the technology we build comes from things that we're doing ourselves you know and that we're learning ourselves it's kind of how we started thinking about microservices serverless - we saw the need we know we would have we would build all these functions that when some kind of object came into an object store we would spin up compute all those tasks would take like three or four hundred milliseconds then we spin it back down and yet we'd have to keep a cluster up in multiple availability zones because we needed that fault tolerance and it was we just said this is wasteful and that's part of how we came up with lambda and that you know when we were thinking about lambda people understandably said well if we build lambda and we build the serverless event-driven computing a lot of people who are keeping clusters of instances aren't going to use them anymore it's going to lead to less absolute revenue for us but we we have learned this lesson over the last 20 years at Amazon which is if it's something it's good for customers you're much better off cannibalizing yourself and doing the right thing for customers and being part of shaping something and I think if you look at the history of Technology you always build things and people say well that's gonna cannibalize this and people are gonna spend less money what really ends up happening is they spend spend less money per unit of compute but it allows them to do so much more that the ultimately long-term end up being you know more significant customers I mean you are like beating the drum all the time customers what they say we implement the roadmap I got that you guys have that playbook down that's been really successful for you yeah two years ago you told me machine learning was really important to you because your customers told what's the next tranche of importance for customers what's on top of mine now as you look at this reinvent kind of coming to a close replays tonight you had conversations your your tech a fleet you're running around doing speeches talking to customers what's that next hill from from my fist machine learning today there's so much I mean that's not it's not a soup question you know I think we're still in this in the very early days of machine learning it's not like most companies have mastered yet even though they're using it much more than they did in the past but you know I think machine learning for sure I think the edge for sure I think that we're optimistic about quantum computing even though I think it'll be a few years before it's really broadly useful we're very enthusiastic about robotics I think the amount of functions are going to be done by these robotic applications are much more expansive than people realize it doesn't mean humans won't have jobs they're just going to work on things that are more value-added I thought we're believers in augmented and virtual reality we're big believers and what's going to happen with voice and I'm also I think sometimes people get bored you know I think you're even bored with machine learning maybe already but yet people get bored with the things you've heard about but I think just what we've done with the chips you know in terms of giving people 40% better price performance in the latest generation of x86 processors it's pretty unbelievable and the difference in what people are going to be able to do or just look at big data I mean big date we haven't gotten through big data where people have totally solved it the amount of data that companies want to store process and analyze is exponentially larger than it was a few years ago and it will I think exponentially increase again in the next few years you need different tools the service I think we're not we're not for with machine learning we're excited to get started because we have all this data from the video and you guys got sage maker yeah we call it a stairway to machine learning heaven we start with the data move up what now guys are very sophisticated with what you do with technology and machine learning and there's so much I mean we're just kind of again in this early innings and I think that it was soaked before sage maker was so hard for everyday developers and data scientists to build models but the combination of sage maker and what's happened with thousands of companies standardizing on it the last two years Plus now sage maker studio giant leap forward we hope to use the data to transform our experience with our audience and we're on Amazon Cloud I really appreciate that and appreciate your support if we're with Amazon and Instant get that machine learning going a little faster for us a big that'll be better if you have requests so any I'm you talked about that you've got the customers that are builders and the customers that need simplification traditionally when you get into the you know the heart of the majority of adoption of something you really need to simplify that environment but when I think about the successful enterprise of the future they need to be builders yeah so has the model flipped if you know I normally would said enterprise want to pay for solutions because they don't have the skill set but if they're gonna succeed in this new economy they need to go through that transformation that yeah so I mean are we in just a total new era when we look back will this be different than some of these previous waves it's a it's a really good question Stu and I I don't think there's a simple answer to it I think that a lot of enterprises in some ways I think wish that they could just skip the low level building blocks and and only operate at that higher level abstraction it's why people were so excited by things like sage maker or code guru or Kendra or contact lens these are all services that allow them to just send us data and then run it on our models and get back the answers but I think one of the big trends that we see with enterprises is that they are taking more and more of their development in-house and they are wanting to operate more and more like startups I think that they admire what companies like Airbnb and Pinterest and slack and and you know Robin Hood and a whole bunch of those companies stripe have done and so when you know I think you go through these phases and errors where there are waves of success at different companies and then others want to follow that success and and replicate and so we see more and more enterprises saying we need to take back a lot of that development in-house and as they do that and as they add more developers those developers in most cases like to deal with the building blocks and they have a lot of ideas on how they can create us to creatively stitch them together on that point I want to just quickly ask you on Amazon versus other clouds because you made a comment to me in our interview about how hard it is to provide a service that to other people and it's hard to have a service that you're using yourself and turn that around and the most quoted line in my story was the compression algorithm there's no compression outliving for experience which to me is the diseconomies of scale for taking shortcuts yeah and so I think this is a really interesting point just add some color comments or I think this is a fundamental difference between AWS and others because you guys have a trajectory over the years of serving at scale customers wherever they are whatever they want to do now you got micro services it's even more complex that's hard yeah how about that I think there are a few elements to that notion of there's no compression algorithm I think the first thing to know about AWS which is different is we just come from a different heritage in a different background we sweep ran a business for a long time that was our sole business that was a consumer retail business that was very low margin and so we had to operate a very large scale given how many people were using us but also we had to run infrastructure services deep in the stack compute storage and database in reliable scalable data centers at very low costs and margins and so when you look at our our business it actually today I mean it's it's a higher margin business in our retail business the lower margin business and software companies but at real scale it's a it's a high-volume relatively low margin business and the way that you have to operate to be successful with those businesses and the things you have to think about and that DNA come from the type of operators that we have to be in our consumer retail business and there's nobody else in our space that does that you know the way that we think about cost the way we think about innovation and the data center and and I also think the way that we operate services and how long we've been operating services of the company it's a very different mindset than operating package software then you look at when you think about some of the issues and very large scale cloud you can't learn some of those lessons until you get two different elbows of the curve and scale and so what I was telling you is it's really different to run your own platform for your own users where you get to tell them exactly how it's going to be done but that's nothing really the way the real world works I mean we have millions of external customers who use us from every imaginable country and location whenever they want without any warning for lots of different use cases and they have lots of design patterns and we don't get to tell them what to do and so operating a cloud like that at a scale that's several times larger the next few providers combined is a very different endeavor and a very different operating rigor well you got to keep raising the bar you guys do a great job really impress again another tsunami of announcements in fact you had to spill the beans early with quantum the day before the event tight schedule I gotta ask you about the music festival because I think there's a really cool innovation it's the inaugural intersex conference yeah it's not part of replay which is the concert tonight right it's a whole new thing big music act you're a big music buff your daughter's an artist why did you do this what's the purpose what's your goal yeah it's an experiment I think that what's happened is that reinvent has gotten so big with 65,000 people here that to do the party which we do every year it's like a thirty five forty thousand person concert now which means you have to have a location that has multiple stages and you know we thought about it last year when we were watching it and we said we're kind of throwing like a four hour music festival right now there's multiple stages and it's quite expensive to set up that set for our partying we said well maybe we don't have to spend all that money for four hours in the rip it apart because actually the rent to keep those locations for another two days is much smaller than the cost of actually building multiple stages and so we we would try it this year we're very passionate about music as a business and I think we are I think our customers feel like we throw in a pretty good music party the last few years and we thought we were trying at a larger scale as an experiment and if you look at the economics the headliners real quick the Foo Fighters are headlining on Saturday night Anderson Park and the free Nashville free Nationals Brandi Carlile Shawn Mullins Willie Porter it's a good set Friday night it's back in Kacey Musgraves so it's it's a really great set of about 30 artists and we're hopeful that if we can build a great experience that people want to attend that we can do it it's scale and it might be something that you know both pays for itself and maybe helps pay for reinvent to overtime and you know I think that we're also thinking about it as not just a music concert and festival the reason we named it intersect is that we want an intersection of music genres and people and ethnicities and age groups and art and Technology all there together and this will be the first year we try it it's an experiment and we're really excited about I'm gone congratulations all your success and I want to thank you we've been seven years here at reinvent we've been documenting the history two sets now once-dead upstairs so appreciate a cube is part of reinvent you know you guys really are a part of the event and we really appreciate your coming here and I know people appreciate the content you create as well and we just launched cube 365 on Amazon Marketplace built on AWS so thanks for letting us cool build on the platform appreciate it thanks for having me guys Jesse the CEO of AWS here inside the cube it's our seventh year covering and documenting they're just the thunderous innovation that Amazon is doing they're really doing amazing work building out the new technologies here in the cloud computing world I'm John Force too many men be right back with more after this short break [Music]