foreign to the AWS re invent Cube coverage I'm John Furrier here with thecube got a great guest line up here talking about computer vision at the edge and saramba product lead AWS events mobile app and Steven White solution architect for Edge ml thanks for joining me today computer vision at the edge with adios Panorama thanks for coming on happy to be here so what is Ada's Panorama let's get that out there right away what's the focus of that let's define what that is and we'll get into this computer vision at the Edge Story yeah so thanks Sean uh AWS Panorama is our managed uh computer vision at the Ed service and so to put that perspective you know imagine with me the last time that you've been into a restaurant or maybe your favorite retail store or even office building and didn't notice a camera and so we were talking to customers and trying to understand you know what is it that they do with all of this uh video content that they're collecting and surprisingly we found out that large part of this data just sits on a hard drive somewhere and never gets used and so as we dug in a little deeper to better understand you know why this data is just sitting there I think there were three main themes that continue to come up across the board uh one is you know around privacy right privacy security a lot of the data that's being captured with these cameras tend to be either intellectual property that is you know focused on kind of the Manifest factoring process or maybe about their products that they don't want to get out there you know or and or it could just be a private pii data privacy data related to their employee Workforce and and maybe even customers so you know privacy is is a big concern second was just the amount of bandwidth that cameras create and produce tend to be uh prohibitive from for you know sending back to a centralized location for processing uh each camera stream tends to generate about a couple of megabytes of data so it could get very voluminous as you've got tons of cameras at your location and the other issue was around just the latency required to take action on the data so a lot of times especially in the manufacturing space um you know as as you've got a manufacturing line of products that are coming through and you need to take action in milliseconds and so latency is extremely important from process processing time to taking action so those three uh main drivers you know we ended up developing this AWS service called Panorama that addressed these three main challenges with uh you know with analyzing video content and database Panorama in particular there's there's two main components right we've got the compute platform that is about the size of a sheet of paper your standard you know eight and a half by eleven size sheet of paper so the platform itself is extremely compact it's a it's a video and and deep learning algorithms it sits at the customer premise and directly interfaces with video cameras using the standard IP protocols collects that data uh processes it and then immediately deletes the data so there isn't any any information that's actually stored at the location and you know basically the only thing that's left over is just metadata that describes that data and then the other key component here is the cloud um you know service component which helps manage the fleet of devices that are existing so all of these Panorama appliances that are sitting at your premise there's a cloud component that helps you configure you know operationalize check the health as well as deploy applications and configure cameras so that's uh basically you know the the service is really hopefully optimal or you know is focused on um helping customers really make use of all of their video data at the edge you know the theme here at re invent this year is applications we've seen things like connect add value to customers this is one of those situations where everyone's got cameras it's easy to connect to an IP address and Cloud kind of gives you all those Services there are a lot of real world applications that people can can Implement with this because with the cloud you kind of have this ability to kind of stand it up and get value out of that data what are some of the real world applications that it was because they're implementing with the camera because I mean I can see a lot of use cases here where I can you don't have to build the clouds there for me I can stand it up and start getting value what kind of use cases do you see implementing from your customers yeah so our customers are really amazing with the different types of problems um and opportunities that they bring to us for uh using computer vision at the edge in their data um you know we've got everything from animal Warfare use cases to being able to use you know video to uh to to make sure that you know food processing and just you know the health of animals is uh is uh sufficient we've got cases in manufacturing doing visual inspection and anomaly detection so looking at products that are on the conveyor belt as they're being manufactured and put together to make sure that obviously they're they're put together in the right in the right way um and then we've got different port authority and airports that use uh for you know security and cargo tracking to make sure that the products get to where they're supposed to go in a timely and efficient manner manager manage and then finally one of the use cases that really show facing a re invent this year is a part of our retail analytics portfolio which is line counting and so in particular we see a lot of customers in the retail space such as quick service restaurants even you know Peril retail and convenience stores where they want to better understand um you know whether their product is being made to the customer specification we've got like french fry use cases to see how the quality of that french fry is um you know over time and if they need to make a new batch when they've got a influx of customers coming in and to understanding employee to customer ratio maybe they need to put somebody on the cash register you know at busy time so there's really just a big number of customers you know opportunities that we've really solving with the computer vision service looks like a great service Panorama looking good and I want to get your thoughts you have the events happy the product lead take us through with your app I know you have decided to use it was Panorama I was a fit for you this year at re invent 2022 but you know you've been doing this event app for a while now take us through the app when it started how it's evolved and kind of what's the focus this year of course Sean app started in 26 4 re invent and since we've really expanded this year we've actually supported up to 34 events for AWS and continue to expand that for future years for this year though specifically we wanted to contribute to the overall event experience at re invent by helping people go through the process of checking in and picking up their badge in a more formed and efficient way so we decided that the AWS Panorama team and their computer vision and Edge capabilities were the best fit to analyze the lines and the registration kiosks that we have on site at both the Venetian and MGM at the airport we'll have digital signage showcasing our bad pickup wait times that will help attendees select which badge pickup location that they want to go to and see the current wait times live on those signs as well as through the mobile app so I can basically um get the feel for the line size when to come in does it give me a little recognition of who I am and kind of when I get there there's a TIA pull up my records as I do a little intelligence behind the scenes give us a little peek under the covers what's the solution look like so you do have to sign into the mobile app with your registration and so with that we will have your QR code specific for your check-in experience available to you you'll see that at the top of the screen and we'll know once you've checked in that will disappear but if you haven't checked in that Banner is at the top of the event screen and when you tap that that's when you can see all the different options where you can go and pick up your badge we do have five locations this year for badge pickup and the app will help you kind of navigate which one of those options will be best for you given you know maybe you want to pick it up right away at the airport or you may want to go even to one of your other Hotel options that we'll have um to pick it up at foreign okay now I gotta get I got to ask you on the app what's the coolest thing you got going on this year what's new every year there seems to be a new feature what's the focus this year so can you share a a peek on some of the key features yeah so our biggest and most popular features are always around the session catalog and calendar as you can utilize both to of course organize your event schedule and really stay on top of what you want to do on site and get the most out of your reinvent experience this year we have a few new exciting features of course badge pickup line counting is is one of our biggest but we also will have a one-way calendar sync so you can sync all of your calendar activities to your native device calendar as well as pure talk which is our newest feature that we launched at the start of November where you can interact with other attendees who have opted in and even set up time on site to meet one-on-one with them we've also filled that experience with peer talk experts that include AWS experts that are ready to meet and interact with attendees who have interest on site you know I love this topic it's a very cool video we love video we're doing this remote video I'm getting ready for you know all the action and and analyzing it video's cool and so to me if we could look at the video and say hey we haven't soon that might have body cams in the future um video is great people love videos very engaging but always people that say what about my privacy so how do you guys put in place uh mechanisms to preserve attendee privacy yeah I think so I'm not I think you know you and our customers share the same concern and so we have built uh foundationally that AWS Panorama to address you know both privacy and security concerns with uh associated with all this video content and so in particular the AWS Panorama Appliance is something that sits at the customer premise it interface directly with video cameras uh the data all the video that's processed is immediately deleted nothing stored um and you know the outcome of the processing is just simple metadata so it's Text data that you know as an example in the case of the AWS uh line counting solution that we're demoing this year at Panorama along with you know the events team uh it's simply a count of the number of people in the video at any given time so so you know we we do take privacy uh at heart and have made every effort to address them and what are some of the things that you're doing at the event app I mean I'm imagining you're probably looking at space I mean there's a fire marshal issues around you know people do you take it to that level I mean what's how far are you pushing the envelope on on Panorama what are some of the things that you guys are doing besides check-ins or anything you can share on what's Happening the area where we're utilizing you know Anonymous attendee data otherwise other things in the app are very Anonymous just in nature I mean you do sign in but besides that everything we collect is anonymous and we don't collect unless you consent with the cookie consent that appears right when you first launch the app experience besides that we do have as I mentioned peer talk and and that's just where you're sharing information that you want to share with other attendees on site and then we do have session surveys where you can provide information that you wish about how this survey or how the sessions rather went that you attended on-site yeah Stephen you're you're uh your title has you the solution architect for Edge ml this is the Ultimate Edge use case you're seeing here I mean it's a big part of the future of how companies are going to use video and data just what's your reaction to all this I mean we're at a time it's very kind of an interesting time in the history of the industry as you look at this this is a really big part of of the future with video and Edge like I mentioned users are involved people are involved spaces are involved kind of a fun area what's your reaction to where this is right now so personally I'm very passionate about this uh particular solution and service I've been doing computer vision now for 12 years I started doing in the cloud but when I heard about you know customers really looking for an edge component solution and this you know AWS was still in the early stages I knew I had to be a part of it and so I I you know work with some amazing talented engineers and scientists putting this solution together and of course you know our customers continue to bring us these amazing use cases that you know that just I wouldn't get an opportunity to um you know witness without without you know the support of our customers and so we've got some amazing opportunity amazing projects and you know I just love the love to uh experience that with our customers and partners yeah and and Stephen this is like one of those times where the industry has always had this everyone's scratching the niche somewhere but then you get cloud and scale and data come in and just it accelerates some of these areas that were you know I won't say not growing fast but very interesting like computer vision video events technology in the cloud is changing in a good way some of these areas uh and we're seeing that like computer vision as you mentioned Stephen so Ann event same thing I can imagine this event app will blow up to probably be all things Amazon events and and be the touch Touchstone for all customers and attendees I'm probably thinking the road map there's looking pretty interesting with all the vision you have there what's your what's your reaction to the cloud scale meets events absolutely yeah I know we we have a lot of events that happen at AWS and our goal is to have as many of them in the app as possible where it makes sense right we have a lot of partial Day events to multi-day events and the multi-day events are definitely the area where it's harder for an attendee to organize all that they have to do going on on site as well as everything surrounding the event pre-event uh topics and sessions looking up what they want to do to make sure that they're getting the most of their time on site so we really want to make sure that that's something that an attendee can do with our app as well as it showcase as many of the AWS Services as we have like we are doing here with Panorama we have a few other services in the app as well Amazon location service and Amazon connect to name a couple and we hope to just include more and more with each year as well as more events as the time goes on I'm sure your roadmaps looking great the computer vision is awesome I mean this is a mashup integration apis are going to come around the corner so much excitement after re invent love to follow up with you guys and find out more I think this is a super interesting area the convergence of what you guys are working on to kind of wrap up where do you guys see um AWS Panorama going and where can people learn more about how to get involved how to use the service how to test it out where's this going and how do people learn more but first off you can get customers can get more information about panorama from our website aws.amazon.com Panorama and you know I think where we're going is super exciting you know we continue to improve the product to add support for as an example containers we've added support for Hardware acceleration to improve the number of cameras that we can support so we've you know we've got um you know we can support now with a single device up to 30 40 cameras we've got the ability now to support many different uh we continue to expand the interface types that we support um you know and the different types of even adding sensors and you know expanding to Sensor Fusion so not just computer vision but we've learned from customers that they actually want to incorporate other uh other sensor types and other interfaces so we're bringing in the ability to handle you know computer vision and video but also many other data types as well all right and and Stephen thank you for sharing great stuff computer vision at the edge with Panorama thanks for coming on thecube appreciate it thanks for coming on thank you okay AWS coverage here in the cube I'm John for your host thanks for watching