>>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.