>> From Boston, Massachusetts it's theCUBE covering LiveWorx 18. Brought to you by PTC. >> Welcome back to Boston, everybody. You're watching theCUBE, the leader in live tech coverage. I'm Dave Vellante with Stu Miniman. This is day one of LiveWorx, theCUBE's special coverage of the PTC-sponsored conference. Karen Leavitt is here. She's the CMO of Locus Robotics. Karen, welcome to theCUBE. Thanks so much for coming on. >> Thanks for having me, Dave. >> So, tell us about Locus Robotics. Most people in our audience might not be familiar with it. >> No, I think when most people think about robots they either think about things that clean their house or something from The Jetsons. But these days robots are really anything that can autonomously fulfill the needs of the job requirements. In our case we build robots that work in e-commerce warehouses. Anybody whose ever purchased anything online realizes that the magic is you click the button, you pay for it, and then two days later it magically shows up at your door. >> How'd that happen? >> Yeah, exactly. Well the magic is the raw materials of most of those goods that you get at your door is human labor. They're actually people who walk through warehouses 10, 15 miles a day pushing glorified shopping carts picking items off of shelves in order to put into a box to ship to you. Well e-commerce has been growing like wildfire and we have actually a labor shortage in this country and so what we need to do is we need to figure out ways of automating the warehouse so that the merchandise can get picked efficiently, cost-effectively, and get it out to the consumers. So let's summarize. The big drivers in the business, the demand drivers you're talking about e-commerce spurring the need for automation, lack of labor, >> Yep. >> or a lot of sort of low level tasks that can be replaced by machines. Is that right? Maybe talk about that a little bit. >> Well, you know there are a few different tasks involved. Humans are still best at the ones requiring manual dexterity. Actually physically picking an item off of a shelf or out of a bin and putting it into a tote, humans are still the best at that. But robots are really the best at transporting merchandise through the warehouse and they not only transport the merchandise, they also transport the instructions. So instead of a worker having to snake her way for 15 miles a day through the warehouse, the worker simply needs a robot at a pick location and a robot displays the information that the worker needs. It shows her a photograph of the item to be picked, tells her the bin location to take it from, then she just does the pick, drops it in, and the robot moves on but it means she can be twice or three times as effective. So we built our robots that are collaborative with humans that make the humans work much better. We created sort of an external bionics, if you will. You know this is like the six million dollar warehouse worker but working with a robot friend. >> And the other trend is there is a labor shortage you're saying >> Absolutely. >> Maybe double click on that a little bit. >> We hear all the time about the labor gap in this country. First of all, we have virtually full employment in this country. When we hear about the labor gap when people say there are six million workers who are unemployed and six million jobs that need to be filled but there's a mismatch. I think a lot of people think well maybe what we need to do is we need to retrain these workers to fill the jobs that need filling and our perspective is maybe we should be doing is training the jobs not to require any training on the part of the humans. So by putting the robots in the warehouse, the robot knows what action needs to be taken, knows what task needs to be performed, and has a really bright, friendly screen to be able to inform the worker. So the entire training is you say to the worker, "Hey whenever you see a robot with it's light turned green, approach the robot and do whatever it tells you to do." And that's the whole training and since we're operating in an industry, e-commerce has a lot of spikes. The last three months of the year, last two months of the year really make up probably 40 percent of all the volume in a typical e-commerce warehouse and so the warehouse operators will often hire temporary workers and those are people that may not be trained on the full layout of the warehouse. But now, with the use of the robots, a warehouse operator can bring in even temporary labor and the training can be minimized to within say 15 minutes so that the robot is really creating an environment where the humans work better and they're more engaged. The work is less cumbersome. They're not having to push or pull a heavy cart and we can use the screen on the robot to really create some gamification to keep that worker engaged and make their job more fun. >> Karen, could you give us a little insight into your business. >> Sure. >> The clients that you sell to, who do you sell to? Are there challenges about them? Do you help them with the kind of the training of the robots aren't going to come put you out of work? >> Absolutely. Sure. The generic form of who our customers are; are warehouse operators, these are large retailers that are operating warehouses from which they do direct shipment to consumers or what are called 3PLs, third-party logistics providers. I'll give you an example. One of customers is DHL. DHL runs thousands of warehouses in which they house other people's products and they store and they ship those good in response to e-commerce orders that come in online. As I said, there are seasonal peaks and valleys to this and everybody is looking to hire workers the same seasonal peaks. So what our robots do is, and actually we've got one back here. Got a robot spinning around. They don't usually spin for a living but they're usually moving through the warehouse. They're effectively self-driving cars that carry things and they have a tablet interface with large text to be able to describe to the workers what's going on. So there's a curious passerby looking at the robot. But the robots integrate with the software that's managing the warehouse. They take the orders as they come in and then the robot will drive through the warehouse to the locations where the merchandise is located and then ask a worker to please grab one of those items, or more than one, and put it into the robot's bin and then the robot will take it to where it needs to go. To packing, it may need to go a gift wrap station or may need to be express shipped. But a company like DHL has found that by using humans alone they get one level of productivity out of their workers and it's typically measured in units picked per hour and with the robots they're getting two and a half to three times that level of productivity. So the worker is still doing the real core part of the task that only the human can do, for now, which is picking the item but the robot's doing everything else: carrying instructions, transporting the merchandise, prioritizing the tasks and actually even directing the workers' motions. >> So for decades in the technology world the innovation of the industry marched to the cadence of Moore's Law. >> Yes. Absolutely >> Metcalf's Law obviously came in so you had these sort of laws that are very predictable Like the sunrise, they come up and you can draw a straight line on a log-log scale. What's the innovation source in this world? >> And there is a Moore's Law and it's being written today for these autonomous vehicles. For the self-driving robots. What we're seeing is the hard tech has really been developed for the automotive industry by and large and we're drafting off of that. So a company our size in this nascent industry of warehouse robotics the price of a robot would be out of reach were it not for the fact that there's been critical mass established in the automotive industry. So they key hard tech items are laser in the form of LIDAR and laser cameras and tactile sensors. So all the things that you would imagine you would equip your self-driving passenger car with the robot gets equipped with and of course this hard tech is advancing along the lines of Moore's Law where it's doubling in functionality or capacity every period and it's dropping in cost. So it gives us the opportunity of either holding the cost steady while continuing to improve the functionality of the robot or holding the functionality steady while dropping the cost and because we offer our robots as a service you're effectively hiring a robot as a worker. There's no capital investment. You don't go and buy this as if you were buying a fork truck, for example. You go and you hire a robot and you pay a monthly salary to the robot and so you're instantly seeing a drop in your operating expense because you've got robots that are able to do the work of a couple of humans and you're paying them a little bit less so that you're able to really make your operating expense that much more predictable and lowering it. >> Presumably with less complaints. >> We were really kind of nervous, honestly, a year and half ago that the workers would revolt but the workers are telling us that they're really enjoying it and so it's also allowing the warehouse operators to retain their workers better because they happier workers. >> So software's the lynchpin as well. You're taking advantage . . . >> It's all software >> . . . of the advances in hard tech and then you've got non-recurring engineering costs and then you've got software-like economics driving the business. >> Yeah, apart from the hard tech robots are probably 90 percent software. They look adorable and they're running around and they have a physical manifestation which is obvious to everyone but it really is all about the software. It's about enabling the robots to move fluidly in an environment that's often very congested and gets more congested at times that are most critical because as the volume rises you need to have more workers, more robots, there's higher volume of product moving through and the robots have to be able to move fluidly through very narrow spaces between people. It's very easy to get a robot to totally avoid a human but in this case because the robots are collaborating with the humans we need them to kind of nuzzle up to you kind of like a service animal and work with you in very close quarters and that's all software. >> So, we've got this demo that I've been mesmerized by, your robot behind us. Do you think that the trend toward robotics will reverse the trend towards offshore manufacturing? Maybe bring some of that back or not? >> So our robots are not manufacturing robots however we sort of play in the same world. We see different robots. One of the interesting characteristics of this display that we're looking at here is you'll notice those robots are hidden behind glass. They're expressly being cordoned off so that they're not working with the humans who are deriving the benefits. [Dave] Much different from what you guys are doing. >> So yeah, ours is really designed to work as closely as you would with a human collaborator, perhaps maybe even more closely. (coughing) Excuse me. What I think we are seeing is we've seen automation again, particularly in large scale manufacturing like the automotive industry, for years as that automation has replaced the need for workers. And of course we now see the automotive industry, even offshore manufacturers, offshore headquartered manufacturers are doing their manufacturing here in the United States and I think because they're able to use this automation to get a more consistent cost of production worldwide. I'm not an expert on the automotive industry but I would imagine that the automation allows them to more consistently predict their costs. >> How large is this market? Can you give us a sense of that? You're probably asked that all the time. You're probably asking yourselves that all the time but when you think about the TAM, it feels like it's enormous. >> Well it's global. Everybody shops. Everybody around the world has e-commerce. It depends on how we slice it, of course. If I just looked at the e-commerce industry today, it's at roughly close to two trillion dollars worldwide in e-commerce top line revenue growing to probably three and a half trillion in just the next four or five years. It's growing about 10 percent a year here in the U.S.. Everybody is seeing the stores disappearing from their malls because people are choosing to buy things online rather than walk into a store to do shopping and we're seeing that trend continue at about ten percent growth every year. So that's growing and then at the same time we can look at it and say in terms of how many robots you need, it's a function of how many humans are required to keep up the pace and the robots sort of represent a fraction of that. The robots are designed to hold payload of varying sizes. Our robots are perfectly-sized for things like consumer packaged goods, clothing, medical devices, things like that. They're not designed to carry large building supplies, for example, but we're seeing robots with different form factors all over. But we're looking at probably a multi-billion dollar market over just the next few years. >> Obviously product costs in e-commerce is huge but the labor costs are quite substantial. >> Labor is the single biggest variable cost. >> So you're attacking a portion of that variable cost. >> Absolutely. >> Be interesting to see as this plays out, sports analogy if I may, what inning are we in here? >> I think we just had the coin-flip. >> Okay, so the national anthem just played. >> Actually, we're a little bit further than that because we have established that they serve their purpose well. We already have 10 customers, four of whom are going on record and saying I'm doubling and tripling my productivity and we expect to see this expanded dramatically over the course of just the next year. I'm seeing this grow at a very rapid pace very similar to the early days of the PC. >> Okay. >> So we've had kickoff, I would say, and the ball is moving downfield. >> And how large are you guys? Headcount-wise. >> Our company is about 70 employees. >> Seven-zero? >> Seven-zero. >> And you're VC-funded presumably? >> We're VC-funded. We're angel-funded. Fairly recently, we took on an additional 25 million dollars about six months ago. >> So that was your A round? >> That was our A round. >> Excellent. Who was in? Who was it? Do you remember offhand or could you tell us? >> Actually, most of the round was taken by a combination of around-the-table folks and a company . . . . . .great I'm going to forget my . . . >> Local VC or East Cost, West Coast? >> No, no. West Coast VC. >> But you guys are a Boston-based company. Just north of Boston, right? >> Yes, just north of Boston. >> Well I guess you're now bi-coastal. Kind of like theCUBE. >> Well, we're international. Our largest customers are DHL, which is obviously a German-domiciled company, and GEODIS, which is a French-domiciled company. So we will be moving offshore very quickly. >> Excellent. Well, Karen, thanks so much for coming to theCUBE. >> Thank you for having me Really interesting story and thanks for bringing your robot here behind us. Really appreciate it. >> Thank you. >> Alright, you're welcome. Keep right there. Stu and I will be back with our next guest right after this short break. You're watching theCUBE live from LiveWorx in Boston. We'll be right back. (electronic music)

(gentle upbeat music) >> Hello, and welcome to theCUBE presentation of the AWS Startup Showcase Open Cloud Innovations. This is season two episode one of an ongoing series covering setting status from the AWS ecosystem. Talking about innovation, here it's open source for this theme. We do this every episode, we pick a theme and have a lot of fun talking to the leaders in the industry and the hottest startups. I'm your host John Furrier here with Lisa Martin in our Palo Alto studios. Lisa great series, great to see you again. >> Good to see you too. Great series, always such spirited conversations with very empowered and enlightened individuals. >> I love the episodic nature of these events, we get more stories out there than ever before. They're the hottest startups in the AWS ecosystem, which is dominating the cloud sector. And there's a lot of them really changing the game on cloud native and the enablement, the stories that are coming out here are pretty compelling, not just from startups they're actually penetrating the enterprise and the buyers are changing their architectures, and it's just really fun to catch the wave here. >> They are, and one of the things too about the open source community is these companies embracing that and how that's opening up their entry to your point into the enterprise. I was talking with several customers, companies who were talking about the 70% of their pipeline comes from the open source community. That's using the premium version of the technology. So, it's really been a very smart, strategic way into the enterprise. >> Yeah, and I love the format too. We get the keynote we're doing now, opening keynote, some great guests. We have Sir John on from AWS started program, he is the global startups lead. We got Swami coming on and then closing keynote with Deepak Singh. Who's really grown in the Amazon organization from containers now, compute services, which now span how modern applications are being built. And I think the big trend that we're seeing that these startups are riding on that big wave is cloud natives driving the modern architecture for software development, not just startups, but existing, large ISV and software companies are rearchitecting and the customers who buy their products and services in the cloud are rearchitecting too. So, it's a whole new growth wave coming in, the modern era of cloud some say, and it's exciting a small startup could be the next big name tomorrow. >> One of the things that kind of was a theme throughout the conversations that I had with these different guests was from a modern application security perspective is, security is key, but it's not just about shifting lab. It's about doing so empowering the developers. They don't have to be security experts. They need to have a developer brain and a security heart, and how those two organizations within companies can work better together, more collaboratively, but ultimately empowering those developers, which goes a long way. >> Well, for the folks who are watching this, the format is very simple. We have a keynote, editorial keynote speakers come in, and then we're going to have a bunch of companies who are going to present their story and their showcase. We've interviewed them, myself, you Dave Vallante and Dave Nicholson from theCUBE team. They're going to tell their stories and between the companies and the AWS heroes, 14 companies are represented and some of them new business models and Deepak Singh who leads the AWS team, he's going to have the closing keynote. He talks about the new changing business model in open source, not just the tech, which has a lot of tech, but how companies are being started around the new business models around open source. It's really, really amazing. >> I bet, and does he see any specific verticals that are taking off? >> Well, he's seeing the contribution from big companies like AWS and the Facebook's of the world and large companies, Netflix, Intuit, all contributing content to the open source and then startups forming around them. So Netflix does some great work. They donated to open source and next thing you know a small group of people get together entrepreneurs, they form a company and they create a platform around it with unification and scale. So, the cloud is enabling this new super application environment, superclouds as we call them, that's emerging and this new supercloud and super applications are scaling data-driven machine learning and AI that's the new formula for success. >> The new formula for success also has to have that velocity that developers expect, but also that the consumerization of tech has kind of driven all of us to expect things very quickly. >> Well, we're going to bring in Serge Shevchenko, AWS Global Startup program into the program. Serge is our partner. He is the leader at AWS who has been working on this program Serge, great to see you. Thanks for coming on. >> Yeah, likewise, John, thank you for having me very excited to be here. >> We've been working together on collaborating on this for over a year. Again, season two of this new innovative program, which is a combination of CUBE Media partnership, and AWS getting the stories out. And this has been a real success because there's a real hunger to discover content. And then in the marketplace, as these new solutions coming from startups are the next big thing coming. So, you're starting to see this going on. So I have to ask you, first and foremost, what's the AWS startup showcase about. Can you explain in your terms, your team's vision behind it, and why those startup focus? >> Yeah, absolutely. You know John, we curated the AWS Startup Showcase really to bring meaningful and oftentimes educational content to our customers and partners highlighting innovative solutions within these themes and ultimately to help customers find the best solutions for their use cases, which is a combination of AWS and our partners. And really from pre-seed to IPO, John, the world's most innovative startups build on AWS. From leadership downward, very intentional about cultivating vigorous AWS community and since 2019 at re:Invent at the launch of the AWS Global Startup program, we've helped hundreds of startups accelerate their growth through product development support, go to market and co-sell programs. >> So Serge question for you on the theme of today, John mentioned our showcases having themes. Today's theme is going to cover open source software. Talk to us about how Amazon thinks about opensource. >> Sure, absolutely. And I'll just touch on it briefly, but I'm very excited for the keynote at the end of today, that will be delivered by Deepak the VP of compute services at AWS. We here at Amazon believe in open source. In fact, Amazon contributes to open source in multiple ways, whether that's through directly contributing to third-party project, repos or significant code contributions to Kubernetes, Rust and other projects. And all the way down to leadership participation in organizations such as the CNCF. And supporting of dozens of ISV myself over the years, I've seen explosive growth when it comes to open source adoption. I mean, look at projects like Checkov, within 12 months of launching their open source project, they had about a million users. And another great example is Falco within, under a decade actually they've had about 37 million downloads and that's about 300% increase since it's become an incubating project in the CNCF. So, very exciting things that we're seeing here at AWS. >> So explosive growth, lot of content. What do you hope that our viewers and our guests are going to be able to get out of today? >> Yeah, great question, Lisa. I really hope that today's event will help customers understand why AWS is the best place for them to run open source, commercial and which partner solutions will help them along their journey. I think that today the lineup through the partner solutions and Deepak at the end with the ending keynote is going to present a very valuable narrative for customers and startups in selecting where and which projects to run on AWS. >> That's great stuff Serge would love to have you on and again, I want to just say really congratulate your team and we enjoy working with them. We think this showcase does a great service for the community. It's kind of open source in its own way if I can co contributing working on out there, but you're really getting the voices out at scale. We've got companies like Armory, Kubecost, Sysdig, Tidelift, Codefresh. I mean, these are some of the companies that are changing the game. We even had Patreon a customer and one of the partners sneak with security, all the big names in the startup scene. Plus AWS Deepak saying Swami is going to be on the AWS Heroes. I mean really at scale and this is really a great. So, thank you so much for participating and enabling all of this. >> No, thank you to theCUBE. You've been a great partner in this whole process, very excited for today. >> Thanks Serge really appreciate it. Lisa, what a great segment that was kicking off the event. We've got a great lineup coming up. We've got the keynote, final keynote fireside chat with Deepak Singh a big name at AWS, but Serge in the startup showcase really innovative. >> Very innovative and in a short time period, he talked about the launch of this at re:Invent 2019. They've helped hundreds of startups. We've had over 50 I think on the showcase in the last year or so John. So we really gotten to cover a lot of great customers, a lot of great stories, a lot of great content coming out of theCUBE. >> I love the openness of it. I love the scale, the storytelling. I love the collaboration, a great model, Lisa, great to work with you. We also Dave Vallante and Dave Nicholson interview. They're not here, but let's kick off the show. Let's get started with our next guest Swami. The leader at AWS Swami just got promoted to VP of the database, but also he ran machine learning and AI at AWS. He is a leader. He's the author of the original DynamoDB paper, which is celebrating its 10th year anniversary really impacted distributed computing and open source. Swami's introduced many opensource aspects of products within AWS and has been a leader in the engineering side for many, many years at AWS, from an intern to now an executive. Swami, great to see you. Thanks for coming on our AWS startup showcase. Thanks for spending the time with us. >> My pleasure, thanks again, John. Thanks for having me. >> I wanted to just, if you don't mind asking about the database market over the past 10 to 20 years cloud and application development as you see, has changed a lot. You've been involved in so many product launches over the years. Cloud and machine learning are the biggest waves happening to your point to what you're doing now. Software is under the covers it's powering it all infrastructure is code. Open source has been a big part of it and it continues to grow and change. Deepak Singh from AWS talks about the business model transformation of how like Netflix donates to the open source. Then a company starts around it and creates more growth. Machine learnings and all the open source conversations around automation as developers and builders, like software as cloud and machine learning become the key pistons in the engine. This is a big wave, what's your view on this? How how has cloud scale and data impacting the software market? >> I mean, that's a broad question. So I'm going to break it down to kind of give some of the back data. So now how we are thinking about it first, I'd say when it comes to the open source, I'll start off by saying first the longevity and by ability of open sources are very important to our customers and that is why we have been a significant contributor and supporter of these communities. I mean, there are several efforts in open source, even internally by actually open sourcing some of our key Amazon technologies like Firecracker or BottleRocket or our CDK to help advance the industry. For example, CDK itself provides some really powerful way to build and configure cloud services as well. And we also contribute to a lot of different open source projects that are existing ones, open telemetries and Linux, Java, Redis and Kubernetes, Grafana and Kafka and Robotics Operating System and Hadoop, Leucine and so forth. So, I think, I can go on and on, but even now I'd say the database and observability space say machine learning we have always started with embracing open source in a big material way. If you see, even in deep learning framework, we championed MX Linux and some of the core components and we open sourced our auto ML technology auto Glue on, and also be open sourced and collaborated with partners like Facebook Meta on Fighter showing some major components and there, and then we are open search Edge Compiler. So, I would say the number one thing is, I mean, we are actually are very, very excited to partner with broader community on problems that really mattered to the customers and actually ensure that they are able to get amazing benefit of this. >> And I see machine learning is a huge thing. If you look at how cloud group and when you had DynamoDB paper, when you wrote it, that that was the beginning of, I call the cloud surge. It was the beginning of not just being a resource versus building a data center, certainly a great alternative. Every startup did it. That's history phase one inning and a half, first half inning. Then it became a large scale. Machine learning feels like the same way now. You feel like you're seeing a lot of people using it. A lot of people are playing around with it. It's evolving. It's been around as a science, but combined with cloud scale, this is a big thing. What should people who are in the enterprise think about how should they think about machine learning? How has some of your top customers thought about machine learning as they refactor their applications? What are some of the things that you can share from your experience and journey here? >> I mean, one of the key things I'd say just to set some context on scale and numbers. More than one and a half million customers use our database analytics or ML services end-to-end. Part of which machine learning services and capabilities are easily used by more than a hundred thousand customers at a really good scale. However, I still think in Amazon, we tend to use the phrase, "It's day one in the age of internet," even though it's an, or the phrase, "Now, but it's a golden one," but I would say in the world of machine learning, yes it's day one but I also think we just woke up and we haven't even had a cup of coffee yet. That's really that early, so. And, but when you it's interesting, you've compared it to where cloud was like 10, 12 years ago. That's early days when I used to talk to engineering leaders who are running their own data center and then we talked about cloud and various disruptive technologies. I still used to get a sense about like why cloud and basic and whatnot at that time, Whereas now with machine learning though almost every CIO, CEO, all of them never asked me why machine learning. Instead, the number one question, I get is, how do I get started with it? What are the best use cases? which is great, and this is where I always tell them one of the learnings that we actually learned in Amazon. So again, a few years ago, probably seven or eight years ago, and Amazon itself realized as a company, the impact of what machine learning could do in terms of changing how we actually run our business and what it means to provide better customer experience optimize our supply chain and so far we realized that the we need to help our builders learn machine learning and the help even our business leaders understand the power of machine learning. So we did two things. One, we actually, from a bottom-up level, we built what I call as machine learning university, which is run in my team. It's literally stocked with professors and teachers who offer curriculum to builders so that they get educated on machine learning. And now from a top-down level we also, in our yearly planning process, we call it the operational planning process where we write Amazon style narratives six pages and then answer FAQ's. We asked everyone to answer one question around, like how do you plan to leverage machine learning in your business? And typically when someone says, I really don't play into our, it does not apply. It's usually it doesn't go well. So we kind of politely encourage them to do better and come back with a better answer. This kind of dynamic on top-down and bottom-up, changed the conversation and we started seeing more and more measurable growth. And these are some of the things you're starting to see more and more among our customers too. They see the business benefit, but this is where to address the talent gap. We also made machine learning university curriculum actually now open source and freely available. And we launched SageMaker Studio Lab, which is a no cost, no set up SageMaker notebook service for educating learner profiles and all the students as well. And we are excited to also announce AIMLE scholarship for underrepresented students as well. So, so much more we can do well. >> Well, congratulations on the DynamoDB paper. That's the 10 year anniversary, which is a revolutionary product, changed the game that did change the world and that a huge impact. And now as machine learning goes to the next level, the next intern out there is at school with machine learning. They're going to be writing that next paper, your advice to them real quick. >> My biggest advice is, always, I encourage all the builders to always dream big, and don't be hesitant to speak your mind as long as you have the right conviction saying you're addressing a real customer problem. So when you feel like you have an amazing solution to address a customer problem, take the time to articulate your thoughts better, and then feel free to speak up and communicate to the folks you're working with. And I'm sure any company that nurtures good talent and knows how to hire and develop the best they will be willing to listen and then you will be able to have an amazing impact in the industry. >> Swami, great to know you're CUBE alumni love our conversations from intern on the paper of DynamoDB to the technical leader at AWS and database analyst machine learning, congratulations on all your success and continue innovating on behalf of the customers and the industry. Thanks for spending the time here on theCUBE and our program, appreciate it. >> Thanks again, John. Really appreciate it. >> Okay, now let's kick off our program. That ends the keynote track here on the AWS startup showcase. Season two, episode one, enjoy the program and don't miss the closing keynote with Deepak Singh. He goes into great detail on the changing business models, all the exciting open source innovation. (gentle bright music)

>> (soft music) >> Presenter: From around the globe. It's theCUBE with digital coverage of IBM Think 2021 brought to you by IBM. >> Welcome back everyone to the CUBE's coverage of IBM Think 2021. I'm your host, John furry with theCUBE. Our next guest Manish Chawla who's the industry general manager of energy, resources and manufacturing, a great guest to break down this next generation of infrastructure modern applications and changing the business in the super important areas he's regulated verticals. Manish, it's great to see you. Thank you for coming back on theCUBE. >> Thank you John. Good to meet you. >> You know, this is the area where I've been saying for years the cloud brings great scale horizontally scalable data, but at the end of the day, AI and automation really has to be specialized in the verticals. In this we're going to see the action the ecosystems for connecting. This is a big deal here I think this year, transformation is the innovation, innovation at scale. This seems to be the underlying theme that we've been reporting on. So I'd love to get your thoughts on how you see this Fourth Industrial Revolution as you say, coming about. Can you define for us what that means? And when you say that, what does it mean for customers? >> Yeah, sure, sure. So, you know, in sort of simple terms all the technologies that we see around us, whether it's AI we talk about AI, we talk about 5G, we talk about Edge Cloud Robotics. So the application of those to the physical world in some sense in the industrial world is what we define as the Fourth Industrial Revolution. Essentially, it's the convergence between the humans, the physical aspect, like the machines and the cyber either digital aspects, bringing that together. So companies can unlock the value from the terabytes and petabytes of data that our connected world is now able to produce. >> How does the IOT world come in? We've been again, I did a panel I think two years ago called you know the industrial IOT Armageddon. And it was really kind of pointing. It was kind of provocative title, but the point was you know, the industrial connections are all devices now and they're connected to the network security super important. This industrial revolution includes this new edge. >> It's got to be smarter and intelligent. What's your take on that? >> Yeah, absolutely. It is about the edge. It's about devices. It's about delivering capturing the data from the umpteen devices. You know, we've recently heard about the chip shortage which gives you an idea that there is so much utilization of compute power everywhere in the world. And the world is becoming very software defined. So whether it's software defined machines software defined products, the washing machines that we use at home, the cars we use home, everything is gradually becoming, not gradually I'd say rapidly becoming intelligent. And so that edge or IOT is the foundation stone of everything we're talking about. >> Well, you mentioned software on a chip SOC that's a huge mega wave coming. That's going to bring so much more compute into smaller form factors which leads me to my next question, which kind of, I'm kind of answering for myself but I'm not a manufacturing company but why should they care about this trend from a business perspective besides the obvious new connection points? What's really in it for them? >> Yeah. So big topic right now is this topic of resilience, right? So that's one aspect. This, the pandemic has taught us that resilience is a core objective. The second objective, which is front and center of all CEOs or CEOs is out-performance. And so what we're seeing is out-performance are investing in technology for many goals, right? So it's either sustainability which is a big topic these days, and a huge priority. It's about efficiency. It's about productivity. It's also now more and more about delivering a much stronger customer experience, right? Making your products easier to use much easily consumable as well. So if you, when you pull it all together it's an end to end thinking about using data to drive those objectives of out-performance as well as resilience. >> What's the progress being made so far on the manufacturing industry on this front? I mean, is it moving faster or you mentioned accelerating but where is the progress bar right now? >> So I think as we came into 2020, I would have described it as we were starting to enter the chapter two where companies were moving from experimentation to really thinking of scaling this. And what we found is the pandemic really caused a big focus on these, as Winston Churchill has been attributed the quote "Never waste a good crisis." A lot of CEOs, a lot of executives and leadership really put their energy into accelerating digital transformation. I think we really, two thirds have been able to accelerate their digital transformation. So the good news is, you know companies don't have to be convinced about this anymore. They're really, their focus is on where should I start? Where should I focus? And what should I do next? Right, is really the focus. And they are investing in sort of two types of technologies is the way we see it. What I would call foundational technologies because there's a recognition that to apply the differentiating technologies like AI and capturing and taking value of the data you need a strong architectural foundation. So whether it's cybersecurity, it's what we call ITOT integration connecting the devices back to the mothership. And it's also applying cloud but cloud in this context is not about typically what we think as public cloud or a central spot. It's really bringing cloud-like technologies also to the edge or to the plant or to the device itself whether it's a mobile device or a physical device. And that foundation is that recognition that you've got to have the foundation that you can build your capabilities on top. Whether it's for customers or clients or colleagues. >> That's a great insight on the architecture. I think that's a successful playbook. It sounds so easy. I do agree with you. I think people have said this is a standard now hybrid cloud, the edge pretty clear visibility on the architecture of what to do or what needs to be done, how to do it, all other story. So I have to ask you, we hear of these barriers. There's always blockers. I think COVID's released some of those relieved some of those blockers because people have to force their way into the transformation but what are those barriers that are stopping the acceleration for customers to achieve the benefits that they need to see? >> Yeah. So I think one or one key barrier is a recognition that most of our plants or manufacturing facilities or supply chains really run in a brownfield manner. I, there's so many machines so many facilities that have been built over decades. So there's a proliferation of different ages of devices, machines, et cetera. So making sure that there is a focus on laying out a foundation, that's a key barrier. There is also a concern that, you know the companies have around cybersecurity. The more you connect the more you increase the attack surface. And we know that that hacks and so on are, are a dominant issue now whether it's for ransomware or for other malicious reasons. And so modernizing the foundation and making sure you're doing it in a secure way those are the key concerns that executives have. And then another key barrier I see is making sure that you have a key, key core objective and not making too many different varied experimentation beds. So keeping a focus on what's the core use case of benefit you're after and then what's the foundation to make sure that you're going after it. Like I said, whether it's quality or productivity or such like. >> So the keys to success, if I get this right is you have the right framework for this as you say, industry 4.0 you got to understand the collaborative dynamics and then have an ecosystem. >> Yeah. Can you unpack those three things? Because take me through that. You got to the framework, the collaboration and the ecosystem. What does that mean specifically? >> So the way I take the simplest way to think of it is the amount of work and effort that all companies have to put in, is so great in front of them. The opportunities are so great as well that nobody can hire all the smart people that are needed to achieve the goals. Everybody has their own specific I would say focus and capabilities they bring to bear. So the collaboration between manufacturers the collaboration between operational technology companies like the Siemens, ABB, Schlumberger, et cetera and IT technology companies like ourselves that three-part collaboration is sort of the heart of what I see as ecosystems coming together. The other dimensionality of ecosystems is also looking at it from a supply chain or a value chain perspective cause how something becomes more intelligent or smarter or more effective is also being able to work across the supply chain or value chain. So those are our key focus areas make sure we are collaborating across value chains and supply chains, as well as collaborating with manufacturers and OT, operational technology companies to be able to bring these digital capabilities with the right capabilities of operational technology companies into the manufacturers. >> If I asked you, how are you doing that? What specifically would you say? I mean, how are you collaborating? What's some examples give some examples of this enaction. >> Certainly. So we recently announced over the last say, nine months or so three strategic, very transformative partnerships. The first one I'll share with you is with Schlumberger. Schlumberger is the world's largest oil field services company. And now also the world's largest distill technology company for the oil and gas industry. So we've collaborated with them to bring hybrid cloud to the digital platform so they now can deploy their capabilities to any customer regardless of whether they want it in country or on a public cloud. Another example is we've established a data platform with Schlumberger for the oil and gas industry, to be able to bring again that data platform to any location around the world. The advantage of hybrid, the advantage of AI. With EVB, what we've done is we've taken our smart sync IT security connected with their products and capabilities for operational systems. And now are delivering an end to end solution that you can get cyber alerts or issues coming from manufacturing systems dry down to right up to an IT command center where you're seeing all the events and alerts so that they can be acted upon right away. So that's a great example of collaborating with IT from a security point of view. The third one is industrial IOT with Siemens and we've partnered with Siemens to deliver the MindSphere private cloud edition. Delivered on our red hat hybrid cloud. So this is an example where we are able to take our horizontal technologies, apply it with their verticals smarts and deep industry context put our services capabilities on top of it so they can deliver their innovations anywhere >> Manish is such an expert on this such a great leader on this area and I have to ask you you know, you've been in this mode of evangelizing and leading teams and building solutions around digital re platforming or whatever you want to call it, renovations. >> Manish: Right >> What's the big deal now, if you had to, I mean, it seems like it's all coming together with red hat under the covers, you get distributed networks with the Edge. It's all kind of coming together now for the verticals because you got the best of both worlds. Programmable scalable infrastructure with modern software applications on top. I mean, you've been even in the industry for many many waves, why is this wave so big and important? >> So I think there is no longer the big reason why it's important is I think there's no reason why companies have to be convinced now that the clarity is there that this needs to happen so that's one. The second is, I think there's a high degree of expectation among consumers, among employees and among customers as well, that everything that we touch will be intelligent. So these technologies really unlock the value unlock the value, and they can be deployed at scale that's really, I think what we're seeing as the focus now. And being able to deliver the innovation anywhere whether someone wants it at the Edge next to a machine that's operating, or be able to look at how a manufacturing facility or different product portfolio is doing in the boardroom. It's all available. And so that shop floor, the top floor connection is what everybody's aiming for but we also now call it Edge to enterprise. >> And everything works better, the employees are happy people are happy, stakeholders are happy. Manish great insight. Thank you for sharing here on theCUBE for Think 2021. Thanks for coming on theCUBE. >> Absolutely thanks John for having me. >> Okay. I'm John Furry host theCUBE for IBM Think 2021. Thanks for watching. (soft music)

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. Yeah, husband. Welcome back to the cubes. Live coverage of AWS reinvent 2020. We're not in person this year. We're virtual This is the Cube Virtual. I'm John for your host of the Cube. Roger Barker, the General Manager AWS Robotics and Autonomous Service. And a lot of other cool stuff was on last year. Always. Speed Racer. You got the machines. Now you have real time Robotics hitting, hitting seen Andy Jassy laid out a huge vision and and data points and announcements around Industrial this I o t it's kind of coming together. Roger, great to see you. And thanks for coming on. I want to dig in and get your perspective. Thanks for joining the Cube. >>Good to be here with you again today. >>Alright, so give us your take on the announcements yesterday and how that relates to the work that you're doing on the robotic side at a w s. And where where does this go from? You know, fun to real world to societal impact. Take us through. What? You how you see that vision? >>Yeah, sure. So we continue to see the story of how processing is moving to the edge and cloud services, or augmenting that processing at the edge with unique and new services. And he talked about five new industrial machine learning services yesterday, which are very relevant to exactly what we're trying to do with AWS robot maker. Um, a couple of them monitor on, which is for equipment monitoring for anomalies. And it's a whole solution, from an edge device to a gateway to a service. But we also heard about look out for equipment, which is if a customer already has their own censors. It's a service that can actually back up that that sensor on their on the device to actually get identify anomalies or potential failures. And we saw look out for video, which allows customers to actually use their camera and and build a service to detect anomalies and potential failures. When A. W s robot maker, we have Ross Cloud Service extensions, which allow developers to connect their robot to these services and so increasingly, that combination of being able to put sensors and processing at the edge, connecting it back with the cloud where you could do intelligent processing and understand what's going on out in the environment. So those were exciting announcements. And that story is going to continue to unfold with new services. New sensors we can put on our robots to again intelligently process the data and control these robots and industrial settings. >>You know, this brings up a great point. And, you know, I wasn't kidding. Was saying fun to real world. I mean, this is what's happening. Um, the use cases air different. You look at you mentioned, um, you know, monitor on lookout. But those depend Panorama appliance. You had computer vision, machine learning. I mean, these are all new, cool, relevant use cases, but they're not like static. It's not like you're going to see them. Just one thing is like the edge has very diverse and sometimes mostly purpose built for the edge piece. So it's not like you could build a product. Okay, fits everywhere. Talk about that dynamic and why the robotics piece has to be agile. And what do you guys doing to make that workable? Because, you know, you want purpose built. The purpose built implies supply chain years. in advance. It implies slow and you know, how do you get the trust? How do you get the security? Take us through that, please. >>So to your point, um, no single service is going to solve all problems, which is why AWS has has released a number of just primitives. Just think about Kinesis video or Aiken. Stream my raw video from an edge device and build my own machine learning model in the cloud with sage maker that will process that. Or I could use recognition. So we give customers these basic building blocks. But we also think about working customer backward. What is the finished solution that we could give a customer that just works out of the box? And the new services we heard about we heard about yesterday were exactly in that latter category. Their purpose built. They're ready to be used or trained for developers to use and and with very little customization that necessary. Um, but the point is, is that is that these customers that are working these environments, the business questions change all the time, and so they need actually re program a robot on the fly, for example, with a new mission to address the new business need that just arose is a dynamic, which we've been very tuned into since we first started with a device robo maker. We have a feature for a fleet management, which allows a developer to choose any robot that's out in their fleet and take the software stack a new software stack tested in simulation and then redeploy it to that robot so it changes its mission. And this is a This is a dialogue we've been seeing coming up over the last year, where roboticists are starting to educate their company that a robot is a device that could be dynamically program. At any point in time, they contest their application and simulation while the robots out in the field verify it's gonna work correctly and simulation and then change the mission for that robot. Dynamically. One of my customers they're working with Woods Hole Institute is sending autonomous underwater robots out into the ocean to monitor wind farms, and they realized the mission may change may change based on what they find out. If the wind farm with the equipment with their autonomous robot, the robot itself may encounter an issue and that ability because they do have connective ity to change the mission dynamically. First Testament, of course, in simulation is completely changing the game for how they think about robots no longer a static program at once, and have to bring it back in the shop to re program it. It's now just this dynamic entity that could test and modify it any time. >>You know, I'm old enough to know how hard that really is to pull off. And this highlights really kind of how exciting this is, E. I mean, just think about the idea of hardware being dynamically updated with software in real time and or near real time with new stacks. I mean, just that's just unheard of, you know, because purpose built has always been kind of you. Lock it in, you deploy it. You send the tech out there this kind of break fixed kind of mindset. Let's changes everything, whether it's space or underwater. You've been seeing everything. It's software defined, software operated model, so I have to ask you First of all, that's super awesome. Anyway, what's this like for the new generation? Because Andy talked on stage and in in my one On one way I had with him. He talked about, um, and referring to land in some of these new things. There's a new generation of developer. So you gotta look at these young kids coming out of school to them. They don't understand what how hard this is. They just look at it as lingua frank with software defined stuff. So can you share some of the cutting edge things that are coming out of these new new the new talent or the new developers? Uh, I'm sure the creativity is off the charts. Can you share some cool, um, use cases? Share your perspective? >>Absolutely. I think there's a couple of interesting cases to look at. One is, you know, roboticists historically have thought about all the processing on the robot. And if you say cloud and cloud service, they just couldn't fathom that reality that all the processing has cannot has to be, you know, could be moved off of the robot. Now you're seeing developers who are looking at the cloud services that we're launching and our cloud service extensions, which give you a secure connection to the cloud from your robot. They're starting to realize they can actually move some of that processing off the robot that could lower the bomb or the building materials, the cost of the robot. And they can have this dynamic programming surface in the cloud that they can program and change the behavior of the robot. So that's a dialogue we've seen coming over the last couple years, that rethinking of where the software should live. What makes sense to run on the robot? And what should we push out to the cloud? Let alone the fact that if you're aggregating information from hundreds of robots, you can actually build machine learning models that actually identify mistakes a single robot might make across the fleet and actually use that insight to actually retrain the models. Push new applications down, pushing machine learning models down. That is a completely different mindset. It's almost like introducing distributed computing to roboticists that you actually think this fabric of robots and another, more recent trend we're seeing that were listening very closely to customers is the ability to use simulation and machine learning, specifically reinforcement. Learning for a robot actually try different tasks up because simulations have gotten so realistic with the physics engines and the rendering quality that is almost nearly realistic for a camera. The physics are actually real world physics, so that you can put a simulation of your robot into a three D simulated world and allow it to bumble around and make mistakes while trying to perform the task that you frankly don't know how to write the code for it so complex and through reinforcement, learning, giving rewards signals if it does something right or punishment or negative rewards signals. If it does something wrong, the machine learning algorithm will learn to perform navigation and manipulation tasks, which again the programmer simply didn't have to write a line of code for other than creating the right simulation in the right set of trials >>so that it's like reversing the debugging protocol. It's like, Hey, do the simulations. The code writes itself. Debug it on the front end. It rights itself rather than writing code, compiling it, debugging it, working through the use cases. I mean, it's pretty different. >>It is. It's really a new persona. When we started out, not only are you taking that roboticist persona and again introduced him to the cloud services and distributed computing what you're seeing machine learning scientists with robotics experience is actually rising. Is a new developer persona that we have to pay attention to him. We're talking to right now about what they what they need from our service. >>Well, Roger, I get I'm getting tight on time here. I want one final question before we break. How does someone get involved with Amazon? And I'll see you know, whether it's robotics and new areas like space, which is verging, there's a lot of action, a lot of interest. Um, how does someone engaged with Amazon to get involved, Whether I'm a student or whether I'm a professional, I want a code. What's what's the absolutely, >>absolutely, so certainly reinvent. We have several sessions that reinvent on AWS robo maker. Our team is there, presenting and talking about our road map and how people can get engaged. There is, of course, the remarks conference, which will be happening next year, hopefully to get engaged. Our team is active in the Ross Open Source Community and Ross Industrial, which is happening in Europe later in December but also happens in the Americas, where were present giving demos and getting hands on tutorials. We're also very active in the academic research in education arena. In fact, we just released open source curriculum that any developer could get access to on Get Hub for Robotics and Ross, as well as how to use robo maker that's freely available. Eso There's a number of touch points and, of course, I'd be welcome to a field. Any request for people to learn more or just engage with our team? >>Arthur Parker, general manager. It is robotics and also the Autonomous Systems Group at AWS Amazon Web services. Great stuff, and this is really awesome insight. Also, you know it za candy For the developers, it's the new generation of people who are going to get put their teeth into some new science and some new problems to solve. With software again, distributed computing meets robotics and hardware, and it's an opportunity to change the world literally. >>It is an exciting space. It's still Day one and robotics, and we look forward to seeing the car customers do with our service. >>Great stuff, of course. The Cube loves this country. Love robots. We love autonomous. We love space programming all this stuff, totally cutting edge cloud computing, changing the game at many levels with the digital transformation just a cube. Thanks for watching

>>long from Las Vegas. It's the Q covering a ws re invent 2019. Brought to you by Amazon Web service is and in along with its ecosystem partners. >>Welcome back Inside the Sands. Here's to continue our coverage here. Live on the Cube of AWS Reinvent 2019 Absolutely jam packed isles. Great educational sessions and one of the feature presenters now joins us well. Dave Alana John Walls with Paul Saville. Who's the SPP of court networking technology solutions at Caen. Freely. Paul, Good to see you again. >>Yeah, let's see you, John. >>So you just finished up. We'll get in that just a little bit. First off, just give me your impression of what's going on here and the energy and the vibe that you're getting. >>Yeah, I think it's fantastic. I mean, it's very high energy here, you know, there's a lot of new things that that are emerging terms of the applications that we're seeing the use cases for the cloud. And of course, exciting stuff happened around ej compute with the announcement of AWS with the outpost, Long >>will jump in Najaf. Everybody has a different idea, right? You weren't so I mean, if you define the edge, at least. How do you see it? >>Yeah, it's very simple definition of how we see the edge. It's putting compute very close to the point of interaction, and the interaction could be with humans or the inner action could be with devices or other electron ICS that need toe that need to be controlled or that need to communicate. But the point is getting that that computers close as possible to it from a performance standpoint that's needed. >>Okay, so we heard that a lot from Andy Jassy ethic yesterday. Right now compute to the data. I mean, with all due respect, it's like he was talking about like it was a new concept, right? We've been here for quite some time, so talk more about how you see the edge evolving. I mean, look, I have a lot of credit to Amazon because, you know, they used to not talk about hybrid. I predict a couple years to talk about multi cloud. Guarantee it because that's what customers are doing, so they respond to customers at the same time. I like their edge strategy because it's all about developers. Infrastructures code on the edge But you guys are about, you know, moving that data on or not necessarily bring in the computer that. So how do you see the edge >>evolving? Yeah, so the reason this whole trend is happening is because what's happening with the new technologies that are enabling a whole new set of applications out there? Things like What's going on with artificial intelligence and machine learning and virtual reality those the robotics control Those things are basically driving this need to place compute as close as possible to that point of interaction. The problem is that when you do that, costs go up. And that's the conundrum that we've kind of been in because when Compute gets housed at the customer premise in a home in a business in an enterprise, then that's the most expensive real estate that that there is, and you can't get the economies of scale that's there. The only other choice to date has been the public cloud, and that could be hundreds or thousands of miles away. And these new applications that require really tight control and interaction can't operate in that kind of environment, And yet it's too expensive to run those applications at the very edge at the premise itself. So that's why this middle ground now of a place and compute nearby, where conserve many locations or must be house more cost effectively. >>Okay, so you got the speed of light problem, right? So you deal with that later by making the compute proximate to the data, but it doesn't have to be like right next to it. Correct. But But what are we talking distance wise? It's that to be synchronised distance or >>when we think of the distance, we think about it in terms of milliseconds of delay, from where the edge device, the thing that needs to interact with the computer, the application needs to interact with. And we have not seen any applications that from the customers we talked to that really get beyond our need tighter than five milliseconds of delay. Now that's one way. So if we get into that range of place and compute within five milliseconds of the of the edge interaction, the device that it needs to interact with, that is enough to meet some of the most tightest requirements that we've seen around robotics control, video analytics and another >>like I could ship code to the data. But the problem is, if it needs to be real time, right, it's still too much. It's too much late, right? That's the problem that you're solving. That's right. Okay, >>so what's what you were talking about? Why milliseconds matter? That's right. So give me some examples, if you will, then about why, why five matters more than 10 or five matters more than eight or 20 or whatever, because we're talking about such an infant testable difference. But yet it does matter. In some respects. It does, >>because so give you an example of robotics, for example, robotics control. You know that is one of things that requires the most tight Leighton see requirement because it depends upon the robotics itself. If it's a machining tools that's working on a laid, then that doesn't require a tide of response time to the controller as, say, a scanning device that Israel time pushing things around very fast in doing an optical read on it to make the decision about how about where it pushes the device next, that type of interaction of control requires a much tighter, late and see performance, and that's why you get start, you start to see these ranges. But as I said, we're not seeing anything below that kind of five millisecond type of range from >>the other thing that's changing it and help me understand. This is yeah, Okay, you're moving the compute closer to the data, which increases costs. And I want to understand how you're addressing that. Maybe one of the ways addresses you're bringing the cloud model, the operating model to the data. So right patches, security patches, maintenance, things like that are reduced. Is that how you're addressing costs? >>Yeah, that is part of it. And that's why the eight of US outpost is very interesting because it is really a complete instance of AWS that is in a much smaller form factor that you can deploy very close to that point of interaction close to the customer to the customer premise, and that enables customers to leverage pretty much the full power of AWS in engaging with those devices and coding to those devices and dropping those applications closed. >>Now you lose the multi tenant aspect Is that right down unnecessarily >>from our understanding of outpost, it's a single 10 a device coming out the gate. But ultimately it's gonna be a multi tenant device. >>Yeah, okay, so near term, it's easier to manage. But it's it's multi instance, I guess, yeah, over time, maybe you could share that. That resource is still not getting. >>The interesting thing is that even though it's a single tenant device, there's still many great use cases because even a single Tenet device in set in one market could serve multiple enterprise locations. So it still has that kind of a sense of scale because you concert as long as it's it's one enterprise. Conserve many locations off of that one. That one device. >>Okay, so you don't get the massive economies of scale, but you're opening abuse cases that never existed before. >>That's right. But what about what do you do with the data supplied basically held something data scale and edge devices creating that much more data. All of a sudden speed becomes a little more challenging, taking in a lot more information, trying to process in different ways after feeding off of that, so a sudden you have a much more complex challenge because it's not static, right? This is a very dynamic environment, >>That's right. Yeah, and there's a very big trend that's happening now, which is that data is being created at the edge, and it's staying at the edge for a whole number of reasons. You know, in the Old World you would pretty much collect data and you'd ship it off to the centralized data center or to the public cloud to be housed there. And that's today. That's where 80% of data resides. But there's a big shift happening where that data now needs to reside at the deep edge because it needs to have that fast interaction with something that's that's working with or because of government regulations that are now coming in that are having much stricter tolerances around. You have to know exactly where your data is can't cross state lines. It can't, you know, get out of certain security zone. Things like that are forcing companies now to keep that massive amount of data in a very understand known localized position. >>You gotta act on it in real time. Yeah, some of it will go back to the cloud, but you see folks persist. The data at the edge or not so much persistent data. People want to store it at the edges. Well, >>uh, people in the story at the edge where where it's going to have a lot of interaction. So if you're running A if you're running a chemical plant, you may not need to have access to a lot of data outside that chemical plant. But you you're intensively analyzing that data in the chemical plant, and you don't want to ship it off someplace centrally, 1000 miles away. To be access from there. It needs to be acted on locally, and that's why it's compute this movement toward EJ computers really building and becoming stronger. >>Talk about your tech. You know what? What's the real value of what you do? You obviously reducing late, sees they gotta secure all this stuff but >>central and brings the number of tools to help in this whole space. So the first of all, the network that we provide that could tie it all together from the enterprise location to the to the edge location where compute can be housed all the way back to the public cloud core way have a network that spans the entire U. S. Fiber all over the place, and we can use those lonely and see fiber optic connections to change those those areas together in the most optimal fashion. To get the kind of performance that you need to handle these distributed computing environments, we also bring compute technology itself. We have our own variety of EJ compute, where we can build custom edge compute solutions for customers that meet their very specific SPECT requirements that could be dedicated to them. We can incorporate AWS computer technology as well, and we have way have I t service's and skilled people, thousands of employees that are focused on the space that build these solutions together. For customers that tie together, the public cloud resource is the edge. Compute resource is the network resource is the wireless connectivity capabilities that's needed on customer premise and the management solutions to tie it all together in that very mixed environment. >>We were just on a session with Teresa Carlson runs public sector for AWS, telling the SAT in a session. Marty Walsh, the mayor of Boston, has got this big smart city initiative going on. I know that's one of the cases you're working on. Maybe talk about that a little bit. And maybe some of the other interesting use cases. >>Yeah, that's right. Definitely. Smart cities are a big our big use case, though. The one and we're we're actually actively working on a number of them. I would say that those used the smart City use cases tend to move very slowly because you're talking about municipalities and long decision making cycle, I'll tell you that. We've seen >>there's a 50 year plan he put forward, >>but the use cases that we're really seeing the most traction with our interestingly is robotics is a really big one, and Video Analytics is another big one. So we're actually deploying edge used case solutions right now. In those scenarios, the Robotics one is a great one because those devices need to be. Those robotic devices need to be controlled within a really tight millisecond tolerance, and but the computer needs to be housed in a very it's much more reliable economic location. The video Analytics piece is a really interesting one that we're seeing very, very big demand for, because retailers have now reached the point with the technology where they can do things like they can, they can figure out by doing video analytics whether somebody is acting suspiciously in the store and we're hearing that they can, they think they can now cut Devery out of retail locations dramatically by using video analytics. And when you talk about big savings to the bottom line of a company that makes a big savings to them so that those very to good use cases we're seeing that a real today. You >>know what the other things you were talking about earlier was about the disappearance of Compute Divide. So where to go? Wait. >>I like to say that in the old days, if you've been around long enough like I know you're old because watching you on TV >>way get out of college, Does that make you feel way get out of college? >>Everything was in the mainframe, right? You essentially. Yet when you went to work, you had a terminal, and everything was house Essentially. Then we went to distributed where client server model, where you everybody was working on desktops and a lot of the compute was on the desk tops and very little went back to a mainframe. Then we made the ship to the cloud where he pushed his much in the centralized location as we can, too. So he's shifted way back to centralized. That's the compute divide. I'm talking about goat, that big ship from decentralized, centralized, decentralized. Now we're actually moving to a new world where that pendulum swing that compute divide is disappearing because compute isn't most economically stored. Anyone location, it's everywhere. It's gonna be at the Io ti edge. It's gonna be at the premise it's going to be in market locations. They were essential. Eyes is gonna be in the public cloud core. It's gonna be all around us. And that's what I mean by the by the disappearance of the compute >>divine. And, you know, I wantto come back on that. You talk about a pendulum. A lot of people talk about the pendulum swings mainframe and distributed. A lot of people say it's the pendulum is swinging back, but you just described it differently. It's It's a ubiquitous matrix. Now you'd is everywhere. >>That's where you hear the term fog computing the idea of the fog. Now it's not the cloud that you can see off in the distance. It's just everywhere, right, surround you and that's how combines we can start to think about how >>I first heard that you're like, I don't know eight years ago. What the heck is this? It was ahead of its time, but now it's really starting to show. This is sort of new expansion of what we know is cloud reading redefining? Yes, exactly. Net ej five g. That's, you know, another big piece of it. You know, Amazon's obviously excited about that with wavelength, right? What do you see for five G? How's that? It can affect this whole equation. >>Yeah, I think five G is gonna have a have a number of EJ applications and was primarily gonna be around the mobile space. You know, it's the the advantage of it is that it increases band with and support smoke mobility, and it allows for a little bit higher resilience because they can take the part of the spectrum and make sure that they're carving it out and dedicating it for particular applications that are there. But I tell you that the five G gets a lot of attention in terms of being how EJ computer's gonna roll out. But we're not saying that at all. edge compute is available today and that we're providing those edge compute solutions through our fiber optic networks. What we're seeing is that every enterprise that we're talking to once fiber into their into their enterprise location. Because once you have fiber there, that's gonna be the most secure, reliable and scalable solutions fiber kin can effectively scale as Bigas. Any customer could ever consume the bandwidth. And they know that once they get fiber into that application into their location that they're good for for the future because they can totally scale with that. And that's how we're deploying edge solutions today, >>Paul. I know you got a plane to catch, and you got to go. But after that age comment, we're gonna keep you for another hour. No, I think it's great. You're doing all right. All right, Hang on. We're about to say goodbye to Paul now. Well, you have a free event. 2019. Coverage continues. Right here on the right

>> from Seattle WASHINGTON. It's the Q covering AWS Imagine brought to you by Amazon Web service is >> Hey, welcome back, You're ready. Geoffrey here with the Cube were in Seattle, >> Washington downtown, right next to the convention center for the AWS. Imagine e d. You show. It's a second year of the show found by Andrew Cohen. His crew, part of Theresa's public sector group, really focused on education. Education means everything from K through 12 higher education and community college education, getting out of the military and retraining education. It's ah, it's a really huge category, and it's everything from, you know, getting the colleges to do a better job by being on cloud infrastructure, innovating and really thinking outside the box are really excited to have the man who's doing a lot of the work on the curriculum development in the education is Ken Eisner is the director of worldwide education programs for AWS. Educate can great to see you. Thank you so much for having absolutely nice shot out this morning by Theresa, she said. She just keeps asking you for more. So >> you want to deliver for Theresa? Carl says she is. She is a dynamo and she drives us >> all she does. So let's dive into it a little bit. So, you know, there was, Ah, great line that they played in the keynote with Andy talking about, You know, we cannot be protecting old institutions. We need to think about the kids is a story I hear all the time where somebody came from a time machine from 17 76 and landed here today. It wouldn't recognize how we talk, how we get around, but they would recognize one thing, and unfortunately, that's the school house down at the end of the block. So you guys are trying to change that. You're really trying to revolutionize what's happening in education, give us a little bit of background on some of the specific things that you're working on today. >> Yeah, I I think Andy, one of the things that he mentioned at that time was that education is really in a crisis on. We need to be inventing at a rapid rate. We need to show that invented simplify inside that occassion. Andi, he's incredibly, he's correct. The students are our customers, and we've got to be changing things for them. What we've been really excited to see is that with this giant growth in cloud computing A W S. It was the fastest I T vendor to ever hit $10,000,000,000 a year. The run rate We're now growing at a 42% or 41% year over year growth Ray and $31,000,000,000 a year Lee company. It's creating this giant cloud computing opportunity cloud computing in the number one Lincoln Skill for the past four years in Rome, when we look at that software development to cloud architecture to the data science and artificial intelligence and data analytics and cyber security rules. But we're not preparing kids for this. Market Gallop ran a study that that showed about 11% of business executives thought that students were prepared for their jobs. It's not working, It's gotta change. And the exciting thing that's happening right now is workforce development. Governments are really pushing for change in education, and it's starting to happen >> right? It's pretty amazing were here last year. The team last year was very much round the community college releases and the certification of the associate programs and trial down in Southern California, and this year. I've been surprised. We've had two guests on where it's the state governor has pushed these initiatives not at the district level, the city level, but from the state winning both Louisiana as well as Virginia. That's pretty amazing support to move in such an aggressive direction and really a new area. >> Yeah, I was actually just moderating a panel where we had Virginia, Louisiana, in California, all sitting down talking about that scaling statewide strategy. We had announcements from the entire CUNY and Sunni or City University of New York and State University of New York system to do both two and four year programs in Cloud Computing. And Louisiana announced it with their K 12 system, their community college system and their four year with Governor John Bel Edwards making the announcement two months ago. So right we are seeing this scaling consortium, a play where institutions are collaborating across themselves. They're collaborating vertically with your higher ed and K 12 and yet direct to the workforce because we need to be hiring people at such a rapid ray that we we need to be also putting a lot of skin in the game and that story that happened so again, I agree with Andy said. Education is at a crisis. But now we're starting to see change makers inside of education, making that move right. It's interesting. I wonder, >> you know, is it? Is it? I don't want to say second tier, that's the wrong word, but kind of what I'm thinking, you know, kind of these other institutions that the schools that don't necessarily have the super top in cachet, you know who are forced to be innovative, right? We're number two. We try harder. As they used to say in the in the Hertz commercial. Um, really a lot of creativity coming out of again the community colleges last year in L. A. Which I was, I was blown away, that kind of understand cause that specifically to skill people up to get a job. But now you're hearing it in much more kind of traditional institutions and doing really innovative things like the thing with the the Marines teaching active duty Marines about data science. >> Yeah, who came up with that idea that phenomenal Well, you know, data permeates every threat. It's not just impure data science, jobs and machine learning jobs. There's air brilliantly important, but it's also in marketing jobs and business jobs. And so on. Dad Analytics, that intelligence, security, cybersecurity so important that you think, God, you Northern Virginia Community College in U. S. Marine Corps are working for to make these programs available to their veterans and active military. The other thing is, they're sharing it with the rest of the student by. So that's I think another thing that's happening is this sharing this ability, all of for this cloud degree program that AWS educate is running. All these institutions are sharing their curricula. So the stuff that was done in Los Angeles is being learned in Virginia is the stuff that the U. S Marine Corps is doing is being available to students. Who are you not in military occupations? I think that collaboration mode is is amazing. The thing they say about community colleges and just this new locus of control for education on dhe. Why it's changing community colleges. You're right there. They're moving fast. These institutions have a bias for action. They know they have to. You change the r A. Y right? It's about preventing students for this work for, but they also serve as a flywheel to those four year institutions back to the 12 into the into the workforce and they hit you underserved audience. Is that the rest? So that you were not all picking from the same crew? You cannot keep going to just your lead institutions and recruit. We have to grow that pipeline. So you thank thank these places for moving quick brand operating for their student, right? >> Right, And and And that's where the innovation happens, right? I mean, that's that's, uh, that that's goodness. And the other thing that that was pretty interesting was, um, you know, obviously Skilling people up to get jobs. You need to hire him. That's pretty. That's pretty obvious and simple, but really bringing kind of big data attitude analytics attitude into the universities across into the research departments and the medical schools. And you think at first well, of course, researchers are data centric, right? They've been doing it that way for a long time, but they haven't been doing it and kind of the modern big, big data, real time analytics, you know, streaming data, not sampling data, all the data. So so even bringing that type of point of view, I don't know mindset to the academic institutions outside of what they're doing for the students. >> Absolutely. The machine learning is really changing the game. This notion of big data, the way that costs have gone down in terms of storing and utilizing data and right, it's streaming data. It's non Columbia or down, as opposed to yeah, the old pure sequel set up right that that is a game changer. No longer can you make just can you make a theory and tested out theories air coming streaming by looking at that data and letting it do some work for you, which is kind of machine learning, artificial intelligence path, and it's all becoming democratized. So, yes, researchers need to need learn these new past two to make sense and tow leverage. This with that big data on the medical center site, there are cures that can be discerned again. Some of our most pressing diseases by leveraging data way gonna change. And we, by the way, we gotta change that mindset, not just yeah, the phD level, but actually at the K 12 levels. Are kids learning the right skills to prepare them for you this new big data world once they get into higher ed, right? And then the last piece, which again we've seen >> on the Enterprise. You've kind of seen the movie on the enterprise side in terms of of cloud adoption. What AWS has done is at first it's a better, more efficient way to run your infrastructure. It's, you know, there's a whole bunch of good things that come from running a cloud infrastructure, but >> that's not. But that's not the end, right? The answer to the question >> is the innovation right? It's It's the speed of change, of speed development and some of the things that we're seeing here around the competitive nature of higher education, trying to appeal to the younger kids because you're competing for their time and attention in there. And they're dollar really interesting stuff with Alexa and some of these other kind of innovation, which is where the goodness really starts to pay off on a cloud investment. >> Yeah, without a doubt, Alexa Week AWS came up with robo maker and Deep Racer on our last reinvent, and there's there's organizations at the K 12 level like First Robotics and Project lead. The way they're doing really cool stuff by making this this relevant it you education becomes more relevant when kids get to do hands on stuff. A W S lowers the price for failure lowers the ability you can just open a browser and do real world hands on bay hands on stuff robotics, a rvr that all of these things again are game changers inside the classroom. But you also have to connect it to jobs at the end, right? And if your educational institutions can become more relevant to their students in terms of preparing them for jobs like they've done in Santa Monica College and like they're doing in Northern Virginia Community College across the state of Louisiana and by May putting the real world stuff in the hands of their kids, they will then start to attract assumes. We saw this happen in Santa Monica. They opened up one class, a classroom of 35 students that sold out in a day. They opened another co ward of 35 sold out in another day or two. The name went from 70 students. Last year, about 325 they opened up this California cloud workforce project where they now have 825 students of five. These Northern Virginia Community College. They're they're cloud associate degree that they ran into tandem with AWS Educate grew from 30 students at the start of the year to well over 100. Now the's programs will drive students to them, right and students will get a job at the end. >> Right? Right, well and can. And can the school support the demand? I mean, that's That's a problem we see with CS, right? Everyone says, Tell your kids to take CS. They want to take CS. Guess what? There's no sections, hope in C. S. So you know, thinking of it in a different way, a little bit more innovative way providing that infrastructure kind of ready to go in a cloud based way. Now we'll hopefully enable them to get more kids and really fulfill the demand. >> Absolutely. There's another thing with professional development. I think you're hitting on, so we definitely have a shortage in terms of teachers who are capable to teach about software development and cloud architecture and data sciences and cybersecurity. So we're putting AWS educators putting a specific focus on professional development. We also want to bring Amazonian, Tze and our customers and partners into the classroom to help with that, because the work based learning and the focus on subject matter expert experts is also important. But we really need to have programs both from industry as well as government out support new teachers coming into this field and in service training for existing teachers to make sure, because yes, we launch those programs and students will come. We have to make sure that were adequately preparing teachers. It's not it's not. It's not easy, but again, we're seeing whether it's Koda Cole out of yeah out of, uh, Roosevelt High School. Are the people that were working with George Mason University and so on were seeing such an appetite for making change for their students? And so they're putting in those extra hours they're getting that AWS certification, and they're getting stronger, prepared to teach inside the clients. >> That's amazing, cause right. Teachers have so many conflict ing draws on their time, many of which have nothing to do with teaching right whether it's regulations. And there's just so many things the teachers have to deal with. So you know the fact that they're encouraged. The fact that they want t to spend and invest in this is really a good sign and really a nice kind of indicator to you and the team that, you know, you guys were hitting something really, really positive. >> Yeah, I think we've had its this foam oh fear of missing out opportunity. There's the excitement of the cloud. There's the excitement of watching your kids. You're really transformed their lives. And it could be Alfredo Cologne who came over from Puerto Rico after Hurricane Maria. You wiped out his economic potential and started taking AWS educate. And you're learning some of these pathways and then landing a job as the Dev Ops engineered. When you see the transformation in your students, no matter what their background is, it is. It is a game changer. This has got to be you. Listen, I love watching that women's team when I win the World Cup, and that the excitement cloud is like the new sport. Robotics is the new sport for these kids. They'll bring them on >> pathways to career, right. We'll take for taking a few minutes in The passion comes through, Andrew Koza big passion guy. And we know Teresa is a CZ Well, so it shines through and keep doing good work. >> Thank you so much for the time. Alright, he's can on Jeff. You're watching the cube. We're in downtown Seattle. A aws. Imagine e d. Thanks for watching. >> We'll see you next time.

>> from Seattle WASHINGTON. It's the Q covering AWS Imagine brought to you by Amazon Web service is >> Hey, welcome back, everybody. Jeffrey here with the Cube were in Seattle, >> Washington downtown, right next to the convention center for the AWS. Imagine e d. You show. It's a second year of the show found by Andrew Cohen. His crew, part of Theresa's public sector group, really focused on education. Education means everything from K through 12 higher education, community college education, getting out of the military and retraining education. It's ah, it's a really huge category, and it's everything from, you know, getting the colleges to do a better job by being on cloud infrastructure, innovating and really thinking outside the box are really excited to have the man who's doing a lot of the work on the curriculum development in the education is Ken Eisner is the director of worldwide education programs for AWS. Educate can Great to see you. Thank you so much for having absolutely nice shot out this morning by Theresa, she said. She just keeps asking you for more. So >> you want to deliver for Theresa. Carl says she is. She is a dynamo, and she drives us >> all she does, so just dive into it a little bit. So, you know, there was, Ah, great line that they played in the keynote with Andy talking about, You know, we cannot be protecting old institutions. We need to think about the kids is a story I hear all the time where somebody came from a time machine from 17 76 and landed here today. It wouldn't recognize how we talk, how we get around, but they would recognize one thing, and unfortunately, that's the school house down at the end of the block. So you guys are trying to change that. You're really trying to revolutionize what's happening in education, give us a little bit of background on some of the specific things that you're working on today. >> Yeah, I think Andy, one of the things that he mentioned at that time was that education is really in a crisis on. We need to be inventing at a rapid rate. We need to show that invented, simple, fine inside education, and he's incredibly, he's correct. The students are our customers and we've got to be changing things for them. What we've been really excited to see is that with this giant growth in cloud computing a W. S. It was the fastest I T vendor to ever a $10,000,000,000 a year. The run rate. We're now growing at a 42% or 41% year over year growth Ray and $31,000,000,000 a year Lee company. It's creating this giant cloud computing opportunity, cloud computing in the number one linked in skill for the past four years in Rome. When we look at that software development to cloud architecture to the data science and artificial intelligence and data analytics and cyber security rules. But we're not preparing kids for this. Market Gallop ran a study that that showed about 11% of business executives thought that students were prepared for their jobs. It's not working, It's gotta change. And the exciting thing that's happening right now is workforce development. Governments are really pushing for change in education, and it's starting to happen right? It's pretty amazing were here last year. >> The team last year was very much round the community college releases and the certification of the associate programs and trial down in Southern California, and this year I've been surprised. We've had two guests on where it's the state governor has pushed these initiatives not at the district level, the city level, but from the state winning both Louisiana as well as Virginia. That's pretty amazing support to move in such an aggressive direction and really a new area. >> Yeah, I was actually just moderating a panel where we had Virginia, Louisiana, in California, all sitting down talking about that scaling statewide strategy. We had announcements from the entire CUNY and Sunni or City University of New York and State University of New York system to do both to end four year programs in Cloud Computing. And Louisiana announced it with their K 12 system, their community college system and their four year with Governor John Bel Edwards making the announcement two months ago. So right, we are seeing this scaling consortium, a play where institutions are collaborating across themselves. They're collaborating vertically with your higher ed and K 12 and yet direct to the workforce because we need to be hiring people at such a rapid ray that we we need to be also putting a lot of skin in the game. And that story that happened So again, I agree with Andy said. Education is at a crisis. But now we're starting to see change makers inside of education, making that move right. It's interesting. I wonder, >> you know, is it is it? I don't want to say second tier, that's the wrong word, but kind of what I'm thinking, you know, kind of these other institutions that the schools that don't necessarily have the super top in cachet, you know who are forced to be innovative, right? We're number two. We try harder. As they used to say in the in the Hertz commercial. Um, really a lot of creativity coming out of again the community colleges last year in L. A. Which I was, I was blown away, that kind of understand cause that specifically to skill people up to get a job. But now you're hearing it in much more kind of traditional institutions and doing really innovative things like the thing with the the Marines teaching active duty Marines about data science. >> Yeah, who came up with that idea that phenomenal Well, you know, data permeates every threat. It's not just impure data science, jobs and machine learning jobs. There's air brilliantly important, but it's also in marketing jobs and business jobs. And so on. Dad Analytics that intelligence, security, cybersecurity so important that you think, God, you Northern Virginia Community College in U. S. Marine Corps are working for to make these programs available to their veterans and active military. The other thing is, they're sharing it with the rest of the student by. So that's I think another thing that's happening is this. Sharing this ability all of for this cloud degree program that AWS educate is running. All these institutions are sharing their curricula. So the stuff that was done in Los Angeles is being learned in Virginia's stuff the U. S. Marine Corps is doing is being available to students. Who are you not in military occupations? I think that collaboration mode is is amazing, the thing they say about community colleges and just this new locus of control for education on dhe. Why it's changing community colleges. You're right there. They're moving fast. These institutions have a bias for action. They know they have to. You change the r A. Y right. It's about preventing students for this work for, but they also serve as a flywheel to those four year institutions back to the 12 into the into the workforce and they hit you underserved audience is that the rest is so that you were not all picking from the same crew. You cannot keep going to just share lead institutions and recruit. We have to grow that pipeline. So you thank thank these places for moving quick and operating for their student, right? >> Right, And and And that's where the innovation happens, right? I mean, that's that's, ah, that that's goodness. And the other thing that that was pretty interesting was obviously Skilling people up to get jobs, you need to hire him. That's pretty. That's pretty obvious and simple, but really bringing kind of big data attitude analytics attitude into the universities across into the research departments and the medical schools. And you think at first, of course, researchers are data centric, right? They've been doing it that way for a long time, but they haven't been doing it in kind of the modern big, big data. Real time analytics, you know, streaming data, not sampling data, all the data. So so even bringing that type of point of view, I don't know, mindset to the academic institutions outside of what they're doing for the students. >> Absolutely. The machine learning is really changing the game. This notion of big data, the way that costs have gone down in terms of storing and utilizing data and right, it's streaming data. It's non Columbia or down, as opposed to yeah, the old pure sequel set up right that that is a game changer. No longer can you make just can you make a theory and tested out theories air coming streaming by looking at that data and letting it do some work for you, which is kind of machine learning, artificial intelligence path, and it's all becoming democratized. So, yes, researchers need to need learn these new past two to make sense and tow leverage. This with that big data on the medical center site, there are cures that could be discerned again some of our most pressing diseases by leveraging data, way gonna change. And we, by the way, we gotta change that mindset, not just yeah, the phD level, but actually at the K 12 levels. Are kids learning the right skills to prepare them for you? This new big data world once they get into higher ed, right? And then the last piece, which again we've seen >> on the Enterprise. You've kind of seen the movie on the enterprise side in terms of of cloud adoption. What AWS has done is at first it's a better, more efficient way to run your infrastructure. It's, you know, there's a whole bunch of good things that come from running a cloud infrastructure, but >> that's not. But that's not the end, right? The answer to the question >> is the innovation right? It's It's the speed of change, of speed, a development and some of the things that we're seeing here around the competitive nature of higher education, trying to appeal to the younger kids because you're competing for their time and attention in there. And they're dollar really interesting stuff with Alexa and some of these other kind of innovation, which is where the goodness really starts to pay off on a cloud investment. >> Yeah, without a doubt, Alexa Week AWS came up with robo maker and Deep Racer on our last reinvent, and there's there's organizations at the K 12 level like First Robotics and project lead the way they're doing really cool stuff by making this this relevant you education becomes more relevant when kids get to do hands on stuff. A W S lowers the price for failure lowers the ability you can just open a browser and do real world hands on bay hands on stuff. Robotics, A R V R. That all of these things again are game changers inside the classroom. But you also have to connect it to jobs at the end, right? And if your educational institutions can become more relevant to their students in terms of preparing them for jobs like they've done in Santa Monica College and like they're doing in Northern Virginia Community College across the state of Louisiana and by May putting the real world stuff in the hands of their kids, they will then start to attract assumes. We saw this happen in Santa Monica. They opened up one class, a classroom of 35 students that sold out in a day. They opened another co ward of 35 sold out in another day or two. The name went from 70 students. Last year, about 325 they opened up this California Cloud Workforce Project, where they now have 825 students of five. These Northern Virginia Community College. They're they're cloud associate degree that they ran in tandem with AWS Educate grew from 30 students at the start of the year to well over 100. Now these programs will drive students to them right and students will get a job at the end. >> Right? Right, well in Ken. And can the schools sports a demand? That's that's a problem we see with CS, right? Everyone says, Tell your kids to take CS. They want to take CS. Guess what? There's no sections, hope in C. S. So you know, thinking of it in a different way, a little bit more innovative way providing that infrastructure kind of ready to go in a cloud based way. Now we'll hopefully enable them to get more kids and really fulfill the demand. >> Absolutely. There's another thing with professional development. I think you're hitting on, so we definitely have a shortage in terms of teachers who are capable to teach about software development and cloud architecture and data sciences and cybersecurity. So we're putting a W. C. Educate is putting a specific focus on professional development. We also want to bring Amazonian, Tze and our customers and partners into the classroom to help with that, because the work based learning and the focus on subject matter expert experts is also important. But we really need to have programs both from industry as well as government out support new teachers coming into this field and in service training for existing teachers to make sure, because yes, we launch those programs and students will come. We have to make sure that were adequately preparing teachers. It's not, it's not. It's not easy, but again, we're seeing whether it's Koda Cole out of out of, uh Roosevelt High School. Are the people that were working with George Mason University and so on were seeing such an appetite >> for >> making change for their students? And so they're putting in those extra hours they're getting that AWS certification, and they're getting stronger, prepared to teach inside the class. That's >> amazing, cause right. Teachers have so many conflict ing draws on their time, many of which have nothing to do with teaching right whether it's regulations and there's just so many things the teachers have to deal with. So you know the fact that they're encouraged the fact that they want t to spend and invest in this is really a good sign and really a nice kind of indicator to you and the team that, you know, you guys were hitting something really, really positive. >> Yeah, I think we've had its this foam oh fear of missing out opportunity. There's the excitement of the cloud. There's the excitement of watching your kids. You're really transformed their lives. And it could be Alfredo Cologne who came over from Puerto Rico after Hurricane Maria. You wiped out his economic potential and started taking AWS educate and you're learning some of these pathways and then landing a job has the Dev ops engineer to Michael Brown, who went through that Santa Monica problem and >> landed an >> internship with Annika. When you see the transformation in your students, no matter what their background is, it is. It is a game changer. This has got to be you. Listen, I love watching that women's team when I win the World Cup, and that the excitement cloud is like the new sport. Robotics is the new sport for these kids. They'll bring them on >> pathways to career, right, well, take for taking a few minutes in The passion comes through Andrew Koza, Big passion guy. And we know Teresa is as well. So it shines through and keep doing good work. >> Thank you so much for the time. Alright, He's Can I'm Jeff, You're watching the Cube. We're in downtown Seattle. A aws. Imagine E d. Thanks for >> watching. We'll see you next time.

>> live from Washington, D. C. It's the Cube covering a ws public sector summit by Amazon Web services. >> Welcome back, everyone to our nation's capital. We are the Cube. We are live at A W s Public Sector summit. I'm your host Rebecca Night, along with my co host, John Farrier. We're joined by Ken Eisner Director Worldwide Educational programs at a WS Thanks so much for coming on the show >> you for having me. >> So tell our viewers a little bit. About what? What you do as the director of educational programs. Sure, I head >> up a program called a Ws Educate a ws educate is Amazon's global initiative to provide students and teachers around the world with the resource is that they need really to propel students into this awesome field of cloud computing. We launched it back in May of 2,015 and we did it to fill this demand. If we look at it today, what kind of right in the midst of this fourth industrial revolution is changing the means of production obviously in the digital on cloud space, But it's also creating this new worker class all around. Yeah, the cloud Advanced services like machine learning I robotics, I ot and so on. And if you looked at the employer demand, um, Cloud computing has been the number one linked in skill for the past four years in a row. We look at cloud computing. We kind of divide into four families. Software development, cloud architecture, the data world, you know, like machine learning I data science, business intelligence and Alex and then the middle school opportunities like technical customer support, age and cybersecurity, which can range all the way from middle school of Ph. D. But yet the timeto hire these people has grown up dramatically. Glass door as study of companies over there platform between two thousand 92 1,050 18 and show that the timeto higher had increased by 80%. Yet just think about that we talk about I mean, this conference is all about innovation. If you don't have builders, if you don't have innovators, how the heck Kenya Kenya innovate? >> Can I gotta ask you, Andy, just to have known him for over eight years and reporting on him and covering it was on when when everyone didn't understand yet what it was. Now everyone kind of does our congratulations and success. But to see him on stage, talk passionately about education. Yeah, mean and knowing Andy means it's kind of boiled up because he's very reserved, very conservative guy, pragmatic. But for him to be overtly projecting, his opinion around education, which was really yeah, pretty critical means something's going on. This is a huge issue not just in politics, riel, state, local areas where education, where >> the root of income inequality it's it's a lot of. >> There's a lot of challenges. People just aren't ready for these new types of jobs that are coming out that >> pay well, by the way. And this is Elliott >> of him out there that are unfilled for the first time, there are more jobs unfilled than there are candidates for them. You're solving this problem. Tell us what's going on in Amazon. Why the fewer what's going on with all this? Why everyone's so jacked up >> a great point. I, Andy, I think, said that education is at a crisis point today and really talked about that racial inequality piece way. Timeto hire people in the software development space Cloud architecture um technical called cloud Support Age. It's incredibly long so that it's just creating excess costs into the system, but were so passionate, like if you look at going to the cloud, Amazon wants to disrupt areas where we do not see that progress happening. Education is an area that's in vast need for disruption. There are people were doing amazing stuff. We've heard from Cal Poly. We've heard from Yeah, Arizona State. Carnegie Mellon. There's Joseph Alan at North Northeastern. >> People are >> doing great stuff. We're looking at you some places that are doing dual enrollment programs between high school and community in college and higher ed. But we're not moving fast enough, but you guys >> are provided with educate your program. This is people can walk in the front door without any kind of going through gatekeepers or any kind of getting college. This is straight up from the front, or they could be dropouts that could be post college re Skilling. Whatever it is, they could walk in the front door and get skilled up through educators that correct, >> we send people the ws educate dot com. All you need is some element of being in school activity, or you won't be going back from Re Skilling perspective and you came free access into resource is whether your student teacher get free access into content. That's map two jobs, because again, would you people warm from the education way? All want enlightenment contributors to sai all important, But >> really they >> want careers and all the stats gallop ransom good stats about both what, yet students and what industry wants. They want them to be aligned to jobs. And we're seeing that there's a man >> my master was specifically If I'm unemployed and I want to work, what can I do? I walk into you, You can go >> right on and we can you sign up, we'll give you access to these online cloud. Career pathways will give you micro credentials so we can bad you credential you against you We belong something on Samarian Robo maker. So individual services and full pathways. >> So this a >> direct door for someone unemployed We're going to get some work and a high paying job, >> right? Right. Absolutely. >> We and we also >> give you free access into a ws because we know that hands on practice doing real world applications is just vital. So we >> will do that end. By the way, at the end of >> this, we have a job board Amazon customer In part of our job, we're all saying >> these air >> jobs are super high in demand. You can apply to get a job as an intern or as a full time. Are you through our job? >> This is what people don't know about Rebecca. The war is not out there, and this is the people. Some of the problems. This is a solution >> exactly, but I actually want to get drilled down a little bit. This initiative is not just for grown ups. It's it's for Kimmie. This is for you. Kid starts in kindergarten, So I'm really interested to hear what you're doing and how you're thinking about really starting with the little kids and particularly underrepresented minorities and women who are not. There were also under representative in the in the cloud industry how you're thinking expansively about getting more of those people into these jacks. And actually, it's still >> Day one within all y'all way started with Way started with 18 and older because we saw that as the Keith the key lever into that audience and start with computer science but we've expanded greatly. Our wee last year reinvent, We introduced pathways for students 14 over and cloud literacy materials such as a cloud inventor, Cloud Explorer and Cloud Builder. Back to really get at those young audiences. We've introduced dual enrollment stuff that happens between high school community college or high school in higher ed, and we're working on partnerships with scratch First Robotics Project lead the way that introduced, whether it's blocked based coding, robotics were finding robotics is such a huge door opener again, not just for technically and >> get into it absolutely, because it's hands on >> stuff is relevant. They weren't relevant stuff that they can touch that. They can feel that they can open their browser, make something happen, build a mobile application. But they also want tohave pathways into the future. They want to see something that they can. Eventually you'll wind up in and a ws the cloud just makes it real, because you, Khun do real worlds stuff from a browser by working with the first robot. Biotics are using scratch toe develop Ai ai extensions in recognition and Lex and Polly and so on. So we've entered into partnerships with him right toe. Open up those doors and create that long term engagement and pipe on into the high demand jobs of tomorrow. >> What do you do in terms of the colleges that you mentioned and you mention Northeastern and Cal Poly Arizona State? What? What are you seeing? Is the most exciting innovations there. >> Yes. So, first of all, we happen to be it. We're in over 24 100 institutions around the world. We actually, by the way, began in the U. S. And was 65% us. Now it's actually 35% US 65% outside. We're in 200 countries and territories around the world. But institutions such as the doing amazing stuff Polo chow at a Georgia Tech. Things that he's doing with visual ization on top of a ws is absolutely amazing. We launched a cloud Ambassador program to reward and recognize the top faculty from around the world. They're truly doing amazing stuff, but even more, we're seeing the output from students. There was a student, Alfredo Cologne. He was lived in Puerto Rico, devastated by Hurricane Maria. So lost his, you know, economic mobility came to Florida and started taking classes at local schools. He found a ws educate and just dove headlong into it. Did eight Pathways and then applied for a job in Dev Ops at Universal Studios and received a job. He is one of my favorite evangelists, but and it's not just that higher ed. We found community college students. We launched a duel enrolment with between Santa Monica College and Roosevelt High School in Los Angeles, focusing again a majority minority students, largely Hispanic, in that community. Um, and Michael Brown, you finish the cloud computing certificate, applied for an internship, a mission clouds so again a partner of ours and became a God. Hey, guys, internship And they start a whole program around. So not only were seeing your excitement out of the institutions, which we are, but we're also seeing Simon. Our students and businesses all want to get involved in this hiring brigade. >> Can I gotta ask. We're learning so much about Amazon would cover him for a long time. You know all the key buzzwords. Yeah, raise the bar all these terms working backwards. So >> tell us about what's your >> working backwards plan? Because you have a great mission and we applaud. I think it's a super critical. I think it's so under promoted. I think we'll do our best to kind of promote. It's really valuable to society and getting people their jobs. Yeah, but it's a great opportunity, you know, itself. But what's your goal? What's your What's your objective? How you gonna get there, What your priorities, What do you what do you what do you need >> to wear? A pure educational workforce? And today our job is to work backwards from employers and this cloud opportunity, >> the thing that we >> care about our customers still remains or student on DH. So we want to give excessive mobility to students into these fields in cloud computing, not just today and tomorrow. That requires a lot that requires machine lurking in the algorithm that you that changed the learning objectives you based on career, so content maps to thes careers, and we're gonna be working with educational institutions on that recruited does. Recruiting doesn't do an effective job at matching students into jobs. >> Are we >> looking at all of just the elite institutions as signals for that? That's a big >> students are your customer and customer, but older in support systems that that support you, right? Like Cal Poly and others to me. >> Luli. We've also got governments. So we were down in Louisiana just some last month, and Governor Bel Edwards said, We're going to state why with a WS educates cloud degree program across all of their community college system across the University of Louisiana State system and into K 12 because we believe in those long term pathways. Never before have governors have ministers of country were being with the Ministry of Education for Singapore in Indonesia, and we're working deep into India. Never had they been more aligned toe workforce development. It creates huge unrest. We've seen this in Spain and Greece we see in the U. S. But it's also this economic imperative, and Andy is right. Education is at a crisis. Education is not solving the needs of all their constituents, but also industries to blame. We haven't been deeply partnered with education. That partnership is such a huge part of >> this structural things of involved in the educational system. It's Lanier's Internets nonlinear got progressions air differently. This is an opportunity because I think if the it's just like competition, Hey, if the U. S Department of Education not get their act together. People aren't going to go to school. I mean, Peter Thiel, another political spectrums, was paying people not to go to college when I was a little different radical view Andy over here saying, Look at it. That's why you >> see the >> data points starting to boil up. I see some of my younger son's friends all saying questioning right what they could get on YouTube. What's accessible now, Thinking Lor, You can learn about anything digitally now. This is totally People are starting to realize that I might not need to be in college or I might not need to be learning this. I can go direct >> and we pay lip >> service to lifelong education if you end. If you terminally end education at X year, well, you know what's what's hap happening with the rest of your life? We need to be lifelong learners. And, yes, we need to have off ramps and the on ramps throughout our education. Thie. Other thing is, it's not just skill, it's the skills are important, and we need to have people were certified in various a ws skills and come but we also need to focus on those competencies. Education does a good job around critical decision making skills and stuff like, um, collaboration. But >> do they really >> do a good job at inventing? Simplified? >> Do they teach kids >> to fam? Are we walking kids to >> social emotional, you know? >> Absolutely. Are we teaching? Were kids have tio think big to move >> fast and have that bias for action? >> I think that I want to have fun doing it way. Alright, well, so fun having you on the show. A great conversation. >> Thank you. I appreciate it. >> I'm Rebecca Knight for John. For your you are watching the cube. Stay tuned.

>> From Times Square in the heart of New York City, it's theCUBE, covering Imagine 2018. Brought to you by Automation Anywhere. >> Hey welcome back everybody. Jeff Frick here with theCUBE. We're in downtown Manhattan, actually midtown Manhattan, at Automation Anywhere Imagine 2018, 1100 people talkin' about bots, talkin' about Robotics Process Automation, or RPA. And we're excited to have the guy that counts the money at the end of the day; it's important part of any business. He's a co-founder, Ankur Kothari, Chief Revenue Officer and Co-Founder, Automation Anywhere. Ankur, great to see you. >> Great to be here, Jeff, thanks for having me. >> So, first off, as a co-founder, I think you're the third or fourth co-founder we've had on today. A little bit of reflection since you guys started this like 14 years ago. >> Yeah. Here we are, there's 1100 people, the room is packed. They had the overflow, they're actually all over us out here with the overflow for the keynote. Take a minute and kinda tell us how you feel about how this thing has evolved over time. >> It feels like a great party to be part of. Always, you're always happy. >> Right. >> One of the traits that you'll find a lot of co-founders is that they are always happy, never satisfied. They're always looking for the next big one. >> Right. >> But it's amazing to be part of Imagine because we learn so much from our customers and our partner as well. It's not just that we bring them together and we're talking. We're learning every time. It's becoming a big ecosystem. >> Right. >> And, an idea as big as a bot or a future of work is too big an idea for one company to continue. You want as many people to come. >> Right. >> So, our idea of Imagine was a little bit like Field of Dreams, you build and they'll come and they'll collaborate and it'll become bigger and bigger. >> And look all around us. I mean, we're surrounded by people and really, the ecosystem. >> And the bots as well, there are bots on the walls and everything else. >> Bots on the walls, partners everywhere. So let's dive into it a little bit. I mean, one of the ways that you guys participate in the ecosystem, and the ecosystem participates, is the Bot Store. >> Yes. >> So it's just like any other kind of an app store. >> Exactly. >> You've got people contributing. I assume you guys have contributed stuff. But we saw earlier in the keynote by Accenture, and EY, and Deloitte. And all types of companies are contributing bots into this ecosystem for lots of different functions or applications. So really, an interesting thing. How's that workin' out? Where'd you come up with the idea? And why's that so important? >> At Automation Anywhere we like to ask ourselves hard questions, as the leaders in this space. And we asked ourselves this question, "What can we now do to further accelerate our journey of all our customers to become a digital enterprise?" The answer came that we are to share in the new bot economy. Now once that answer was clear, every economy requires a marketplace. >> Right. >> And that's where the Bot Store came. It's a marketplace where producers meet the consumers, and you connect them. All we do is, we curate and make sure that the right things go up. But other than that, it's just like any other marketplace. And we thought that if we'll build the right marketplace where the producers meet consumers, we have thousands of customers and large companies looking at it. It will allow perfect place where all the right ideas get converted into product. >> Right. >> We have tons of partners who have domain expertise, functional expertise, vertical expertise; they can prioritize their expertise, they can convert it into IP. >> Right. >> They can do it for free, they can monetize it. So there's lots to gain for producers of all these bots. And if I am a consumer, now suddenly my time clock to make further shrinks, because instead of creating these bots all from scratch, I can download them from this Bot Store and snap them together like a Lego block. >> Right. >> So that's how the whole idea came. We launched it just two months ago and we have hundreds-- >> You just launched it two months ago? >> Yeah! And we have hundreds of bots in it. More than 80-100 partners have participated. We are getting at least 20-30 more submissions coming every day, and we have few hundred submissions coming every week. So, just like any free marketplace, it has an exponential nature. And that's the thing we are counting on. >> That's amazing, that you've got that much traction in such a short period of time. >> Thousands of downloads on a daily basis. Thousands of users just in two month's time. >> You know, we go to a ton of shows. We do over a hundred shows a year. And once shows get to a certain size, it starts to change a little bit. But when they're small like this, it's a very intimate affair on a couple floors here at the Sheraton, everyone is still really involved. They're really sharing. >> Yes. >> There's so much sharing of information. Not so much, you know ... Because they're not really competitors. Within their own companies, they're all part of this same team that are trying to implement this new thing. >> Exactly. >> And you really feel it. >> Exactly. >> So, the store's cool, but the bot economy. When you talk about the bot economy, we talk about API economy a lot. >> Yes. >> How do you see the bot economy? What are the factors that drive the bot economy, and how's it gonna evolve over time? >> We look at it as a few elements. The current version, we think that bot economy, like any economy, has a marketplace, which is our Bot Store. We have a program which we call Bot Games, because any good economy, any new economy, one of the trait is that the good idea can come from anyone. >> Right. >> It can come from anyplace. Like, any customers, any partner, anyone can bring. A good economy, what it does is it brings that idea from anyone, and it gives these vehicles for good ideas to take flight. If the idea is good, it becomes viral, and it has vehicles where those ideas can go to market. What we did was, we created a program called Bot Games. Yesterday on May 29th, we had the 1st Inaugural Bot Games. We invited developers, people who are part of these programs and their companies. And we gamified and created different games. And we thought that if we bring all these champions and pioneers and like-minded people in the same room, give them certain same problem, and then gamify it, put a clock on it, a lot of great ideas will come out of it. >> Right. >> And that came. And some of those ideas will make it to the marketplace, like a Bot Store, like an Imagine. >> Right. >> So that's where all the ideas connect to the customers. And the people who bring those ideas, they also come up. So that's the other aspect. So the Bot Games is where the ideas, you can crowdsource from places. Bot Store is where they go to the market. In between there is a gap. And we are trying to remove that gap by creating a stimulus package for this new bot economy. Like any economy time and again requires a stimulus pack, and we have created one. What we have done is that if you want to learn Automation Anywhere, right? If you want to understand, because that gap is you're to understand Automation Anywhere. We have created Automation Anywhere University a year ago. And now anyone can take courses for free to learn how to create bots. Whether they are customers or partners. And then, if you purchase these bots through one of our certified partners, the first three bots in year one are free. So we are removing the friction in between. If you have not started on this journey, your learning is free, you get ideas from different places, we can get these prebuilt bots, and the first three bots, if you purchase it through our partners, they are free. So we are removing that friction. And then, we are supporting that whole economy with the industry's largest customer success program. >> Right. So I'm curious if you know, maybe you don't know, of the bots in the bots store, how many are free and how many are paid, as a percentage? >> Interestingly, I don't have that stat because we don't actually worry about that. We let all our partners and people who are contributing to this Bot Store decide that. >> Right. >> Some bots they may decide to monetize, some they may not. It's listed on the Bot Store. Offhand, I would say-- >> Take a guess. Is it 50/50? A third? Two-thirds? >> The nature of it looks like 50/50. >> That's a good guess. Full caveat, it's a guess. We didn't do the analysis. >> Exactly. But here is the unique aspect. Yesterday we had a Bot Game, and the winner had an amazing idea that none of us had ever think of. He created this bot that automates the COE of all these programs. Now, we are talking. He is thinking of putting that on Bot Store. That's the power of bringing multiple people together. >> Right. >> That's the power of free economy, where the exponential nature of it is what we are counting on. And we are getting on a daily basis these new bot ideas, these new bots that are making it to the Bot Store. Just like your App Store. I go to App Store to get ideas what I can do on my phone. >> Right, right. >> Just like that, now we are finding our customers are going to Bot Store to figure out what else can they automate. >> Right, right. >> And that's been another amazing part of it. >> You know, it's so consistent. All these shows we go to, right? How do you unlock innovation? There's some really simple ways. One is, give more people the power, give more people the tools, and give more people the data. >> Exactly. >> And you'll get stuff out of it that the small subset of people that used to have access to those three things, they never found. They just didn't think of it that way, right? >> Exactly. And then we firmly believe that any technology, anything, once you democratize it, you give it in hands of everyone-- >> Right, right. >> You can't have a thriving economy unless everyone forms their own point of view. Unless everyone creates their own perspective. And that's our vision of this bot economy. We are bringing everyone and giving them these vehicles to try it out. Look, the technology has reached a stage where it's cheaper to try it out than talk about it. >> Yes. >> And we are doing that so that everyone forms their own unique point of view, and then they express that point of view and we connect those points of view to these thousands of customers worldwide. >> Right. >> Good ideas take flight, and all we have to do is create vehicles for those good ideas to take flight. >> Alright. So, Ankur, I gave you the last word before we wrap up here. If we come back next year, a year from now, inspired 2019, what are we gonna be talking about? What's on your roadmap? What're some of the priorities that you guys are workin' on over the next 12 months? >> We are talking about ... The next 12 months, we are looking at how to further accelerate this journey. Because what people are in this, the real problem people are trying to achieve is how to become a digital enterprise. Not just to automate, but how do you create a digital enterprise? You cannot become a digital enterprise unless your operations are digital. You cannot make your operations digital unless your processes are digital. And you cannot do that unless your workforce is digital. So we are trying to create technologies, vehicles, platforms, so that everyone can scale their program. Where pretty much everyone should have a digital colleague. Everyone should be able to create a bot. Everyone should be able to work with a bot. Every process, every department, every system should have a digital workforce working in it and that can allow you to create a digital enterprise that can scale up and scale down with the demand and supply. >> Alright-- >> That's what we are trying to start. >> Well, we look forward to gettin' the update next year. >> Exactly. >> Alright, Ankur, thanks for taking a few minutes out of your busy day with us. >> Thanks for having me here, and I appreciate and enjoy the conversation. >> Alright, he's Ankur, I'm Jeff. We're at Automation Anywhere Imagine 2018. Thanks for watching theCUBE. See you next time.

>> Announcer: From Milpitas, California, at the edge of Silicon Valley, it's theCUBE covering autonomous vehicles. Brought to you by Western Digital. (upbeat electronic music) >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We are at the Autotech Council Autonomous Vehicles event here at Western Digital. It's part of our ongoing work that we're doing with Western Digital about #datamakespossible and all the really innovative and interesting things that are going on that at the end of the day, there's some data that's driving it all and this is a really crazy and interesting space. So we're excited for our next guest. He's Mark DeSantis. He's the CEO of RoadBotics. Mark, great to see you. >> Welcome. >> Thanks, thanks for having me, Jeff. >> So just to give the quick overview of what is RoadBotics all about? >> Sure, we use a simple cellphone as a data collection device. You put that in the windshield, you drive, it records all the video and all that video gets uploaded to the Cloud and we assess the road's surface meter by meter. Our customers would be Public Works departments at the little town to a big city or even a state, and we apply the same principles that a pavement engineer would apply when they look at a piece of pavement. Looking for all the different subtle little features so that they can get, first of all, get an assessment of the road and then they can do capital planning and fix those roads and do a lot of things that they can't do right now. >> So I think the economics of roads and condition of roads, roads in general, right? We don't think about them much until they're closed, they're being fixed, they're broken up, there's a pothole. >> Mark: Yeah. >> But it's really a complex system and a really high value system that needs ongoing maintenance. >> That's right. I always use the example of the Romans who built a 50,000 mile road network across Europe, the Middle East, and Africa. Some of those roads, like the Appian Way, are still used today. They were very good road builders and they understand the importance of roads. Regrettably, we take our roads for granted. The American Society for Civil Engineers annually rates infrastructure and we're rated about 28% of our nation's 11 million lane miles as poor. Unfortunately, that's- >> Jeff: 28%? >> 28%. And that really means that you need to invest, we'll need to invest at least a million to two million bucks a mile to get those roads back into shape. So we take our roads for granted. I'm enjoying this conference and there's one point that I want to make that I think is very poignant, is the AV revolution will also require a revolution in the maintenance and sustenance of our road network, not just the United States but everywhere in the world. >> So it's interesting, and doing some research before we got together in terms of the active maintenance that's not only required to keep a road in good shape but if you keep the active maintenance in position, those roads will last a very long time. And you made an interesting comment that now the autonomous vehicles, it's actually more important for those vehicles, not only for jolting the electronics around that they're carrying, but also for everything to work the way it's supposed to work according to the algorithms. >> Andrew Ang, who's an eminent computer scientist, machine learning, we were spun out of Carnegie Mellon and he was a graduate of that program, recognized early on that the quality of the roads made all the difference in the world for these vehicles to move around. We, in turn, were spun out of Carnegie Mellon, out of that same group of AV researchers, and in fact, the impetus for the technology was to be able to use the sensing technology that allows a vehicle to move around to assess the quality of roads. And it's road inspection, really, is an important part of road maintenance. The ability to go look at an asset. Interestingly, it's an asset whose challenge is not the fact that it can't be inspected, it's the sheer size of the asset. When you're talking about a small town that might have a 60-mile road network, most and the vast majority of inspection is visual inspection. That means somebody in a car riding very slowly looking down and they'll do that for tens, thousands, hundreds of thousands of miles, very hard to do. Our system makes all that very, much more efficient. The interesting thing about autonomous vehicles is they'll have the capacity to use that data to do that very assessment. So for our company, we ultimately see us embedded in the vehicle itself, but for the time being, cellphones work fine. >> Right. So I'm just curious, what are some of those leading indicator data points? Because obviously we know the pothole. >> Mark: Yeah. >> By then things have gone too far but what are some of the subtle things that maybe I might see but I'm not really looking at? (laughs) >> Well, I think I've changed you right now and you don't know it. You're never going to look at a road the same- >> Oh, I told you, I told you. (laughs) >> After you hear me talk for the next three minutes. I don't look at roads the same and I'm not a civil engineer nor am I a pavement engineer, but as the CEO of this company I had to learn a lot about those two disciplines. And in fact, when you look at a piece of asphalt, you're actually looking for things like alligator cracks, which sort of looks like the back of an alligator's skin. Block cracks, edge cracks, rutting, a whole bunch of things that pavement engineers, frankly, and there is a discipline called pavement engineering, where they look for. And those features determine the state of that road and also dictate what repairs will be done. Concrete pavement has a similar set of characteristics. So what we're looking for when we look at a road is, I always say that, people say, "Well, you're the pothole company." If all you see are potholes, you don't have a business. And the reason is, potholes are at the end of a long process of degradation. So when you see a pothole, there are two problems. One is, you can certain blow out a tire or break an axle on that pothole but also it's indicative of a deeper problem which means the surface of the road has been penetrated which means you to dig up that road and replace it. So if you can see features that are predictive of a road that's just about to go bad, make small fixes, you can extend the useful life of that asset indefinitely. >> Right. So before I let you go, unfortunately, we're just short on time. >> Mark: Yeah. >> I would love to learn about roads. I told you, I skateboard so I pay a lot of attention to smooth roads. >> Mark: (laughs) And you'll pay even more now. >> Now I'll pay even more and call the city. (chuckles) But I want to pivot off what happened at Carnegie Mellon and obviously academic institutions are a huge part of this revolution. >> Yeah, yeah. >> There's a lot of work going on. We're close to Stanford and Berkeley here. Talk a little bit about what happens... It's happening at Carnegie Mellon and I think specifically you came out of the Robotics Institute in something called the Traffic21 project. >> Yeah, Traffic21 is funded by some local private interests who believed that the various technologies that are, really, CMU is known for around computer science, robots, engineering, could be instrumental in bringing about this AV revolution. And as a consequence of that, they developed a program early on to try to bring these technologies together. Uber came along and literally hired 27 of those researchers. Argo, now... Argo, Ford's autonomous vehicle now, is big in Pittsburgh as well. On any given day, by my estimate, it's not an official estimate here, there are about 400 autonomous vehicles, Ford and Uber vehicles, on Pittsburgh's streets every single day. It's an eerie experience being driven around by a completely autonomous Uber vehicle, believe me. >> I've been in a couple. It's interesting and we did a thing with a company called Phantom. They're the ones that step if your Uber gets stuck. >> Oh, yeah. >> Which is interesting. (laughs) So really interesting times and exciting and I will go and pay closer attention for the alligator patterns (laughs) on my route home tonight. (laughs) All right, Mark, thanks for stopping by and sharing the insight. >> Thanks again, Jeff. Appreciate you having me. >> All right, he's Mark, I'm Jeff. You're watching theCUBE from the Autotech Council Autonomous Vehicles event in Milpitas, California. Thanks for watching. (upbeat electronic music)

>> Announcer: From San Jose, it's theCUBE. (upbeat music) Presenting Big Data, Silicon Valley, brought to you by Silicon Angle Media and its ecosystem partners. >> Welcome back to theCUBE. We are live on our first day of coverage of our event, Big Data SV. This is our tenth Big Data event. We've done five here in Silicon Valley. We also do them in New York City in the fall. We have a great day of coverage. We're next to where the Startup Data conference is going on at Forger Tasting Room and Eatery. Come on down, be part of our audience. We also have a great party tonight where you can network with some of our experts and analysts. And tomorrow morning, we've got a breakfast briefing. I'm Lisa Martin with my co-host, Peter Burris, and we're excited to welcome to theCUBE for the first time the CEO of Kinetica, Paul Appleby. Hey Paul, welcome. >> Hey, thanks, it's great to be here. >> We're excited to have you here, and I saw something marketer, and terms, I grasp onto them. Kinetica is the insight engine for the extreme data economy. What is the extreme data economy, and what are you guys doing to drive insight from it? >> Wow, how do I put that in a snapshot? Let me share with you my thoughts on this because the fundamental principals around data have changed. You know, in the past, our businesses are really validated around data. We reported out how our business performed. We reported to our regulators. Over time, we drove insights from our data. But today, in this kind of extreme data world, in this world of digital business, our businesses need to be powered by data. >> So what are the, let me task this on you, so one of the ways that we think about it is that data has become an asset. >> Paul: Oh yeah. >> It's become an asset. But now, the business has to care for, has to define it, care for it, feed it, continue to invest in it, find new ways of using it. Is that kind of what you're suggesting companies to think about? >> Absolutely what we're saying. I mean, if you think about what Angela Merkel said at the World Economic Forum earlier this year, that she saw data as the raw material of the 21st century. And talking about about Germany fundamentally shifting from being an engineering, manufacturing centric economy to a data centric economy. So this is not just about data powering our businesses, this is about data powering our economies. >> So let me build on that if I may because I think it gets to what, in many respects Kinetica's Core Value proposition is. And that is, is that data is a different type of an asset. Most assets are characterized by, you apply it here, or you apply it there. You can't apply it in both places at the same time. And it's one of the misnomers of the notion of data as fuels. Because fuel is still an asset that has certain specificities, you can't apply it to multiple places. >> Absolutely. >> But data, you can, which means that you can copy it, you can share it. You can combine it in interesting ways. But that means that the ... to use data as an asset, especially given the velocity and the volume that we're talking about, you need new types of technologies that are capable of sustaining the quality of that data while making it possible to share it to all the different applications. Have I got that right? And what does Kinetica do in that regard? >> You absolutely nailed it because what you talked about is a shift from predictability associated with data, to unpredictability. We actually don't know the use cases that we're going to leverage for our data moving forward, but we understand how valuable an asset it is. And I'll give you two examples of that. There's a company here, based in the Bay Area, a really cool company called Liquid Robotics. And they build these autonomous aquatic robots. And they've carried a vast array of senses and now we're collecting data. And of course, that's hugely powerful to oil and gas exploration, to research, to shipping companies, etc. etc. etc. Even homeland security applications. But what they did, they were selling the robots, and what they realized over time is that the value of their business wasn't the robots. It was the data. And that one piece of data has a totally different meaning to a shipping company than it does to a fisheries companies. But they could sell that exact same piece of data to multiple companies. Now, of course, their business has grown on in Scaldon. I think they were acquired by Bowing. But what you're talking about is exactly where Kinetica sits. It's an engine that allows you to deal with the unpredictability of data. Not only the sources of data, but the uses of data, and enables you to do that in real time. >> So Kinetica's technology was actually developed to meet some intelligence needs of the US Army. My dad was a former army ranger airborne. So tell us a little bit about that and kind of the genesis of the technology. >> Yeah, it's a fascinating use case if you think about it, where we're all concerned, globally, about cyber threat. We're all concerned about terrorist threats. But how do you identity terrorist threats in real time? And the only way to do that is to actually consume vast amount of data, whether it's drone footage, or traffic cameras. Whether it's mobile phone data or social data. but the ability to stream all of those sources of data and conduct analytics on that in real time was, really, the genesis of this business. It was a research project with the army and the NSA that was aimed at identifying terrorist threats in real time. >> But at the same time, you not only have to be able to stream all the data in and do analytics on it, you also have to have interfaces and understandable approaches to acquiring the data, because I have a background, some background in that as well, to then be able to target the threat. So you have to be able to get the data in and analyze it, but also get it out to where it needs to be so an action can be taken. >> Yeah, and there are two big issues there. One issue is the inter-offer ability of the platform and the ability for you to not only consume data in real time from multiple sources, but to push that out to a variety of platforms in real time. That's one thing. The other thing is to understand that in this world that we're talking about today, there are multiple personas that want to consume that data, and many of them are not data scientists. They're not IT people, they're business people. They could be executives, or they could be field operatives in the case of intelligence. So you need to be able to push this data out in real time onto platforms that they consume, whether it's via mobile devices or any other device for that matter. >> But you also have to be able to build applications on it, right? >> Yeah, absolutely. >> So how does Kinetica facilitate that process? Because it looks more like a database, which is, which is, it's more than that, but it satisfies some of those conventions so developers have an afinity for it. >> Absolutely, so in the first instance, we provide tools ourselves for people to consume that data and to leverage the power of that data in real time in an incredibly visual way with a geospatial platform. But we also create the ability for a, to interface with really commonly used tools, because the whole idea, if you think about providing some sort of ubiquitous access to the platform, the easiest way to do that is to provide that through tools that people are used to using, whether that's something like Tablo, for example, or Esri, if you want to talk about geospatial data. So the first instance, it's actually providing access, in real time, through platforms that people are used to using. And then, of course, by building our technology in a really, really open framework with a broadly published set of APIs, we're able to support, not only the ability for our customers to build applications on that platform, and it could well be applications associated with autonomous vehicles. It could well be applications associated with Smart City. We're doing some incredible things with some of the bigger cities on the planet and leveraging the power of big data to optimize transportation, for example, in the city of London. It's those sorts of things that we're able to do with the platform. So it's not just about a database platform or an insights engine for dealing with these complex, vast amounts of data, but also the tools that allow you to visualize and utilize that data. >> Turn that data into an action. >> Yeah, because the data is useless until you're doing something with it. And that's really, if you think about the promise of things like smart grid. Collecting all of that data from all of those smart sensors is absolutely useless until you take an action that is meaningful for a consumer or meaningful in terms of the generational consumption of power. >> So Paul, as the CEO, when you're talking to customers, we talk about chief data officer, chief information officer, chief information security officer, there's a lot, data scientist engineers, there's just so many stakeholders that need access to the data. As businesses transform, there's new business models that can come into development if, like you were saying, the data is evaluated and it's meaningful. What are the conversations that you're having, I guess I'm curious, maybe, which personas are the table (Paul laughs) when you're talking about the business values that this technology can deliver? >> Yeah, that's a really, really good question because the truth is, there are multiple personas at the table. Now, we, in the technology industry, are quite often guilty of only talking to the technology personas. But as I've traveled around the world, whether I'm meeting with the world's biggest banks, the world's biggest Telco's, the world's biggest auto manufacturers, the people we meet, more often than not, are the business leaders. And they're looking for ways to solve complex problems. How do you bring the connected card alive? How do you really bring it to life? One car traveling around the city for a full day generates a terabyte of data. So what does that really mean when we start to connect the billions of cars that are in the marketplace in the framework of connected car, and then, ultimately, in a world of autonomous vehicles? So, for us, we're trying to navigate an interesting path. We're dragging the narrative out of just a technology-based narrative speeds and feeds, algorithms, and APIs, into a narrative about, well what does it mean for the pharmaceutical industry, for example? Because when you talk to pharmaceutical executives, the holy grail for the pharma industry is, how do we bring new and compelling medicines to market faster? Because the biggest challenge for them is the cycle times to bring new drugs to market. So we're helping companies like GSK shorten the cycle times to bring drugs to market. So they're the kinds of conversations that we're having. It's really about how we're taking data to power a transformational initiative in retail banking, in retail, in Telco, in pharma, rather than a conversation about the role of technology. Now, we always needs to deal with the technologists. We need to deal with the data scientists and the IT executives, and that's an important part of the conversation. But you would have seen, in recent times, the conversation that we're trying to have is far more of a business conversation. >> So if I can build on that. So do you think, in your experience, and recognizing that you have a data management tool with some other tools that helps people use the data that gets into Kinetica, are we going to see the population of data scientists increase fast enough so our executives don't have to become familiar with this new way of thinking, or are executives going to actually adopt some of these new ways of thinking about the problem from a data risk perspective? I know which way I think. >> Paul: Wow, >> Which way do you think? >> It's a loaded question, but I think if we're going to be in a world where business is powered by data, where our strategy is driven by data, our investment decisions are driven by data, and the new areas of business that we explored to creat new paths to value are driven by data, we have to make data more accessible. And if what you need to get access to the data is a whole team of data scientists, it kind of creates a barrier. I'm not knocking data scientists, but it does create a barrier. >> It limits the aperture. >> Absolutely, because every company I talk to says, "Our biggest challenge is, we can't get access to the data scientists that we need." So a big part of our strategy from the get go was to actually build a platform with all of these personas in mind, so it is built on this standard principle, the common principles of a relational database, that you're built around anti-standard sequel. >> Peter: It's recognizable. >> And it's recognizable, and consistent with the kinds of tools that executives have been using throughout their careers. >> Last question, we've got about 30 seconds left. >> Paul: Oh, okay. >> No pressure. >> You have said Kinetica's plan is to measure the success of the business by your customers' success. >> Absolutely. >> Where are you on that? >> We've begun that journey. I won't say we're there yet. We announced three weeks ago that we created a customer success organization. We've put about 30% of the company's resources into that customer success organization, and that entire team is measured not on revenue, not on project delivered on time, but on value delivered to the customer. So we baseline where the customer is at. We agree what we're looking to achieve with each customer, and we're measuring that team entirely against the delivery of those benefits to the customer. So it's a journey. We're on that journey, but we're committed to it. >> Exciting. Well, Paul, thank you so much for stopping by theCUBE for the first time. You're now a CUBE alumni. >> Oh, thank you, I've had a lot of fun. >> And we want to thank you for watching theCUBE. I'm Lisa Martin, live in San Jose, with Peter Burris. We are at the Forger Tasting Room and Eatery. Super cool place. Come on down, hang out with us today. We've got a cocktail party tonight. Well, you're sure to learn lots of insights from our experts, and tomorrow morning. But stick around, we'll be right back with our next guest after a short break. (CUBE theme music)

>> Narrator: From Hell's Kitchen in New York City, it's The Cube on the ground at Serverlessconf. Brought to you by SilliconANGLE Media. >> Hi, I'm Stu Miniman with The Cube, and we're here are Serverlessconf in Hell's Kitchen New York City, really happy to welcome to the program, another one of the keynote speakers. Ben Kehoe, who's the Cloud Robotics research scientist at iRobot. >> Yeah. >> Ben, great to see you. >> Great to see you too. >> All right, so tell us a little bit about how you got involved with Serverless. >> Yeah, I mean it all started, I was a grad student in robotics, and I started thinking about, you know, we have all these robotics algorithms. And as the cloud can enable robots to do more and better things, how do we help turn those robotics algorithms into web services. And I didn't get very far in that, right towards the end of my PHD, and then that was 2014, LAMBDA was released, and it was like hey, that looks like it does the kind of thing that I was thinking about that we needed. So then I joined iRobot, and we were developing a cloud solution, a cloud application for our connected robots and apps, and to help us scale that to stay lean. Serverless was the right choice, and we've been doing that since 2015. >> Yeah, so Ben, what is it about Serverless that made it a fit for this? You know, I think about, doesn't their responsiveness, performance, latency if I have to go >> Yeah. >> up to the cloud and back like that way. I think some of this needs to kind of live locally. And some that goes there, maybe you can just briefly tease through some of those dynamics for us. >> Yeah, when you're talking about robots, you definitely have to keep things local. You want a robot to be responsive to its environment. You want, that even if its cloud connection disappears, that it can still accomplish all of its tasks. So it's always a mix of keeping it as a timeless robot that is enabled to do better things through the cloud, in terms of additional computational power, or accessing libraries of information to help it understand its world better. And of course, when one robot learns something, all robots can benefit from that experience. >> Excellent, so this is the first step for Skynet is what you're saying, right? >> Could be. >> All right, bring us in a little bit. Your keynote, what were you looking to share? You know, some of the key points. >> Yeah, I think in the talks that I've given at Serverlessconf, they tend to be as much as I am enthusiastic about Serverless, fully bodying, I try and pull us back a little bit to say, "What are we still missing? "What's not here yet? "Where do we need to go?" And so I had some frowny face emoji in my talk about event driven programming, event driven Serverless, and Serverless without event driven programming. Now we're still, you know, we have areas to improve in each one of those. And then that transitioned really into, "How do we start bringing in people who "are just starting into Serverless?" Larger organizations, more traditional architectures, and people who are experienced with that, and understand traditional architectures well. How do we get them on board with Serverless? And so that starts with just the gateway drug, which is infrastructure automation at the edges of their application, taking scripts that they run from developer machines with Cron jobs, and moving those into a function that's triggered by some cloud event. And then from there, starting to bring them over in terms of you can reduce your costs by eliminating idle resources. You can start to simplify and strengthen by refactoring some of that. And then once you really get them thinking about, "Oh, this is really working for the things "that we're doing." New features will start to be developed. Serverless native or event driven native. And then sort of at the end of the talk, the key is that because Serverless architectures look different from traditional architectures, there's something called Conway's law that says, "The design of your application will follow "the communication patterns in your organization." >> Stu: Right. >> And so you have to sort of flip that around to say, "Well if our design is changing, then we have "to make our organization change as well." >> Right, does that mean we're going to have, micro-employees you know? Instead of micro services we have, you know, employees that we hire them, and then we fire them pretty quick when we don't need them, or? >> I hope not. >> Yeah. >> I hope not. >> (crosstalk) that that's the part time, the uber's >> Yes. >> nation of the workforce. >> Yes. That would be, I think an inefficient way of going about it. >> Yeah. >> But I think we do need to reset expectations around what we have control over, and what we don't, because when you're on a traditional architecture with servers, you can reach in and fix problems that you have. And recognizing that when you're running on functions as a service platform, and using managed services, that when the provider has some sort of incident, you're out of control of that. It's a very uncomfortable place to be of not being in control of your own destiny, even though when you look at the big picture, that's going to happen less often, then if you were doing it yourself. >> Stu: Yeah. >> And so that's making sure that the mindset inside the organization, and the way that people communicate, is appropriately tuned to that sort of new paradigm. >> Okay, yeah. Ben, some of those frowny faces, what are things that the community is working on that you're hopeful for? What are some of the areas that we need for the maturation of this space? >> Yeah, I think something that I talked about previously that's coming around, is monitoring. So there's much more tools out there to monitor the infrastructure to know what's going on inside these functions and these managed services. And there's now some security analysis tools that are coming out, that some of these people are present here. And that was a big aspect that I've harped on for a long time of... We have a lot of mature traditional tools, that will do network analysis of your servers. Well it's like, "I don't have any servers." And those vendors then say, "Well, we can't help you." And there's static code analysis vendors who say we look at your whole application, and the flows inside it. And we say, well most of my application exists outside of code that I've written. I just write little bits, that glue it together in the way that my business works. And they say, "Oh, well we can't help you." >> Yeah. It reminds me, I think you know for so many years, people were really excited about how they could build their infrastructure. >> Yeah. >> And now they look to environments, well I can get out of that. So it caught my eye. You know, you put out on twitter, said "Maybe we need to have, you know, my next talk will be, "Work dumber not harder." Maybe explain that a little bit. >> Yeah, so I think, >> Yeah. >> I've been thinking about, you know, with some of the talks here about how it's not building it yourself. That in some ways, there's not invented here syndrome. And we kind of want to go a little bit down the road of invented here syndrome, of if you're building something that is not business logic, you're probably ideally thinking, "Maybe I shouldn't be doing this." So turning it into, I don't want to have to be clever in setting up my architecture, because being clever and like writing, it's always interesting to do, right? When you're developing, you're solving a computer science problem. But often that mean you're not delivering business value. And so, in Paul Johnson's talk, he was talking about the kind of people he looks like. What the kind of people he looks for, look like. >> Yeah. >> And he was saying, you know, "It's people "who want to get stuff out the door. "And who think about good enough." And I think that's really the thing of, how do we, when the people you hire are people who just want to ship features, they're going to say, "I can pull together services to do that "without having to actually solve any hard problems." And that means that you're delivering value, and you're operating more in your business space then in a technology space." >> All right, Ben I want to give you the final word. >> Thank you. >> You know, only 460 people here, which is good growth for the show, but a lot of people out there that are still learning about Serverless, what tips do you give them? You know, first steps to get involved, get involved with the community, (mumbles) some early wins they can have? >> I think there's a couple of things. There is training out there, there's blogs. There's twitter. Ask questions. You know, ping me on twitter if you wonder about something. And there's a Serverless slack that's very active, and if you ask basically anybody, the link is floating around. >> All right, well Ben Kehoe, thanks so much. Great to meet you, and thanks for sharing in this community. >> Yeah, thanks for having me. >> And our community, I'm Stu Miniman and thanks for watching The Cube. (upbeat, exciting music bumper)

>> It's a pleasure to be here with you and to tell you about something I've been dreaming about and working for for many years and now is coming to the surface quite powerfully and quite usefully in many areas. I apologize, sometimes this flickers for some reason but I hope it doesn't disturb the story. I'd like to give you a little touch of history since I was there at the beginning of this journey and give you a brief introduction to what we mean for Fog Computing. And then go quickly to three powerful application spaces for this technology, together with industrial internet and one is industrial automation. That's the focus of our activity as Nebbiolo Technologies. The other one is one of my favorite ones and we'll get there is the automotive that caught fire here in Silicone Valley in the last years, the autonomous car, the connected vehicle and so on. And this is related to also to intelligent transportation and Smart Cities. And then a little touch on what Fog Computing means for Smart grid energy but many, many other sectors will find the same usefulness, the same architecture dimensions of Fog Computing applicable. So this is the story that comes back hopefully, here, the day in 2010 when Fog Computing, the word started here, oh God, is this jumping around? I think it's the connector, this is the age of the connector, this is the age of the Dongles. This is not an Apple Dongle and so we are having troubles. And this is not yet one of the last machines that are out. Let's hope for, I never had this problem, okay. Alright, this date 2010 at the Aquarium Research Center in Monterey where I gave a talk about robots going down deep in the bottom of those big valleys under the ocean and when I finished, the lady, Ginny in the middle approached me and told me, look, why don't you call what you're talking about fog computing? Because it's cloud computing brought too close to the ground and I protested for about 15 minutes. And on the drive home, I thought that's really a good name for what we are doing, what we have been doing in the last years and I started trying it out and using it and more and more I found good response and so seven years later, I'm still here talking about the same thing. What's happening is Fog, the edge of the metric zone was very important but it was always very important in IT, is still very important in IT in mobile, in content distribution but when IOT came to the surface, it became even more relevant to understand the need of resources, virtualized real time capable, secure, trusted with storage computing and networking coming together at the edge. At the edge of the IT network, now they are calling this mobile edge, they realize we are realizing that mobile can benefit from local resources at the edge, powerful real time capable resources but also and more importantly for what we are doing in this space of operational technologies, this is the space, the other and the other side of the boundary between information technologies and operational technologies and here is where we are living with Fog Computing these days so, apologize, I apologize for this behavior that is, maybe I have another Dongle, Apple Dongle. Maybe I could look at that, maybe Morris can help me out here, anyway, so what is Fog Computing? Fog Computing is really the platform that brings modern, Cloud inspired Computing storage here is important here for our friends at Western Digital and networking functions closer to the data producing sources. In our case, machines, things, but not just bringing Cloud down, it's also bringing functions up from the machine world, the real time, the safety functions, the trusting and reliability functions required in that area and this is a unified solution at the edge that really brings together communication, device management, data harvesting, analysis and control. So this is kind of new except for our friends in Wall Street. The real time part was not as sensitive. Now we are realizing how important it is and how important the position of resources is in the future of solutions in this space and so it's not boxes. It's a distributed layer of resources, well managed at the edge of the network and really has a lot of potential across multiple industries. Here we see the progress also in the awareness of this topic with the open fog control room that is now a very active and even the Vcs. Peter Levine here is talking about the importance of the edge. What is really happening is the the convergence. I think we should probably stop and use a different Dongle. Is this the one, no, no, this is not the right Dongle. The world of Dongles, sorry. Oh boy. Oh you have the computer with the, okay, is the right Dongle with the right computer, okay. Here we are, okay. Alright, we're getting back there. This is the new Apple. Okay, we are here, this looks better, thank you. Alright, so this is to be understood. This is the convergence of IT functionality, the modern IT functionality with the OT requirements and this is fundamentally the powerful angle that Fog Computing brings to IOT and machine world so all the nice things that happened in the Cloud come down but meet the requirements of resources, the needs and the timing of the Edge. And so when you look at what is brought into particularly the world of operations, you see these kind of functions that are not usually there. In fact, when you meet this operational world, you find microprocessors, you find Windows machines, industrial Pcs and so on, not so much Linux, not so much the modern approaches to computing. These are the type of dimensions that you'll see have a particular impact on the pain points seen in the wold of applications. So now we go to the Use cases in, use cases in the internet of things. I think it's on your side, I'm sorry. Because it's the second machine. Okay, well, maybe here's the solution. So we have seen this picture of IOT multiple times. A lot of verticals, we are concentrating on this tree, one is the industrial, the second one is the autonomous vehicle in intelligent transportation, the third one, just touched upon is the Smart Grid. This is the area of activity for Nebbiolo Technologies. Those kind of body shops and industrial floors with large robots with a lot of activity around those robots with cells protecting the activities within each working space, this is the world PLCs, industrial Pcs controlling robots, very fragmented. Here we are really finding even more critical this boundary between operational and informational technologies. This is a fire wall, also a mental fire wall between the two worlds and best practice is very different in one place than the other particularly also in the way we handle data, security, and many other areas. In this space, which is also a little more characterized here with this kind of machines that you see in this ISA 99 or ISA 95 type of picture, you see the boundary between the two spaces, once more when we come back. And alright, so the key message here, very tough to go across, it's very complex, the interaction between the two worlds. And there is where deeply we find a number of pain points at the security level, at the Hardware architecture level, at the data analytics and storage level, at the networking, software technologies and control architecture. There's a lot happening there that is old, 1980's time frame, very stable but in need of new approaches. And this is where Fog Computing has a very strong impact And we'll see, sorry, this is a disaster here. Alright, what do we do, alright. Maybe I should go around with this computer and show it to you. Okay, now it's there for a moment. Now, this is, maybe you have to remember one picture of all this talk, look at this, what is this? This is a graphical image of a body shop of a an important car company, you see the dots represent computers within boxes, industrial Pcs, PLCs, controllers for welding machines, tools and so on. That is, if you sum up the numbers, it's thousands of computers, each one of them is updated through a UPC, USB stick, sorry and is not managed remotely. It's not secure because there's a trust that the whole area is enclosed and protected through a fire wall on the other side but it's very stable but very rigid. So this is the world that we are finding with dedicated, isolated, not secure computing, this is Edge Computing. But it's not what we hope to be seeing soon as Fog Computing in action there so this is the situation. Very delicate, very powerful and very motivating. And now comes IOT and this is not the solution. It's helping, IOT tries to connect this big region, the operational region to the back end to the Clouds, to the power of computing that is there, very important, predicting maintenance, many other things can be done from there but it's still not solving the problem. Because now you have to put little machines, gateways into that region, one more machine to manage, one more machine to secure and now you're taking the data out. You are not solving a lot of the pain points. There's some important benefits, this is very, very good. But it's not the story, the story is sold once you really go one step deeper, in fact, from connectivity between information technologies and informational technologies to really Convergence and you see it here where you're starting to replace those machines supporting each cell with a fog node, with a powerful convergent point of computing, real time computing that can allow control, analytics and storage and networking in the same nodes so now these nodes are starting to replace all the objects controlling a cell. And offer more functions to the cell itself. And now, you can imagine where this goes, to a convergent architecture, much more compact, much more homogeneous, much more like Cloud. Much more like Cloud brought down to the Edge. When this comes back, okay, almost there. So this is okay, this is now the image that you can image leads to this final picture that is now even not, okay, do you see it, okay. Now you're seeing the operational space with the fabric of computing storage and networking that is modern, that is virtualized, that supports an application store, now you have containers there. You can imagine virtual machines and dockers living the operational space. At the same time, you have it continuing from the Cloud to the network, the modern network, moving to the Edge into the operational space. This is where we are going and this is where the world wants us to go and the picture representing this transition and this application of Fog Computing in this area is the following, the triangle, the pyramid is now showing a layer of modern computing that allows communications analysis control application hosting and orchestration in a new way. This is cataclysmic, really is a powerful shift, still not fully understood but with immense consequences. And now you can do control, tight, close to the machines, a little slower through the Fog and a little slower through the Cloud, this is where we are going. And there's many, many used cases, I don't dwell on those. But we are proceeding with some of our partners exactly in this direction. Now the exciting topics if I can have five more minutes making up the time wasted. What's going on here, the connected vehicle, the autonomous vehicle, the electrification of automobile are all converging and I think it's very clear that the para dime of Fog Computing is fundamental here. And in fact, imagine the equivalent of a manufacturing cell with a converging capabilities into the Fog and compare it with what's going on with the autonomous vehicle. This is a picture we used a Sysco seven years ago. But this is now, a car is a set of little control loops, ECUs, little dispersed, totally connected computers. Very difficult to program, same as the manufacturing cell. And now where are we going, we are going towards a Fog node on wheels, data center on wheels but better a Fog node on wheels with much better networking between, with a convergence of the intelligence, the control, the analytics, the communications in the middle and a modern network deterministic internet called TSN is going to replace all these CAN boxes and all these flakey things of the past. Same movement in industrial and in the automobile and then you look at what's going on in the intelligent transportation, you can imagine Fog Computing at the edge, controlling the junctions, the traffic lights, the interactions with cars, cars to cars and you see it here, this is the image, again where you have the operational space of transportation connected to the Clouds in a seamless way which these nodes of computing storage and networking at the junctions inside the cars talking to each other, so this is the beautiful movement coming to us and it requires the distribution of resources with real time capabilities, here you see it. And now, the Smart Grid, again, it cannot continue to go the same way with a utility data center controlling everything one way, it has to have and this is from Duke and a standardization body, you can see that there's a need of intelligence in the middle, Fog nodes, distributed computing that are allowing local decisions. Energy coming from a microcell into the grid and out, a car that wants to sell it's energy or buy energy doesn't need to go slowly to a utility data center to make decisions so again, same architecture, same technologies needed, very, very, very powerful. And we could go on and on and on, so what are we doing? We won't advertise here but the name has to be remembered. The name comes from a grape that grows in the Fog in Northern Italy, it's in Piedmont, my home town is behind that 13th century castle you see there. Out there is Northern Italy close to Switzerland. That vineyard is from my cousin, it's a good Nebbiolo, starting to be sold in California too. So this is the name Nebbia Fog comes to, Nebbiolo Technologies, we are building a platform for this space with all the features that we feel are required and we are applying it to industrial automation. And our funders are not so much from here, are from Germany, Austria, KUKA Robotics, TTTech, GiTV from Japan and a few bullets to complete my presentation. Fog Computing is really happening. There's a deep need for this converged infrastructure for IOT including Fog or Edge as someone calls it. But we need to continue to learn, demonstrate, validate through pilots and POCs and we need to continue to converge with each other and with the integrators because these solutions are big and they are not from a little start up. They are from integrators, customers, big customers at the other end, an ecosystem of creative companies. No body has all the pieces, no Sisco, no GE and so on. In fact, they are all trying to create the ecosystem. And so let's play, let's enjoy the Cloud, the Fog and the machines and try to solve some of the big problems of this world. >> Okay, Flavio, well done. >> Sorry for that. Sorry for the hiccups. >> Now we do that on purpose to see how you'd react and you're a pro, thank you so much for the great presentation. >> Alright. >> Alright, now we're going to get into panel one, looking at the data models and putting data to work.