>> live from London, England. It's the queue covering a ws summat. London twenty nineteen, Brought to you by Amazon Web services, >> come to the A. W s summit in London's Excel Center. I'm Susanna Street, and David Aunty is my co host today on the Cube. This means so much to talk about here at the summit today to do with machine learning and a I. And I'm really pleased to say that we have to really key people here to discuss this. We've got time. Tom Summerfield, who is head off commerce, a foot asylum on also Richard Potter, who is the CEO of Peak. Now you guys have really formed a partnership. Haven't you put asylum? Is a leisure wear really? Retailer started in bricks and mortar stores. Really moved online on Peak is a pioneer for artificial intelligence. System's really well to get together. What What sparked? Really your demands. Ready for their services, Tom. >> Yeah, well, so way knew that we needed to be doing something with data on A and we didn't really know exactly what it would be Way were interested in personalization, but then also in a bigger picture, like a wider digital transformation piece for the business where well established bricks, a martyr business, but then a fast growing online business. And we're interested to know how way could harness the momentum of the stores to help the digital side of the business and also vice versa. On we thought data would be the key, and we ended up having a conversation with the guys at Peak, and that's exactly what we've been able to do. Actually, on the back of that deliver, we're delivering a hyper personal experience for our consumers Now. >> I was one of the statue that I notice when looking into what you be doing, a twenty percent increase in email revenue. So that's quite remarkable, Really. So Richard, tell us, you know how you're able to do this? What kind of services that you lean on? T make those kind of result. >> It's a combination of a lot of things, really. You know, you obviously need people who know what they're doing from a returning a business perspective. Married with technical experts, data science algorithms, data. Um, I think specifically how we've done it is a pig's built, a fairly unique A I system that becomes almost like the central brain within our customers. Businesses on off that algorithms help automate certain business processes and deliver tangible uplifts in business performance like the twenty eight percent uplifting sales here, Um, in order to do it. So it's quite a long journey, I suppose. The outlook we took when we started collaborating was was that if we could deliver that hyper personalized shopping experience, we were always going to be ableto show customers the right product at the right time. And if we were doing that that we would lead Toa High brand engagement, higher loyalty higher on higher lifetime values of customers. And that's and that's what's shown to be the case in silent example. >> Yeah, definitely that echo that. You know that the high profits hypothesis wass If you can show the right custom of the right product at the right time, then their purchase frequency average order Volumetrics all start to move positively and ultimately than affecting their long term engagement with our brand, which increases revenue on also delivers a more, you know, a frictionless consumer experience, hopefully for the customer, >> because I suppose your experience is the same. So many companies out there they're sitting on this huge pile of data, yet they don't know how to best optimize that data. When did you first realize, Richard that there was this kind of gap in the market for Pete to grow? >> Yeah, I think data and analytics have come on a bit of a journey away from common sense reporting tio more advanced analytics. But when you get a I and machine learning what you're talking about, his algorithms being our self learning make predictions about things that actually fundamentally changes the way businesses can operate on DH. And in this case, a great example is you know, we're sending hyper personalized marketing communications, Teo, every single for silent customer. They don't realize necessarily that they are tailored to them, but they just become more relevant. But it doesn't require a digital marketing to create every single one of those campaigns or emails and even trigger the sending of those materials. Brain takes care of that. It can automate it. And what the marketer needs to do is it's faded, engaging content and set up digital campaigns. And then and then and then you're left with this capability where eyes saying you might be a market for this product. Let's let's send you something that might appeal to you on DH that just gives that gives a marketing team scale. And then, as we move into other use cases like in the supply chain for film and delivery of product the same thing the team's just get huge scale out of letting algorithms do those things for them. Andi, I suppose the realization for us that there was that gap in the market was just that you can see the out performance of certain cos you can see that Amazon attributes five percent of their sales to their machine learning recommendation systems. I think Netflix says eighty five percent of all content is consumed >> because it's Al Burns. Andi. Companies >> like that can harness machine learning to such a great degree. How does how did howto other businesses do it? Who can't access that talent pool of Silicon Valley or along the global? You know, the global talent leaders in tech and that's that's where we had the insight that his peak way could create a company that gave our custom is that that technology and that capability Teo deliver that same kind results that the Amazon and Netflix >> so before the Internet brand's had all the power you could price however you wanted if you overprice, nobody even even knew. And the Internet was sort of like the revenge of the consumer. Aye, aye, And data now gives the brands the ability to learn more about its customers. But you have to be somewhat careful, don't you? Because their privacy concerns obviously DPR etcetera. So you have to have a value proposition for the customer, as you were saying, which they made are you know that machine is providing these offers, but they get value out of it. So how do you guys think about that in terms of experience for the customer? And how do you draw that balance? >> I think from my angle, that Richard touch on a couple of bits there to do it scale first and foremost across the entire alarm on Thai network of consumers is killer element to it. But to deliver that personal experience, I think consumers nowadays are so they're more expectant of this. Really. We would have considered it innovation a couple of years ago, but now actually it's expected, I think, from the consumer. So it's actually in the name ofthe You have to move forward to stand still. So but way think where we're right at the front of this at the moment. And we're really looking now how we optimize the journey for the consumer so that actually we know if we're from some transactional data that we have in a little bit of over behavioral data that, you know, we're really conscious of the whole GDP, our peace and stuff, and that's really, really relevant and super important. Andi, I'm pleased to say that you know, we have that. We know that by a peek, it's completely on lock down from that perspective as >> well. Where did the data's where the data source of comfort. You mentioned some transaction data. Where is the other day to come from using show social data and behavioral data? Where does that come? >> So those elements of social data, some of it is a little bit black box. You can't always access it, and that's a GDP, our peace there, and rightly so. Actually, in some cases we have a loyalty scheme which allows us to understand our Kashima's better in our bricks and mortar retail, which is really cool that we've got some of that transactional data on a customer level from the stars. We know that some people in our sector maybe don't have that, so that so that allows us to complete sort of single customer view, which then we can aggregate in peaks brain, then transaction data on the website in the app and bits off browsing, you know, just within our own network. You know where customs potentially being and reacted with somethin. A piece of content. Janet within the website, that's that's how we build that view. >> Do you think this is the way that more bricks and more two stores Khun survive? Because so many are closing in high streets up down the UK and in other countries because simply they're not really delivering what the customer wants? >> Yeah, I think so. We rich now. Both feel quite strongly now that wear so onto this now a little bit. It's a really As as our relationship for the two businesses has evolved, it's become clearer and clearer that actually we've armed with this. You know this data, our fingertips, we can actually breathe fresh life into the stores, and it's in the eye of proper true Omnichannel retailing way. Don't mind where the cost consumer spends the money. We just need to be always on in a connected environment so that A Z said before pushing the right product at the right time. And when they're when they're in market, we turn up the mark the message a little bit. But then understanding when they're not in market and maybe to back off him and maybe we warn them what with a little bit of a different type of message then and actually we're trapped with one challenge ourselves to send but less better marketing communications to our consumers. But absolutely that store piece is now, so we tail back. Our store opening strategy is a business to focus more on the digital side of things, but now it's possible that way might open some more stores now, but it will be with a more reform strategy of wet, wet where, why we need to do that? >> Isn't this ironic? The brick and mortar marketplaces getting disrupted by online retailers, obviously Amazons, that big whale in the marketplace, and your answer to that is to use Amazons, cloud services and artificial intelligence to pave the way for your future. Yeah, I mean, that's astounding when you think about >> me. Yeah, this sort of unified commerce approach, Tio, you know, there's a place in the world for shops. It's like it's not Romance isn't completely dead and going shopping. It turns out, you know so on. Actually, yeah, we're using honesty in the eight of us, but we'LL hire our friends at Peak. Yeah, it's it's some irony there. I think it's really cool. >> And that decision that you made obviously wasn't made made lightly. But you saw the advantages of working with the clouds outweighing the potential trade offs of competition. >> Yeah, I mean, that's not that was never really, really no, I'm certainly not know. I think this is something that is happening, that data, and on harnessing it in a safe, responsible, effective way, I believe, is the future of all commerce. So >> that as far as security is concerned because, of course, we have had data breaches your customers, credit card details, access. How do you ensure that it's as secure as possible in the way that you you you choose the services I think >> that come that just comes down to best practice infrastructure on the way we look at it, a peak is there's no bear tools in the world to do that, then the same technologies that Amazon themselves use. It's to do with how you configure those services until ls to make it secure, you know, And if you have an unsecure open database on a public network, of course that's not secure. But you could have the same thing in your own infrastructure, and it wouldn't be secure. So I think the way we look at it is exactly the same thing on actually, being in the Amazon prime for us gives us a greater comfort, particularly in terms of co location of date centers and like making sure that our application fails over into different locations. It gives us infrastructure we couldn't afford otherwise, and then on top of that, we get all these extra pieces of technology that can make us even more secure than we could do. Otherwise we'd have to wait, have to employ an army of infrastructure engineers, and we don't have to do that because we run on Yes. >> Okay, so we were able to eliminate all that heavy lifting. That same goes. You've got this corpus of data. I'm interested in how long it took to get through. A POC trained the models how much data science was involved. How much of a heavy lift was that? Yeah, well, I think for >> us we better be pretty rapid. Actually, we started working together in January last year, so we're only just sort of year into that. >> And in that faith in that entire >> sofa length of of our relationship, we've gone from high for personalizing digital campaigns to recommendation systems on a website to now optimizing customer acquisition on social media and then finally into the supply chain and optimizing demand and so on it. And I think there's >> a lot of reasons >> why we've been able to do it quickly. But that's fundamental to the technologies that the peak is built. There's two. There's two sides to it. Our technologies cut out a lot of the friction so way didn't run a proof of concept. We were able to just pick it up, run with it and deliver value. And that's to do with I think, the product that peak is built. But then you obviously need a a customer who's who's going on a transformation journey and is hungry to make that make that stick in London on. Then when the two come together, >> I think that it's an interesting point that, though, because while suite for asylum, we always I always say it's that we're not. We're not massive, but we're not tiny, but it's the sort place you Khun turn upon a Monday and say, I've had an idea about something and we're not doing it by Friday. That's That's a nice, agile culture. It can create some drama as well. Possibly. I think it's really straightforward to get straight into it. And I think this is where some of the bigger, um, sleepier high street retailers that Amar, fixed in a in a brick from our world, needs to not be too afraid to come out and start embracing it, because I think some of them are trying now. I think it might be a little bit late for some now, but it's just it's just it just wasn't that hard really to get going >> and you've seen the business results, can you share any measurements? or quantification. We've >> got a really a really good one that we're just talking about at the moment. Actually, Way were able to use segmentation tools within within the peak brain Teo to use them on Social than Teo. Create lookalike audiences. So Facebook Custom tools, Right? We'LL help you create audiences that it thinks you're the right buyer. It's complex algorithms itself, but we almost took a leap ahead of their algorithms by fire, our algorithms uploading our own segments to create a more sophisticated lookalike audience. We produced a row US results or return on that spend. People are not familiar with that of eight thousand four hundred percent, which Wei would normally be happy as a business, we've sort of seven, eight hundred percent. If you're running that that we've say on AdWords campaign or something like that, that's quite efficient campaign. So it's at zero. We were a bit like it felt like it's a mistake that, you >> know that is >> not the right, >> Yeah, but not so that's super cool. And that's really that's really opened our eyes to the potential of punishing that the, you know, our sort of piquet I brain to then bring it onto Social on. Do more outward. Advertise on there. >> So moving the goal post meant that your teeth are really high school. Thank you. Thank you very much for telling us all about that time someone feels on which floor. Sir. Thank you for joining me and David Auntie here at the eight of US Summit in London. Merchant to come on the King.

>> live from London, England. Q. Covering A Ws summat. London twenty nineteen Brought to you by Amazon Web services >> to the A. W s Summit in London's Excel Center home. Susanna Street and David is my co host today on the Cube. They mean so much to talk about here at the summit today to do with machine learning an A I and I'm really pleased to say that we have to really key people here to discuss this. But we've got some Tom Summerfield who is head off commerce, a foot asylum on also Richard Potter, who is the CEO of Peak. Now, you guys have really formed a partnership, haven't you? Foots asylum is a leisure wear really. Retailer started in bricks and mortar stores. Really moved online on Peak has been a pioneer for artificial intelligence systems really well to get together. What what comes? Sparked Really your demands ready for their services, Tom? >> Yeah, well, so way knew that we needed to be doing something with data on A and we didn't really know exactly what it would be way were interested in personalization, but then also in a bigger picture, like a wider digital transformation piece for the business where well established bricks, a martyr business but a fast grow in online business. And we're interested to know how we could harness the momentum of the stores to help the digital side of the business and also vice versa. On we thought data would be the key, and we ended up having a conversation with the guys at Peak, and that's exactly what we've been able to do. Actually, on the back of that deliver, we're delivering a hyper personal experience for our consumers Now. >> I was one of the statue that I notice when looking into what you be doing, a twenty percent increase in email revenue. So that's quite remarkable, really. So Richard, tell us you how you're able to do this. What kind of services that you lean on? T make those kind of result. >> It's a combination of a lot of things, really. You know, you obviously need people who know what they're doing from a returning a business perspective. Married with technical experts, data science algorithms, data, I think specifically how we've done is picks built a fairly unique A I system that becomes almost like the central brain within our customers businesses on off that algorithms help automate certain business processes and deliver tangible uplifts in business performance like the twenty eight percent up lift in sales here, Um, in order to do it. So it's quite a long journey, I suppose. The outlook we took when we started collaborating was was that if we could deliver that hyper personalized shopping experience, we were always going to be ableto show customers the right product at the right time. And if we were doing that that we would lead Tio Hi brand engagement, higher loyalty, higher on higher lifetime values of customers. And that's and that's what's shown to be the case in a silent example. >> Yeah, definitely that echo that. You know that the hypothesis hypothesis, wass. If you can show the right custom of the right product at the right time, then their purchase frequency average order Volumetrics all starts move positively and ultimately than affecting their long term engagement with our brand, which increases revenue on also delivers a more, you know, a frictionless consumer experience, hopefully for the customer, >> because I suppose your experience is the same. So many companies out there they're sitting on this huge pile of data, yet they don't know how to best optimize that data. When did you first realize, Richard that there was this kind of gap in the market for Pete to grow? >> Yeah. I think data and analytics have come on a bit of a journey away from common sense reporting Thio more advanced analytics. But when you get a I and machine learning what you're talking about, his algorithms being our self learning make predictions about things, and that actually fundamentally changes the way businesses can operate on DH. And in this case, a great example is you know, we're sending hyper personalized marketing communications, Teo every single foot silent customer. Um, they don't realize necessarily that they are tailored to them, but they just become more relevant. But it doesn't require a digital marketed to create every single one of those campaign or emails and even triggered the sending of those materials. The brain takes care of that. It can automate it. And what the marketer needs to do is feed it engaging content and set up digital campaigns. And then and then and then you're left with this capability where eyes saying you might be a market for this product. Let's let's send you something that might appeal to you on DH that just gives that gives a marketing team scale. And then, as we move into other use cases like in the supply chain for film and delivery of product the same thing that teams just get huge scale out of letting algorithms do those things for them. Andi, I suppose the realization for us that there was that gap in the market was just that you can see the out performance of certain cos you can see that Amazon attributes thirty five percent of their sales to their machine learning recommendation systems. I think Netflix says eighty five percent of all content is consumed >> in prison. It's Al Burns. Andi. Companies >> like that can harness machine learning to such a great degree. How does how do you know howto other businesses do it? Who can't access that talent pool of Silicon Valley or along the global? You know, the global talent leaders in tech and that's that's what we have. The insight that is Peak Way could create a company that gave our system is the that technology and that capability Teo deliver that same kind results that the Amazon and Netflix >> So before the Internet Yeah. Brand's had all the power you could price however you wanted if you overprice, nobody even even knew. And the Internet was sort of like the revenge of the consumer. Aye, aye. And data. How gives the brands the ability to learn more about its customers. But you have to be somewhat careful, don't you? Because your privacy concerns, obviously. Gpr etcetera. So you have to have a value proposition for the customer, as you were saying, which they may not even know that machine is providing these offers. Yeah, but they get value out of it. So how do you guys think about that in terms of experience for the customer? And how do you draw that balance? >> I think from my angle that Richard touch on a couple of bits there to do it scale first and foremost across the entire all on on Thai network of consumers is killer element to it. But to deliver that personal experience, I think consumers nowadays are so they're more expectant of this. Really? We would have considered it innovation a couple of years ago, but now Actually, it's expected, I think, from the consumer. So it's actually in the name ofthe You have to move forward to stand still. So but way Think we're We're right at the front of this at the moment. And we're really looking now how we optimize the journey for the consumer so that actually we know if we're from Simpson transactional data that we have in a little bit of over behavioral data that, you know, we're really conscious of the whole GDP, our peace and stuff, and that's really, really relevant and super important. Andi, I'm pleased to say that you know, we have that backed by a peek. It's completely on lock down from that perspective as >> well. Where do the data's where the data source of comfort. You mentioned some transaction data. Where is the other data come from? Using show social data and behavioral data? Where does that come >> with these elements of social data? Some of it is a little bit black box, so you can always access it. And that's the GPR piece there. And rightly so. Actually, in some cases we have a loyalty scheme which allows us to understand our Kashima's better in our bricks and mortar retail, which is really cool that we've got some of that transactional data on a customer level from the store's way know that some people in our sector maybe don't have that, so that so that allows us to complete sort of single customer view, which then we can aggregate in peaks brain, then transaction data on the website in the app and bits off browsing, you know, just within our own network. But you know where customers potentially being and reactive of somethin, a piece of content on journeys within the website, That's that's how we build that view. >> Do you think this is the way that more bricks and more two stores Khun survive? Because so many are closing in high streets up down that you can in other countries, because simply they're not really delivering what the customer wants? >> Yeah, I think so. Rich Now, both feel quite strongly now that wear something to this now a little bit. It's a really As as our relationship for the two businesses has evolved, it's become clearer and clearer that actually we've armed with this. You know this data, our fingertips, we can actually breathe fresh life into the stores, and it's in the eye of proper true omnichannel retailing way. Don't mind where the cost consumer spends the money. We just need to be always on in a connected environment. So that way said before pushing the right product at the right time. And when that when they're in market, we turn up the mark the message a little bit. But then understanding when they're not in market and maybe to back off him and maybe we warn them what with a little bit of a different type of message then and actually we're trapped would want to challenge ourselves to send but less better marketing communications to our consumers. But absolutely that store piece is now, so we tail back. Our store opening strategy is a business to focus more on the digital side of things, but now it's possible that way might open some more stores now, but it will be with a more reform strategy of wet, wet where, why we need to do that? >> Isn't this ironic? The brick and mortar marketplaces getting disrupted by online retailers, obviously Amazons, that big whale in the marketplace and your answer to that is to use Amazon's cloud services and artificial intelligence to pave the way for your future. Yeah, I mean, that's astounding when you think about >> coming. >> Yeah, sort of unified commerce approach, Tio. You know, there's a place in the world for shops. It's like it's not Romance isn't completely dead and going shopping Friends out, you know so on. Actually, yeah, we're using honest in the eight of us, but we'LL hire our friends at Peak. Yeah, it's it's some irony there. I think it's really cool. >> And that decision that you made obviously made made lightly. But you saw the advantages of working with the clouds outweighing the potential trade offs of competition. >> Yeah, I mean, that's not that was never really, really no, I'm certainly not know. I think this is something that is happening, that data, and on harnessing it in a in a safe, responsible, effective way, I believe, is the future of all commerce. So >> that as far as security is concerned because, of course, we have had data breaches. Yeah, customers, credit card details, access. How do you ensure that it's as secure as possible in the way that you you you choose the services. I think >> that come that just comes down to best practice infrastructure on the way we look at it, a peak is there's no bear tools in the world to do that, then the same technologies that Amazon themselves use. It's to do with how you configure those services until ls to make it secure. You know, if you have an unsecure open database on a public network, of course that's not secure. But you could have the same thing in your own infrastructure, and it wouldn't be secure. So I think the way we look at it is exactly the same thing on actually, being in the Amazon plan for us gives us a greater comfort, particularly in terms of co location of data centres, like making sure that our application fails over into different locations. It gives us infrastructure we couldn't afford otherwise, and then on top of that, we get all these extra pieces of technology that can make us even more secure than we could do. Otherwise we'd have to wait, have to employ an army of infrastructure engineers, and we don't have to do that because we run on Yes, >> okay, so we were able to eliminate all that heavy lifting. Same goes. You've got this corpus of data. I'm interested in how long it took to get through. A POC trained the models how much data science was involved. How much of a heavy lift was that? Yeah, well, I think for us >> we better be pretty rapid. Actually, we start working together in January last year, so we're only just sort of year into that. >> And in that faith in that entire >> sofa length of of our relationship, we've gone from high for personalizing digital campaigns to recommendation systems on a website to now optimizing customer acquisition on social media and then finally into the supply chain and optimizing demand. And so on and on. I think there's a lot of reasons why we've been able to do it quickly, but that's fundamental to the technologies that that peak is built. There's two. There's two sides to it. Our technologies cut out a lot of the friction so way didn't run a proof of concept. We were able to just pick it up, run with it and deliver value. And that's to do with I think, the product that peak is built. But then you obviously need a a customer who's who's going on a transformation journey and is hungry to make that make that stick in London on. Then when the two come together, >> I think that it's an interesting point that, though, because while suite for asylum, we always I always say it's that we're not. We're not massive, but we're not tiny, but it's the sort place you Khun turn upon a Monday and say, I've had an idea about something and we're not doing it by Friday. That's That's a nice, agile culture. It can create some drama as well. Possibly. I think it's really straightforward to get straight into it. And I think this is where some of the bigger, um, sleepier high street retailers that Amar fixed in a in a brick Samara world need to not be too afraid to come out and start embracing it. Because I think some of them are trying now. I think it might be a little bit late for some now, but it's it was just it was just wasn't that hard really to get going here >> and you've seen the business results. Can you share any measurements or quantification. We've >> got a really a really good one that we're just talking about at the moment. Actually, Way were able to use segmentation tools within within the peak brain, too to use them on social than Teo. Create lookalike audiences. So Facebook custom tools, right? We'LL help you create audiences that it thinks will be wrapped pirates complex algorithms itself. But we almost took a leap ahead of their algorithms by fire, our algorithms uploading our own segments to create a more sophisticated lookalike audience. We produced a row US results or return on that spend People are not familiar with that of eight thousand four hundred percent which we we would normally be happy as a business. We've sort of seven, eight hundred percent. If you're running that that we've say on AdWords campaign or something like that, that's quite efficient campaign. So it's at zero. We were a bit like it felt like it's a mistake that, you >> know, that is >> not the right Yeah, but not so that's super cool. And that's really that's really opened our eyes to the potential of punishing that the, you know, our sort of piquet I brain to then bring it onto Social on. Do more outward. Advertise on there. >> So moving the goal post meant that your teeth have really high school. Thank you. Thank you very much for telling us all about that time someone feels on Richard for so thank you for joining me and David Auntie here at the age of Lou s summit in London. Merchant to come on the King.

>> Pomp YouTubers. Welcome to another cube conversation from ours, the Cube Studios in Palo Alto, California In this conversation, we're going to build upon some other recent conversations we've had which explores this increasingly important relationship between Senate conductor, memory or flash and new classes of applications that are really making life easier and changing the way that human beings in Iraq with each other, both in business as wells and consumer domains. And to explore these crucial issues. We've got two great guests. Brian Kumagai is the director of business development at Kashima Memory America. Scott Beekman is the director of managed flashes to Sheba Memory America's Well, gentlemen, welcome to the Cube. And yet so I'm gonna give you my perspective. I think this is pretty broadly held generally is that as a technology gets more broadly adopted, people get experience with. And as designers, developers, users gain experience with technology, they start to apply their own creativity, and it starts to morph and change and pull and stretch of technology and a lot of different directions. And that leads to increased specialization. That's happening in the flash work I got there, right? Scott? >> Yes, you know the great thing about flashes. Just how you because this it is and how widely it's used. And if you think about any electronic device it needs, it needs a brain processor. Needs to remember what it's doing. Memory and memories, What? What we do. And so we see it used in, you know, so many applications from smartphones, tablets, printers, laptops, you know, streaming media devices. And, uh and so you know, that that technology we see used, for example, like human see memory. It's a low power memory is designed for, for, like, smartphones that aren't plugged in. And, uh, and so when you see smartphones, one point five billion smartphones, it drives that technology and then migrates into all kinds of other applications is well, and then we see new technologies that come and replace that like U F s Universal flash storage. It's intended to be the high performance replacement. Mm. See, And so now that's also mag raiding its way through smartphones and all these other applications. >> So there's a lot of new applications that are requiring new classes of flash. But there's still a fair amount of, AH applications that require traditional flash technology. These air not coming in squashing old flash or traditional flasher other pipe types of parts, but amplifying their use in specialized ways. Brian Possible. But about >> that. So it's interesting that these days no one's really talks about the original in the hand flash that was ever developed back in nineteen eighty seven and that was based on a single of a cell, or SLC technology, which today still offers the highest reliability and fastest before me. Anand device available in the market today. And because of that, designers have found this type of memory to work well for storing boot code and some levels of operating system code. And these are in a wide variety of devices, both and consumer and industrial segments. Anything from set top boxes connecting streaming video. You've got your printers. You, Aye aye. Speakers. Just a numerous breath of product. I >> gotta also believe a lot of AA lot of i o t lot of industrial edge devices they're goingto feature. A lot of these kinds of parts may be disconnected, maybe connected beneath low power, very high speed, low cost, highly reliable. >> That's correct. And because these particular devices air still offered in lower densities. It does offer a very cost effective solutions for designers today. >> Okay, well, let's start with one of the applications. That is very, very popular. Press. When automated driving autonomous funerals on the work, it's it's There's a Thomas vehicles, but there's autonomous robots more broadly, let's start with Autonomous vehicle Scott. What types of flash based technologies are ending up in cars and why? >> Okay, so we've seen a lot of changes within vehicles over the last few years. You know, increasing storage requirements for, like, infotainment systems. You know, more sophisticated navigations of waste recognition. Ah, no instrument clusters more informed of digital displays and then ate ass features. You know, collision avoidance things like like that and all that's driving maur Maureen memory storage and faster performance memory. And in particular, what we've seen for automotive is it's basically adopting the type of memory that you have in your smartphone. So smart phones have a long time have used this political this. Mm. See a memory. And that has made you made my greatest weigh in automotive. And now a CZ smartphones have transition been transitioning do you? A fast, in fact, sushi. But it was the first introduced samples of U F U F S in early two thousand thirteen, and then you started to see it in smartphones in two thousand fifteen. Well, that's now migrating in tow. Automotive as well. They need to take advantage of the higher performance, the higher densities and so and so to Chiba. Zero. We're supporting, you know this, this growth within automotive as well. >> But automotive is a is a market on DH. Again, I think it's a great distinction you made. It's just not autonomous. It's thie even when the human being is still driving. It's the class of services that provided to that driver, both from an entertainment, say and and safety and overall experience standpoint. Is driving a very aggressively forward that volume in and the ability to demonstrate what you can do in a car is having a significant implications on the other classes of applications that we think for some of these high end parts. How is the experience that were incorporating into an automotive application or set of applications starting to impact? How others envision how their consumer products can be made better, Better experience safer, etcetera in other domains >> uh, well, yeah, I mean, we see that all kinds of applications are taking advantage of the these technologies. Like like even air via air, for example. Again, it's all it's all taking advantage of this idea of needing higher, larger density of storage at a lower cost with low power, good performance and all these applications air taking an advantage of that, including automotive. And if you look it automotive, you know, it's it's not just within the vehicle. Actually, it's estimated, you know, projected that autonomous vehicles we need, like one two, three terabytes of storage within the within the vehicle. But then all the data that's collected from cameras and sensors need to be uploaded to the cloud and all that needs to be stored. So that's driving storage to data centers because you basically need to learn from that to improve the software. For the for, Ah, you know, for the time being, Yeah, exactly. So all these things are driving more and more storage, both with within the devices themselves, like a car is like a device, but also in the data centers as >> well. So if we can't Brian take us through some of the decisions that designer has to go through to start to marry some of these different memory technologies together to create, whether it's an autonomous car, perhaps something a little bit more mundane. This might be a computing device. What is the designer? How does is I think about how these fit together to serve the needs of the user in the application. >> Um, I think >> these days, you know a lot of new products. They require a lot of features and capabilities. So I think a lot of input or thought is going into the the memory size itself. You know, I think software guys are always wanting to have more storage, to write more code, that sort of thing. So I think that is one lt's step that they think about the size of the package and then cost is always a factor as well. So you know nothing about the Sheba's. We do offer a broad product breath that producing all types of I'm not about to memory that'll fit everyone's needs. >> So give us some examples of what that product looks like and how it maps to some of these animation needs. >> So we like unmentioned we offered the lower density SLC man that's thought that a one gigabit density and then it max about maximum thirty to get bit dying. And as you get into more multi level cell or triple level cell or cue Elsie type devices, you're been able to use memory that's up to a single diet could be upto one point three three terror bits. So there's such a huge range of memory devices available >> today. And so if we think about where the memories devices are today and we're applications or pulling us, what kind of stuff is on the horizon scarred? >> Well, one is just more and more storage for smartphones. We want more, you know, two fifty six gigabyte fight told Gigabyte, one terabyte and and in particular for a lot of these mobile devices. You know, like convention You f s is really where things were going and continuing to advance that technology continuing to increase their performance, continuing to increase the densities. And so, you know, and that enables a lot of applications that we actually a hardman vision at this point. And when we know autonomous vehicles are important, I'm really excited about that because I'm in need that when I'm ninety, you know can drive anywhere. I want everyone to go, but and then I I you know where I's going, so it's a lot of things. So you know, we have some idea now, but there's things that we can't envision, and this technology enables that and enables other people who can see how do I take advantage of that? The faster performance, the greater density is a lower cost forbid. >> So if we think about, uh, General Computer, especially some of these out cases were talking about where the customer experience is a function of how fast a device starts up or how fast the service starts up, or how rich the service could be in terms of different classes of input, voice or visual or whatever else might be. And we think about these data centers where the closed loop between the processing and the interesting of some of these models and how it affects what that transactions going to do. We're tournament lower late. See, that's driving a lot of designers to think about how they can start moving certain classes of function closer to the memory, both from a security standpoint from an error correction standpoint, talk to us a little bit about the direction that to Sheba imagines, Oh, the differential ability of future memories relative Well, memories today, relative to where they've been, how what kinds of features and functions are being added to some of these parts to make them that much more robust in some of these application. >> I think a >> CZ you meant mentioned the robustness. So the memory itself. And I think that actually some current memory devices will allow you to actually identify the number of bits that are being corrected. And then that kind of gives an indication the integrity or the reliability of a particular block of memory. And I think as users are able to get early detection of this, they could do things to move the data around and then make their overall storage more reliable. >> Things got way. Yeah. I mean, we continue, Teo, figure out how to cram orbits within a given space. You know, moving from S l see them. I'll see the teal seemed. And on cue, Elsie. That's all enabling that Teo enabled greater storage. Lower cost on DH, then, Aziz, we just talked from the beginning. Just that there's all kinds of differentiation in terms of of flash products that are really tailored for certain things. Someone focus for really high performance and give up some power. And others you need a certain balance of that. Were, you know, a mobile device, you know, handheld device. You're not going to play. You know, You give up some performance for less power. And so there's a whole spectrum. It's someone you know. Endurance is incredibly important. So we have a full breast of products that address all those particular needs. >> The designer. It's just whatever I need. I could come to you. >> Yeah, that's right. So she betrays them. The full breath of products available. >> All right, gentlemen. Thank you very much for being on the Cube. Brian Coma Guy, director of business development to Sheba Memory America. Scott Beekman, director of Manage Flash. Achieve a memory. America again. Thanks very much for being on the Q. Thank you. Thank you. And this closes this cube conversation on Peter Burress until next time. Thank you very much for watching