(upbeat music) >> Welcome to theCube's continuous coverage of AWS re:Invent 2021. I'm Dave Nicholson, and we are running one of the industry's most important and largest hybrid tech events this year with AWS and its partners with two live sets on the scene. In addition to two remote studios. And we'll have somewhere in the neighborhood of a hundred guests on the program this year at re:Invent. I'm extremely delighted to welcome a very, very special guest. Right now. He served as the director of the NSA under two presidents, and was the first commander of the U.S Cyber Command. He's a Cube alumni, he's founder and co-CEO of IronNet Cybersecurity. General Keith Alexander. Thanks for joining us today General. >> Thanks, David. It's an honor to be here at re:Invent, you know, with AWS. All that they're doing and all they're making possible for us to defend sector states, companies and nations in cyber. So an honor to be here. >> Well, welcome back to theCube. Let's dive right in. I'd like to know how you would describe the current cyber threat landscape that we face. >> Well, I think it's growing. Well, let's start right out. You know, the good news or the bad news, the bad news is getting worse. We're seeing that. If you think about SolarWinds, you think about the Hafnium attacks on Microsoft. You think about this rapid growth in ransomware. We're seeing criminals and nation states engaging in ways that we've never seen in the past. It's more blatant. They're going after more quickly, they're using cyber as an element of national power. Let's break that down just a little bit. Do you go back to two, July. Xi Jinping, talked about breaking heads in bloodshed when he was referring to the United States and Taiwan. And this has gone hot and cold, that's a red line for him. They will do anything to keep Taiwan from breaking away. And this is a huge existential threat to us into the region. And when this comes up, they're going to use cyber to go after it. Perhaps even more important and closer right now is what's going on with Russia in the Donbas region of eastern Ukraine. We saw this in 2014, when Russia took over the Crimea. The way they did it, staging troops. They did that in 2008 against Georgia. And now there are, by some reports over a hundred thousand troops on the border of Eastern Ukraine. Some call it an exercise, but that's exactly what they did in Georgia. That's what they did in the Crimea. And in both those cases, they preceded those attacks, those physical attacks with cyber attacks. If you go to 2017, when Russia hit the Ukrainian government with the NotPetya attack that had global repercussions. Russia was responsible for SolarWinds, they have attacked our infrastructure to find out what our government is doing and they continue going. This is getting worse. You know, it's interesting when you think about, so what do you do about something like that? How do we stop that? And the answer is we've got to work together. You know, Its slam commissioner addressed it. The meeting with the president on August 25th. This is a great statement by the CEO and chairman of Southern Company, Tom Fanning. He said this, "the war is being waged on our nation's critical infrastructure in particular, our energy sector, our telecommunications sector and financial sector." The private sector owns and operates 87% of the critical infrastructure in the United States, making collaboration between industry and the federal government imperative too, for these attacks. SO >> General, I want to dig just a little bit on that point that you make for generations, people have understood that the term is 'kinetic war', right? Not everyone has heard that phrase, but for generations we've understood the concept of someone dropping a bomb on a building as being an attack. You've just mentioned that, that a lot of these attacks are directed towards the private sector. The private sector doesn't have an army to respond to those attacks. Number one, that's our government's responsibility. So the question I have is, how seriously are people taking these kinds of threats when compared to the threat of kinetic war? Because my gosh, you can take down the entire electrical grid now. That's not something you can do with a single bomb. What are your, what are your thoughts on that? >> So you're hitting on a key point, a theoretical and an operational point. If you look back, what's the intent of warfare? It's to get the mass of people to give up. The army protects the mass of people in that fight. In cyber, there's no protection. Our critical infrastructure is exposed to our adversaries. That's the problem that we face. And because it's exposed, we have a tremendous vulnerability. So those who wish us harm, imagine the Colonial Pipeline attack an order of magnitude or two orders of magnitude bigger. The impact on our country would paralyze much of what we do today. We are not ready for that. That's the issue that Tom Fanning and others have brought up. We don't practice between the public sector and the private sector working together to defend this country. We need to do that. That's the issue that we have to really get our hands around. And when we talk about practice, what do we mean? It means we have to let that federal government, the ones that are going to protect us, see what's going on. There is no radar picture. Now, since we're at re:Invent, the cloud, where AWS and others have done, is create an infrastructure that allows us to build that bridge between the public and private sector and scale it. It's amazing what we can now do. We couldn't do that when I was running Cyber Command. And running Cyber Command, we couldn't see threats on the government. And we couldn't see threats on critical infrastructure. We couldn't see threats on the private sector. And so it all went and all the government did was say, after the fact you've been attacked. That's not helpful. >> So >> It's like they dropped a bomb. We didn't know. >> Yeah, so what does IronNet doing to kind of create this radar capability? >> So, well, thanks. That's a great question because there's four things that you really got to do. First. You've got to be able to detect the SolarWinds type attacks, which we did. You've got to have a hunt platform that can see what it is. You've got to be able to use machine learning and AI to really cut down the number of events. And the most important you need to be able to anonymize and share that into the cloud and see where those attacks are going to create that radar picture. So behavioral analytics, then you use signature based as well, but you need those sets of analytics to really see what's going on. Machine learning, AI, a hunt platform, and cloud. And then analytics in the cloud to see what's going on, creates that air traffic control, picture radar, picture for cyber. That's what we're doing. You see, I think that's the important part. And that's why we really value the partnership with AWS. They've been a partner with us for six years, helping us build through that. You can see what we can do in the cloud. We could never do in hardware alone. Just imagine trying to push out equipment and then do that for hundreds of companies. It's not viable. So SaaS, what we are as a SaaS company, you can now do that at scale, and you can push this out and we can create, we can defend this nation in cyber if we work together. And that's the thing, you know, I really, had a great time in the military. One of the things I learned in the military, you need to train how you're going to fight. They're really good at that. We did that in the eighties, and you can see what happened in 1990 in the Gulf war. We need to now do that between the public and private sector. We have to have those training. We need to continuously uplift our capabilities. And that's where the cloud and all these other things make that possible. That's the future of cybersecurity. You know, it's interesting David, our country developed the internet. We're the ones that pioneered that. We ought to be the first to secure. >> Seems to make sense. And when you talk about collective defense in this private public partnership, that needs to happen, you get examples of some folks in private industry and what they're doing, but, but talk a little bit more about, maybe what isn't happening yet. What do we need to do? I don't want you to necessarily get political and start making budgetary suggestions, but unless you want to, but what, but where do you see, where do we really need to push forward from a public perspective in order to make these connections? And then how is that connection actually happen? This isn't someone from the IronNet security service desk, getting on a red phone and calling the White House, how are the actual connections made? >> So it has to be, the connections have to be just like we do radar. You know, when you think about radars across our nation or radar operator doesn't call up one of the towers and say, you've got an aircraft coming at you at such and such a speed. I hope you can distinguish between those two aircraft and make sure they don't bump into each other. They get a picture and they get a way of tracking it. And multiple people can see that radar picture at a speed. And that's how we do air traffic control safety. We need the same thing in cyber, where the government has a picture. The private sector has a picture and they can see what's going on. The private sector's role is I'm going to do everything I can, you know, and this is where the energy sector, I use that quote from Tom Fanning, because what they're saying is, "it's our job to keep the grid up." And they're putting the resources to do it. So they're actually jumping on that in a great way. And what they're saying is "we'll share that with the government", both the DHS and DOD. Now we have to have that same picture created for DHS and DOD. I think one of the things that we're doing is we're pioneering the building of that picture. So that's what we do. We build the picture to bring people together. So think of that is that's the capability. Everybody's going to own a piece of that, and everybody's going to be operating in it. But if you can share that picture, what you can begin to do is say, I've got an attack coming against company A. Company A now sees what it has to do. It can get fellow companies to help them defend, collective defense, knowledge sharing, crowdsourcing. At the same time, the government can see that attack going on and say, "my job is to stop that." If it's DHS, I could see what I have to do. Within the country, DOD can say, "my job is to shoot the archers." How do we go do what we're authorized to do under rules of engagement? So now you have a way of the government and the private sector working together to create that picture. Then we train them and we train them. We should never have had an event like SolarWinds happen in the future. We got to get out in front. And if we do that, think of the downstream consequences, not only can we detect who's doing it, we can hold them accountable and make them pay a price. Right now. It's pretty free. They get in, pap, that didn't work. They get away free. That didn't work, we get away free. Or we broke in, we got, what? 18,000 companies in 30,000 companies. No consequences. In the future there should be consequences. >> And in addition to the idea of consequences, you know, in the tech sector, we have this concept of a co-op petition, where we're often cooperating and competing. The adversaries from, U.S perspective are also great partners, trading partners. So in a sense, it sounds like what you're doing is also kind of adhering to the old adage that, that good fences make for great neighbors. If we all know that our respective infrastructures are secure, we can sort of get on with the honest business of being partners, because you want to make the cost of cyber war too expensive. Is that, is that a fair statement? >> Yes. And I would take that analogy and bend it slightly to the following. Today every company defends itself. So you take 90 companies with 10 people, each doing everything they can to defend themselves. Imagine in the world we trying to build, those 90 companies work together. You have now 900 people working together for the collective defense. If you're in the C-suite or the board of those companies, which would rather have? 900 help new security or 10? This isn't hard. And so what we say is, yes. That neighborhood watch program for cyber has tremendous value. And beyond neighborhood watch, I can also share collaboration because, I might not have the best people in every area of cyber, but in those 900, there will be, and we can share knowledge crowdsource. So it's actually let's work together. I would call it Americans working together to defend America. That's what we need to do. And the states we going to have a similar thing what they're doing, and that's how we'll work this together. >> Yeah. That makes a lot of sense. General Alexander it's been a pleasure. Thanks so much for coming on to theCube as part of our 2021 AWS re:Invent coverage. Are you going to get a chance to spend time during the conference in Las Vegas? So you just flying in, flying out. Any chance? >> Actually yeah. >> It's there, we're still negotiating working that. I've registered, but I just don't know I'm in New York city for two meetings and seeing if I can get to Las Vegas. A lot of friends, you know, Adam Solski >> Yes >> and the entire AWS team. They're amazing. And we really liked this partnership. I'd love to see you there. You're going to be there, David? Absolutely. Yes, absolutely. And I look forward to that, so I hope hopefully we get that chance again. Thank you so much, General Alexander, and also thank you to our title sponsor AMD for sponsoring this year's re:Invent. Keep it right here for more action on theCube, you're leader in hybrid tech event coverage, I'm Dave Nicholson for the Cube. Thanks. (upbeat music)

>>this session will be reviewing the power benefits of implementing a secure software supply chain and how we can gain a cloud like experience with flexibility, speed and security off modern software delivery. Hi, I'm Matt Bentley, and I run our technical pre sales team here. Um Iran. Tous I spent the last six years working with customers on their container ization journey. One thing almost every one of my customers is focused on how they can leverage the speed and agility benefits of contain arising their applications while continuing to apply the same security controls. One of the most important things to remember is that we are all doing this for one reason, and that is for our applications. So now let's take a look at how we could provide flexibility all layers of the stack from the infrastructure on up to the application layer. When building a secure supply chain for container focus platforms, I generally see two different mindsets in terms of where the responsibilities lie between the developers of the applications and the operations teams who run the middleware platforms. Most organizations are looking to build a secure yet robust service that fits the organization's goals around how modern applications are built and delivered. Yeah. First, let's take a look at the developer or application team approach. This approach follows Mawr of the Dev ops philosophy, where a developer and application teams are the owners of their applications. From the development through their life cycle, all the way to production. I would refer this more of a self service model of application, delivery and promotion when deployed to a container platform. This is fairly common organizations where full stack responsibilities have been delegated to the application teams, even in organizations were full stack ownership doesn't exist. I see the self service application deployment model work very well in lab development or non production environments. This allows teams to experiment with newer technologies, which is one of the most effective benefits of utilizing containers and other organizations. There's a strong separation between responsibilities for developers and I T operations. This is often do the complex nature of controlled processes related to the compliance and regulatory needs. Developers are responsible for their application development. This can either include doctorate the development layer or b'more traditional throw it over the wall approach to application development. There's also quite a common experience around building a center of excellence with this approach, where we can take container platforms and be delivered as a service to other consumers inside of the I T organization. This is fairly prescriptive, in the manner of which application teams would consume it. When examining the two approaches, there are pros and cons to each process. Controls and appliance are often seen as inhibitors to speak. Self service creation, starting with the infrastructure layer, leads to inconsistency, security and control concerns, which leads to compliance issues. While self service is great without visibility into the utilization and optimization of those environments, it continues the cycles of inefficient resource utilization and the true infrastructure is a code. Experience requires Dev ops related coding skills that teams often have in pockets but maybe aren't ingrained in the company culture. Luckily for us, there is a middle ground for all of this Doc Enterprise Container Cloud provides the foundation for the cloud like experience on any infrastructure without all of the out of the box security and controls that are professional services Team and your operations team spend their time designing and implementing. This removes much of the additional work and worry Run, ensuring that your clusters and experiences are consistent while maintaining the ideal self service model, no matter if it is a full stack ownership or easing the needs of I T operations. We're also bringing the most natural kubernetes experience today with winds to allow for multi cluster visibility that is both developer and operator friendly. Let's provides immediate feedback for the health of your applications. Observe ability for your clusters. Fast context, switching between environments and allowing you to choose the best in tool for the task at hand. Whether is three graphical user interface or command line interface driven. Combining the cloud like experience with the efficiencies of a secure supply chain that meet your needs brings you the best of both worlds. You get Dave off speed with all the security controls to meet the regulations your business lives by. We're talking about more frequent deployments. Faster time to recover from application issues and better code quality, as you can see from our clusters we have worked with were able to tie these processes back to real cost savings, riel efficiency and faster adoption. This all adds up to delivering business value to end users in the overall perceived value. Now let's look at see how we're able to actually build a secure supply chain. Help deliver these sorts of initiatives in our example. Secure Supply chain. We're utilizing doctor desktop to help with consistency of developer experience. Get hub for our source Control Jenkins for a C A C D. Tooling the doctor trusted registry for our secure container registry in the universal control playing to provide us with our secure container run time with kubernetes and swarm. Providing a consistent experience no matter where are clusters are deployed. You work with our teams of developers and operators to design a system that provides a fast, consistent and secure experience for my developers that works for any application. Brownfield or Greenfield monolith or micro service on boarding teams could be simplified with integrations into enterprise authentication services. Calls to get help repositories. Jenkins Access and Jobs, Universal Control Plan and Dr Trusted registry teams and organizations. Cooper down his name space with access control, creating doctor trusted registry named spaces with access control, image scanning and promotion policies. So now let's take a look and see what it looks like from the C I c D process, including Jenkins. So let's start with Dr Desktop from the doctor desktop standpoint, what should be utilizing visual studio code and Dr Desktop to provide a consistent developer experience. So no matter if we have one developer or 100 we're gonna be able to walk through the consistent process through docker container utilization at the development layer. Once we've made our changes to our code will be able to check those into our source code repository in this case, abusing Get up. Then, when Jenkins picks up, it will check out that code from our source code repository, build our doctor containers, test the application that will build the image, and then it will take the image and push it toward doctor trusted registry. From there, we can scan the image and then make sure it doesn't have any vulnerabilities. Then we consign them. So once we signed our images, we've deployed our application to Dev. We can actually test their application deployed in our real environment. Jenkins will then test the deployed application, and if all tests show that is good, will promote the r R Dr and Mr Production. So now let's look at the process, beginning from the developer interaction. First of all, let's take a look at our application as is deployed today. Here, we can see that we have a change that we want to make on our application. So marketing Team says we need to change containerized injure next to something more Miranda's branded. So let's take a look at visual studio coat, which will be using for I D to change our application. So here's our application. We have our code loaded, and we're gonna be able to use Dr Desktop on our local environment with our doctor desktop plug in for visual studio code to be able to build our application inside of doctor without needing to run any command line. Specific tools here is our code will be able to interact with docker, make our changes, see it >>live and be able to quickly see if our changes actually made the impact that we're expecting our application. Let's find our updated tiles for application and let's go and change that to our Miranda sized into next. Instead of containerized in genetics, so will change in the title and on the front page of the application, so that we save. That changed our application. We can actually take a look at our code here in V s code. >>And as simple as this, we can right click on the docker file and build our application. We give it a name for our Docker image and V s code will take care of the automatic building of our application. So now we have a docker image that has everything we need in our application inside of that image. So here we can actually just right click on the image tag that we just created and do run this winter, actively run the container for us and then what's our containers running? We could just right click and open it up in a browser. So here we can see the change to our application as it exists live. So once we can actually verify that our applications working as expected, weaken, stop our container. And then from here, we can actually make that change live by pushing it to our source code repository. So here we're going to go ahead and make a commit message to say that we updated to our Mantis branding. We will commit that change and then we'll push it to our source code repository again. In this case we're using get Hub to be able to use our source code repository. So here in V s code will have that pushed here to our source code repository. And then we'll move on to our next environment, which is Jenkins. Jenkins is gonna be picking up those changes for our application, and it checked it out from our source code repository. So get Hub Notifies Jenkins. That there is a change checks out. The code builds our doctor image using the doctor file. So we're getting a consistent experience between the local development environment on our desktop and then and Jenkins or actually building our application, doing our tests, pushing in toward doctor trusted registry, scanning it and signing our image. And our doctor trusted registry, then 2.4 development environment. >>So let's actually take a look at that development environment as it's been deployed. So here we can see that our title has been updated on our application so we can verify that looks good and development. If we jump back here to Jenkins, will see that Jenkins go >>ahead and runs our integration tests for a development environment. Everything worked as expected, so it promoted that image for production repository and our doctor trusted registry. Where then we're going to also sign that image. So we're signing that. Yes, we have signed off that has made it through our integration tests, and it's deployed to production. So here in Jenkins, we could take a look at our deployed production environment where our application is live in production. We've made a change automated and very secure manner. >>So now let's take a look at our doctor trusted registry where we can see our game Space for application are simple in genetics repository. From here we will be able to see information about our application image that we've pushed into the registry, such as Thean Midge signature when it was pushed by who and then we'll also be able to see the scan results of our image. In this case, we can actually see that there are vulnerabilities for our image and we'll actually take a look at that. Dr Trusted registry does binary level scanning, so we get detailed information about our individual image layers. From here, these image layers give us details about where the vulnerabilities were located and what those vulnerabilities actually are. So if we click on the vulnerability, we can see specific information about that vulnerability to give us details around the severity and more information about what, exactly is vulnerable inside of our container. One of the challenges that you often face around vulnerabilities is how, exactly we would remediate that and secure supply chain. So let's take a look at that and the example that we were looking at the vulnerability is actually in the base layer of our image. In order to pull in a new base layer of our image, we need to actually find the source of that and updated. One of the ways that we can help secure that is a part of the supply chain is to actually take a look at where we get our base layers of our images. Dr. Help really >>provides a great source of content to start from, but opening up docker help within your organization opens up all sorts of security concerns around the origins of that content. Not all images are made equal when it comes to the security of those images. The official images from Docker, However, curated by docker, open source projects and other vendors, one of the most important use cases is around how you get base images into your environment. It is much easier to consume the base operating system layer images than building your own and also trying to maintain them instead of just blindly trusting the content from doctor. How we could take a set >>of content that we find useful, such as those base image layers or content from vendors, and pull that into our own Dr trusted registry using our rearing feature. Once the images have been mirrored into a staging area of our DACA trusted registry, we can then scan them to ensure that the images meet our security requirements and then, based off the scan result, promote the image toe a public repository where we can actually sign the images and make them available to our internal consumers to meet their needs. This allows us to provide a set of curated content that we know a secure and controlled within our environment. So from here we confined our updated doctor image in our doctor trust registry, where we can see that the vulnerabilities have been resolved from a developers point of view, that's about a smooth process gets. Now let's take a look at how we could provide that secure content for developers and our own Dr Trusted registry. So in this case, we're taking a look at our Alpine image that we've mirrored into our doctor trusted registry. Here we're looking at the staging area where the images get temporarily pulled because we have to pull them in order to actually be able to scan them. So here we set up nearing and we can quickly turn it on by making active. Then we can see that our image mirroring will pull our content from Dr Hub and then make it available in our doctor trusted registry in an automatic fashion. So from here, we can actually take a look at the promotions to be able to see how exactly we promote our images. In this case, we created a promotion policy within docker trusted registry that makes it so. That content gets promoted to a public repository for internal users to consume based off of the vulnerabilities that are found or not found inside of the docker image. So are actually users. How they would consume this content is by taking a look at the public to them official images that we've made available here again, Looking at our Alpine image, we can take a look at the tags that exist. We could see that we have our content that has been made available, so we've pulled in all sorts of content from Dr Hub. In this case, we have even pulled in the multi architectural images, which we can scan due to the binary level nature of our scanning solution. Now let's take a look at Len's. Lens provides capabilities to be able to give developers a quick, opinionated view that focuses around how they would want to view, manage and inspect applications to point to a Cooper Days cluster. Lindsay integrates natively out of the box with universal control playing clam bundles so you're automatically generated. Tell certificates from UCP. Just work inside our organization. We want to give our developers the ability to see their applications and a very easy to view manner. So in this case, let's actually filter down to the application that we just deployed to our development environment. Here we can see the pot for application and we click on that. We get instant, detailed feedback about the components and information that this pot is utilizing. We can also see here in Linz that it gives us the ability to quickly switch context between different clusters that we have access to. With that, we also have capabilities to be able to quickly deploy other types of components. One of those is helm charts. Helm charts are a great way to package of applications, especially those that may be more complex to make it much simpler to be able to consume inversion our applications. In this case, let's take a look at the application that we just built and deployed. This case are simple in genetics. Application has been bundled up as a helm chart and has made available through lens here. We can just click on that description of our application to be able to see more information about the helm chart so we can publish whatever information may be relevant about our application, and through one click, we can install our helm chart here. It will show us the actual details of the home charts. So before we install it, we can actually look at those individual components. So in this case, we could see that's created ingress rule. And then it's well, tell kubernetes how to create the specific components of our application. We just have to pick a name space to to employ it, too. And in this case, we're actually going to do a quick test here because in this case, we're trying to deploy the application from Dr Hub in our universal Control plane. We've turned on Dr Content Trust Policy Enforcement. So this is actually gonna fail to deploy because we're trying to deploy application from Dr Hub. The image hasn't been properly signed in our environment. So the doctor can to trust policy enforcement prevents us from deploying our doctor image from Dr Hub. In this case, we have to go through our approved process through our secure supply chain to be able to ensure that we know our image came from, and that meets our quality standards. So if we comment out the doctor Hub repository and comment in our doctor trusted registry repository and click install, it will then install the helm chart with our doctor image being pulled from our GTR, which then has a proper signature, we can see that our application has been successfully deployed through our home chart releases view. From here, we can see that simple in genetics application, and in this case we'll get details around the actual deploy and help chart. The nice thing is that Linds provides us this capability here with home. To be able to see all the components that make up our application from this view is giving us that single pane of glass into that specific application so that we know all the components that is created inside of kubernetes. There are specific details that can help us access the applications, such as that ingress world that we just talked about gives us the details of that. But it also gives us the resource is such as the service, the deployment in ingress that has been created within kubernetes to be able to actually have the application exist. So to recap, we've covered how we can offer all the benefits of a cloud like experience and offer flexibility around dev ups and operations controlled processes through the use of a secure supply chain, allowing our developers to spend more time developing and our operators mawr time designing systems that meet our security and compliance concerns

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation hi I'm Stu minimun and welcome to the cube from our Boston area studios we've been doing a series of CXO leadership discussions talking about how everyone's dealing with the global global endemic I've been welcome program a first-time guest Katy Bullard she is the president of a tile guru of course a cloud guru a online learning company we've had on the cube many times over the years Katy thanks so much thank you so much sue for having me I really appreciate it all right so Katie I remember I saw the in I think the announce was the end of at the beginning of the year your based at the headquarters in Austin you know online you know learning is a huge topic cloud of course you know one of those mega waves that we've been walking a long time and then you know out of nowhere global pandemic you know it's striking us so you know bring us inside you know obviously you know taking a new role in a new organization as it own challenges normally it's like okay what am I going to do for the first 90 days and make that plan tell us you know how were you reacted in how the company has reacted with the koban 19 did you get a chance to look at my 90-day plan dude that was exactly where it was no well let me take you back I'll take you back to kind of why I chose to come to ECG because I think it informs actually what's happening right now as well when I when I was looking for the next opportunity what I look for is I look for two things primarily in a company one is a product that's in a market that's growing really really fast and a product that has raving customer bands and obviously ACG really you know check both of those boxes you think about this is pre Co but if you think about the cloud computing market growing you know 50 60 % a year and the number one challenge for people who are both moving to the cloud or moving to a multi cloud strategy was having enough skilled workers to to do that effectively there really wasn't a better intersection of two you know two who value propositions than what a CG offered which was serving the cloud computing market and skilling up workers in that market fast forward to February you know was interesting I actually went out to Australia offices in mid-february as this was starting to heat up came back just in time I think to not go into quarantine but we very quickly saw the impact and you know this isn't easy for anybody in in any situation but what we are hearing from our customers and from the market is that that move to the cloud is even more important now I think the latest that I saw from the the 2028 odd report said 65 percent of companies are planning a cloud migration 95 percent are of companies are employing a multi cloud strategy so that is accelerating and then of course we're all sitting at home right now and you're getting me in my in my dining room and we have the both learn online versus in person there's no longer in-person training there's no longer events for us to go to lives we're doing that online we also are seeing that you know the way that we use our time is changing so we're not spending hours anymore muting we have a lot of customers who are saying let's use that time instead of muting to learn improve ourselves improve our skills so you know everything is very unpredictable in this environment but we do feel like at ACG our fundamental mission is to help customers get through this to give them the skills that they need so that hopefully as everybody emerges from this later this year they're better positioned to take advantage of the opportunities in front of them ya know you hit on a lot of topics you know so much right now you know remote learning remote work or you know a big discussion the developer world has been looking at that for a long time and you know when I see you know the the the elementary and high school children as well as you know colleges and how they're handling distant learning I was well come on the Cronenberg's brothers you know built something in you know two or three week from your mother's basement Amazon and serverless and they framed millions of people now yeah you know good absolutely translate but it's challenging so I'm curious yes you know and you're working with the team is there anything you're doing to connect to some of the broader audience you know lessons that can be learned as I said you're you know highly scalable you know large scale and you know you have nowhere near the budget of you know these municipalities and colleges yet you do reach you know a very broad audience with some very important skill yes I mean if I think about the actual products itself and why it worked worked so well previously right why the Cronenberg brothers brought to market something that was so beloved but but more importantly why I think it's working so well now is that there was a recognition that we learn these days in bite-sized chunks right most of us don't have four hours a day or three days a week just to sit leave our job and go learn something and so from the very beginning their concept was let's break every single lesson up into these 20 minutes chunks so whether you know I'm on my commute in a previous world or whether I'm you know using some time that I used to spend on the road learning something new I can do it in very digestible forms and in a way that's really engaging to me so I think that model that they've employed from day one is even more valuable now in today's environment I think the other thing is that there was a recognition that we all have different learning styles right we all learn a little bit differently and so whether it's learning in 20 minute chunks so that's learning through video and PowerPoint or whether it's learning hands-on testing things breaking things building things the platform has evolved in a way to enable people no matter where they are in that cloud learning journey whether they're novice that's just getting started and wanting to learn kind of you know the PowerPoint basics like me when I first came on board right of the or a seasoned architect who's trying to get in and build new applications so I think those things are the things that allowed the platform to really resonate with the developer audience for so long and now as we have you know added out of the platform specifically for enterprises where previously you know is for individual developers we now have both I think that's the other thing that is really attractive to large enterprises is the fact that they now right are trying to train thousands of workers at the same time realizing again that every single one of them has a different learning style yeah Katie is as you said before there is you know a broad need or the skill set of cloud computing I'm curious have you seen anything in kind of your customer base either from the enterprise side or individuals is there are there any skill sets that are bubbling up right now that are a critical need or anything that is grown and you know we're curious we're always you know there's some people it's like oh I'm gonna come out of this you know whole experience and you know I love you know work in my home gym and you know learn new languages and become a master baker of sourdough you know me personally I've been really busy so you know I wish I had more spare time travel has definitely reduced thing but it's also given up the time that normally I was gonna you know read a book or you know catch up on raining yeah the sourdough bread is definitely not in my wheelhouse so we well we have seen some really interesting trends actually over the last few months the first one is that we've seen the percentage of our users that are logging in on a daily basis go up about 30 percent so people are taking advantage I think of a little bit of extra time to accelerate their learning the other thing that we are seeing and I was just looking at these stats last week is the kinds of courses and content that are being consumed are changing some of this was happening free covert and some of this was happening post covitz all split those up freako but what we've seen over the last order two 2/4 actually is a pretty significant increase in consumption across multi-cloud skills as you're in particular is seeing about a three times higher increase in consumption than the other two large CCS these although they're all three increasing rapidly so as we think about like the curriculum and our instructors that we're bringing on and what we're building up know historically ACG specifically had grown up in the AWS world but we are responding to that change very very late and in investing in you know a juror GCP and some of the other cloud adjacent courses so that we had been seeing happening over the last couple of quarters most recently what we're seeing is an increase in what i call our beginner or fundamental courses they think that is a direct reflection of people who are looking at this as an opportunity to rescale to set themselves up for a new career i'm so you know our introduction to AWS or introduction to Azure fundamentals or the introduction to DCP those are actually the courses that are increasing the fastest in ranking and anecdotally one of my favorite things to do is to go on LinkedIn or Twitter each day and look at you know what people are saying about ACG and over the last week especially I can't even count the number of folks who've said I'm using my lock down I'm for you know learning or I'm putting my my time and Quarantine to the best use by you know getting trained on ECG and so I think that what we are seeing there is a direct reflection of that alright yeah Katie maybe you can give us a little bit of the update on you know a cloud guru there was the Linux Academy acquisition and if you can share a little bit about this kind of the the the numbers of how many people have gone through your programmed you attract how many people actually get certifications afterwards which I know they need to go to the providers you know pay a fee for that kind of thing yeah we do yeah there's only been a few things happening over here in the last six months right I've got a small acquisition and then you know we're dealing with this now so we acquire Linux Academy in December so actually I came on board about the same time that we acquired the business one of my favorite stories is when I first started talking to Sam and team back in June a cg had about a hundred employees total by the time I was actually accepting an offer in October I think it was 200 employees in total so in a four month span the company had actually doubled we acquired Lenox Academy which was of equivalent size the ACG and so by the end of December we were a 400 person company a company that had been a hundred people know in in the middle of 2019 so 400 people now we are our biggest office is here in Austin we do have a large office in Melbourne Australia which was where the company was originally founded and where Sam is we have an office in London where Ryan is and Linux Academy was actually headquartered right outside of Fort Worth Texas so we've got an office there in Fort Worth as well so it's been amazing to see this company essentially quadruple in size over the last six months everything that goes into scaling a business like that bringing two competitors together integrating the business you know we are in the process of integrating the products and the content and the course dialogues right now so we're excited to bring that market later this year all in the midst of everyone also getting used to this very new and unprecedented environment yeah you know congratulations you know that you know always good to see great growth you know the thing I've noticed is you know ACG just as really goodwill in the community I see the orange shirts at many of the shows I you know right many of the other teams yeah we'll definitely have to get back to you about being on brain feed I was trying to coordinate with my background um one of the other things you know is some of my favorite content over the last few years that we've done the cube has been the serverless cough event so you know any discussion about you know will there be smokers to that or are we just going to need the weight or you know the physical events return before we see those so we actually have just started a new virtual event calendar actually our very first one was yesterday we had almost 3,000 people registering to attend and so it will be a series it's a series of virtual events and webinars that are done in partnership with other leading influencers and practitioners in the industry so expects if anyone's interested you can go online and register for one of the ACG webinars but we'll be having those every two week through the course of this year awesome love that and I guess the last thing Katie there's some other things you've been doing help unity in this need of the pandemic tell us a little bit about that yeah so two things in particular that we've really focused on the first one is across both the Linux Academy and the ACG platforms we have lowered permanently the price of our individual memberships so for individuals from 449 down to 379 we've seen that that has helped enable more people to be able to afford it who otherwise couldn't afford it so that's now in in market the other thing that we're really excited about that we launched this week is a free educational assistance program so we are offering 1,000 subscriptions to ACG for the year so annual subscriptions for people who have been most impacted by kovat so we have a couple of different specific criteria but if you've lost your job due to Ovid and you're in one of the the most heavily impacted industries whether that you know retail or hospitality or travel and are looking to really change careers get into the tech field get your initial certification we do now have a program for that so you go online to our website you're able to apply to that program we launched it yesterday maybe two days ago and I know we already have hundreds of applications so we're really excited to offer that all right well we'll make sure to get this out to the community is build out of that all right Katie thanks so much really pleasure to act up with you and I'm glad Congrats on all the progress thank you so much - thanks for having me alright serverless absolutely one of the topics I've been personally enjoying digging into the last couple years hope you've enjoyed I'm an attorney I'm sue minimun and as always thank you for watching thank you [Music]

>> Live from Orlando, Florida It's the Cube covering Enterprise Connect twenty nineteen brought to you by five nine. >> Hi. Welcome back to the Q. We are live at Enterprise Connect. Twenty nineteen. Can you hear the buzz behind Stew, Minutemen and me? It's party time. It's five o'Clock kicking things off, welcoming a couple of guests to our program this afternoon. We've got Blair Pleasant, president and principal analyst at Confusion and co founder of BC Strategies, and Michael Rose, the director brand and corporate communications from five nine. Welcome to the Q. Thank you. >> Good afternoon. >> Welcome to the party. >> I know. With the beer and the wine for us, >> we think it's momentarily momentary. So you have been coming to Enterprise Connect about the last ten years or so. A little bit of an overview about what you're doing at this year's easy. >> Sure, So I'm going to be doing for different sessions here. Esso. On Wednesday, I'm going to be giving a presentation. Well, one is going to be to the Channel partners who are selling, you see, telling them about why they should be selling Contact Center and all the wonders about contact center and customer experience. And I'Ll also be doing a session on unified communications end user adoption, and I'm gonna have a panel of and users who were going to tell about their talk about their adoption programs on Thursday. I'm doing a session on collaboration about team collaboration and how to migrate and things to do there. And then I'm participating in the last note where a bunch of analysts consultants, they're gonna basically wrap up the show and talk about, you know, key findings and key messages, and it's going to really good discussion. >> You have a very busy week ahead. I'm curious as to when I were chatting earlier today about the evolution of this event over the last twenty eight twenty nine years, but also paralleling the massive evolution of communications and collaborations, the rise of the empowered consumers who wants to be able to have a conversation on any channel at any time and have our issues resolved right away. Give us your perspective cause you have a very full week here about some of the turns that you you've seen in the last year that you're looking forward to helping customers understand. You talked about selling, you see, so contact centers of service. Yes. >> So when it comes to unified communications, as I mentioned one thing that I've been really focused on is user adoption because companies will buy technology and they'LL deploy technology. But they don't necessarily. That doesn't mean that uses air actually going to be using it. So that's one thing that they really have to focus on. And then when we turn to the contact center side, it's all about customer experience. And in fact, Michael and I have been doing a lot of work in this area. And so we've been hearing the term customer experience. You know, c X. But what's also important is employees or agent experience and a X, as we're calling it. So getting the agent involved also and making sure that they've got the tools that they need to help them do a really good job. >> Alright, so Michael, you have brand and you did a very nice job bringing us the five nine mugs. Yes, there's water in them, but this customer service index can you bring us inside what you're working on, what we're Blair's been involved and let's get into that. >> It's basically an annual study that we've been doing now for two years, and we plan to continue in the first part of it looks at what the consumers are saying about why they raid a customer experience the way they do want that, what's important to them and, more importantly, what turns them off. And as we found in when we did the analytics with Blair is a bad customer engagement. They're likely to leave you and not to business anymore. We were talking earlier about consumers now have voice and choice. You know, they they've got voice through social media to complain, and they will leave and find another brand to partner with. And so that's sort of a key finding around. What is it the people want? And it's basically a quick response. Know who I am and engage me the way I want to be engaged. >> But what was interesting is they want a quick response. But they're also willing to spend more time on the phone or whatever in an interaction talking to an agent if it means that they're going to get the response that they need and get the information that they need to get their problem solved. So speed is important when it comes to getting an agent on the phone or getting that agent, but then they're willing to take the time if it means I'm going to get my problems solved. Do >> you think that one of the things we chatted about with Ryan can? The CMO of five nine earlier today is is the fact that five nine has five billion recorded customer conversations and we were chatting, I think, also with Jonathan Rosenberg. It's an expectation, right? We call contact Center for whatever product or service or whatnot that we're having an issue with her were enquiring about. And you hear that? So there's an expectation that is going to be reported. How did cos actually glean insight from that data? Because I'm there, I'LL tell you, I never think when I'm on the phone call, I have a problem to resolve. And I don't think that they're recording my conversation to help me and all the customers that probably have the same problem. So I thought that was an interesting sort of way of of looking at it. But it's also interesting that that you found that people are willing to spend more time if the value to them is greater. >> Yep, absolutely. And we're finding that companies are using that data. You know, we hear about Big Data Analytics. So analytics is really the big thing, you know, looking at the the whole picture, getting that holistic view of what's working, what isn't working. And then turning that also into I talked before about the agent experience using this to improve what the agent is doing and how the agent is interacting with the customer. >> And that's that's probably a good build to the next part of the study, which is a business decision maker. And so we survey them to see other, any parallels and what they're thinking compared to the consumer on one of the probably most disappointing findings issue and we're doing a webinar on this next week is the lowest thing they write is employeessatisfaction. So they look ATT, you know, is that the right product we're selling? Do we have the right tools but actually looking after the agent, all the employees that ranks the least on their list of priorities, which is quite distressing and sad. But >> the good news is that they did great customer satisfaction very highly, So when it came when we were looking at what's really important to your business and to growing your revenues. Customer satisfaction was very important. So we're happy about that. >> Which it has to be directly tied to the agent experience like, for example, making sure that an agent has is empowered to make a decision. But they had to have the information. They have to have the content to be delivered through the right channels. So that's interesting finding that you are you expecting to hear on DH talk Claremore this week with companies to say, This is why Employeessatisfaction has got to move up the rights because it is directly tied to customer satisfaction. >> So I've been talking about that for a long time, and it's so important, and I think cos they're starting to get it. And we're also seeing more tools like a I. You know, that's really going to be used to help provide the information to the agents and help them do that. Better job. >> One of things. It's always interesting when you have these annual studies to see what is actually changing over time. You know, I've got background on telecommunications, you know, we talk about Omni Channel today. We talked about, you know, unified messaging twenty years ago, we talked about a today. We talked about intelligence and data decades ago. So what's changing? What? Staying the same. Any insight that you're getting, As as we've been moving with the survey Overtime >> voices still K as in, people want to make a phone call if they need help and believe it or not, that's across all age groups that even tops out number one for Millennials, which surprised you. And I know Blake. You did a little test group at home with that? >> Yeah, I had my twenty somethings. They had some friends over. And I asked him, You know, when you have a problem and you need to call contact customer service, what do you do? It? And the first thing they do is try to do self service, you know, try to figure it out on their own. You know, Google it go to YouTube or whatever, but then, if they can't find the problem, they will pick up the phone and called a contacts and, you know, call customer service and you would think that twentysomethings wouldn't do that. But they know that if it's something important and they need to get that information right away or solve that problem right away. They pick up the phone, and they also do chat and email. But the study found that chat actually went down this year, which were kind of surprised about so the use of email went up. But these of chat went down >> Any thoughts as to why that might be going down? >> I think it's because companies haven't been providing that good experience. So even though they're offering chat, it's it's not optimized. So sometimes you know when you're doing shots, you know you're on a website. You doing chat, you can tell when the agent is talking to like ten other people at the same time. So it's it's really frustrating. So I think companies have the technology, but they're not doing it the right way. >> I mean, I know I've had Sometimes you get a chat and I'm like, I'm not talking to a person. It's a chat, Bott. Oh, is this some outsourced chat that maybe doesn't have the skill level that I need as opposed to? If I pick up the phone, I know most of the time that agent I'm going to get either can answer my question or can escalate to the person that, >> interestingly to the one that's right down near the bottom is social media and it hasn't moved for two years. So we're not saying now that could be a chicken and the egg. Is it because companies are not offering it? So therefore, I don't know. I can use it or don't people want to use it on? We had a theory cause. Social Media's had a bit of a rocky ride in the last year with data and privacy and everything else. So maybe consumers just don't trust it yet. And there are other channels, like email as you said, that we've seen increasing. >> But if customers are unhappy about something, they're going to go on. Social media >> is the first thing I do. When you were saying that it was surprising it was low, because if I at a recent experience with an S B and wasn't getting five minutes with a robot on the phone, couldn't get all I wanted was a tech to come out to my house to fix something, Then I had to have somebody call me back and verify. Have you do the exact same thing I've been through this, so I went to Twitter to escalate that. So that's how I think about that. I appreciate that, they responded, But it's I guess it's a couple of a number of interesting things that you guys have brought up today that surprised you. The X factor being lower millennials actually wanting to talk to human. That's good. But also this the fact that people aren't using social as much as maybe you would've thought, or they may be. They don't release. I can't. Or maybe it's to customers not have appropriate affected social listening programs to respond to the volume. >> So that's the chicken and egg thing Michael was talking about. A lot of companies don't offer social as a channel because they think that customers don't want to use it. The customers aren't using it because they don't realize that companies are offering it. >> So, Claire, while we have you, you've got a good perspective on this space. What's differentiating the leaders in the space from some of the laggards in this space? >> Oh, that's a good question. I think a lot of it has to do with again the Focus on the customer experience, you know? So if you're talking about the vendors, the vendors that are succeeding are the ones that really do. Look at the customer, not just the technology. So so many companies could do technology. The technology is the easy part, its doing it right. It's really making that difference and making things simple, making things unified, making it not complex for customers. Because right now things are just so complex. You have to go no to so many different places. Teo, to make things work. So the more you can make things seamless and simple. I think that's what's really separating. The winners from the losers >> will make Michael Maybe you can elaborate on, you know, delivering a integrated connected on the channel experience. But I think there's still some of maturation curve that it's on, whereby I might have an expectation as a consumer than I'm goingto go through chat or email or another channel. And then if I go through Twitter or social, I'm hoping that this conversation is connected. Where can five nine help customers across industries to really integrate and deliver Omni Channel? >> I think the first thing is the cloud because moving to the cloud enables you to move quickly is a business. And as we were saying today, the software updates all the time and it's easy. It's like your phone, you just downloading away you go. So it's It's the cloud first to get to the data, and we talked about that before, too, and growing. Our CEO calls it the dark data because no one's using it. And you need to mind that data to get the inside, because then the system will start directing the consumer based on what the intelligence is telling them, irrespective of which channel they come through on. Do you really want an experience where I've done tweeting away with a company? And they said, Well, privately email you now because we want to take it off line and then they'LL say, Well, no, now we need to call, but it's it's fluid. All the data and all the information is passed through that communication, So it's seamless for me, the consumer, and it's more rewarding for the agent because they can actually get to the core issue for the customer and resolve it. >> That's a customer there. Maybe Blair, This is a question for you. How does a customer take what's probably traditional silos of customer experiences and culturally evolved as a business to be able to deliver what Michael was talking about? I mentioned that those Silas and that kind of cultural disparity might be kind of a challenge for an organisation to pivot as quickly as they need to when customer lifetime value was on the line. >> Yeah, and it's definitely been a challenge for a lot of companies, but they know that they have to get there. So I think even though some of them might be resistant, they realised that to get the results that they need, they really do have to do that. But it's a cultural change, and you asked before about what's separating some of the winners from losers. I think that's a big part of it is being able to make that change >> player, you know, as I was getting ready for the show, there's general belief that customers are embracing of the cloud. It's no longer we're no longer in the evangelization phases. I've heard five nine, but we're in adoption. I'm curious player. When it comes to a I, though our users ready. Everybody we talk about these technologies are going to be infused with aot. There's some, you know, fear. Sometimes out there is like the robots, or they're going to take my personal data or anything like that. What do you see out there and what should we be aware of and where do we need to go? As an industry, I want to come stay. I So >> as far as consumers, they do need to be worried. You know, they're definitely issues about privacy, and you know what's going to happen with the information. But I think user shouldn't really know that there's a I involved on, and that's also debate we have, like, if you're interacting with the pot, you know, if you're doing a chat, do you know if it's a body or an agent? So some companies, you know, make it clear, you know? Hi. This is, you know, Joe the Bob, But other companies don't. So then you have to say I and I've had these experiences are youa, but no, I am a real person. Okay, prove to me your real person. So it's so it's really interesting. So some companies feel that customers are more open if they're talking to a bomb. And in certain industries, like if it's healthcare or finance, people are going to be more open if it's about because they don't want to share their personal information with a live person. But if it's a computer is like okay, I can share the information. So it were very much in early days, so we don't really I have the experience to drawn yet. So let's talk about this again next year. >> Well, Blair, Michael, thank you so much for joining student. Be on the Cube this afternoon and sharing spending some time since you have such a busy week where we appreciate your insights on the event on enterprise, collaboration and communication. And we appreciate your time. Thank you for soon. Minutemen. I'm Lisa Martin. You're watching the Cube

(exciting, upbeat music) >> (Announcer) Live from Orlando, Florida. It's theCUBE, covering ServiceNow Knowledge '17. Brought to you by ServiceNow. >> We're back. Dave Vellante with Jeff Frick. This is theCube and we're here at ServiceNow Knowledge '17. Stanley Toh is here, he's the Global IT Director at semiconductor manufacturer Broadcom. Stanley, thanks for coming to theCUBE. >> Nice to be here. >> So, semiconductor, hot space right now. Things are going crazy and it's a good market, booming. That's good, it's always good to be in a hot space. But we're here at Knowledge. Maybe talk a little bit about your role, and then we'll get into what you're doing with ServiceNow. >> Sure. You're right. Semiconductor is booming. But we don't do anything sexy. Everything is components that go into your iPhones and stuff like that. They do the sexy stuff. We do the thing that make it work. So, I'm the what we call the Enterprise and User Services Director, so basically anything that touches the end user, from the help desk to collaboration to your PC support desk, everything is under. Basically anything that touches the end user, even onboarding, and then, now with the latest, we actually moved our old customer support portal to even ServiceNow CSM. >> Okay, so what led you to ServiceNow? Maybe take us back, and take us through the before and the after. >> Okay. Broadcom Limited, before we changed our name to Broadcom, we were Avago Technologies. We are very cloud centric. Anything that we can move to the cloud, we moved to the cloud. So we were the first multi-billion dollar company to move to Google, back in 2007. That was 10 years ago. And then we never stopped since. We have Opta, we have Workday. And if you look at it, all this cloud technology works so well with ServiceNow. And ServiceNow is a platform that has all the API and connectors to all these other cloud platforms. So, when we were looking and evaluating, first as just the ITSM replacement, we selected ServiceNow because of the ease of integration. But as we get into ServiceNow, and as we learn ServiceNow, we found that it's not just an ITSM platform. You can use it for HR, for finance, for legal, for facilities. Recently, probably about six months ago, we launched the HR module. And then three weeks ago, we went live with a CSM portal for the external customer. >> When you say you go back to 2007 with Google, you're talking about what, Google Docs? >> Everything. >> Dave: Everything. >> Email, calendar, docs, sites, Drive, but it was unknown. >> Dave: All the productivity stuff. >> Everything. >> Dave: Outsourced stuff. >> They were unknown then, >> Jeff: Right, right, right. >> And it's a risk. >> So what was the conversation to take that risk? Because obviously there was a lot of concern at the enterprise level on some of these cloud services beyond test/dev in the early days. Obviously you made the right bet, it worked out pretty well. (Stanley laughing) But I'm curious, what were the conversations and why did you ultimately decide to make that bet? >> Okay. So 2007 was just after the downturn. >> Jeff: Right. >> So everyone was looking at cost, at supportability. But at the same time, the mobile phone, the smart phone is just exploding in the market. So we want something that is very flexible, very scalable, and very easy to integrate, plus also give you mobility. So that's why we went with Google as the first cloud platform, but then we started adding. So right now, we can basically do everything on your smart phone. We have Opta as our single sign-on. From one portal, I go everywhere. >> Dave: Okay, so that's good. So you talked about some of the criteria for the platform. How has that affected how you do business, how you do IT business? >> See, IT has always been looked upon as a cost center. And we are always slow, legacy system, hard to use, we don't listen to you. (Jeff laughing) >> Dave: What do those guys do? >> You know, why are we paying those guys, right? And then you look at all the consumer stuff. They are sexy, they are mobile, they have pretty pictures. Now all your internal users want the same experience. So, the experience has changed. The old UNIX command key doesn't work anymore. They want something touch, GUI, mobile. They want the feel, the color, you know. >> That might be the best description (Stanley laughing) of the consumerization of IT, Dave, that we've ever had on theCUBE. >> It's really honest. Coming from an IT person, it is, it is honest. And now you've driven ServiceNow into other areas beyond IT. >> Stanley: Yes. >> You mentioned HR. >> HR. We went live six months ago. >> Okay. And these other areas, are you thinking about it, looking at it, or? >> So we are also looking with legal, because they have a lot of legal documents and NDAs and stuff like that. And ServiceNow have a very nice integration to DocuSign and Vox. So we are looking at that. But the latest one, we went live three weeks ago, is the CSM, the customer support management portal. And that one actually replaced one of our legacy system that has a stack of sixteen application running. And we collapsed that, and went live on ServiceNow CSM three weeks ago. >> And what has been, two impacts - the business impact, and, I'm curious, is it the culture impact. You sort of set it up as the attitude. We had fun with it, but it's true. What's the business impact? And what has the cultural impact been? >> The last few years, we have been doing a lot of acquisition. So we have been bringing in a lot of new BU's. Business units. And they want things to move fast, and we want to integrate them into one brand. So speed and agility is key when you do acquisitions. So that's why we are moving into a platform where we can integrate all these new companies easily. We found that in ServiceNow and we can integrate them. So for example, when we acquired Broadcom Corporation, they have 18,000 employees. We onboarded them on day one, and usually when you do an acquisition, they don't give you the employee information until the last minute. Two days, all I need, is to bring them all on, onboarded into my collaboration suite. I only need two days of the information, and on day one, Turn it on, they are live. Their information is in, they have an email account. All their information is in ServiceNow. They call one help desk, they call our help desk, they get all the help and services. So it's fully integrated on day one itself. >> And you guys also own LSI now, right? >> Yes, LSI. >> Emulex? >> Emulex, PLX. >> PLX. >> The latest acquisition is Brocade, which we will close in the summer. And then, the rumored Toshiba NAND business. So, yeah, we are doing a lot of acquisitions. >> Yeah, quite a roll-up there. >> Correct. So as you can see, they are all very different companies. So when they come in, they have different culture. They have different workflow, they have different processes. But if you integrate them into a platform that we are very familiar right now, it's the consumerized look and feel, it's very easy to bring them in. >> And that is the cultural change that has occurred. >> Yes, it's a huge, >> So do people love IT now? >> They still hate IT. (Jeff and Dave laughing) They still say iT is a cost center. But right now, they are coming around. They see that we are bringing value to them. So right now, IT is just not to provide you the basic. IT is to enable the business to be better and more competitive. >> A true partner for the business. >> Yes, correct. >> Stanley, thanks very much for coming to theCUBE. It was great to hear your story, we appreciate it. >> Stanley: Thanks for having me. >> You're welcome. All right, keep it right there, buddy. We'll be back with our next guest. This is theCUBE, we're live from ServiceNow Knowledge '17. We'll be right back. (upbeat music)

>> Welcome everyone. Thank you for coming to the Intel AI lounge and joining us here for this economist world event. My name is Jack. I'm the chief architect of our autonomist driving solutions at Intel and I'm very happy to be here and to be joined by an esteemed panel of colleagues who are joining to, I hope, engage you all in a frayed dialogue and discussion. There will be time for questions as well, so keep your questions in mind. Jot them down so you ask them to us later. So first, let me introduce the panel. Next to me we have Michelle, who's the co-founder and CEO of Fine Mind. She just did an interview here shortly. Fine Mind is a company that provides a technology platform for retailers and brands that uses artificial intelligence as the heart of the experiences that her company's technology provides. Joe from Intel is the head of partnerships and acquisitions for artificial intelligence and software technologies. He participated in the recent acquisition of Movidius, a computer vision company that Intel recently acquired and is involved in a lot of smart city activities as well. And then finally, Sarush, who is data scientist by training, but now has JDA labs, which is researching emerging technologies and their application in the supply chain worldwide. So at the end of the day, the internet things that artificial intelligence really promises to improve our lives in quite incredible ways and change the way that we live and work. Often times the first thing that we think about when we think about AI is Skynet, but we at Intel believe in AI for good and that there's a lot of things that can happen to improve the way people live, work, and enjoy life. So as things in the Internet, as things become connected, smart, and automated, artificial intelligence is really going to be at the heart of those new experiences. So as I said my role is the architect for autonomous driving. It's a common place when people think about artificial intelligence, because what we're trying to do is replace a human brain with a machine brain, which means we need to endow that machine with intelligent thoughts, contexts, experiences. All of these things that sort of make us human. So computer vision is the space, obviously, with cameras in your car that people often think about, but it's actually more complicated than that. How many of us have been in a situation on a two lane road, maybe there's a car coming towards us, there's a road off to the right, and you sort of sense, "You know what? That car might turn in front of me." There's no signal. There's no real physical cue, but just something about what that driver's doing where they're looking tells us. So what do we do? We take our foot off the accelerator. We maybe hover it over the brake, just in case, right? But that's intelligence that we take for granted through years and years and years of driving experience that tells us something interesting is happening there. And so that's the challenge that we face in terms of how to bring that level of human intelligence into machines to make our lives better and richer. So enough about automated vehicles though, let's talk to our panelists about some of the areas in which they have expertise. So first for Michelle, I'll ask... Many of us probably buy stuff online everyday, every week, every hour, hourly delivery now. So a lot has been written about the death of traditional retail experiences. How will artificial intelligence and the technology that your company has rejuvenate that retail experience, whether it be online or in the traditional brick and mortar store? >> Yeah, excuse me. So one of the things that I think is a common misconception. You hear about the death of the brick and mortar store, the growth of e-commerce. It's really that e-commerce is beating brick and mortar in growth only and there's still over 90% of the world's commerce is done in physical brick and mortar store. So e-commerce, while it has the growth, has a really long way to go and I think one of the things that's going to be really hard to replace is the very human element of interaction and connection that you get by going to a store. So just because a robot named Pepper comes up to you and asks you some questions, they might get you the answer you need faster and maybe more efficiently, but I think as humans we crave interaction and shopping for certain products especially, is an experience better enjoyed in person with other people, whether that's an associate in the store or people you come with to the store to enjoy that experience with you. So I think artificial intelligence can help it be a more frictionless experience, whether you're in store or online to get you from point A to buying the thing you need faster, but I don't think that it's going to ever completely replace the joy that we get by physically going out into the world and interacting with other people to buy products. >> You said something really profound. You said that the real revolution for artificial intelligence in retail will be invisible. What did you mean by that? >> Yeah, so right now I think that most of the artificial intelligence that's being applied in the retail space is actually not something that shoppers like you and I see when we're on a website or when we're in the store. It's actually happening behind the scenes. It's happening to dynamically change the webpage to show you different stuff. It's happening further up the supply chain, right? With how the products are getting manufactured, put together, packaged, shipped, delivered to you, and that efficiency is just helping retailers be smarter and more effective with their budgets. And so, as they can save money in the supply chain, as they can sell more product with less work, they can reinvest in experience, they can reinvest in the brand, they can reinvest in the quality of the products, so we might start noticing those things change, but you won't actually know that that has anything to do with artificial intelligence, because not always in a robot that's rolling up to you in an aisle. >> So you mentioned the supply chain. That's something that we hear about a lot, but frankly for most of us, I think it's very hard to understand what exactly that means, so could you educate us a bit on what exactly is the supply chain and how is artificial intelligence being implied to improve it? >> Sure, sure. So for a lot of us, supply chain is the term that we picked up when we went to school or we read about it every so often, but we're not that far away from it. It is in fact a key part of what Michelle calls the invisible part of one's experience. So when you go to a store and you're buying a pair of shoes or you're picking up a box of cereal, how often do we think about, "How did it ever make it's way here?" We're the constituent components. They probably came from multiple countries and so they had to be manufactured. They had to be assembled in these plants. They had to then be moved, either through an ocean vessel or through trucks. They probably have gone through multiple warehouses and distribution centers and then finally into the store. And what do we see? We want to make sure that when I go to pick up my favorite brand of cereal, it better be there. And so, one of the things where AI is going to help and we're doing a lot of active work in this, is in the notion of the self learning supply chain. And what that means is really bringing in these various assets and actors of the supply chain. First of all, through IOT and others, generating the data, obviously connecting them, and through AI driving the intelligence, so that I can dynamically figure out the fact that the ocean vessel that left China on it's way to Long Beach has been delayed by 24 hours. What does that mean when you go to a Foot Locker to buy your new pair of shoes? Can I come up with alternate sourcing decisions, so it's not just predicting. It's prescribing and recommending as well. So behind the scenes, bringing in a lot of the, generating a lot of the data, connecting a lot of these actors and then really deriving the smarts. That's what the self learning supply chain is all about. >> Are supply chains always international or can they be local as well? >> Definitely local as well. I think what we've seen over the last decades, it's kind of gotten more and more global, but a lot of the supply chain can really just be within the store as well. You'd be surprised at how often retailers do not know where their product is. Even is it in the front of the store? Is it in the back of the store? Is it in the fitting room? Even that local information is not really available. So to have sensors to discover where things are and to really provide that efficiency, which right now doesn't exist, is a key part of what we're doing. >> So Joe, as you look at companies out there to partner or potentially acquire, do you tend to see technologies that are very domain specific for retail or supply chain or do you see technologies that could bridge multiple different domains in terms of the experiences we could enjoy? >> Yeah, definitely. So both. A lot of infant technologies start out in very niched use cases, but then there are technologies that are pervasive across multiple geographies and multiple markets. So, smart cities is a good way to look at that. So let's level set really quick on smart cities and how we think about that. I have a little sheet here to help me. Alright, so, if anybody here played Sim City before, you have your little city that's a real world that sits here, okay? So this is reality and you have little buildings and cars and they all travel around and you have people walking around with cell phones. And what's happening is as we develop smart cities, we're putting sensors everywhere. We're putting them around utilities, energies, water. They're in our phones. We have cameras and we have audio sensors in our phones. We're placing these on light poles, which is existing sustaining power points around the city. So we have all these different sensors and they're not just cameras and microphones, but they're particulate sensors. They're able to do environmental monitoring and things like that. And so, what we have is we have this physical world with all these sensors here. And then what we have is we've created basically this virtual world that has a great memory because it has all the data from all the sensors and those sensors really act as ties, if you think of it like a quilt, trying a quilt together. You bring it down together and everywhere you have a stitch, you're stitching that virtual world on top of the physical world and that just enables incredible amounts of innovation and creation for developers, for entrepreneurs, to do whatever they want to do to create and solve specific problems. So what really makes that possible is communications, connectivity. So that's where 5G comes in. So with 5G it's not just a faster form of connectivity. It's new infrastructure. It's new communication. It includes multiple types of communication and connectivity. And what it allows it to do is all those little sensors can talk to each other again. So the camera on the light pole can talk to the vehicle driving by or the sensor on the light pole. And so you start to connect everything and that's really where artificial intelligence can now come in and sense what's going on. It can then reason, which is neat, to have computer or some sort of algorithm that actually reasons based on a situation that's happening real time. And it acts on that, but then you can iterate on that or you can adapt that in the future. So if we think of an actual use case, we'll think of a camera on a light post that observes an accident. Well it's programmed to automatically notify emergency services that there's been an accident. But it knows the difference between a fender bender and an actual major crash where we need to send an ambulance or maybe multiple firetrucks. And then you can create iterations and that learns to become more smart. Let's say there was a vehicle that was in the accident that had a little yellow placard on it that said hazard. You're going to want to send different types of emergency services out there. So you can iterate on what it actually does and that's a fantastic world to be in and that's where I see AI really playing. >> That's a great example of what it's all about in terms of making things smart, connective, and autonomous. So Michelle as somebody who has founded the company and the space with technology that's trying to bring some of these experiences to market, there may be folks in the audience who have aspirations to do the same. So what have you learned over the course of starting your company and developing the technology that you're now deploying to market? >> Yeah, I think because AI is such a buzz word. You can get a dot AI domain now, doesn't mean that you should use it for everything. Maybe 7, 10, 15 years ago... These trends have happened before. In the late 90s, it was technology and there was technology companies and they sat over here and there was everybody else. Well that not true anymore. Every company uses technology. Then fast forward a little bit, there was social media was a thing. Social media was these companies over here and then there was everybody else and now every company needs to use social media or actually maybe not. Maybe it's a really bad idea for you to spend a ton of money on social media and you have to make that choice for yourself. So the same thing is true with artificial intelligence and what I tell... I did a panel on AI for Adventure Capitalists last week, trying to help them figure out when to invest and how to evaluate and all that kind of stuff. And what I would tell other aspiring entrepreneurs is "AI is means to an end. "It's not an end in itself." So unless you're a PH.D in machine learning and you want to start an AI as a service business, you're probably not going to start an AI only company. You're going to start a company for a specific purpose, to solve a problem, and you're going to use AI as a means to an end, maybe, if it makes sense to get there, to make it more efficient and all that stuff. But if you wouldn't get up everyday for ten years to do this business that's going to solve whatever problem you're solving or if you wouldn't invest in it if AI didn't exist, then adding dot AI at the end of a domain is not going to work. So don't think that that will help you make a better business. >> That's great advice. Thank you. Surash, as you talked about the automation then of the supply chain, what about people? What about the workers whose jobs may be lost or displaced because of the introduction of this automation? What's your perspective on that? >> Well, that's a great question. It's one that I'm asked quite a bit. So if you think about the supply chain with a lot of the manufacturing plants, with a lot of the distribution centers, a lot of the transportation, not only are we talking about driverless cars as in cars that you and I own, but we're talking about driverless delivery vehicles. We're talking about drones and all of these on the surface appears like it's going to displace human beings. What humans used to do, now machines will do and potentially do better. So what are the implications around human beings. So I'm asked that question quite a bit, especially from our customers and my general perception on this is that I'm actually cautiously optimistic that human beings will continue to do things that are strategic. Human beings will continue to do things that are creative and human being will probably continue to do things that are truly catastrophic, that machines simply have not been able to learn because it doesn't happen very often. One thing that comes to mind is when ATM machines came about several years ago before my time, that displaced a lot of teller jobs in the banking industry, but the banking industry did not go belly up. They found other things to do. If anything, they offered more services. They were more branches that were closed and if I were to ask any of you now if you would go back and not have 24/7 access to cash, you would probably laugh at me. So the thing is, this is AI for good. I think these things might have temporary impact in terms of what it will do to labor and to human beings but I think we as human beings will find bigger, better, different things to do and that's just in the nature of the human journey. >> Yeah, there's definitely a social acceptance angle to this technology, right? Many of us technologists in the room, it's easier for us to understand what the technology is, how it works, how it was created, but for many of our friends and family, they don't. So there's a social acceptance angle to this. So Michelle as you see this technology deployed in retail environments, which is a space where almost every person in every country goes, how do you think about making it feel comfortable for people to interact with this kind of technology and not be afraid of the robots or the machines behind the curtain. >> Yeah, that's a great question. I think that user experience always has to come first, so if you're using AI for AI's sake or for the cool factor, the wow factor, you're already doing it wrong. Again, it needs to solve a problem and what I tend to tell people who are like, "Oh my God. AI sounds so scary. "We can't let this happen." I'm like, "It's already happening "and you're already liking it. "You just don't know "because it's invisible in a lot of ways." So if you can point of those scenarios where AI has already benefited you and it wasn't scary because it was a friendly kind of interaction, you might not even have realized it was there versus something that looks so different and... Like panic driving. I think that's why the driverless car thing is a big deal because you're so used to seeing, in America at least, someone on the left side of the car in the front seat. And not seeing that is like, woah, crazy. So I think that it starts with the experience and making it an acceptable kind of interface or format that doesn't give you that, "Oh my God. Something is wrong here," kind of feeling. >> Yeah, that's a great answer. In fact, it reminds me there was this really amazing study by a Professor Nicholas Eppily that was published in the journal of social psychology and the name of this study was called A Mind In A Machine. And what he did was he took subjects and had a fully functional automated vehicle and then a second identical fully functional automated vehicle, but this one had a name and it had a voice and it had sort of a personality. So it had human anthropomorphics characteristics. And he took people through these two different scenarios and in both scenarios he's evil and introduced a crash in the scenario where it was unavoidable. There was nothing going to happen. You were going to get into an accident in these cars. And then afterwards, he pulled the subjects and said, "Well, what did you feel about that accident? "First, what did you feel about the car?" They were more comfortable in the one that had anthropomorphic features. They felt it was safer and they'd be more willing to get into it, which is not terribly surprising, but the kicker was the accident. In the vehicle that had a voice and a name, they actually didn't blame the self-driving car they were in. They blamed the other car. But in the car that didn't have anthropomorphic features, they blamed the machine. They said there's something wrong with that car. So it's one of my favorite studies because I think it does illustrate that we have to remember the human element to these experiences and as artificial intelligence begins to replace humans, or some of us even, we need to remember that we are still social beings and how we interact with other things, whether they be human or non-human, is important. So, Joe, you talk about evaluating companies. Michelle started a company. She's gotten funding. As you go out and look at new companies that are starting up, there's just so much activity, companies that just add dot AI to the name as Michelle said, how do you cut through the noise and try to get to the heart of is there any value in a technology that a company's bringing or not? >> Definitely. Well, each company has it's unique, special sauce, right? And so, just to reiterate what Michelle was talking about, we look for companies that are really good at doing what they do best, whatever that may be, whatever that problem that they're solving that a customer's willing to pay for, we want to make sure that that company's doing that. No one wants a company that just has AI in the name. So we look for that number one and the other thing we do is once we establish that we have a need or we're looking at a company based on either talent or intellectual property, we'll go in and we'll have to do a vetting process and it takes a whole. It's a very long process and there's legal involved but at the end of the day, the most important thing for the start up to remember is to continue doing what they do best and continue to build upon their special sauce and make sure that it's very valuable to their customer. And if someone else wants to look at them for acquisition so be it, but you need to be meniacally focused on your own customer. That's my two cents. >> I'm thinking again about this concept of embedding human intelligence, but humans have biases right? And sometimes those biases aren't always good. So how do we as technologists in this industry try to create AI for good and not unintentionally put some of our own human biases into models that we train about what's socially acceptable or not? Anyone have any thoughts on that? >> I actually think that the hype about AI taking over and destroying humanity, it's possible and I don't want to disagree with Steven Hawking as he's way smarter than I am. But he kind of recognizes it could go both ways and so right now, we're in a world where we're still feeding the machine. And so, there's a bunch of different issues that came up with humans feeding the machine with their foibles of racism and hatred and bias and humans experience shame which causes them to lash out and what to put somebody else down. And so we saw that with Tay, the Microsoft chatbot. We saw that with even Google's fake news. They're like picking sources now to answer the question in the top box that might be the wrong source. Ads that Google serves often show men high paying jobs, $200,000 a year jobs, and women don't get those same ones. So if you trace that back, it's always coming back to the inputs and the lens that humans are coming at it from. So I actually think that we could be in a way better place after this singularity happens and the machines are smarter than us and they take over and they become our overlords. Because when we think about the future, it's a very common tendency for humans to fill in the blanks of what you don't know in the future with what's true today. And I was talking to you guys at lunch. We were talking about this harbored psychology professor who wrote a book and in the book he was talking about how 1950s, they were imagining the future and all these scifi stories and they have flying cars and hovercrafts and they're living in space, but the woman still stays at home and everyone's white. So they forgot to extrapolate the social things to paint the picture in, but I think when we're extrapolating into the future where the computers are our overlords, we're painting them with our current reality, which is where humans are kind of terrible (laughs). And maybe computers won't be and they'll actually create this Utopia for us. So it could be positive. >> That's a very positive view. >> Thanks. >> That's great. So do we have this all figured out? Are there any big challenges that remain in our industries? >> I want to add a little bit more to the learning because I'm a data scientist by training and a lot of times, I run into folks who think that everything's been figured out. Everything is done. This is so cool. We're good to go and one of the things that I share with them is something that I'm sure everyone here can relate to. So if a kindergartner goes to school and starts to spell profanity, that's not because the kid knows anything good or bad. That is what the kid has learned at home. Likewise, if we don't train machines well, it's training will in fact be biased to your point. So one of the things that we have to kep in mind when we talk about this is we have to be careful as well because we're the ones doing the training. It doesn't automatically know what is good or bad unless that set of data is also fed to it. So I just wanted to kind of add to your... >> Good. Thank you. So why don't we open it up a little bit for questions. Any questions in the audience for our panelists? There's one there looks like (laughs). Emily, we'll get to you soon. >> I had a question for Sarush based on what you just said about us training or you all training these models and teaching them things. So when you deploy these models to the public with them being machine learning and AI based, is it possible for us to retrain them and how do you build in redundancies for the public like throwing off your model and things like that? What are some of the considerations that go into that? >> Well, one thing for sure is training is continuous. So no system should be trained once, deployed, and then forgotten. So that is something that we as AI professionals need to absolutely, because... Trends change as well. What was optimal two years ago is no longer optimal. So that part needs to continue to happen and we're the where the whole IOT space is so important is it will continue to generate relevant consumable data that these machines can continuously learn. >> So how do you decide what data though, is good or bad, as you retrain and evolve that data over time? As a data scientist, how do you do selection on data? >> So, and I want to piggyback on what Michelle said because she's spot on. What is the problem that you're trying to solve? It always starts from there because we have folks who come in to CIOs, "Oh look. "When big data was hot, we started to collect "a lot of the data, but nothing has happened." But data by itself doesn't automatically do magic for you, so we ask, "What kind of problem are you trying to solve? "Are you trying to figure out "what kinds of products to sell? "Are you trying to figure out "the optimal assortment mix for you? "Are you trying to find the shortest path "in order to get to your stores?" And then the question is, "Do you now have the right data "to solve that problem?" A lot of times we put the science and I'm a data scientist by training. I would love to talk about the science, but really, it's the problem first. The data and the science, they come after. >> Thanks, good advice. Any other questions in the audience? Yes, one right up here. (laughing) >> Test, test. Can you hear me? >> Yep. >> So with AI machinery becoming more commonplace and becoming more accessible to developers and visionaries and thinkers alike rather than being just a giant warehouse of a ton of machines and you get one tiny machine learning, do you foresee more governance coming into play in terms of what AI is allowed to do and the decisions of what training data is allowed to be fed to Ais in terms of influence? You talk about data determining if AI will become good or bad, but humans being the ones responsible for the training in the first place, obviously, they can use that data to influence as they, just the governance and the influence. >> Jack: Who wants to take that one? >> I'll take a quick stab at it. So, yes, it's going to be an open discussion. It's going to have to take place, because really, they're just machines. It's machine learning. We teach it. We teach it what to do, how to act. It's just an extension of us and in fact, I think you had a really great conversation or a statement at lunch where you talked about your product being an extension of a designer because, and we can get into that a little bit, but really, it's just going to do what we tell it to do. So there's definitely going to have to be discussions about what type of data we feed. It's all going to be centered around the use case and what that solves the use case. But I imagine that that will be a topic of discussion for a long time about what we're going to decide to do. >> Jack: Michelle do you want to comment on this thought of taking a designer's brain and putting it into a model somehow? >> Well, actually, what I wanted to say was that I think that the regulation and the governance around it is going to be self imposed by the the developer and data science community first, because I feel like even experts who have been doing this for a long time don't rally have their arms fully around what we're dealing with here. And so to expect our senators, our congressmen, women, to actually make regulation around it is a lot, because they're not technologists by training. They have a lot of other stuff going on. If the community that's already doing the work doesn't quite know what we're dealing with, then how can we expect them to get there? So I feel like that's going to be a long way off, but I think that the people who touch and feel and deal with models and with data sets and stuff everyday are the kind of people who are going to get together and self-regulate for a while, if they're good hearted people. And we talk about AI for good. Some people are bad. Those people won't respect those convenance that we come up with, but I think that's the place we have to start. >> So really you're saying, I think, for data scientists and those of us working in this space, we have a social, ethical, or moral obligation to humanity to ensure that our work is used for good. >> Michelle: No pressure. (laughing) >> None taken. Any other questions? Anything else? >> I just wanted to talk about the second part of what she said. We've been working with a company that builds robots for the store, a store associate if you will. And one of their very interesting findings was that the greatest acceptance of it right now has been at car dealerships because when someone goes to the car dealer and we all have had terrible experiences doing that. That's why we try to buy it online, but just this perception that a robot would be unbiased, that it will give you the information without trying to push me one way or the other. >> The hard sell. >> So there's that perception side of it too that, it isn't that the governance part of your question, but more the biased perception side of what you said. I think it's fascinating how we're already trained to think that this is going to have an unbiased opinion, whether or not that true. >> That's fascinating. Very cool. Thank you Sarush. Any other questions in the audience? No, okay. Michelle, could I ask, you've got a station over there that talks a little bit more about your company, but for those that haven't seen it yet, could you tell us a little bit about what is the experience like or how is the shopping experience different for someone that's using your company's technology than what it was before? >> Oh, free advertising. I would love to. No, but actually, I started this company because as a consumer I found myself going back to the user experience piece, just constantly frustrated with the user experience of buying products one at a time and then getting zero help. And then here I am having to google how to wear a white blazer to not look like an idiot in the morning when I get dressed with my white blazer that I just bought and I was excited about. And it's a really simple thing, which is how do I use the product that I'm buying and that really simple thing has been just abysmally handled in the retail industry, because the only tool that the retailers have right now are manual. So in fashion, some of our fashion customers like John Varvatos is an example we have over there, it's like a designer for high-end men's clothing, and John Varvatos is a person, it's not just the name of the company. He's an actual person and he has a vision for what he wants his products to look like and the aesthetic and the style and there's a rockstar vibe and to get that information into the organization, he would share it verbally with PDFs, thing like that. And then his team of merchandisers would literally go manually and make outfits on one page and then go make an outfit on another page with the same exact items and then products would go out of stock and they'd go around in circles and that's a terrible, terrible job. So to the conversation earlier about people losing jobs because of artificial intelligence. I hope people do lose jobs and I hope they're the terrible jobs that no one wanted to do in the first place, because the merchandisers that we help, like the one form John Varvatos, literally said she was weeks away from quitting and she got a new boss and said, "If you don't ix this part of my job, I'm out of here." And he had heard about us. He knew about us and so he brought us in to solve that problem. So I don't think it's always a bad thing, because if we can take that route, boring, repetitive task off of human's plates, what more amazing things can we do with our brain that is only human and very unique to us and how much more can we advance ourselves and our society by giving the boring work to a robot or a machine. >> Well, that's fantastic. So Joe, when you talk about Smart Cities, it seems like people have been talking about Smart Cities for decades and often people cite funding issues, regulatory environment or a host of other reasons why these things haven't happened. Do you think we're on the cusp of breaking through there or what challenges still remain for fulfilling that vision of a smart city? >> I do, I do think we're on the cusp. I think a lot of it has to do, largely actually, with 5G and connectivity, the ability to process and send all this data that needs to be shared across the system. I also think that we're getting closer and more conscientious about security, which is a major issue with IOT, making sure that our in devices or our edge devices, those things out there sensing, are secure. And I think interocular ability is something that we need to champion as well and make sure that we basically work together to enable these systems. So very, very difficult to create little, tiny walled gardens of solutions in a smart city. You may corner a certain part of the market, but you're definitely not going to have that ubiquitous benefit to society if you establish those little walled gardens, so those are the areas I think we need to focus on and I think we are making serious progress in all of them. >> Very good. Michelle, you mentioned earlier that artificial intelligence was all around us in lots of places and things that we do on a daily basis, but we probably don't realize it. Could you share a couple examples? >> Yeah, so I think everything you do online for the most part, literally anything you might do, whether that's googling something or you go to some article, the ads might be dynamically picked for you using machine learning models that have decided what is appropriate based on you and your treasure trove of data that you have out there that you're giving up all the time and not really understanding you're giving up >> The shoes that follow you around the internet right? >> Yeah, exactly. So that's basically anything online. I'm trying to give in the real-world. I think that, to your point earlier about he supply chain, just picking a box of cereal off the shelf and taking it home, there's not artificial intelligence in that at all, but the supply chain behind it. So the supply chain behind pretty much everything we do even in television, like how media gets to us and get consumed. At some point in the supply chain, there's artificial intelligence playing in there as well. >> So to start us in the supply chain where we can get the same day even within the hour delivery. How do you get better than that? What's coming that's innovative in the supply chain that will be new in the future? >> Well, so that is one example of it, but you'd be surprised at how inefficient the supply chain is, even with all the advances that have already gone in, whether it's physical advances around building modern warehouses and modern manufacturing plants, whether it's through software and others that really help schedule things and optimize things. What has happened in the supply chain just given how they've evolved is they're very siloed, so a lot of times the manufacturing plant does things that the distribution folks do not know. The distribution folks do things that the transportation folks don't know and then the store folks know nothing other than when the trucks pulls up, that's the first time they find out about things. So where the great opportunity in my mind is, in the space that I'm in, is really the generation of data, the connection of data, and finally, deriving the smarts that really help us improve efficiency. There's huge opportunity there. And again, we don't know it because it's all invisible to us. >> Good. Let me pause and see if there's any questions in the audience. There, we got one there. >> Thank you. Hi guys, you alright? I just had a question about ethics and the teaching of ethics. As you were saying, we feed the artificial intelligence, whereas in a scenario which is probably a little bit more attuned to automated driving, in a car crash scenario between do we crash these two people or three people? I would be choosing two, whereas the scenario may be it's actually better to just crash the car and kill myself. That thought would never go through my mind, because I'm human. My rule number one is self preservation. So how do we teach the computer this sort of side of it? Is there actually the AI ethic going to be better than our own ethics? How do we start? >> Yeah, that's a great question. I think the opportunity is there as Michelle was talking earlier about maybe when you cross that chasm and you get this new singularity, maybe the AI ethics will be better than human ethics because the machine will be able to think about greater concerns perhaps other than ourselves. But I think just from my point of view, working in the space of automated vehicles, I think it is going to have to be something that the industry, and societies are different, different geographies, and different countries. We have different ways of looking at the world. Cultures value different things and so I think technologists in those spaces are going to have to get together and agree amongst the community from a social contract theory standpoint perhaps in a way that's going to be acceptable to everyone who lives in that environment. I don't think we can come up with a uniform model that would apply to all spaces, but it's got to be something though that we all, as members of a community, can accept. And so yeah, that would be the right thing to do in that situation and that's not going to be an easy task by any means, which is, I think, one of the reasons why you'll continue to see humans have an important role to play in automated vehicles so that the human could take over in exactly that kind of scenario, because the machines perhaps aren't quite smart enough to do it or maybe it's not the smarts or the processing capability. It's maybe that we haven't as technologists and ethicists gotten together long enough to figure out what are those moral and ethical frameworks that we could use to apply to those situations. Any other thoughts? >> Yeah, I wanted to jump in there real quick. Absolutely questions that need to be answered, but let's come together and make a solution that needs to have those questions answered. So let's come together first and fix the problems that need to be fixed now so that we can build out those types of scenarios. We can now put our brainpower to work to decide what to do next. There was a quote I believe by Andrew Ningh Bidou and he was saying in concerning deep questions about what's going to happen in the future with AI. Are we going to have AI overlords or anything like that? And it's kind of like worrying about overpopulation at the point of Mars. Because maybe we're going to get there someday and maybe we're going to send people there and maybe we're going to establish a human population on Mars and then maybe it will get too big and then maybe we'll have problems on Mars, but right now we haven't landed on the planet and I thought that really does a good job of putting in perspective that that overall concern about AI taking over. >> So when you think about AI being applied for good and Michelle you talked about don't do AI just for AI's sake, have a problem to solve, I'll open it up to any of the three of you, what's a problem in your life or in your work experience that you'd love somebody out here would go solve with AI? >> I have one. Sorry, I wanted to do this real quick. There's roads blocked off and it's raining and I have to walk a mile to find a taxi in the rain right now after this to go home. I would love for us to have some sort of ability to manage parking spaces and determine when and who can come in to which parts of the city and when there's a spot downtown, I want my autonomous vehicle to know which one's available and go directly to that spot and I want it to be cued in a certain manner to where I'm next in line and I know. And so I would love for someone to go solve that problem. There's been some development on the infrastructure side for that kind of solution. We have a partnership Intel does with GE and we're putting sensors that have, it's an IOT sensor basically. It's called City IQ. It has environmental monitoring, audio, visual sensors and it allows this type of use case to take place. So I would love to see iterations on that. I would love to see, sorry there's another one that I'm particular about. Growing up I lived in Southern California right against the hills, a housing development, because the hills and there was not a factory, but a bunch of oil derricks back there. I would love to have sensor that senses the particulate in the air to see if there was too many fumes coming from that oil field into my yard growing up as a little kid. I would love for us to solve problems like that, so that's the type of thing that we'll be able to solve. Those are the types of innovations that will be able to take place once we have these sensors in place, so I'm going to sit down on that one and let someone else take over. >> I'm really glad you said the second one because I was thinking, "What I'm about to say is totally going to "trivialize Joe's pain and I don't want to do that." But cancer is my answer, because there's so much data in health and all these patterns are there waiting to be recognized. There's so many things you don't know about cancer and so many indicators that we could capture if we just were able to unmask the data and take a look, but I knew a brilliant company that was using artificial intelligence specifically around image processing to look at CAT scans and figure out what the leading indicators might be in a cancerous scenario. And they pivoted to some way more trivial problem which is still a problem and not to trivialize parking an whatnot, but it's not cancer. And they pivoted away from this amazing opportunity because of the privacy and the issues with HIPPA around health data. And I understand there's a ton of concern with it getting into the wrong hands and hacking and all of this stuff. I get that, but the opportunity in my mind far outweighs the risk and the fact that they had to change their business model and change their company essentially broke my heart because they were really onto something. >> Yeah that's a shame and it's funny you mention that. Intel has an effort that we're calling the cancer cloud and what we're trying to do is provide some infrastructure to help with that problem and the way cancer treatments work today is if you go to a university hospital let's say here in Texas, how you interpret that scan and how you respond and apply treatment, that knowledge is basically just kept within that hospital and within that staff. And so on the other side of the country, somebody could go in and get a scan and maybe that scan brand new to that facility and so they don't know how to treat it, but if you had an opportunity with machine learning to be able to compare scans from people, not only just in this country, but around the world and understand globally, all of the hundreds of different treatment pads that were applied to that particular kind of cancer, think how many lives could be saved, because then you're sharing knowledge with what courses of treatment worked. But it's one of those things like you say, sometimes it's the regulatory environment or it's other factors that hold us back from applying this technology to do some really good things, so it's a great example. Okay, any other questions in the audience? >> I have one. >> Good Emily. >> So this goes off of the HIPPA question, which is, and you were talking about just dynamically displaying ads earlier. What does privacy look like in a fully autonomous world? Anybody can answer that one. Are we still private citizens? What does it look like? >> How about from a supply chain standpoint? You can learn a lot about somebody in terms of the products that they buy and I think to all of us, we sort of know maybe somebody's tracking what we're buying but it's still creepy when we think about how people could potentially use that against us. So, how do you from a supply chain standpoint approach that problem? >> Yeah and it's something that comes up in my life almost every day because one of the thing's we'd like to do is to understand consumer behavior. How often am I buying? What kinds of products am I buying? What am I returning? And so for that you need transactional data. You really get to understand the individual. That then starts to get into this area of privacy. Do you know too much about me? And so a lot of times what we do is data is clearly anonymized so all we know is customer A has this tendency, customer B has this tendency. And that then helps the retailers offer the right products to these customers, but to your point, there are those privacy concerns and I think issues around governance, issues around ethics, issues around privacy, these will continue to be ironed out. I don't think there's a solid answer for any of these just yet. >> And it's largely a reflection of society. How comfortable are we with how much privacy? Right now I believe we put the individual in control of as much information as possible that they are able to release or not. And so a lot of what you said, everyone's anonymizing everything at the moment, but that may change as society's values change slightly and we'll be able to adapt to what's necessary. >> Why don't we try to stump the panel. Anyone have any ideas on things in your life you'd like to be solved with AI for good? Any suggestions out there that we could then hear from our data scientist and technologist and folks here? Any ideas? No? Alright good. Alright, well, thank you everyone. Really appreciate your time. Thank you for joining Intel here at the AI lounge at Autonomous World. We hope you've enjoyed the panel and we wish you a great rest of your event here at South by Southwest. (audience clapping) (bright music)