Alrighty hello everyone and welcome to today's session on building planetary scale mobile edge computing applications on Kubernetes super excited to have everyone here wish we could have been in person, but we're super excited today to talk a little bit more about our experiences with Verizon 5G edge, which is our mobile edge computing platform and tell you a little bit more about why we believe. The Kubernetes community should care about this infrastructure and what it means for you as you start to deploy network intelligence across your edge applications. I think to start off just introduce myself. My name is Robbie Wilson, and on behalf of the entire Verizon team, we're super happy to be here. I come from part of our corporate strategy team where I lead our developer relations efforts for all things 5G edge. Everything from blogs developer newsletters immersion days hands on labs, working with developers day and day out is what I do. I love nothing more than having the opportunity to share with this very community about the integration opportunities and just ways that network intelligence can play a role in orchestrating applications. But joined alongside me today is Raghu from our mix strategy and architecture team want to introduce yourself here we go. Hi, hello everyone. My name is a good one for any part of my strategy and architecture team here at Verizon, and my today day to day responsible does include the 5G edge architecture design. So my core functionality is application experience management and how do we manage the network exposure so all of you guys can go ahead and develop some crazy amazing applications on top of the 5G edge that we just delivered. I'm pretty much into cloud native distributed systems and also have a lot of experience with software defined networking and pretty excited to be here along with you. Fantastic. Well, we're going to have a lot of fun today as we talk about first and foremost. What is 5G edge? How does it relate to 5G? Understanding what you need to know about deploying your first Kubernetes application on 5G edge. So from an infrastructure perspective, the key components, where's the control plane live, what are the workers, worker nodes live, how do they self registered the control plane. Then starting to think about things like experience management, what tools are Verizon developing. To solve some of these key challenges that you may not even know our problems today, and then start to think about building your edge enablement journey. How do you get started and where are those resources to follow as you hope to build your first EKS cluster or Kubernetes cluster more broadly on Verizon 5G edge. So let's get started here and I think a really important place or interesting place to start is why the mobile edge. And I think to me, as you think about consumers ever increasing demand for data for immersive experiences, the infrastructure and network today may not be good enough for tomorrow said differently. The cloud today is often concentrated in a few geographies that if you happen to be outside of those geographies, say in Miami, Florida, that cloud endpoint or cloud application is probably being delivered 1000 miles away. And so wouldn't it be nice if you could bring the best experiences of the network with the best experiences the cloud, bring them together at the network edge to physically have those resources topologically closer to users than ever before, perhaps within the radio network in Miami. And in doing so, start to solve challenges around conversion, particularly with transaction based workloads. We see for an example that a share 100 milliseconds in delay can affect conversion rates by as much as 7%. And so if you're trying to really decrease that end to end delay. It's not just about the optimizations we've made today, things like using a CDN more intelligent back end operations asynchronous requests. All of those optimizations are no longer enough, you can physically move where that application lives closer to you, you reduce the non deterministic behavior of the internet those incremental hops and in turn deliver that more performing user experience. But we have Verizon wanted to ask ourselves, well, where do we come in. And so the question we found ourselves asking was, how do you optimize application logic for the network. And can the network finally become an asset. Kubernetes applications and applications at large, and we fundamentally believe that the answer is yes, because we found a way to do so without having without having you to have to learn the nuances of the 5G network. We have to use the cloud platforms you know and love and simply put, that is what Verizon 5G Edge is all about. It's worth noting that as you think about our portfolio 5G Edge is our portfolio of mobile edge computing solutions. We have two different flavors. We have our private mech solutions which ride on top of a private network with compute co located right there. But today we're going to focus almost exclusively on public mech, otherwise known as Verizon 5G Edge with AWS Waveline. And the reason why we wanted to focus on that is first and foremost, this solution is available in 13 cities today across the US East one and US West two regions, meaning compute is topologically closer to you than ever before. In more cities, you no longer have to just rely on those parent region diplomas those very few cities that deliver cloud applications today. And also, you don't have to be an expert in 5G networks as we mentioned. Let Verizon deal with the complexities of managing the network and you can focus on building your application. And lastly, you don't want to have to learn new language, new syntax, new infrastructure concepts. We wanted that sort of uniform pane of glass as you develop for the non edge and for the edge you want it to feel the same, because at the end of the day, a VM is a VM, a Kubernetes cluster is a Kubernetes cluster. It shouldn't really matter where it is. And that's why we partnered with AWS to deliver the AWS Wavelength service, because if that same single pane of management across both Wavelength and what we call the parent region, with all of those services, such as EC2, your virtual machines, EKS for Kubernetes, EBS for persistent storage volumes, all of those services you know and love are also in AWS Wavelength. And what we want to do today is actually deep dive into those services. We talk, we talk a lot about right now, but what's the same. But we do want to highlight what's different so that we can help you build your first application on the network edge using Verizon 5G Edge and AWS Wavelength. And I think a great place to start is, well, why would you want to use Kubernetes at the network edge and to me, I always say that application modernization practices should still apply that for POC is what we're seeing from customers. It is admittedly a lot of EC2 instances at the edge, perhaps in an auto scaling group, but as these workloads become ever complex, particularly as you start to deploy only those microservices, which require low latency and low latency only. Well, then you don't have to move the whole application, you only have to move select components. And that's what you're seeing here the consistency across the infrastructure the scalability the flexibility that you get from Kubernetes. And that's why we believe that's going to be the application deployment pattern of the future. Kubernetes on AWS Wavelength. And there are a couple things that are particularly compelling that I want to call out. First and foremost, the first question we get is, I'm an application developer, I already have an EKS cluster, do I need to create another cluster in the edge? Worse, worse yet, if there are 13 Wavelength zones, is that 13 EKS clusters or just Kubernetes clusters more broadly to manage? The answer is no. And we're very proud to share that as you look at the reference architecture on the left. At the highest level and will delve into the networking nuances here in a second, what you want to know is an existing control plane running in the region can also support node groups or worker nodes at the mobile edge without making any major changes to the cluster itself. You're just adding another node group. And we thought that would be the easiest way to allow clusters to support not only greenfield deployments but brownfield deployments as well. And we think that that's incredibly important that you take existing workloads and you're able to extend them to the edge. And the best way to do that is keep the control plane as is and incrementally deploy additional node groups and have them self register to that control plane. AWS has a few handy infrastructure templates for self managed worker nodes and we can happily refer you to our github.com slash Verizon slash 5g edge tutorials, where we've already automated all of this for you but the key point is incremental node groups at the edge that self register to the control plane. And it's that simple. And who cares. The reason this is so compelling is now really for the first time ever before, you can have a single control plane orchestrating containers that are physically geographically separated by potentially 1000 miles apart, said differently, that one control plane in northern Virginia and East one can now have node groups in Boston, New York City, DC, Atlanta, Miami, etc. You could never do that before. And if you did, would require a series of undifferentiated heavy lifting. You don't have to do that anymore. It's really that simple. We take care of the connectivity from each of these wavelength zones back to the parent region via the service link. We take care of optimizing the complexity of the network itself so you can focus on building the application. There are a few things you do need to know about and it has to do with the connectivity you see here in the bottom right key components and mobile edge architectures. We think it's very important and worth calling out. First and foremost, we know about our VPC is that virtual private cloud that logical isolation of resources. The key thing here is this wavelength zone this mobile edge. It's not this weird standalone entity outside of the VPC. It's just another subnet. In fact, a wavelength zone is an availability zone. And when you create subnets in a VPC, you can have a subnet in an availability zone in a wavelength zone multiple of each it doesn't matter it's just treated as an availability zone from a subnetting perspective. However, from a routing perspective, you need to carry a gateway. And the reason you need to carry gateway is the traditional network address translation that happens between private IPs that are allocated to your VPC and public IPs doesn't actually make sense in the context of wavelength because those public IPs are actually Verizon allocated devices that are unique to our network. We call them carrier IPs. And because these carrier IPs are unique to our network, we needed a different appliance. And so it's not called a internet gateway, but a carrier gateway and you need to attach that to your VPC. Much like you would to the internet gateway. And in turn, have a route table unique for your carrier subnet traffic which I've tried to highlight here in that little purple box in the middle. This is a traffic desk and for your VPC, your local route stays within your VPC. However, the route table attached to that wavelength zone for egress traffic is probably going to send it through the carrier gateway. You don't want to have to go all the way back to northern Virginia or that parent region, and then proxy traffic out. You could, but you may as well use the carrier network that's right there. That's the whole point to get that low latency connection. That's why we design the carrier gateway. So between care gateways and carrier IPs you understand the networking fundamentals. The Kubernetes fundamentals that we just described are incredibly simple. You just have to extend your cluster. Add node groups and then make sure the connectivity is sound. And then one thing worth noting for those who want to delve into the nuances here, depending on the cluster endpoint type, that self registration to the control plane needs to be able to talk to the control plane, which it might not be able to do if you haven't attached a carrier IP to those worker nodes. What you have to do the very simple EC2 interface endpoints, you can talk to the EC2 control plane and in turn registered to the cluster. All of this information can be found on our GitHub Verizon that we mentioned our Verizon 5 GH tutorials GitHub repo. Now we talked a little bit about Kubernetes, but I want to set up a problem statement here that there is truly no better person than Ragu to talk about. That's the following problem statement. We talked about these carrier IPs that only Verizon really natively understands. To you, they all look like 155.146.x.y. They all look the same to you, but they're actually going to correspond to different endpoints in Miami, San Francisco, Las Vegas, Boston. This is a headache. And worst of all, DNS today, geolocation based routing has no idea where these addresses are. And so you need a way to figure out at any given point, I don't want to hard code a carrier IP address. There's got to be a better way to figure out what's closest to me at any given point and allow network intelligence to take over here. And so I'll turn it over to Ragu to talk a little bit more about the edge discovery service. And I believe you're on mute here Ragu. Thanks, Robbie. Any application that we can imagine today is geographically distributed and the problem statement that Robbie mentioned earlier is aptly suited for this kind of geographically distributed application. In public region, the concept is pretty simple. You have four regions to choose from East one East two West one West two taking the Amazon as an example and any application developer can pick one region and deploy the application. And a device or an end user connecting to that application can pick out of those four regions based on the geolocation and just connect to it. And DNS is pretty much suited for this kind of an resolution. But when it comes to 5g edge or this kind of an multi-axis edge compute, we have much denser deployments taking the example of wavelength itself. We have like 10 sites for 5g edge or 13 sites including the sites that we launched this year. Then how does an application developer determine where to place your application? Or how does an end user connect to out of all those 13 sites, which is the right site for the user to connect to? So this is a very big problem statement where it comes to edge computing. And here at Verizon, we are using our network intelligence abstracting all the complexity and giving you a very simple service you can actually use to solve two use cases. Looking at it from the point of view an application developer. How do I find an optimal Mac platform that needs that meets the application requirements, right? You might have some policy requirements stating the latency requirements or application performance. How do we determine the optimal Mac that satisfy your application requirements? The second point of view is the end user point of view. How does a device or how does an user connect to those application servers which are already determined or already running on the predetermined Mac sites? And we at Verizon have developed a very simple to use edge discovery service and that is what we're going to talk about in the next couple of slides. Let's take a very practical example, right? So there's a cloud gaming application and a cloud gaming developer have developed the application and wants to deploy it on out of the 13 sites they want to deploy in certain sites which maximizes their ROI for the application. They use edge discovery service to determine and determines that they need to place the application in three sites. Boston, Miami and New York. Let's talk about East Coast for a second. Now, when the application is deployed, how does the client or the mobile know which wavelength zone or which application endpoint to connect to, right? Between Boston and New York and then Miami. Geolocation is not going to solve the problem. And especially for these three examples, between Boston and New York, you can just use the reverse geolocation or reverse IP address and then figure out rough estimate. But the more denser we go, the problem becomes much more complex now because you have a lot more sites to choose from and also the resolution might not be accurate. And for latency critical applications and this kind of an performance sensitive applications that even the small difference is going to be critical. So once the application is deployed, now the end user needs to connect to that endpoint. So the developer programs the edge application to call the Verizon edge discovery service or we call it as EDS. And then Verizon EDS identifies what is the optimal network path for the mobile to connect to the Mac platform. And in this, respectively, we also determine what is the optimal endpoint on the which is running on the Mac for the application server that the device can connect to so it gets the optimal experience. And again, the optimal experience is defined by the enterprise or the cloud gaming application developer as part of the policy as part of the profile of the application. As a result, now the device will connect to the Mac instance or the applications were running on the Mac platforms which is selected by Verizon by looking at the network conditions by looking at the various latency metrics and abstracting all of that and providing a simple interface. So let's do a bit of a technical deep diver giving you an example of exactly how it works. Right now the cloud gaming application has determined to deploy the application in three sites Boston, New York and DC, right? And the application is deployed and you get a carrier IP address as you can see in the 155 146 range. These are again allocated by Verizon. So the enterprise in this case, consolidates all this information, and then pushes it towards the edge discovery service making an API call with information like the application server ID, calling it as Boston test instance. And then the New York test instance and the DC test instance, and also allocating some information about it like what is the address IP address where the application is running. And all this information is provided to edge discovery service as part of service registry. And next when the device or the application running on the device makes a query to the edge discovery service, passing in the UV identity, so the identity of the end device. And in this case we are taking an example of IP address to the end mobile device IP address. And then the edge discovery service will use that IP address to determine which is the optimal application server out of the three application servers provided by the application enterprise developer and then returns it back to the device to connect it. As you can see all of this complexity of determining the right application based on the user IP address is abstracted from the user and it makes it very simple for the application developer and enterprise or even the end device to determine the application server. That's back to you. Thanks for go. So what I wanted to do in the final slide here is close with a thought experiment, an open challenge and opportunity that we see as one great application of the edge discovery service you see how incredibly important it is because without it. You're either going to guess and guess wrong or guests in this case. You're only going to guess right one out of every three times you could just have a high level DNS DNS records that round Robin you to victory, which in most cases again would be wrong. Or we get a little bit smarter about this and use the edge discovery service to our advantage particular in a Kubernetes environment. And one thing I've been seeing a lot from today is that it's been invoked manually most of the time even if you're using you've developed your own SDK for it congratulations but anytime you create let's say you're exposing your services today and worth noting that in the absence of a load balancer, a lot of customers today are using node ports to expose services. And so today, those three addresses we saw before in Boston, New York City and DC respectively, you have to call manually. The EDS API each time the node port is exposed, or when you port for it. And that's a challenge as the application grows as you use more wavelength zones, you can see a scenario where one manual error results in clients being blissfully unaware of application infrastructure that you're paying for. So we started thinking, maybe Kubernetes can help. Maybe we can tie together the network intelligence story we just talked about with the Kubernetes world and it occurred to us that we can start thinking about admission web books, or in the future operators so I'll start with the operator story that's a little perhaps longer term thinking here, and then talk about something we could do today. Conceivably, there's nothing stopping the edge discovery service from being a CRD. And if that's the case, then we can have these custom controllers here taking care of all the application logic, or the creation the updating all the credit operations associated with these end points being exposed to the node port load balancer or otherwise, always watching for changes and manually updating EDS so now the API is only going to be invoked in the back end essentially once you create once you create that resource type, you never have to touch it again because Kubernetes takes care of it. And to me, that's incredibly powerful, particularly in a world today, you know what we're seeing from customers is what we're seeing is it's not always even stable care IPs, they're ephemeral in their very nature you spin up an EC2 instance has a care IP it goes down it comes back up with a different address. Imagine the operational complexity of managing that yourself. Using operators as one example, but something we can definitely use today is admission web books, a much simpler way to say, Hey, Kubernetes, always watch out for the integration of these node ports, and in doing so, populate the edge discovery service accordingly. And so to me, this is a really really new admittedly new, but exciting problem space for the Kubernetes community, and the network intelligence community here at Verizon and beyond can come together to build some really unique integrations. And worth noting that this is just one example of network intelligence I'll give you one more to close out the session here. And that is today by and large, application metrics make application decisions are favorite example. That's often discussed when you're first getting into DevOps or infrastructure monitoring is that CPU utilization. Once you get a particular threshold you scale out, maybe from one instance to two instance instances rather. In the future, maybe you don't have to rely on CPU utilization as a proxy for load. Maybe you already know where your devices are, and can preemptively scale before you hit that utilization threshold. And so, across all of these different examples and by the way the example I just highlighted, we have working code to prove using Verizon think space and basic auto scaling groups on AWS Wavelength so whether you're looking at that perspective, or even you can have your auto scaler tied out to that, to those things based devices so whether you're thinking about this on the perspective of IoT devices and auto scaling groups, Kubernetes and admission web hooks network intelligence. We think there's a huge opportunity to consider network intelligence like never before, in how you create update and maintain Kubernetes clusters, and we invite you to participate in this community by getting started with your first Kubernetes cluster on AWS Wavelength. And as a few examples of ways that you can get started, you can visit our developer resources page by going to Verizon.com slash 5G edge and clicking on our developer resources page. You can go to our GitHub page that we mentioned 5G edge tutorials. You can visit the Verizon 5G edge blog. You can check out our 5G labs at Verizon 5G labs.com slash edge to check out our latest immersion day, hands on training and more. And we'd love to continue the discussion with you. You can find us on Twitter. You can email Verizon 5G edge or Verizon.com to continue the discussion. We'd love to have them, and I will leave the final word to you, Rugo. Yeah, pretty much excited for what all amazing things the developers here can build with the technology that we are providing. And I'm pretty sure the network intelligence is going to change the game that we're playing with the edge computing and as well as the low latency applications are being built. And the way Robby explained, we have all these services, tutorials, blogs and everything for you in our edge portal. And please do visit and start building amazing things. And with that, thanks everyone for joining. Stay safe, stay healthy and hope you enjoy the rest of the conference. Thank you.


Yes, good morning. Good morning. Good morning. Bonjour. Salamat Paghi. It's really great to be here, a great pleasure to be here. So my name is actually Gard Leonhardt with an H, but we can skip the H. It's fine. I was born in Bonn, Germany. So if my presentation is perfect, that's my German background. I live in Switzerland in Zurich. So if there's no risk in my presentation, that's why because of my Swiss background. And if it's awesome, that's because I lived in the US for 15 years. It's also because I speak rather fast sometimes. So please apologize because if you speak in the US and you speak slowly, then you get kicked off the stage, right? It's just no point in it. So first of all, I wanted to say briefly what a future is. As a futurist, I don't predict the future. Some futurists have done that like Alvin Toffler and Isar Gazi-Moff and, you know, brilliant people like this. I basically observe the future and this is something that all of us are doing, but I do it about 95% of the time. So I don't operate a business while I have a future business, but it's basically thinking about the next five years and I want to share some of my key insights with you today. So my real job is listening and I would definitely recommend that we start thinking about this as being part of your job as well because it's so important to listen to the future to the next five years. You know, in China, they say if you want to know about the future, ask your children. And if we're open to understanding what the future brings, you know, the next five, seven years, not 50 years, then things change for us. And the most important thing that's happening today is the convergence of man and machine, technology and humanity. I happen to have a book on this. I just wrote Technology vs. Humanity. It's been out for three weeks. So all of your questions you may ever want to have, they answer in the book. Just kidding. This is the most important curve of the day. Exponential technological change. It's very hard for people to understand exponential because obviously humans are not exponential. You know, we do learn occasionally. We get a little bit linearly faster. We go step by step. But we're not computers. You know, what's happening now in computing and pretty much everything around computing is that it's mind-boggling explosive. Not just Moore's law and computers, but also artificial intelligence. Now we're seeing things around us that used to be science fiction. They're becoming science fact. So I've driving cars, automatic language translation, intelligent machines, robots that people fall in love with. You've seen the movie Hurd. It's actually happening already. I'll talk about that a little while. So we're now moving into a world where you say this can't be true. This is actually working. I mean, we have two years away, pretty much less than two years, until language understanding of computers becomes completely normal. You can speak in 50 languages, even mix languages, and command computers, natural language understanding. And this has always been tested, but finally it's here. So the mistake that we often make is that we say, okay, it hasn't happened and it won't happen because we were here, right? We were doubling 0.01. It's still nothing. But now we're at four. The next step is eight and 16. So we're going to be at the top of this curve in roughly seven years. That's 30 times as much as we're here. So my kids, that are millennials, you know, they will probably never know. The kids of my kids will never know how to drive a car without a computer running it. They will never know what a CD looks like. They will never be offline in their lives. Is it a sad thought or not? I don't know, but it's more like a mental state of being offline. Basically, our future is we're at the pivot point. And if we keep thinking in a linear way, we will see catastrophic results for businesses, but also for politics and culture. Because thinking linear means that we say, okay, we wait and see, but now pretty much in this kind of world, wait and see means wait to die. Because things are moving so quickly that we don't have time. The car industry is the best example. Six years ago, I had a workshop with some of the major German car makers, all of their leaders, and we talked about self-driving cars, autonomous vehicles, car sharing. And what did we get in a room like this? We got laughter. No, we got literally got laughter. Nobody wants to share their car. Are you kidding? That's a crime in Germany. Share my car. We're thinking of that. So today, the number one initiative of all car makers is electric vehicles, self-driving vehicles, car sharing, you know, mobility. Imagine if we would have thought of that earlier. So we would have had possibility of changing things. So today on this curve, we have exponential connectivity. The world is connecting at really high speed, mobile and otherwise. We have data as the new oil. We talked about this for a long time. It's finally here. The data companies are the most powerful companies in the universe as far as we know. So no longer oil, but data. Intelligence. What can you do with lots of data when you don't have intelligence? Well, a doctor can't possibly remember 140,000 cases of cancer of the same patient that he's seeing. The machine can. That's turning us into a bit of a super human, you could say. So this is also the key question. How do we keep the human inside? I would propose to you that it's actually totally meaningless if your business is really great with technology if you have no meaning. This is probably not news to you, but basically people don't make decisions based on data. I mean, we do all kinds of things. What we do as a human is vast and more complex and saying, okay, the focus group has proven X, Y, Z, and so that's what we do. Data is really crucial to what we do in business. It's a big decision point, but just like you don't eat in every place that TripAdvisor tells you, TripAdvisor is a great tool, but God, you'd be in deep trouble if you'd just eat where TripAdvisor tells you. It's a data point. So what's really important is how do we keep the human inside? I've developed in my book these two terms. One is algorithms, of course, you know what that is. And the other one is andro-rhythms, the things that humans do. And there are some little things that humans do, mystery, secrets, lying, deceptions, humor, empathy, compassion. You know, this goes on. And this is very important for business because business is about trust. You could say in a way that the only currencies that really matter in business are trust and data, but sometimes they're of course at odds, because you don't really know what to say. Ginny Rometti, the CEO of IBM, and IBM is one of my clients just to divulge this, but Ginny said one day that, and a speech that basically in the future, decisions, major decisions will be made by algorithms and data, not by intuition and experts. I don't know if you agree with this. I would say I hope not. I think basically data is becoming increasingly powerful and important. But will we remove the human part of decision-making based on data? Will you let an AI decide whether you should have a baby or not based on the reading of DNA of that baby? Or would you let an AI run the government? That would be a logical conclusion. Well, at least in Germany, it may not be useful. So we have to think about what that means. Basically, this is bringing home an interesting thing called the Morovac paradox. And that paradox simply put says that whatever is really easy for computers is hard for people, and what's hard for computers is very easy for people. In other words, the stuff that we do as people is almost impossible for computers. For example, when I meet you in the hallway, it takes us about one second, sometimes less, to figure out if we're basically in the same tribe, you know, if we can talk to each other. And that's without saying anything. So there's a huge amount of information that takes place between people. That is sort of unquantified. And never mind those issues like ethics, morals, values, understanding, trust. So at that point, we can say, well, it's kind of an interesting angle. You know, for example, you remember that story on Facebook? This Pulitzer Prize-winning photographer, Nick Utt, he had put his photo on Facebook.  And well, I took out the part here, but basically it's more or less a new child, right? But this was a photograph and it's won all kinds of prizes. And he was kicked off Facebook for the picture. That's how smart the algorithm is. Did not recognize art from pornography. That's the Morovac paradox. So we have to do better than that in the future, because basically the bottom line is machines don't think like humans do. We think with our bodies. Daniel Kahneman, the Nobel Prize-winning psychologist once said, we think with our bodies, not our brain. So I would submit to you when we're talking about data analytics, that's the good thing. Let the computers think like they're going to think like machines. Let them think in an entirely different way. They don't have to be like us. They shouldn't be like us. It's fantastic if a computer can do its own thing, its own thinking, its own cognition. Do we need a computer to really understand what we feel like, what kind of ethics we have? Do we need a computer to decide who to kill when an autonomous car has an accident? I would submit to you that 99.999% of what we're talking about here could be very well achieved with computers being cognitive without going anywhere close to this. And that's the low-hanging fruit of what you guys are doing. In business, we don't need computers to think like us. We can take care of that, right? There's a few things that we should keep. We have to think about the possibilities that may leave us baffled, like this one is a software made in Switzerland by accident. It's called Emotion Advisor. Check out the video and then let me know what you think. It's called EnViso. This software analyzes people's facial movements as they're looking at financial products. So if you... It's kind of funny, isn't it? It would not be happy what mostly we would discuss, I suppose. So you're looking at things and the software says, this is what people are really thinking.  It's a very interesting angle. This is kind of baffling because maybe very useful. Do you believe that this is a useful product? Well, maybe, or maybe not. It's actually an interesting angle. It's really hard to understand where it goes. Just take it one step further yesterday. Newsweek was running an article saying that some people had proposed the next president of the US should be an artificial intelligence because the argument was an artificial intelligence and machine would not have misgivings about things, wouldn't lie, wouldn't have any bias. So after Trump it's going to be IBM Watson, or something like Watson. I suppose you could say that Trump already is an AI but a badly programmed one and that really wouldn't make any difference. In any case, I think that's probably not a good idea, right? But here are some of the mega shifts I think that are underpinning the DNA revolution. If you understand those, I don't have time to go through all of them but I'll show you a list and if you understand those, then you can look forward and say, okay, how do we actually use this? Here's the list. They all end with Asian. That's why I used to call them the Asians. I live in Switzerland so I use the data-fied cow as a symbol because now the cows are actually getting wired in Switzerland to track them and to see what they're doing, how much they're eating, how often they have sex and things like that. So the mega shift underpinning this is really a very complex scenario of many things you've seen before. Let's just look at one data-fication. That's kind of a fake word but data-fication means something like your doctor that you used to go and see. He used to scribble things with hand and put it into his folder with a bad handwriting. Today, the doctor has all the data about you from your Fitbit and from your remote diagnosis and writes on an iPad. So everything you talk about is recorded. Well, some doctors at least, right? Not my doctor. That data is turned into actual data streams. Now we have a hiking boot from an American company called REI. The hiking boot connects to my app when I'm walking and it says, you know, 43 kilometers, you need new shoelaces because it can analyze this. Everything is turned into data. Everything is becoming automated and everything is becoming virtualized and robotized. We put all these trends together, we get things like the blockchain, which I'm sure you heard about. This is the current hot topic of the day. It wouldn't be possible without all those trends. We get the HoloLens, which you'll see outside, the possibility of seeing things differently. We get the fourth industrial revolution and we get intelligent digital assistants. The last one is a biggie. Very soon, we're not going to have websites, we're not going to have apps, we're still going to have those, right? We're just going to talk to computers, wherever in whatever shape they are in the car, on the mobile at home and hopefully that fly to Morocco and my favorite Riyadh, right? And off it goes and takes care of things for us. So you've heard this before, you know, data is the new oil, but now intelligent data is the petrol, is the gas that we drive on.  And there's no way that we humans can actually take all that data and say, okay, let me work on that, right? That's just not going to happen. So what happens here is we have all these helpful tech companies who are now the new oil companies. You know, if you look on the left, just 10 years ago, the big companies in the world were the data of the oil companies and of course some banks. That has changed too bad. Now we're over here, all the big companies, market caps, our technology companies, data companies, social networks and platforms. If you look a little bit further down, there's Chinese companies. That's the next edition of all of these guys, right? In fact, Baidu and Alibaba are already in the upper piece. So that's really interesting to see where things are going. Facebook, for example, has a great correlation to this whole discussion about data oil. You can see, for example, the market cap of Facebook is higher than the market cap of Walmart. Connecting people and being a pleasure trap and doing stuff. It's amazing. I mean, we are the content of Facebook. Maybe we should get a piece of this, but you can bet that regulation is a certainty. Just like your oil companies were regulated. I mean, it's interesting to see the most powerful companies of the world used to be very regulated, but now they're not or very little. That's going to change. This is Facebook's battle plan, 10 years roadmap. We can learn something about DNA here. They're mining us. I'm not saying this badly. I'm a Facebook user, but you do feel sometimes like you're being mined. Look at the key point here in Facebook's roadmap. Connectivity, that's obvious, but artificial intelligence. DNA. The global brain. So how do they do it? I used to be in the music business as a musician and producer. I helped the record labels to understand the internet, which of course was a useless undertaking. In fact, the most incomplete transition to digital is the one of the music business. But you see on this really happy chart here, as I have kind of a laugh and a look at this, is the music business actually not doing so bad because we're kind of in the valley of death where it's gone down a lot. But all of a sudden streaming, all of you guys are probably streaming music, Spotify or YouTube. It's about 20 euros a month for 20 million songs. And it used to be about 20 euros for one CD, for 12 songs. That's kind of an issue on a per song basis. But do you see this happening here? Who are all these new guys, the streaming guys? Well, they're not the record labels. They're Spotify, they're Baidu and Alibaba and maybe Facebook eventually and companies like YouTube, of course. They're doing a data analytics. Spotify makes it work and the money is there but you're not getting it. Somebody else is getting it. Same goes for print newspapers. You've seen these curves.  The advertising, look what happened here, the internet and then of course the mobile phone and before you knew it, deep dive into the valley of death. At the same time, everything. There's a great saying on the internet, Facebook is eating the world. It's 92% of digital advertising in users run by Google and Facebook. And what do they do? The answer is data analytics, artificial intelligence. That's their tool. So these are the areas that are ripe for disruption by intelligent data analytics. There's four areas. One is the complex environments and obsolete intermediaries to access. And then we can clearly say that banking and financial is quite a few banks I think in the room. I think banks qualify for all four. That's good news, isn't it? Just kidding. It means that you're ready for disruption but looking at this, for example, obsolete intermediaries, media, travel, transportation and government and military. And again behind all of this is taking data analytics to the next level by using computers that can think about the data. I think it's actually all good news because quite clearly in the summary is Sundar, the new CEO of Google says basically we're going from mobile first to AI first. Computing will be universally available like air. We interact with it naturally. We're descending into a world of digital everywhere. There's fantastic opportunities here. I would say at this point there's 90% positive. There's 10% of issues, you know, privacy, application, losing control, all of those things that we're currently already seeing around us. But this is really a question of governance, you know, of policy. But really great to see that this sort of global brain is emerging and that's what we talked about earlier, right? Basically what we're talking about is a place where we keep all data and analytics and intelligence is kind of a global brain, right? We're all flows together. We're not talking about Skynet here just in case you're thinking about Skynet, right? Thinking about much more positive way. But this is a place where intelligent assistance is the number one thing that happens, right? I turned this around the word, right?  This is a place where you can go to the garage like pretty much every car will do in the near future. That is the low-hanging fruit. So to me, this is a really powerful thing that's happening all around us. For example, the e-mail service that Google has just launched that can answer the own messages, you know, very simply, quickly or slack where you can set up a meeting instantly by automating it and this is basically the reverse of artificial intelligence. A great, called Discover Weekly. Here's a funny story on this. You know, I used to be a musician and producer but under a different name 20 years ago and the other day I got the list by Spotify curated by a robot essentially by artificial intelligence and on the playlist, six of the 20 songs were mine. Of course, Spotify didn't know that it was me but recommended to my own songs to me which was kind of interesting.  Then we got rid of these songs, right? And then we have automated insights where you can write articles based. Computers write articles, right? We have IBM Watson doing the things for the jacket company North Face, right? I'll show you a short clip on this. Todd Spalletto, president of the North Face. We are working on the prototype to match customers to gear. Watson, let's give it a try. See, it's mid-June and there are 353 jackets. I can recommend nine. Watson, what if it rains? There is just a 3% chance of rain so I recommend the breathable stretch fleece-fuse-formed Dolomiti jacket. A perfect choice, Watson. No wonder our customer loyalty numbers keep climbing. I believe we can do even better. I like the way you... If you go to the North Face website you can actually try out this engine by IBM Watson. It's really funny. I think the bottom line is we shouldn't confuse a clear view with a short distance. This is working somewhat today but it's not entirely here. It's not like we can just go there and do this. It still needs a bit more time. So regardless of this we're heading into a new relationship of man and machine between the algorithm and the humor rhythm. And this is happening in financial industries, for example, on the bottom line level. And that's happening everywhere. That's actually a work and I've tested quite a few and it's really interesting angle. And then there's some people saying that maybe we shouldn't risk putting our knowledge in the hands of machines. It's kind of this back and forth between those two things. But one thing that's quite clearly happening is that we're moving from apps to the global brain so from the mobile phone to the digital assistants. Imagine if you have a real estate company and you're planning to build something. And now you do all your research online, you have people doing the research in the future just in a few short years. You sit down and say give me analysis of the city of Frankfurt the need for this kind of housing in this area. Very complex question and the assistant will get back to you 14 seconds later with the super power for us. Obviously commanding the global brain via voice control. That's right here. I mean if you try to use voice control now on a Mac for example it works pretty well. There's a few things that don't really work too well like mixing German and English words and names you know not so good in a year over. Most of our kids will never actually type with a computer. They'll just speak. Like a lover. I guess. Talk about that in a second. So you have apps like the Amazon Echo. Four and a half million Americans are using this at home. The Echo listens to you and then you say Echo please turn on the bedroom light. Play a song. Buy me some new toothbrush. Alexa order me some pens. Multiple matches in your past orders. One point two millimeters. Black ink pack of twenty eight. The order total is nine dollars and ninety nine cents. Should I order it. Yes. You could say this heaven or it's as hell right. It's hard to tell. I mean this device is listening to you the entire time. Literally the entire time just paying attention to whatever is you're saying it will know if you're drunk or tired although all these things about you right this is a minor infriction on privacy. But. So we're talking about these intelligent agents that can do a sector this. These are not dumb machines like Siri and Cortana used to be right they're actually getting very smart now.  I think I have alcohol poisoning and Siri suggests that you would go to the next liquor store to get some more. And today you can ask really complex questions and you'll get an answer from this global brain. So now we have these intelligent agents you know deep driving diving into into our heads you know finding out what's inside of us. Extremely useful but also extremely open to all kinds of abuse right and this is something we have to think about when you think about data because this is only years away not decades. This merging of man that machine that's really what we're talking about here. This is only years away. Not two years but you know most people say the singularity called the singularity the place where man and machine are have the same capacity seven to ten years and 2050 experts are saying that one machine will have the capacity of all human brains. One machine. So at that point you know the ethics are no longer nice to have. Imagine if we weren't thinking about the rules of how we use data when we when we get this we already have quite a few issues about that today. But why would we go down a road of the Internet of Things of connecting everything if we don't have a way of saying well who's actually in charge. How does it work. So when we think about data analytics you know it's inevitable and this is the power of commerce driving it clearly. So we have to think about you know what is the social contract in what we do. Who agrees to what. What's the deal. In this global super brain. I mean let me make no doubt about this right. There is about a chance of some 90 percent increased efficiency in having a global brain for example in logistics. There's some estimates saying between 40 and 65 percent of cost of logistics could be diminished by using a global database Internet of Things right. And this kind of concept. So now if you think about what does it mean where do we go with this you know what is the next step in this whole debate and that brings me to the what I call the era of digital ethics. Everything that we do today about data analytics artificial intelligence cloud computing has an ethical component values understand this is by KPMG and other companies like KPMG are very heavily talking about what does it mean for human life for our culture and for work right. I mean let's take the wrapper off we're going to have a lot less jobs if this works. If the large company wants to have less jobs less employees that's the nature of the beast. What do we do with this there will be new jobs. Yes. So you can be a drone operator rather than a taxi driver. But still you know whether we go what's the next step in this chain. So now just a few days ago the major tech company six of them announced this new collaboration called the partnership on AI to benefit people and society. Now that's an interesting term. Who would have thought about six tech companies having a partnership to benefit people and society. It's kind of interesting to see that this is the whole idea of saying what we do has responsibility. Finally it actually changes the world what we do. And here's a key question. We have to we have to actually put human flourishing first because a customer that likes you is happy is the best customer you can expect. Ultimately the goal of business is not efficiency. That's just one of the goals of the CFO. The goal of business is customer happiness. And then there's a question of control. When we talk about all these things you know what about our sovereignty sovereignty whatever that's a difficult word you understand what I'm saying. Who is mission control for humanity? Where is that data kept? This is a very important question. There is no doubt we can do all these fabulous things and we can do stuff like solve cancer and dying. Increase longevity solve climate change fix the energy crisis have abundant energy we can do all these things but how do we figure out who's in charge of this? This is a very important question. Who is mission control for humanity? Is it going to be Silicon Valley or even worse China? Or the two together? So when we talk about data analytics we have to think about examples like this one. This is the first example that's been a case a trial in the US that says if we have to release prisoners that are out on bail who decides if they get released or not because they may actually do it again. So the judges went and did this and their percentage was pretty good so they are 18.6% failed and came back or were repeat offenders but the computer failed better. The computer actually made better decisions on if people should be released or not than the judges. Well in this trial I don't know who ran the trial I'm not going to talk about that what do you believe what is better to do? Well you would say it depends that's not that black or white this case automated driving I think automated vehicles and autonomous driving will be in all cities all major cities around the world it will be a long time before in the German freeway in Bavaria we can drive in an automated car because there's a substantial difference in how we drive and why we drive and what the purpose of driving is in fact just now the German government yesterday announced that Tesla should no longer use the word autopilot because it's not it's not an autopilot call it a assisted pilot and this is the problem with data right this is actually a fantastic tool I mean I've been in a Tesla with autopilot it rocks right it's fantastic but it's not driving by itself I'm not turning the seat around and eating a hamburger well if I did I would probably not be here to show you this right it's called judgment erosion judgment erosion happens when you do things based on data that isn't actually so and that I think is a problem for example that was pointed out in the Guardian last week this psychologist pointed out that when the algorithms are getting better making decisions people often stop working to get better we actually take a seat back and let the algorithm take over it's called automation bias and so what we need to do with data analytics we have to think about well how do we go in the future that's not going to be like this right where we think of this as being a solution I call this machine thinking or even worse worm-holing finding a shortcut through space and time that's like saying I don't actually have to build a relationship with a person I can just marry a robot believe it or not there's people proposing this as well so this whole idea of saying what should not be automated that's a key question when we think about data analytics we have to think about what should be automated because there are some things that are not automated like these minor things on this side here you cannot automate trust of the customer you can destroy it by automation and you can further it by automation that's completely different trust is not generated with a mouse click but it can be helped with a mouse click it can be increased or destroyed with a mouse click so those human things are becoming much more important in fact I would say anything that can be automated will be that is an assumption I think that's completely clear let's say anything that can be digitized automated virtualized or robotized will be that's digital Darwinism that is going to happen the flip side is also true anything that cannot be automated becomes extremely valuable and that's us hopefully you in this room your kids some people like to say that basically if you can describe what you're doing for work then chances are you'll be automated this is I'm faring pretty well here because I can never describe what I do to my kids they're like you know you make money telling people about the future that's a crazy idea so this is an interesting interesting angle I think that we're pursuing here on this conversation but I like to say that every great algorithm needs a great algorithm a great human thing so when you use data analytics to make your business better you also have to think of a purpose and your brand and what you're saying in the context of all these things and rather than firing everyone that is now being replaced by algorithms maybe you could put them to good use somewhere else to create the algorithms the human part I work with a very large international chain of retailers and what they do is they say we don't need people at the cash register but now we're going to use the same people to do customer service advisory in the store right or online we train them to do something different to create more value I'll finish with this quote and then we'll have some questions very important quote from Alvin Toffler that talks about our future says in dealing with the future it is far more important to be imaginative than to be right to say that here this would be interesting angle we don't really like imagination in Germany so much we think about this this is kind of a dangerous thing productivity that's better but this is really important for us I mean look at this chart the World Economic Forum says what is the future of our skills it's totally obvious of course complex problem solving isn't always on top of that list but there's a bunch of stuff sorry that's new sorry about this people management emotional intelligence remember when the time when emotions were a total no-no at work emotions can't be emotions don't exist at work and now we're talking about emotional intelligence that is the prime new thing on this chart is emotional intelligence and of course creativity so here's the bottom line now when we think about this what is your choice are you going to be on team robot or on team human here's the choice that you're going to make there ultimately using data and being exponential with analytics is a clear requirement for the future at what point does it overlap with being human or not being human here's a great list of these things that I enhanced or diminished by my Frank Frank Diana he's talking about all the things that technology enhances and all the things that it diminishes and we have to think about what is the ultimate middle ground and I think that there's some CIOs here among you I think CIOs may very soon need to become chief understanding officers not chief information officers this is not really about information this is about understanding it's about this thing that makes us human so as a summary data analytics and intelligence and humanity that's our future the founder of the World Economic Forum says we must put human beings at the center of our systems now this means the center of DNA is human flourishing is put the human inside and to find the balance between the two I think that's ultimately the best value that we can generate Albert Einstein said years ago already computers are incredibly fast accurate and stupid well they're no longer stupid but okay human beings are incredibly slow, inaccurate and brilliant to which I would add expensive and together they are powerful beyond imagination I think that's the ultimate destination of data analytics that we want to get to thanks very much for listening and hope you join the rest of the day


You see Berkeley wants to build housing here at People's Park. But community members and students have made it clear time and time again that's not happening without a fight. If you're a Cal student watching this, get to the park. They've been here day and night all week long. This is our time to save People's Park. When the university put up fences to collect soil samples earlier this week, they moved unhoused community members' tents. So students set up their own. We belong here. This is our home. It's been the same fight for over 50 years. The university wants to build and the people want to save the park. But in 2022, the university insists on breaking ground and it may actually happen this time. I would just hate to see this park built on. Well, we know that there's certainly those who are opposed to the university's plans to address the student housing crisis. That has not had any impact on our plans. We remain very committed to this project. New housing will be for over 1,000 students and community members. Prominent supportive housing is for formerly homeless and very low income individuals. So they can live in dignity in the community. The park has been ground zero for community activism and organizing in Berkeley since the 60s. The university always owned the land, but they say housing is needed now more than ever. Only 40% of students live in Berkeley and Cal houses fewer students than any other UC. This housing crisis is not a crisis of housing availability or the existence of housing. It's housing affordability and housing accessibility. The community has many questions and concerns. They wonder if they can even afford to live there. Where the unhoused community members who currently live there will go and how those unhoused persons will be treated leading up to construction. On Monday, they showed up at five in the morning and told them to move their stuff. They should not be planning on building anything until they have a plan for where people are going. We're very clear with the residents at the park that no one would be evicted and no one would be forced to leave the park while that work took place. One of the reasons of supportive housing is to make that housing deeply affordable. But it wouldn't be People's Park if there wasn't resistance each step of the way. People's Park, we want to make this a good space not only for the residents, but for everyone in this city. We're not worried about burnout. We're going to be here. And we're going to be here until the very end. Amanda Ramirez, CalTV News.


Okay, hi everyone. I'm Julia and today I'm talking about the recipe for enduring and meaningful workplace relationships. Who is this talk for? We might think relationships come easy and naturally but more often than not workplaces are riddled with tensions and stresses which can make work spaces uncomfortable and unproductive. Building, enduring and meaningful relationships require effort and practice like any skill and at times we can feel uncomfortable about the effort required to focus on our workplace friendships as it can take us out of our comfort zone or make us feel vulnerable because we are focusing on something which maybe we're not particularly good at. This talk is designed for anyone who wants to lead positive change in their workplace but is mainly focused on the people who are here today who feel that their organisation is not doing enough to create a positive work culture. So first up about me. I am a Drupal South Committee member and I've been working with our teams building Drupal site since 2007.  This was Drupal South Brisbane last year and that photo up the very top there that's the first dinner I had with the Morphed team six months into working at Morphed where I'm currently head of delivery. As you can see from the photos I also love animals so we've got Arnie there, Luna and Otis the cat. I'm also a food junkie. Must be something to do with web development agencies and food and oh sorry my notes have gone a bit weird. Yeah and yeah so it's just I guess this is a collection of all the things that I sort of do. Also I'm quite big in the volunteer space as well so I've spent about 16 years volunteering for organizations like Rotary International working with kind of the most disadvantaged people in the Melbourne community. So I have a very well-rounded busy life I like to fill in all of my gaps and spaces often to the complaints of my family. Anyway moving on I could talk for a long time about the kind of things that I love to do. Okay so what turns a workplace sour? Some of the key things that can turn a workplace sour include negativity, fear of failure, confusion, drama and gossiping and this can lead to kind of unhappy people and unproductive work environments. And as a result of that I think in a lot of workplaces we can experience high staff turnover and certainly dissatisfied customers. So the core ingredients in my recipe and what we will be covering today are active listening, making time for people, asking for help and offering to help, being positive, setting boundaries, being gracious and skiffing gossip and focusing on creating inclusive environments. And we're going to whiz through, we only got a few minutes. So active listening it's about taking the time to listen to what people are saying. This requires giving people your full attention and developing skills such as repeating back their words and confirming that you've understood what you're being told. This will ensure that the other person knows that they have been heard and that your values, that you value their thoughts and opinions. Make time for people. Let your team and clients know that you care about them and the things happening in their lives and what's important to them. Remember the things which are important and make sure that you connect back to them so that you can build empathetic connections. In a big team it can be sometimes hard to stay connected to everyone and time can pass really quickly when you're focusing on work. So make sure that you're making that time to have a chat or if you're meeting regularly make sure you're taking the time to have a social element to it like icebreakers. We've just learnt. And when you ask people questions like what have you done on the weekend or what plans you might have, remember to check back with them later on in the following week to continue on that conversation and build that rapport. So know when to ask for help and to offer to help. So everyone loves to think that they're valued and respected. Asking for help and asking opinions from those around you lets your co-workers know that you respect what they bring to the table. Likewise asking for help can build deeper bonds and trust between co-workers and develop an implied understanding that you have each other's backs. Be positive. Focus on solutions and a way forward. Saying no or it cannot be done closes a conversation. Look at ways to continue the communication. The more you talk through an issue the more likely you will uncover a remedy. My boss, Margie, has a common statement for problem solving which is called the rubber ducky method. You can check this out on Wikipedia but essentially the theory is that a programmer who needs to debug their code can actually use an object like a rubber ducky to explain, to verbally explain the problem to the duck. And as a consequence of explaining that problem, step by step will come up with a solution through that simple action. It's a really good method to use when you're programming and trying to problem solve but what is even more fun and rewarding is actually talking to your team and together coming up with a solution. Setting boundaries. Setting boundaries between work time, which is focused work and chat time socializing is important. Make sure that you make the time to deliver on your commitments and be a productive member of your team. Showing gratitude. So let's face it. thanking people and being gracious is just good manners. Moving out of the COVID phase we should still remember the things we've learned from that experience, such as being more understanding, more accepting, more flexible and more grateful. Skip the gossip. So rather than feeding gossip or creating niche groups at work, take the time to have open and fair conversations on challenges you have with someone. Take the time to find out the common ground and shared interests that you might have with that person. Building an inclusive workplace and creating spaces where people can explore the things they have in common is really important. Let's face it. Work is a big part of all of our lives and we all want to work with people we like and in an environment where we can be comfortable. So tasting notes. So a creative positive workplace culture promotes open communication, respect and teamwork. And also a happy workplace is one that a client generally love to engage with. But it takes time. It takes practice like every skill that we develop over time. So we just need to think about it and spend the time making the effort. Thank you. Any questions? It's a really tricky one. So the question is how do you move from a social conversation or a positive interaction into the workspace? And it is very much a kind of like a challenge on how to articulate that. So some of the language that I would use is that's really interesting. I would love to spend some more time talking to you about that. Maybe we can catch up because I work mainly remotely. So maybe we can catch up on an online lunch and follow on with that conversation. But we really need to get back and get this work done now. Yeah. That's the kind of approach I would take. Yeah. So I haven't had that exact experience but I had a similar experience. I think it was one of the first projects that I worked on at Morved where I came in as a contractor. So I was not exactly part of the Morved team but I was coming into that team. And the first job I had was to be a project manager on the digital transformation for I think it was four or five websites for a government agency. And we were all working remote because it was during COVID. And the project manager in the government agency was not turning his monitor on, his video camera on and he was being very silent. So he was really inaccessible. So one of the things that I did to break that down was I organized an online lunch for everyone. And I invited our team and their team together. And he came, sat in the background with his camera off but he started to talk. And interestingly enough, the subject that we connected on was food.  And in particular, he was really into into rubs and barbecues, you know? And it can be something that small that can be an absolute turning point. And today, like we're now three years down the track and he's a great mate, you know, we catch up on the phone maybe once every two or three weeks. So yeah. So I would recommend something like that where you're getting together. Yeah, yeah. Yeah, it's really challenging and it's something that you have to jump onto really quickly. A group of people working together once that toxic atmosphere comes in can turn really quickly and it's really hard to wind back. I find, for me, you know, like kindness leading, you know, by example and facing those issues front on rather than letting them kind of fester underneath. Like if you leave them untouched and don't address those concerns, they're only going to get worse.  How can we work through whatever these issues are together? Yeah, and I think it's really important today, you know, in building sort of inclusive environments and recognizing that we're all different and actually that's what makes us all amazing people. But together, we're even more awesome. Thank you.


How do you evaluate your added? Yeah, a bit of a grind, some really good pitches, some poor pitches, some excellent defense, some good catching, some great offense. We were able to stop them when it really counted. I was fortunate to get with the lead twice, but it's a good team game. You mentioned that it was a little bit of a grind. What do you think made it a bit of a grind for you tonight? I mean, it's post-season. They're locked in. We're locked in. I mean, trying to make as many good pitches as we can, but they capitalized on a few mistakes, certainly. And that's probably from some poor location, just not quite bringing out the best game possible, which is going to happen. So we had to duck and dive a little bit and then roll with the punches. What impressed you with the defense that Gio provided behind you? Oh, yeah. He was just showing off that one inning.  No, I thought the defense was great all around. It's a surface that nobody on this team is really familiar with, which can pose some challenges, I think, especially because how quick it is. But we were on top of the wall. And we made some good plays. And so, fortunately, it worked out for us. Thanks, there. Next one to Tom Marion. Can you talk about the contributions of Figesioka tonight, both behind the plate and at that? Yeah, I mean, the power stroke is there. He walked tonight, which is a very rare occasion for him. But I may be biased. Probably the most important play of the evening from Kyle was when I crossed him up with the curve ball to Margo, just to be able to keep it in front would have been nice. But to catch it, that goes to the backstop. And it could be a totally different ball game.  Next one to Bruce Beck. Garrett, the strikeout of Margo and the fifth game on the wide bases loaded, is that the kind of situation that makes the postseason special and that you thrive on? Yeah, that's fun. It's fun. Big pitch, big moment. Executed it perfectly. Glad, because I really got myself into a bit of a mess there. Next one to Aaron Bolland. Garrett, you've been very complimentary of David Garcia, just wondering your thoughts on him getting the ball in game two tomorrow. Yeah, excited for him. I remember my first postseason start. The nerves will be there, but they'll never go away. We all get nervous before these things. So he's very poised. He certainly is on the ball well for us. He's in a good position to take the ball and lead the charge. I'm sure he's going to remember it forever, and he's going to have a good time. Next one to Tyler Kepner. You've seen the Yankees over the years do this sort of thing, October, be at their best. Is this kind of what you envisioned when you signed here that the Yankees would look like when they are at their best? And what makes you guys so dangerous when you're playing at the top of your whole team? Yeah, I mean, it's kind of an every year thing for me. I think ultimately, you want to be playing your best baseball when it's the most important. That's how you get to the ultimate prize. So whether it's the Yankees or any other team, that's everybody's goal. Obviously, leading the charge with the most amount of world championships ever, more often times than none, the Yankees have come through. So thankful to be a part of the organization, thankful for the opportunity to lead the charge into the postseason again. And the second part of your question, what makes us so dangerous? I think, obviously, the talent level. I mean, we have a lot of really, really good players, but we have a lot of really smart players. Good common theme between all the good teams that I've played on is high level of communication, whether it be talking about the pitchers in the dugout from the lead off guy to the nine hole, or whether we're talking about defense, conversing about how we're pitching somebody, maybe trying to get an edge in terms of shading one way or the other. Just any sort of feedback from anybody, facilitating that conversation is huge. And so we do those things well. Next on to Bradford Davis.  Did you feel like you had any issues, particularly with basketball, come in? And also, I guess, what do you know, is there anything that you give so, is there anything that you're working on to try and make sure that you're hitting the spots that's not right? It was probably not as good as last start. Certainly, let's see, certainly a few times losing some cattle leverage, trying the top of the zone or trying the outside part of the plate to the left-handers. I thought we got the ball in exceptionally well to right-handers today. At times, we commanded the zone the way we wanted to. Some quality misses towards the upper part of the zone or towards the side of the plate that we were working. But at the same time, there were some pitches there that cost us some 2-2 counts to 3-2 counts. And then, obviously, with a Rosa Reina, you could debate whether it's a bad pitch or whether the whole problem was getting the 2-0 in the first place.   There was another good swing by Rosa Rana later in the game on a fastball, kind of challenging middle up, maybe a bit over the zone, blocked it off through the other way. But I would say it's not its best, always room for improvement, but it was good enough.


Right, we've just arrived at Renaissance and we're not going to find out what is behind those gates just yet I'm gonna have to press this button or thing. Press to open. Yeah Right, let's find out what is hidden behind these gates, Lou This is the first time it's beyond the wall, isn't it? It's beyond the wall. King of the North But that grass is long. Don't go, I thought you were driving well, Lou. It makes it sound like there's a lot of room down there, doesn't it? There's plenty of room down there, revealing winds, so So three-way off the tee for me, Lou. Get that back there and let's see what happens. No pressure, Lou. Just think the tad down the right. Right, really excited to get out here at Renaissance. We're very lucky to get out here just what is about four weeks away from the start of the Scottish Open. Great to have an experienced caddy show us around this place and or guide us around this place and The whole point of the day is to show you what this whole venue is like and hopefully me and Louie are having a bit of fun along the way. From here to the flag. To the flag. So I would definitely recommend down the left side of the fairway to give you a better look at it. Like an A-side or something like that. Yeah, that'd be two A-hands or something like that going in. Maybe a bit longer. Yeah, you can probably go a bit longer. So you can see the mound in the fairway to the left of the flag there. You can go down there about 180. Try that, yeah. I'm sensing a bit of air. What are we doing here in the middle? It's all going to have a caddy, but I don't want to let him down. Yeah, I was just like, he's called the shop for you and hit a bit. As he just shouted down the left for you. And that's perfect, isn't it? Yeah. I think it's just bounced off the fairway. Just to the left, but it was a nice strike, Lou. That's it. Great start, but out of much excitement. Well, I don't know what it is for me having a caddy. I absolutely love it. There he is down there. It's not a gazelle watch. He's actually looking for my ball. So this is going to be the second hole when he play the Scottish Open up here in just a few weeks from now. 5, 10, did you say from this? From the back. So they're a bit further back. We're just a little bit further forward of that. But what a gorgeous golf ball that is. 480s long enough for all of them. 480s long enough for all of them. This is stroke 1 as well, did you say Gary? That wind's dropped. I needed to carry this too. Now it can get windy again now. Put a smile on my face, I'll be honest with you. I'm only two holes in and I don't smile a lot as you know on camera. But that is a smile, trust me. I'm a bit miserable, Gary, when I'm playing golf. That's alright. That is a smile. No, not really. I don't raise much of a smile. So you'll be a bit tighter lying on the... So more on the side of that big tree. The next stage you're going to head for driver. Things are going well at the minute, Gary. But you do know I'll go all Jordan's beef on you if it goes long or not. Two holes in, mate. It's incredible, do you know my biggest enjoyment is having a caddy? It's crazy.  It's unbelievable.  No, I don't think so. Why was I at the YouTube off there? You were a caddy, mate. You were a hindrance. You just... Was I a more videographer? You just tutted a lot of my shots. I thought I was there for that. The mis-tapping compilation. Three hump and bump on these greens. He straight to your ball, he's marking it, he's cleaning it. He's giving you your yardage. And maybe for some people it's not such a big deal. But for me on a personal level, it's making a big difference to my experience. I'm loving this. And as I've said before, smiling quite a bit more than I would normally. Driver off the deck, Lou. Driver off the deck, mate. Driver driver. It's a bit windy, isn't it? Look at that. That's a fist bump, mate. So we're like... Not just like, on into, we're like pin-seeking. Mate, we're going after this place. We're going after it. Such as to happen. How does this work then, Gary? There's obviously... He's not a man who could have helped you. So, on the bigger events, we've put some people out here to serve our guests and our members. On the one-time experience, none of the carry will look after the players and our guests. So it's an honest state process. You just put your name on the sheet. And then you pay for it later on after your car. After you leave. Yeah. So that's kind of what happens. The ideal line is off the high left side of the fairway. Yes. Short of the bunkers. Probably in the region, it's 200 yards away based on the winds. Did some wind there. Right, so we've got Lewis. What have you got? A bit of breeze. When it's breezy, it's going to get easy, is that what it is? That's what they say, mate.  It's playing... It's 160, playing 185. Is the sort of shout from the caddy? And he doesn't get it wrong. Oh, Louie. Louie, I'm loving that. What a golf shot. Oh, that is just a pure strike, mate. Well done. I love that strike. Great shot, Lou. That is so good. Let's play a game, mate, of how many good shots in a row can you hit? It's been... How do you quantify sort of... How do you quantify happiness on a golf course? What is it that floats you about? What do you want from your golf? This kind of experience, it comes at a cost, but it's called a one-time experience. And I think that's the thing, it's a special occasion. For most of us golfers, this is not something we're going to do every day, but if it's a special birthday, it's just that one-off occasion. Then what you want to do is that experience needs to be special. You need to feel like you're effectively treated for me. I feel like a professional golfer. I can't hit the ball like one, but at least I may to feel like one. And these people here, right throughout the staff, from the minute you arrive, it's a very warm welcome. You're not made to feel uncomfortable, you're not made to feel out of place, and it's a great environment, a real great environment. Like I said for me, just making me feel, yeah, important for the day. Well out. You've got this shot though, I like it. I like you with this shot. I'd be happy with that from there. Half a cup on the right. Oh, great effort. Right, so let's get some comments down below and tell me what you think of this experience that I'm lucky enough to be having here today at Renaissance Club. What do you think of the course? I think the players will do it with the Scottish Open. What do you think of the experience? What do you think of this whole thing from the minute you arrive? You're met by this cad, you're met by this whole team. We're going to have a further look at what happens post round in the clubhouse very, very shortly. We're getting there to the end of the round, but yeah, I like your feedback. So what have we got? Just explain that again for us. So we've got two types of sausage. We've got the North Barrick, which is beef, chili and black pudding. And then we've just got chorizo sausage as well. Brilliant. You're welcome to. Dive in, yeah? Dive in, yeah, sure. You all right with one hand there or do you want to grab another hand now? I'll make it on here. I'm not. I just got a bit too much for it. It's going to go bad, you know what I mean? So this is normally, what hold on would this be? This fifth and everyone at the end of this hold will, someone will come out and offer them sausages and if someone wants a drink we'll go up and get you a bowl of water or whatever. And then when is it ready? And then we'll get that to you once you've teed off on the sixth. Right. Nice. And that's part of the one-time experience. It's for everyone. For everyone that, everyone that plays. There'll always be someone making sure that they're down here too. Yeah. It's nice isn't it? To be, yeah. They're in there in the wind. I'm sure. 119, Suffolk's Bar 3 in Scotland. I've seen him play this so many times. This could go in the hole. It's all over it. He's ironing it up and down. What a shot. I'm going to give it a bit of ace cam then. That's a super shot. Well done. I knew you'd play that well. I had every faith in you. Yes.  North Beric sausage and Territo sausage. Beautiful. Beautiful. Wild old sausage. So that's Lewis. And our man is giving him an instruction to put right up the hill there. Lewis is not looking at that line when he stood up there. So that's not too bad. Well I'll tell you what, he's absolutely played that in terms of pace. I'll tell you what, Lewis. That's some effort, mate. Thank God for the caddy. I'm glad you're all there. What a great drive to finish with. Centre of the fairway. Lewis, find words. Do you have any? I need another one of them. Fantastic shot. How are you feeling, mate? Confidence. You've been that well. Five-yard bullet draw. You've hit that. You've hit that. Absolutely superb all day. I need one more, though. Beautiful shot, mate. Always had confidence. It was going to carry that. There was like a deadly silence. We watched it carry. That was like Michael Grell Jordan's beating to the action there. Positive. Friendly. At all times. We get a free drop from there lying aside, mate. That's it. Up and down for par. Right, Luke. Come on. Small of us needs to finish in a blazer glory and it's not going to be me. So, over to you. Come on, nice finish. Well, we've got one 70-yard into there. Still 200 into the breeze. Or playing 200 into the breeze. But this man's got it. That's a pure strike. Picked that one up in the sky. Yeah, great strike. Well done. Like it said, mate, exactly as I visualised it. Off the roof. Yeah. Little bit of draw. Seen the camber. Feed it in off the roof and... Oh, it's a bit of a pipe all the way. Super that. Just coming down off the slope there. I'll play that. Well, that's it from the caddy in terms of the line from Gary. He's been amazing. There's a birdie. It's a great puffer up there. Well done.