>> Announcer: Live from Las Vegas, it's theCUBE. Covering AWS re:Invent 2017. Presented by AWS, Intel and our ecosystem of partners. >> Hey, welcome back everyone. Live here this is theCUBE in Las Vegas for AWS Amazon Web Services re:Invent 2017. Our 5th year covering the event. Wall to wall coverage. Three days, this is our day two. 45,000 people here. Developers and business connecting together this year. Big show. Amazon continues its growth. I'm John Furrier, my co-host Justin Warren. Our next guest is from Washington County Sheriff's Office using Amazon, Amazon Recognition, Chris Adzima, who is the Senior Information Systems Analyst at the Washington County Sheriff. Welcome to theCUBE. >> Nice to have you. >> So Chris. >> be here. >> So, so tons of cool stuff we saw on stage today. You know they've had polylex out for awhile. But you're gonna start to see some of these multi-media services around. Human identification, transcription, Recognition's been out for awhile. With the power of the cloud, you can start rollin' out some pretty cool services. You have one of 'em, talk about your solution and what you guys are doing with it. >> Sure, about last year when Recognition was announced, I wanted to provide our deputies at the Sheriff's office with the way to identify people based on videos that we get from either surveillance or eyewitnesses. So, I looked into Recognition and decided that we should give it a try by giving all of our booking photos or mugshots up to the cloud for it to be indexed. So, that's what I did. I indexed all, about 300,000 booking photos, we have in the last 10 years, and put that into a Recognition Collection. And now I can use the simple tools that AWS gives me to search against that index for any new image that we get in, either from surveillance or an eyewitness, allowing us to get identification within seconds as opposed to having to go through all 700 employees at the Sheriff's Office for the chance that they might have known the person. >> So the old way was essentially grab the footage, and then do the old mugshot kinda scan manually, right? >> Yeah, manually. It wasn't in a book, it was on a website, but essentially, yeah, you had to-- >> I made my point, it sucks. It's hard as hell. >> It's very difficult, very difficult. >> You see on TV all the magic pictures goin' on and the facial recognition, you see on the movies and stuff. How close are we to that right now in terms of that capability? >> Well as far as facial recognition goes it all depends on the data that you have at your fingertips. Right now I have booking photos, so I can identify people with a very high level of certainty if they've been in our jail. If they haven't been in our jail, I obviously don't have much of a chance of identifying them. So, what you see on the TV where it's like, we looked through all the DMV records. We looked through all of the people on the street and all this stuff, We're pretty far off from that because nobody has a catalog of all those images. >> You need to incorporate of all the pictures, all the data. >> Yeah, but when you have the data, it's very simple. >> Right, and it's a lot like scanning for fingerprints. It's like, people would have seen that. You know, you have a fingerprint that you've collected from the crime scene-- >> Chris: Exactly. >> We see it on NCIS or something where you scan through all of that. So, it's pretty similar to that. >> Yeah, it's similar to that, or DNA, or anything like that. If you have the data set, it's very easy to search for those people. >> Yeah. >> So, faces are no different. >> So, how long did it take you to get up and running? Did you have to ingest the photos? How did you do that or? >> So... >> John: They're on a website so you had 'em on digital already. >> From never knowing anything about Amazon Web Services, to a fully-functional prototype of this product took me 30 days. >> John: Wow. >> I had the photos uploaded and the ability to actually run the searches via the API in three. So, extremely easy. Extremely easy. >> So, given the success that you've had with that particular producr, are there other services at AWS that you're looking into? That say, hey, that would actually be really useful for us? >> Yes, a couple that were announced today. First off, the recognition for video. Something that we have a problem with, and I'm hoping recognition for video's going to help with is when you have a surveillance camera, people are moving all the time. Therefore, trying to get a screenshot is going to get a blurry image. We're not getting good results with low-light or low frame rate. But recognition for video is gonna be able to take that movement and still look at the face. Hopefully we're gonna be able to get a better facial identification that way. >> Justin: Okay. >> Another thing that I want to look into is this DeepLens they just announced today. >> John: Awesome. >> That looks extremely promising in the way of me being able to teach it things that we need. A great example of what I would use this for is when a inmate comes in, we take pictures of scars, marks and tattoos. That way, we have a database of all the scars, marks and tattoos on somebody. In case, if they recommit a crime and our eye-witness says, "They had a skull tattoo on their chest" we can then look through all of the people that have a skull tattoo and say, "These are our list of possible suspects." The problem with that is, is that you may enter somebody in as a skull, and you may enter it in as crossbones. Somebody else might put an accidental I in there. So it's very hard to do a text search against that. But if recognition were to come through, or it wouldn't be recognition in this case. If whatever model I built with the DeepLens came through, and said this is a skull and this is the word we use, then I'd be able to index all of those images, quickly pull them up, so we wouldn't even need a picture. We would just need to know, from an eye-witness, that there was a skull on that person's chest. >> John: We had a guest on yesterday from Thorn, which Intel is doing AI for good, and they use essentially, and they didn't say Craigslist, but trying to look for women who were being sold for prostitution, and exploited children and whatnot. And it's all machine learning, and some natural language processing. When you look at the Sage announcement, that looks promising, 'cause they're gonna make, as I was try to democratize the heavy-lifting around all of this, you know, voodoo machine learning. Which, I mean, if you're totally a computer science geek and that's all you do, yeah, you could probably master machine learning. But if you're a practitioner, you're just whipping up. >> Well, yeah, and that's a good example. Because I am not a data scientist. I have no idea how this stuff works in the back end. But being able to utilize, stand on the shoulders of these giants, so to speak, is allowing people like me who A, I only have seven people on my team to devote to this kind of thing. We don't have a lot of resources. We wouldn't be able to get a data scientist. But opening this stuff up to us allows us to build these things, like this facial recognition and other things based on machine learning. And ultimately keep our citizens safe through the work that AWS does in getting this to us. >> Justin: Yeah, and we've been saying at a couple of different interviews so far, that humans don't scale. So these tools that provide the humans that you do have a lot more leverage to get things done. So, we were talking just before, before we started recording that these are tools that assist the humans. You're not replacing the humans with machines that just go oh we're gonna cede all decision-making to you. This is just another tool like being able to fingerprint people and search that. It's one more way of doing the standard policing that you are already doing. >> Exactly, and the tool that I've already created, and any tool I create after that, doesn't ever look to replace our deputies or our detectives. We give them things so that they don't have to do the things like flipping through that book for hours upon hours. They can be out in the field, following the leads, keeping the community safe and apprehending these criminals. >> Do they have on body cameras too? >> Not yet. We are currently looking into body cameras. >> John: That's a trend. They're gonna be instrumented basically like warriors: fully loaded, you know, cameras. >> I tend not to think of it like that. Only because, again, that's a tool that we use. Not to, you know, be that land-warrior so to speak. But more of a-- >> Documentation, I mean, you see 'em on cars when people get pulled over. >> Exactly. >> You've got the evidence. >> It's documentation, just like anything else. It's just that one more tool that helps that deputy, that detective, that police officer get a better idea of the entire situation. >> Maybe I shouldn't have said war. Maybe I'm just into the Twitch culture where they're all geared up with all the gear. Okay, so next question for you is what's your vibe on the show? Obviously you have great experience working at Amazon. You're a success study because you're trying to get a job done, you got some tools and, >> Right. >> making it happen. What's your take this year? What's your vibe of the show? >> I'm really excited about a lot of stuff I'm seeing at the show. A lot of the announcements seemed like they were almost geared towards me. And I know they weren't obviously, but it really felt like announcement after announcement were these things that I'm wanting to go home and immediately start to play with. Anywhere from the stuff that was in the machine learning to the new elastic containers that they are announcing, to the new LAM defunctions that they're talking about. I mean, just all over the board. I'm very excited for all these new things that I get to go home and play with. >> What do you think, Justin? What's your take on the vibe show? >> I find that it's an interesting show. I'm finding it a little different than what I was expecting. This is my first time here at AWS re:Invent. I go to a lot of other trade shows and I was expecting more of like a developer show. Like I'm going to CubeCon next week and that's full of people with spiky hair, and pink shoes, and craziness. >> John: That's the area, by the way. >> Oh that's the area, right. It's a bit more casual than some of the other more businessy sort of conferences. I mean, here I am, wearing a jacket. So I don't feel completely out of place here, but it does feel like it's that blending of business and use cases and the things that you actually get done with it as well as there being people who have the tools that they want to go and build amazing new things with. >> Chris: Right, right, yeah. >> So it's a nice blend, I think. >> Yeah, I've found that it definitely doesn't feel like any other developer conference I've been to. But being in the public sector, I tend to go to the more business-suit conferences. >> John: This is like total developer for you, from a public sector perspective. >> From where I'm coming from, this is very laid back. And extremely... >> Oh yeah. >> But at the same time, it's very like a mixture. Like you said, you see executives mingling with the developers talking about things-- >> John: You're a good example I think of Amazon. First of all, there's the builder thing in the area is supposed to be pretty cool. I was told to go there last night. People came back, it was very much builder, kind of maker culture. They're doing prototypes, it was very developer-oriented. But the public sector, I'm astonished by Amazon's success there because the stuff is easy and low-cost to get in. And public sector is not known for its agility. >> Chris: No. >> I mean, it's music to your ears, right? I mean, if you're in the public sector, you're like, "What? Now I can get it done?" >> Very much so. And one thing I love to share about our solution is the price, right? Because I spent $6 a month for my AWS bill. Right? >> John: Wow. >> That's extremely easy to sell to tax payers, right? It's extremely easy to sell to the higher-ups in government to say, I'm gonna tinker around with this, but even if we solve one crime, we've already seen a return on our investment above and beyond what we expected. >> Yeah. >> No brainer, no brainer. Chris, thanks so much for sharing your story. We really appreciate it. Congratulations on your success and keep in touch with theCube. Welcome to theCube Alumni Club. >> Alright. >> John: For coming out, it's theCube here. Amazon re:Invent, bringing all the action down, all of the success stories, all of the analysis. I'm John Furrier with theCube. More live coverage after this short break. (upbeat music)

>> Narrator: Live from Las Vegas, it's theCUBE. Covering AWS re:Invent 2017 presented by AWS, Intel and our ecosystem of partners. >> Hello and welcome back. Live here is theCUBE's exclusive coverage here in Las Vegas. 45,000 people attending Amazon Web Services' AWS re:Invent 2017. I'm John Furrier with Lisa Martin. Our next guest is Miles Kingston, he is the General Manager of the Smart Home Group at Intel Corporation. Miles, it's great to have you. >> Thank you so much for having me here, I'm really happy to be here. >> Welcome to theCUBE Alumni Club. First time on. All the benefits you get as being an Alumni is to come back again. >> Can't wait, I'll be here next year, for sure. >> Certainly, you are running a new business for Intel, I'd like to get some details on that, because smart homes. We were at the Samsung Developer Conference, we saw smart fridge, smart living room. So we're starting to see this become a reality, for the CES, every 10 years, that's smart living room. So finally, with cloud and all of the computing power, it's arrived or has it? >> I believe we're almost there. I think the technology has finally advanced enough and there is so much data available now that you have this combination of this technology that can analyze all of this data and truly start doing some of the artificial intelligence that will help you make your home smarter. >> And we've certainly seen the growth of Siri with Apple, Alexa for the home with Amazon, just really go crazy. In fact, during the Industry Day, yesterday, you saw the repeat session most attended by developers, was Alexa. So Alexa's got the minds and has captured the imagination of the developers. Where does it go from here and what is the difference between a smart home and a connected home? Can you just take a minute to explain and set the table on that? >> Yeah and I agree, the voice capability in the home, it's absolutely foundational. I think I saw a recent statistic that by 2022, 55% of US households are expected to have a smart speaker type device in their home. So that's a massive percentage. So I think, if you look in the industry, connected home and smart home, they're often use synonymously. We personally look at it as an evolution. And so what I mean by that is, today, we think the home is extremely connected. If I talk about my house, and I'm a total geek about this stuff, I've got 60 devices connected to an access point, I've got another 60 devices connected to an IOT hub. My home does not feel very smart. It's crazy connected, I can turn on lights on and off, sprinklers on and off, it's not yet smart. What we're really focused on at Intel, is accelerating that transition for your home to truly become a smart home and not just a connected home. >> And software is a key part of it, and I've seen developers attack this area very nicely. At the same time, the surface area with these Smart Homes for security issues, hackers. Cause WiFi is, you can run a process on, these are computers. So how does security fit into all of this? >> Yeah, security is huge and so at Intel we're focused on four technology pillars, which we'll get through during this discussion. One of the first ones is connectivity, and we actually have technology that goes into a WiFi access point, the actual silicon. It's optimized for many clients to be in the home, and also, we've partnered with companies, like McAfee, on security software that will sit on top of that. That will actually manage all of the connected devices in your home, as that extra layer of security. So we fundamentally agree that the security is paramount. >> One of the things that I saw on the website that says, Intel is taking a radically different approach based on proactive research into ways to increase smart home adoption. What makes Intel's approach radically different? >> Yeah, so I'm glad that you asked that. We've spent years going into thousands of consumers' homes in North America, Western Europe, China, etc. To truly understand some of the pain points they were experiencing. From that, we basically, gave all this information to our architects and we really synthesized it into what areas we need to advance technology to enable some of these richer use cases. So we're really working on those foundational building blocks and so those four ones I mentioned earlier, connectivity, that one is paramount. You know, if you want to add 35 to 100 devices in your home, you better make sure they're all connected, all the time and that you've got good bandwidth between them. The second technology was voice, and it's not just voice in one place in your home, it's voice throughout your home. You don't want to have to run to the kitchen to turn your bedroom lights on. And then, vision. You know, making sure your home has the ability to see more. It could be cameras, could be motion sensors, it could be vision sensors. And then this last one is this local intelligence. This artificial intelligence. So the unique approach that Intel is taking is across all of our assets. In the data center, in our artificial intelligence organization, in our new technology organization, our IOT organization, in our client computing group. We're taking all of these assets and investing them in those four pillars and kind of really delivering unique solutions, and there's actually a couple of them that have been on display this week so far. >> How about DeepLens? That certainly was an awesome keynote point, and the device that Andy introduced is essentially a wireless device, that is basically that machine learning an AI in it. And that is awesome, because it's also an IOT device, it's got so much versatility to it. What's behind that? Can you give some color to DeepLens? What does it mean for people? >> So, we're really excited about that one. We partnered with Amazon at AWS on that for quite some time. So, just a reminder to everybody, that is the first Deep Learning enabled wireless camera. And what we're helped do in that, is it's got an Intel Atom processor inside that actually runs the vision processing workload. We also contributed a Deep Learning toolkit, kind of a software middleware layer, and we've also got the Intel Compute Library for deep neural networks. So basically, a lot of preconfigured algorithms that developers can use. The bigger thing, though, is when I talked about those four technology pillars; the vision pillar, as well as the artificial intelligence pillar, this is a proof point of exactly that. Running an instance of the AWS service on a local device in the home to do this computer vision. >> When will that device be available? And what's the price point? Can we get our hands on one? And how are people going to be getting this? >> Yeah, so what was announced during the keynote today is that there are actually some Deep Learning workshops today, here at re:Invent where they're actually being given away, and then actually as soon as the announcement was made during the keynote today, they're actually available for pre-order on Amazon.com right now. I'm not actually sure on the shipping date on Amazon, but anybody can go and check. >> Jeff Frick, go get one of those quickly. Order it, put my credit card down. >> Miles: Yes, please do. >> Well, that's super exciting and now, where's the impact in that? Because it seems like it could be a great IOT device. It seems like it would be a fun consumer device. Where do you guys see the use cases for these developing? >> So the reason I'm excited about this one, is I fundamentally believe that vision is going to enable some richer use cases. The only way we're going to get those though, is if you get these brilliant developers getting their hands on the hardware, with someone like Amazon, who's made all of the machine learning, and the cloud and all of the pieces easier. It's now going to make it very easy for thousands, ideally, hundreds of thousands of developers to start working on this, so they can enable these new use cases. >> The pace of innovation that AWS has set, it's palpable here, we hear it, we feel it. This is a relatively new business unit for Intel. You announced this, about a year ago at re:Invent 2016? Are you trying to match the accelerated pace of innovation that AWS has? And what do you see going on in the next 12 months? Where do you think we'll be 12 months from now? >> Yeah, so I think we're definitely trying to be a fantastic technology partner for Amazon. One of the things we have since last re:Invent is we announced we were going to do some reference designs and developer kits to help get Alexa everywhere. So during this trade show, actually, we are holding, I can't remember the exact number, but many workshops, where we are providing the participants with a Speech Enabling Developer toolkit. And basically, what this is, is it's got an Intel platform, with Intel's dual DSP on it, a microarray, and it's paired with Raspberry Pi. So basically, this will allow anybody who already makes a product, it will allow them to easily integrate Alexa into that product with Intel inside. Which is perfect for us. >> So obviously, we're super excited, we love the cloud. I'm kind of a fanboy of the cloud, being a developer in my old days, but the resources that you get out of the cloud are amazing. But now when you start looking at these devices like DeepLens, the possibilities are limitless. So it's really interesting. The question I have for you is, you know, we had Tom Siebel on earlier, pioneer, invented the CRM category. He's now the CEO of C3 IOT, and I asked him, why are you doing a startup, you're a billionaire. You're rich, you don't need to do it. He goes, "I'm a computer guy, I love doing this." He's an entrepreneur at heart. But he said something interesting, he said that the two waves that he surfs, they call him a big time surfer, he's hanging 10 on the waves, is IOT and AI. This is an opportunity for you guys to reimagine the smart home. How important is the IOT trend and the AI trend for really doing it right with smart home, and whatever we're calling it. There's an opportunity there. How are you guys viewing that vision? What progress points have you identified at Intel, to kind of, check? >> Completely agree. For me, AI really is the key turning point here. 'Cause even just talking about connected versus smart, the thing that makes it smart is the ability to learn and think for itself. And the reason we have focused on those technology pillars, is we believe that by adding voice everywhere in the home, and the listening capability, as well as adding the vision capability, you're going to enable all of this rich new data, which you have to have some of these AI tools to make any sense of, and when you get to video, you absolutely have to have some amount of it locally. So, that either for bandwidth reasons, for latency reasons, for privacy reasons, like some of the examples that were given in the keynote today, you just want to keep that stuff locally. >> And having policy and running on it, you know, access points are interesting, it gives you connectivity, but these are computers, so if someone gets malware on the home, they can run a full threaded process on these machines. Sometimes you might not want that. You want to be able to control that. >> Yes, absolutely. We would really believe that the wireless access point in the home is one of the greatest areas where you can add additional security in the home and protect all of the devices. >> So you mentioned, I think 120 different devices in your home that are connected. How far away do you think your home is from being, from going from connected to smart? What's that timeline like? >> You know what I think, honestly, I think a lot of the hardware is already there. And the examples I will give is, and I'm not just saying this because I'm here, but I actually do have 15 Echos in my house because I do want to be able to control all of the infrastructure everywhere in the home. I do believe in the future, those devices will be listening for anomalies, like glass breaking, a dog barking, a baby crying, and I believe the hardware we have today is very capable of doing that. Similarly, I think that a lot of the cameras today are trained to, whenever they see motion, to do certain things and to start recording. I think that use case is going to evolve over time as well, so I truly believe that we are probably two years away from really seeing, with some of the existing infrastructure, truly being able to enable some smarter home use cases. >> The renaissance going on, the creativity is going to be amazing. I'm looking at a tweet that Bert Latimar, from our team made, on our last interview with the Washington County Sheriff, customer of Amazon, pays $6 a month for getting all the mugshots. He goes, "I'm gonna use DeepLens for things like "recognizing scars and tattoos." Because now they have to take pictures when someone comes in as a criminal, but now with DeepLens, they can program it to look for tattoos. >> Yeah, absolutely. And if you see things like the Ring Doorbell today, they have that neighborhood application of it so you can actually share within your local neighborhood if somebody had a package stolen, they can post a picture of that person. And even just security cameras, my house, it feels like Fort Knox sometimes, I've got so many security cameras. It used to be, every time there was a windstorm, I got 25 alerts on my phone, because a branch was blowing. Now I have security cameras that actually can do facial recognition and say, your son is home, your daughter is home, your wife is home. >> So are all the houses going to have a little sign that says,"Protected by Alexa and Intel and DeepLens" >> Don't you dare, exactly. (laughs) >> Lisa: And no sneaking out for the kids. >> Yes, exactly. >> Alright, so real quick to end the segment, quickly summarize and share, what is the Intel relationship with Amazon Web Services? Talk about the partnership. >> It's a great relationship. We've been partnering with Amazon for over a decade, starting with AWS. Over the last couple of years, we've started working closely with them on their first party products. So, many of you have seen the Echo Show and the Echo Look, that has Intel inside. It also has a RealSense Camera in the Look. We've now enabled the Speech Enabling Developer Kit, which is meant to help get Alexa everywhere, running on Intel. We've now done DeepLens, which is a great example of local artificial intelligence. Partnered with all the work we've done with them in the cloud, so it really is, I would say the partnership expands all the way from the very edge device in the home, all the way to the cloud. >> Miles, thanks for coming, Miles Kingston with Intel, General Manager of the Smart Home Group, new business unit at Intel, really reimagining the future for people's lives. I think in this great case where technology can actually help people, rather than making it any more complicated. Which we all know if we have access points and kids gaming, it can be a problem. It's theCUBE, live here in Las Vegas. 45,000 people here at Amazon re:Invent. Five years ago, our first show, only 7,000. Now what amazing growth. Thanks so much for coming out, Lisa Martin and John Furrier here, reporting from theCUBE. More coverage after this short break. (light music)