Hello and welcome, my name is Shannon Kemp and I'm the Executive Editor of DataVersity. Excuse me, Chief Digital Manager. I've got to update my title. We'd like to thank you for joining the current installment of the Monthly DataVersity Smart Data Webinar Series with Adrienne Bowles. Today, Adrienne will discuss streaming analytics for the Internet of Things-oriented applications. Just a couple of points to get us started. Due to the large number of people that attend these sessions, you will be muted during the webinar. For questions, you'll be collecting them via the Q&A in the bottom right-hand corner of your screen. Or if you like to tweet, we encourage you to share highlights of questions via Twitter using hashtag Smart Data. If you'd like to chat with us or with each other, we certainly encourage you to do so. Just click the chat icon in the top right-hand corner for that feature. And as always, we will send a follow-up email within two business days containing links to the slides, to the recording of the session, and any additional information requested throughout the webinar. Now let me introduce to you our series speaker for today, Adrienne Bowles. Adrienne is an industry analyst and recovering academic providing research and advisory services for buyers, sellers, and investors in emerging technology markets. His coverage areas include cognitive computing, big data analytics, and the Internet of Things, and cloud computing. Adrienne co-authored Cloud Computing and Big Data Analytics, published by Wiley in 2015, and is currently writing a book on the business and societal impact of these emerging technologies. Adrienne earned his BA in Psychology and MS in Computer Science from SUNY Binghamton and his PhD in Computer Science from Northwestern University. And with that, I will give the floor to Adrienne to get today's webinar started. Hello and welcome. Thank you, Shannon, and thanks to everybody out there. Sometimes when I start these, I feel like I'm talking about my kids.  But when I look at this topic, it certainly is a favorite for me. Looking at the futures as we move to a world of streaming analytics, and in particular, as we look at the opportunities that the IoT is going to bring to us. So to kick it off, I'd like you to imagine for a minute a world where everything and everyone is connected. Augmented in instrumented reality is reality. So let's talk now about how close we are to that world, how we'll get there, and how you should prepare now to thrive in it. Spoiler alert, we're almost there. So today, what we're going to do is I'm going to present some context, what the IoT does for us in terms of new data and demands and opportunities. Then I'm going to outline sort of a view of what streaming analytics is, what it's all about, the types of technologies and the types of questions you should be asking. We're going to look at some of the open source projects and libraries that are supporting streaming analytics and supporting IoT development. And then briefly close and look at what some of the interesting vendors are doing in this space. So starting out, when everything is connected, what happens? And when I say everything is connected, I mean that every device, basically everything that's manufactured is producing some data about itself or about its condition or about the environment that it lives in. So there's lots of these. And I don't like to quote numbers in terms of how many billion devices there are, but we're at the point now where devices are outnumbering people, just like certain insects outnumber people. And that's only going to continue, particularly as the underdeveloped areas of the world develop. We tend to have more devices than we have people. And I think that what we're going to see is that as the cost of building sensors to report on conditions drops, and it's very low right now, the speed at which we instrument devices is going to increase. So we need to challenge some of our assumptions about what is worth instrumenting or turning into a device that reports on itself and what isn't. This slide is one that I've been actually using for a few years now. It's from 2014. This is a view from a website called Thingful. It was in beta in 2014. It was an attempt to create a search engine for IoT devices. And the reason I use this is because I first discovered it when I was giving a talk at the Seaport Hotel and found that in close to real time, I could look at this site and discover how many empty spaces there were in the bike rack at the hotel. You could zoom in and look at each of these dots. The different colors represent different types of devices. But the point here is that they're all over. They're different types. Out there, some of them are for commercial purposes, like the Seaport. Some of them are for safety purposes, like some of the sensors in the water. They tend to represent things like a buoy or a signal. And the challenge is to figure out what value we can get from the data that they're producing. If you're in the business of creating the data, then that's a different way of looking at the world. But today we're going to look at it as all this data is out there, more is coming. How do we build an architecture that supports it? How do we analyze the value of the data? Are the values of the data and then create value? Sorry, two different versions of the same word. When I say the value of the data, I'm talking both about the economic value and the actual data itself. So we know, and I'll go fairly quickly through the first few slides here, I just want to kind of set the context in terms of the scope. And this one's, again, from a couple of years ago, a locomotive, the GU's featuring, creates 150,000 data points per minute, and these locomotives are expected to last 20 years. So if you think about what that does in terms of the life of the locomotive, how much data is created, it's just a vast sum. And I was thinking about it last night. In terms of just my own week, I started the week in Connecticut. I drove to an airport in New York. There's data being generated at that point by my phone, by my car. There's sensors in the car. Get on an airplane and go through the TSA. First of all, there's additional data being generated. Get on the plane. One of the things that everybody talks about as an example is how much data is actually being produced by a jet engine today. So Delta Airlines reports, or it's been reported that they typically process about five million business events per day. And inside joke with Shannon, I would say it's a little more when it's raining in Atlanta. But on a typical day, five million business events. A Pratt & Whitney jet engine. It's 5,000 sensors. They're producing 100, I'm sorry, 10 gigabytes per second per engine. This happens to be a Pratt & Whitney engine out of a SR Blackbird. This one predates all the instrumentation, or actually maybe it doesn't. We just know what they had a few years ago. And Formula One cars are now producing about 1.2 gigabytes per second. So if you look at all that, these are producing data that we can use for everything from forecasting fuel usage to maintenance requirements. But we also would like to be able to predict the future. So when I say predict the future, predicting things like the engine is going to fail, or a part is going to fail, or a part is going to need to be replaced. We've got all of this going on around us. And the question is, how do we take advantage of it? So one way to do this is sort of a simple two-tier IoT architecture where the dots on the left represent sensors. And if you think about that bike rack for a minute, that's a pretty simple sensor. I forgot how many spaces it had. They've had 12 spaces. And each of those has a sensor in it that tells you whether it's being used or it's open. And now they can report. They can report to the world. Generally, you're going to want to have some system, some compute engine, which may be something as small as a Raspberry Pi. It may be a network. It may be a data center. It may be access to an application in the cloud. And that's fine if you have a couple of those. But as you start to build up and scale up, you really just kind of go into it. Now we think about this as being the jet engine example. You've got hundreds of things in the engine that could fail or that could give you information about activities that you should be undertaking. And as that grows, as the number of sensors grows, it just becomes unwieldy. There's also the issue that sensors can either be in motion, as would be the case with a jet engine, or in my car as I'm traveling, or if you've got sensors on a cruise ship, for example. And a lot of the time, they're not going to be in constant contact with a stationary and reliable compute engine, if you will. So this is not something that scales. What you want to do, what people are doing today, is moving to a three-tier IoT architecture where you have the sensors and you can still have an external compute engine. But between them, aggregating the data from the different sensors or devices are gateways or intelligent gateways. And one of the companies that's doing interesting work on this, I did a few interviews with them recently that are on YouTube. Red Hat is building some interesting intelligent gateways. It's kind of that buffer between the devices and the compute. But once you start to do that, and what you're doing is obviously creating a higher bandwidth, but fewer in number connection between the devices and where the computation is being done, that simplifies things, but it also gives you new opportunities. And so what we can do is to start to move the analytics, the evaluation of the data itself from the compute engine and create these smaller compute engines, if you will, at the device or at the aggregation level. So if let's say one of these is maybe we're doing a automobile system and the pink color here may be representing information about the engine, the purple, maybe about fewer tires. And instead of having a system like this that's reporting on each tire, including the spare, so you've got product going into the dealer or the manufacturer, that gets aggregated. And so you could actually cut those lines, the dotted lines, and say, okay, maybe we need to be able to push intelligence and computation out closer to the edge, which is what we show here. And so maybe we can do some things that require heavy lifting. Like we're going to do a machine learning model to help do predictive maintenance on an engine. We want to get a lot of data. We need to train this. We can train the model in a data center. That was the topic that we talked about last month, the webinar. But you can actually deploy it. You can compress and deploy the deep learning model on an intelligent gateway. So now we're moving the intelligence closer to the edge. In fact, it means that we can kind of cut the cord and we're doing things as they happen or we're reacting to things as they happen close to the source of the action. And that has a number of benefits. It means that we're not as dependent on connectivity. We can, in the case of the locomotive, for example, we may choose to send some information back to the manufacturer, to the leaseholder or a lease engine in real time as things are happening. Some things we may just batch up at the end of every run or at the end of every cruise on a ship. Then we offload the information. So now let's just distribute the intelligence and the analytics and the computation. And so we have things closer to the edge to the devices themselves, to the sensors, where some computation is going on. We've distributed that. And then ultimately we can do the things that require, don't require real time response, get pushed into the cloud or the cluster or the network or whatever sort of device we use. Now, what happens when we do this, though, if we, sorry, going back to the picture for a second, if different companies are manufacturing devices for different functions, you know, if you were thinking about the automotive world, for example, there are several companies that are actually manufacturing cars, but components of cars, there are, similarly, there's a market there, and you'll have half a dozen of companies that are manufacturing tires, different companies that are manufacturing spark plugs, and one car may have components from several different manufacturers. What you want to be able to do is to have this intelligent gateway gather information from the different devices in a way that's standardized so that you can plug and play and you're not dependent on any one manufacturer. And that's where things like the Industrial Internet Consortium come in where companies like Cisco, GE and Intel, IBM and some of the other members, the founding members here, and now there are lots and lots of companies, but we're on standards for communication between these devices. And really, that's what enables us to build the type of gateway that I was talking about. So, looking into where this is going, now we have different companies that are providing platforms for this communication, and just name some of the bigger ones that you would know about. But as we start to do that, think of these as the infrastructure companies, think of these as the companies that are building the roads, if you will, that we might travel on with all this information. We need to get from the platform level to building applications, because that's really where the, I don't want to say where the interesting stuff comes from, because if you're working with a platform company, that's pretty interesting, too. So now I want to look at what is it that's going to be computed and communicated from these various devices. So, very simply, we do a number of chats on analytics if you have questions about this part of it afterwards, or any of them, obviously, just to get in touch. So, when we talk about streaming analytics, let's have a common definition here first. When we talk about analytics, there's generally a hierarchy. Descriptive analytics are things that describe the known data values. Everything is known, so if I have test scores for a particular class at a high school, I know what the values are. Descriptive analytics might be the mean, the median, the load, different scores. You can tie that and say, the students, we can rank them. There's no uncertainty there. There's the values, and they're easily computed, and they simply describe what has already happened. Higher up on the stack may have predictive analytics, this is where most of our efforts are today, that use statistics and a model of the world, including your assumptions about the data, whether it's uniformly distributed, what sorts of rules it follows. But predictive analytics, which gets us into machine learning, is where we use algorithms to look at the values and compute or estimate with some level of confidence missing values. So, if we have information about 50 classes of students, and we have another school that has comparable values for other things, then we may predict how they're going to score on a particular test. So it's either filling in something that has already happened, or it's predicting what people are going to do next, and this is where we get things like recommendation engines. Prescriptive analytics, not as common, that's where we have statistical models that tell us not only the prediction, but what's the next best action. So it's a combination, really, of predictive analytics, if you will, and operational research telling you what to do next. So that's the analytics part of streaming analytics. On the data side, the streaming part, I just want to build a similar hierarchy. When you think of data, it's in a database, for example, it's not going anywhere. Once you put it in, we can change values, but if we take a snapshot at any given point in time, the data is there, so it's static. If we take it a little higher up, what I refer to as the stop and frisk, data is going from one place to another, and we divert it so that we can analyze it. That could be if you're doing water samples in an environmental study, you go out and you take water out of the population, you do a sample, and then perhaps you put it back in, maybe you don't, but basically it's changing the flow of data so that you can analyze it. And at the higher level, we have the data that is actually in motion, and what we want to do is to analyze it while it's moving without changing it. And that's where we get into the whole idea of streaming analytics. So the problem is, as we've known for hundreds of years, you can't step twice into the same river, meaning that it may look the same, but you don't know the actual values that are in there. And so this adorable little kid is in the water, and if he goes in tomorrow, this one goes in tomorrow, it's going to look a lot different because he's 17 now, but there are different things in the water, even though a lot is the same. You need to be able to take a snapshot and say, what is it that's important that we want to measure? So we need to be looking when the data itself is moving. Is it something where we can divert it? Is it something where we can pull it? Can we put it aside? Can we evaluate it without changing the flow? And for those of you that think in terms of physics, we're talking Heisenberg here, by evaluating something, are we going to change it? In terms of data, that's often the case. We have to divert it, we have to delay it, or we're going to sample it. And sampling is valid under some conditions, but under others it creates more problems. So let's take a quick look at that. So streaming analytics, we're looking at, I'm going to take a prescriptive off the table for the moment, but descriptive and predictive analytics at data that's moving. So when I say streaming analytics, I'm talking about statistical analysis of data in motion. The main issue is, are we going to move the process to the data, or are we going to move the data to the process? If we move the data out of our streaming, if you will, we pull it out, we can either sample it, or we can make sure that everything goes through a place at which it can be monitored. Think of it as we have water going through a canal, and we have locks. We can stop it, and we can look at it, and then let it go on. But that changes the nature of the data. It changes the value of the data. So the conventional architecture for data analysis is that we've got data flowing on the edges of this graph. We've got the queries that we do on the vertices. So there's a stopping point. So when something is held and it's analyzed, I think when you see documentaries and birds are taken out of the population, they do some measurements, they put a band on the bird, and they put it back in, that has changed the results are not what they would be if the data hadn't been moved. Moving to a streaming architecture, a real streaming architecture, but we're going to see some examples on that. What happens is at any point where we're going to check this, we're observing without deflecting or diverting, and that requires different technologies, and unfortunately the good news is, of course, that they're out there today. There's some interesting stuff going on. I want to talk about how we're going to take advantage of it. So just a quick note when I talk about sampling. If you have a signal and you're looking at data, which is an analog sine wave, depending on how often and when you sample it, if you're not looking at every data point along that curve, as it goes up and down, in this case, I just sample every period, it would look like, this is a frequency 440 Hz versus D80, even though the sound itself is going up and down, or the signal is going up and down, I could sample it like this inadvertently, and then if I go to plot it, it's going to look like it's a constant 880, but if I sample more frequently, and we've got an analog signal, then I can get a more accurate representation. So when we're doing streaming analytics, and the signal is something that has a variance in amplitude, for example, or in frequency pitch, then it becomes critical that the model that we have for how the data is created is accurate and we know how to sample it. For the rest of the webinar, we're going to just focus on things that are where we're not sampling, where we're really going in, and we're going to try and look at every data point. So I'm going to ask you, again, to consider sort of this world where you as an individual are producing data, and some of it is streaming data, some of it is more static, there are things around you that are creating data, and some of those are streaming, and some of those are right in your physical space, if you will. And I think that the way to think about the future, the stuff that's really interesting and exciting and challenging from a technical standpoint is when you have an individual and you have data about them and you have data about the immediate environment, not what I'm calling environmental data. And just as an example, this morning, actually in San Francisco today, I took the train up from San Jose further south. As I was looking on the phone, my iPhone, a typical smartphone, has a lot of sensors. I looked at it and I saw my location. I could see it moving. So I was creating data by my device. It could have been monitored. I happened to check in on my son to make sure that he'd made it to school on time, 2,500 miles away. I could see because I could see the data from the sensor on his phone, the guess at that point he was at school, or at least he was smart enough to send his phone to school, but he didn't. But now you start to look around and say, okay, as I'm traveling on this train, there are things around me that are creating data. And by knowing about my data and that data, those are new opportunities to create value for me by being aware of what I'm doing. So let's take a look at the types of infrastructure that we need to build systems that can leverage all that data. And then look at who's doing what in the space. So this is one area where you really can't, I don't think today you can see any enterprise-grade system or any infrastructure upon which you would build an application that isn't heavily dependent on open source software. It certainly made the argument that you can hardly build anything today without using some open source in your infrastructure stack. But here there's just no way around it because to do the kind of systems that we're talking about, collecting analytics on data that's streaming, as soon as it starts to scale up, we need access to systems that can collect the data, aggregate data from different sources, and then do the analysis. And so I'm not going to read through these.  This is a good starting point. These are a number of projects from the Apache Software Foundation. So we've got Apache Apex, Link, SAMHSA, Spark, Storm. All of these are projects that have found a following that creates software at the infrastructure level, if you will, that enable you to build systems on top. So I'll just take a couple of Apex. It's a unified stream and batch processing engine. You get into SAMHSA. It's a distributed processing. But here it uses multiple levels of other pieces of open source software. In this case, SAMHSA uses Kafka and Hadoop. Just in the interest of time, I'm going to just say, if you're dealing with something like Hadoop or Spark storage engines, this is where you're going to put your data so that you can analyze really large quantities of fast-moving data. One of the recommendations at the end, and I'll just sort of foreshadow it, is that you really need to start looking at what's available there and which of these projects are getting the most support. These are all fairly well-established. And just as, going back to 1999, 2000, so less than a couple of decades ago, when Linux was just starting to get commercialized, Red Hat did their IPO in 1999, there was some resistance today. I think we're past that, and most people would look at this and say, okay, yeah, if something has made it through the Apache Software Foundation, it's now a top-level project as most of these are, then it's something that's stable enough it has enough of a community behind it that we can start to look at products that are developed on top of it. It is a pretty rigorous process to make it to that level. I mean, like most things, there are a lot more projects that are started than finished or that people contribute, but it doesn't make it to that level of rigor, if you will, where a group like the Apache Software Foundation will promote it as a top-level project, like Linux became and Spark, et cetera. But now we're at the point where this is the place to start, I think, if you're interested in building a fully instrumented world, you need to have a data architecture that can handle the volume you're going to deal with, and one that's going to be developed and refined. I like to think of it that when we're dealing with some of these open-source projects, it's not that, I mean, it's nice that something may be available for free or at low cost, but the reality is that most people that are using these, the results of these projects, are getting them with support from a commercial vendor anyway, so it's probably less expensive than a purely proprietary solution if you could find one, but the real benefit to building your system knowing that this infrastructure is underneath is that you're dealing with something where there's a higher rate of innovation, because there are people from different companies that are building it and contributing to the code base. So here's a more graphical representation of this, this part of the slide from the folks at Stream, a company that I'll mention again in a little bit, but I like the way they put it together, so you look at it and say, okay, well, we've got open-source projects that collect data, we've got open-source projects on the right-hand side, board-dated delivery, this is where we've got Kafka and Cassandra, you know, maybe on one or both sides, and then in the middle, we have all these other open-source components or projects that, you know, the project is what the term is used for the group or federation, if you will, that's actually maintaining it and expanding it. And so for each task, there's typically one or more open-source project that provides that functionality. So this is kind of the whole ecosystem. There are more, but this is a good representative sample. And so as you look at projects and then you look at the type of applications that you're going to use or using applications to indicate any kind of package of functionality, we can start to see that for most of these projects, there are now companies that develop expertise and maybe, well, practically in many cases, the original team that started working on a project that then gets turned over into the open-source community, those people go off and commercialize it. So you have a number of companies that are focused on, companies or university groups, typically, that are focused on any one of these. And so now we start to see a market develop and that's what really builds it and frankly takes a lot of the risk out of something where you can't just say, okay, I'm buying this from XYZ company that's been around for 10 years or 50 years or 100 years and we know that if something doesn't work, we can bring the lawyers in and get it fixed. Well, you can't do that if it's a loose federation that's not a commercial entity. But the fact that so many people are depending on it, by the time it gets to this level of maturity, it's okay, now we can start to build. Let's look at the types of companies and products that are now building on this infrastructure. So one of the things we're dealing with analytics is you have to have that compute engine that I mentioned. And today, one of the big differences between the way we build systems today and 10 or 20 years ago, is that most of the approaches for this type of an application for streaming analytics are going to run at some point in a cloud environment or in a distributed environment. And so you want to look at who are providing platforms for that. And obviously if we're dealing with cloud services, you're going to be dealing with Microsoft or AWS or Google or IBM on Bluemix. And so it's interesting that from a commercial standpoint, if we take just that group, Microsoft, Amazon, IBM, Google, Oracle, I guess, each of these companies provides a platform that you can build on. They all use some combination of the, or permit if you will, use some combination of those open source projects. So you can go to IBM Bluemix, you can get access to different databases, different data sources, go to Microsoft Azure and get access to Amazon. But some of them also are developing their own services. And a big part of the economic model for this is streaming analytics as a service. You have to have a platform so you can have access to the platform in an on-demand fashion. But then you need the analytics software on top. Most of the companies that are providing cloud services are providing their own, but also access to any number of commercial vendors that are building on those platforms. And so that gets us to just a couple of slides that are taking a look at some of them. This is Azure with their IoT suite. And with the Azure suite, you've also got Microsoft machine learning and a number of analytics tools. Something similar here. This is AWS, Amazon web services. They have a big data analytics framework. And just take a quick look. You can see, for example here, there's an open source project that they are building on. So you can get access to those at different levels. You can access to Amazon. Less so than with Microsoft, you would get access to some of their own services. They're more of a, I don't want to say more open, because certainly with AWS or Bluemix, you can build whatever you want on top of it. But you have choices from Microsoft and IBM at the application level too. So one more here. Big data analytics on Bluemix. It's the same idea. You can have access at a high level of abstraction where basically you're dealing with APIs and plug and play to figure out what you're going to do, what sort of analytics you need, and then your application that you're building, it's one that you're composing an application from components that are available to you from one of the platforms. Yeah, that's the last one I'm going to do with that. So you take that, and then the key to the last few slides is that those companies provide both the platform and some of their own applications on top, as well as giving you access to the platform to build on top of with solutions from vendors like Informatica or TIPCO or SAP, SAS. The idea here is that even though these companies all build proprietary commercial software that have some of the functionality that I've been talking about in terms of streaming processing, you're buying that and you're running it, you're executing it if you want to compose it on one of the other platforms. But what I wanted to do today, and we're going to have some time for questions, is just to look at another view, if you will, of this whole landscape and say besides the actual platform providers, as a service providers, if you will, that will take you right down to the bare metal in some cases, besides the big companies that are moving into a SAS model with analytic software that in the past was largely proprietary, there are a number of emerging firms that are focused on the idea, on the functions of streaming analytics. They're doing some really interesting work and I think they're worthy of consideration. So I'm just going to go through fairly quickly four of the ones that we see as quite interesting and I put the comment at the bottom, integrate and analyze, because that's where these things have had a lot of value. You want to be able to take data from a variety of sources if you go back about 20 minutes in the webinar to the automobile example, that was almost grotesquely simplified where you had a system for tires and a system for the engine and maybe a system for fuel monitoring, something like that. In larger applications, if you're trying to do business planning, and let's say you've got historical data about your customers and now you want to also look at that historical data as static, it's not going anywhere, you have information on what your customers have done in the past and now you have sensor-based data, you know that a customer is in the store, you want to be able to integrate data from the historical view, the current view and be able to predict next behavior in order to make an offer at the right time. And in the diagram that I had where there's a circle about the individual and you've got information that's streaming and you've got static information and then you've got information about what you have, perhaps as your inventory and you know what your offers are and you know maybe we'll take the information from an outside source like weather information. If I'm building a system and I've got information about my customer and let's say I'm a soft drink manufacturer, I know that the person that's walking by the machine right now has a preference for, we're taking a really low value if you will here, for one drink over another and I know that the proclivity to buy that drink goes up as the temperature goes up. Now I know that it's going to get hotter in the next two hours and I'm not going to be able to refill the machine in the next two hours, maybe I won't make a special offer, maybe I'll raise the price as the temperature goes up. But to be able to do something like that, I need to be able to integrate data from all these different sources. So in this case it's about the individual, it's about the stock in the machine, it's information about my supply chain, how long it's going to get there and it's information or data about the weather and the forecast of the weather. So all of these four are interesting companies in the way that they think about integrating and analyzing. So data torrent is the first of the four and for each I'm just going to do one slide I'll have resources at the end so you can take a look and do more details. So data torrent, the folks that are involved in data torrent are people who are involved in the original development of Apache Apex, one of the infrastructure systems that's been promoted to a top-level project by the Apache Software Foundation. And here is just a representation that shows the kind of data that can be aggregated, which open source systems, the second oval if you will, we've got Hadoop at the top, but that is using Amazon Web Services as one of the ways to get to it. And then in the center is the actual data torrent system, as they say, powered by Apex, which is their development here. What it runs on, so this is showing that yes, it interacts with other systems, but you can run it on AWS, you can run it on Azure. So if you have a preference or a standard in your organization that you're only building on, AWS Azure gives you more options. And then showing what the features are in terms of analytics on the data in motion and visualization. Visualization is something that we really don't have time to get into much detail in terms of how these things differentiate based on visualization, but that's obviously a key way of evaluating the different tools. So that's data torrent stream. I had one of their diagrams earlier stream, it's pronounced stream, but the double I is where it refers to integration and intelligence. And this is another one that's really interesting stuff. Again, built on aggregating and integrating data from a variety of sources. It's a little difficult to read on the blue background here, but we've got Kafka and Flume and other open source projects that are feeding into it. I owe through Hadoop. Hadoop is still sort of a major presence in the market, even though Spark gets all the buzz today. So we can use Hadoop and feed Spark from Hadoop. It just interacts, pulls it all together, and allows you to do the kind of intelligence that I was talking about earlier where we're pushing the intelligence to where it needs to be. And so the integration here is with the existing jobs, the ETL, the transformer load jobs. So this is just a diagram that does a pretty good job at showing how they can pull in the data from the legacy applications. And we could do the kind of thing I was just describing, where you're looking at that historical data about the customer. And now we're looking at the real-time application, what's going on with the customer right now. And another data source, go back to my example with the weather, that allows you to start to do predictive analytics based on all these different data sources. Stream analytics. Stream analytics comes from a company called IMPITUS. Stream analytics is a derivative of business out of the IMPITUS company. And basically this is a... I hate the term next generation, but it's a very current way of approaching this integration of data from the multiple sources that we talked about. Doing the analysis and being able to do predictive analytics based on current and historical. And what's interesting here is that IMPITUS is more the services company and started to develop what became stream analytics out of their services business, because they were getting repeated requests to build systems that did this, and so they turned that into a product. Or if it gets, again, it's one of the four that I'm going to mention today that I would encourage you to take a look at. And finally, Zoom data. What to me was interesting about Zoom data is that their approach is sort of a model of aggregation and visualization, if you will, that looks like a VCR. So you can look at the data, integrate, again, all of these will allow you to pull in data from different sources, including historical, more static data, and stuff that's acquired real-time as streaming data and then start to make some predictive analysis based on that. But what's interesting about their approach is that they break the world, build the query about the data up into what they call microqueries that can run in parallel over very large data sets. And the thing that I found very interesting here is that you can very quickly get a view of the query that's perhaps more abstract than the ultimate one, but it starts to refine as it goes through processes, microqueries, and refer to that as data sharpening. So you get something that can be used very quickly and that may change the following queries, or the subsequent queries that you make based on early information rather than waiting for a complex query to go through. It's not a sampling technology. So there, it's the actual sharpening algorithms that they use that I think is interesting in advances. All right. So to get started, I say this almost at nausea in my head. Sorry, but it's always about the data. So if you're looking at this now and we're thinking about the IoT, how do I get started? Well, I've said that you're going to start by looking at open source tools and trying to choose the infrastructure that will let you look at both your historical data and your real-time data to do your analytics. But in terms of figuring out which applications you can upgrade or turn it into streaming data, the idea is to look at where you have that historical data. But now the other part that you have to look at for the next, this is one way to get started in the next 6, 12, 18 months. But if you're going to look at a business and say, well, how am I going to leverage my data assets? What you use as assets in a year from now may not even exist today. The sensors may not even exist today. So you need to be looking at how you're going to create new sources of data, new aggregations of data, and new algorithms, frankly, for creating that value based on this combination of streaming and static data. And with that, I'm going to look at eight or nine minutes, open it up to questions. I will just say that I know Shannon will tell you about getting a copy of the slides. I have a number of references for each of the products, but also each of the open source projects. There are links and more information. I'll just say we've got more in the series coming up. And I've got some new content that if you check out our research, you can see that too. So be in touch. Send me an email. And if you want to connect on LinkedIn, I have to say this because every month I get LinkedIn requests with no context. And if you want to connect because you've heard one of the webinars, just tell me that. I'll be happy to connect. All right, Shannon, and I turn it back to you. Adrienne, thank you for another great presentation. Feel free to submit your questions in the bottom right hand corner of the screen in the Q&A section if you have any questions for Adrienne. And just a reminder, as Adrienne mentioned, that I'll be sending a follow-up email by the end of day Monday with links to the slides, links to the recording of the session. Something very quiet today, Adrienne. I think you explained it all. There we go. So no questions coming in. So that's great. So just as Adrienne is showing there, there's additional resources for you that we'll get in the follow-up email as well. And next month, we hope you all will join us for machine learning case studies. I'm really looking forward to that. That's another hot topic for our audience, I know. So thanks, everyone, for everything. And Adrienne, thanks for another great presentation. And I hope everyone has a great day. Oh. Oh, I forgot I was on mute. Actually, we did have a question come in right at the last second here. So I'm just really quickly, Adrienne. So can you comment a bit on the Apache Edgint project? I'm sorry, can you say that again? Can you comment a bit on the Apache Edgint project? I don't know if I'm pronouncing that right. Edgint project. Ooh. No, not intelligently in the time that we have. But if somebody's... Let me ask you, if the person that asked that, I can't see the questions right now. I'm in a space where I don't... All I can see right now is unfortunately my own slides. But if the person that asked the question is in the process of evaluating or wants to know about contributing, by all means, let's put that in the queue. And when you send that to me, I'll write up an answer that goes out to everybody. Yeah, absolutely. They provided a link to it. Yeah, I'll get off of it. Okay, great. Yeah. All righty. That is it. That's all the questions for today. Adrienne, again, thank you so much, and thanks to all of our attendees for joining in in the presentation. I hope everyone has a great day, and we'll see you next month. Great. Take care. Thanks.


Hello and welcome to this presentation of the STM32MP1 USB Full Speed and High Speed Interfaces. It covers all the features of these interfaces which are widely used to connect either a PC or a USB device to the microcontroller. This figure shows the connections between an STM32MP1 microcontroller and two USB connectors. The STM32MP1 features a two-port USB high speed communication interface allowing the microcontroller to communicate, for example, with two USB storage devices. Let's look at some of the key features of this USB high speed interface, which is a USB specification 2.0 compliant interface that operates at 480 megabits per second bitrate. A USB 2.0 high speed PHY is integrated on chip avoiding the need for external ULPI transceivers. Built-in support for linked power management adds enhanced power modes on top of the USB 2.0 specification. The battery charger detection function allows for increased current to be drawn from BC 1.2 compliant chargers up to 1.5 amps. In this block diagram, the USB OTG host controller core is shown at the top. It can be used with both ports of the HS or high speed PHY. If desired, the second port can be controlled by the OTG controller, which also has unique access to the FS or full speed PHY. These PHYs on its right side handle the analog signal levels, including many specific level detections relating to on-the-go and battery charger detection functions. The USB interrupt goes to the Cortex processor to signal various USB events. The AHB slave interface enables read-write access of the controller registers and the power and clock control block. Transfers to and from memory are handled by a DMA engine inside the controller via the AHB master interface. At any given time, one of the two operating modes will be functional. Peripheral mode, which will be used for a regular device or an OTG device when operating in peripheral mode. Or targeted host mode, which will be used for an embedded host or an OTG device when operating in host mode. Interrupts from this USB block can be triggered by a large number of events or state changes. This slide shows all the events that can trigger an interrupt. As can be seen, these interrupt sources are diverse events. Low power modes for the high speed core are similar to the full speed. But the modes concerning the PHY are not listed, as in this case the PHY or transceiver is an external component. The USB H controller is fully active in run mode. During USB suspend, sleep, stop and LP stop modes may be used. USB PHY-C is a small controller needed whenever the high speed PHY will be used. It is to be used for controlling the PLL inside the high speed PHY and enabling the USB H controller access to its second port. Fine tuning of the high speed PHY should also be done by using USB PHY-C. This is necessary to get notably a well-adjusted eye diagram. Here is an application example of a low power device. Power is drawn directly from the USB Vibus signal. A single crystal oscillator starting from 4 MHz is needed outside. For complete USB specification documents, please refer to usb.org. The USB 2.0 document homepage has a zip file containing the USB 2.0 and OTG 2.0 specifications and an ECN for LPM. The USB device class documents page has the battery charger specification.


T.L.O.S. POP! We are on Twitch. We are live. By the time you see this, we won't be. So just leave a like, comment, subscribe, turn on your post notification bells. Let's continue to grow the family from Chicago to the U.K. and all around the world. You know, including Australia, because that's where we're about to visit. At this point, we only have Australia every week, ain't we? God damn! Might be twice this week. Oh my God, I gotta get that. Anyway, I missed it. Yep, so did. Twitch.com, right at the bottom of the screen, that's the username to catch any lives and things of that nature. Yeah, this is inside Brisbane's roughest area, Logan. Spanian, of course, man. Spanian, like I said, man, that's the president, prime minister of Australia at this point. Let's get into it, man. Copyright disclaimer under Section 107 of Copyright Act 1976. Allowances made for fair use for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use. No copyright infringement intended. All rights belong to respective owners. True. Uh, into here. Talk to me. So breaking news now, fans of controversial Australian rapper Spanian turned on offices. They kicked vehicles and set off flares as local poons turned the surrounding streets into a crime scene. Nine News has been told a YouTuber was visiting to showcase this part of Logan. In the streets of Waterford West to send into chaos, police under attack as hundreds flood the streets. Hundreds have descended on Logan, south of Brisbane. This is Logan? Oh, you sat on this video and waited for news reports. Oh my God. Three police cars are targeted, kicked out, and then... Controversial YouTuber. Since when? Do you guys just reckon you're on the streets? Yeah. It's chaos. The police are inevitably outnumbered. All right, everyone. Welcome back into the hood. I'm in Brisbane, Queensland, northern East... Wait a minute now. Uh, wait. Wait, what an intro. I'm ready for this, actually. And when I was searching up hoods in Brisbane, I found this article from the end of last year, December 2023, just a couple months old, Queensland's roughest area, Logan. That's where we're going, lad. A suburb in southeast Queensland is shaped up to be the state's most dangerous place to live, Logan Central. And that's put the crime right now of Logan more than double the Brisbane average. I don't know if these two things go hand in hand, but it's also Queensland's cheapest... What type of crime? Place to live. So we're going to the roughest, most dangerous and cheapest place to live in Queensland, Logan City. One of the most notorious suburbs there where we're getting off the train is called Woodridge. So we're meeting lads there, of course. I got a hookup with a very known head there. His name's James. He's going to take us through all the areas there. I'm Jade, bro. We'll put the sum of the lads, see what's going on in Queensland's roughest, most dangerous hood. Man, the crazy thing about this, man, at some point, I hope not, but at some point, he's not going to be able to do this anymore because it's getting too crazy for him. Not for him, but for like the areas and things of that nature. Well, this is a rough area in general, allegedly. I haven't seen yet, but from what I've seen that popped up on the screen, it looks like a good time, though. Sounds like a good time. Brother, let's hooch. And that's my problem right there. Insert me where it's lit, and I'm going to have a good time. Once a beanie. Like, so far, Alice Springs? The best. I don't see nothing that could compare to it. Oh, look, you can use your phone. You can use your credit card. Like Sydney. What's going on, Melbourne? What are you all in there still living in the 1990s, lads? What's going on, you cunts? Say, brother! I wouldn't trust the bane lay, lad. Bane loss. I'm not going to lie. Like, Australia's more built up than I thought it would ever be. Like, I always thought Australia was pure outback. Pure Steve Irwin, RIP. You know what I'm saying? But I like the cities in there. Like, they're nice. James said as soon as I get off, he's going to be at the station in a car and we're going to jump in the car and he started this other hood. It's a little drive away. I think he said Mazdan or something. And boom! It's on, lad. We're in no time, lad. That's done. Don! Hey! How are you? How are you, James? Hey, Vinny? What's your name? Vinny. Vinny, Don, boss. Welcome to Logan. Vinny, biggest... What is he, security? Otto. How are you, boss? How are you, bro? How are you, bro? You're going to be driving us. Oh, hectic. Don. I've got some stickers for you guys. This is Woodridge. Yeah, Woodridge train station. Is this the centre of... The centre of Logan. The centre of Logan. Alright, mate. Straight after... I'm literally making people's whole year. Like chicken out here. All the points up in here. Like, yeah, all school kids. It's pretty big. All the entrants here. This is why this is Woodridge shops. Yeah. Oh, that's cool, though. You see, this is like a shopping area. This is expected. Younger kids. You know what I'm saying? Oh, let's go see Spain. He's coming through. Plus, you know, it's the hood. Like, any hood is the same. And any type of celebrity is coming through. It shines a light, man. It's a good moment for the place. This is the train station. It's called Woodridge. It's called Woodridge, bro. Straight up that way to Monsignor. And we'll make our way back to Woodridge. Alright, come on.  I'm about to thank you for saying that. Oh, really? You just get that crazy... See what I've been talking about? I'm not even there yet. None of these bugs is coming out of nowhere. You see what I'm saying? Only when I watch a Spanian video about Australia, all these bugs get to flying around. Like I'm really here or something. Chill. I had to put a comp shop right in the middle. Right, so this is pretty much probably... Yeah, yeah, yeah. Mad, mad, mad. You're gonna hit the monster now? Yeah, we're gonna hit the monster. Hey, he's got it. How long you had that for? Three years, like. Oh, you want me to sign up? I'll sign that for him, babe. Oh, Gino. You can hope. If I wait through the walkman, we go for you in Boston. There you are. You wear it too fast, babe. I also forget Spain at one point was a rapper as well. But he's for sure known more for this than rapping. I don't know for sure, but like, that's... Worldwide he's known for this at least. They've done an article last year and the last year. Dangerous, roughest part of Queensland is Logan City. I don't know if you knew that. No, well, it's just a different breed, but like, it's just... We punch on here, you know what I mean? Yo, yo, yo. It's a majority punch on here. There's shootings, there's stabbings and that, but we grew up just punchin' it. There's probably like... There's shootings? Everyone crackin'. Like, in Sydney too, but like, bro, Logan's different. Logan's... The boys are walled here, eh? Yeah. Like, it's... Well, look at it. We've got Boxers, you've got UFC fighters. Boys in the USA from here. Yeah, the tougher brothers. Oh, are they from here? Yeah, yeah. They're full of them. Oh, really? Yeah. Yeah, yeah. Junior and Justice. He's the boxer? Yeah, Justice. Yeah. No, they're all from here. Trent Porter. The Mayden's from here. Well, the Mayden's are from here, ladies. He'll say. You know, a lot of different ethnic groups here. Yep. Africans, Islanders, Aussies, Aboriginals. Yep. Africans, like, heaps. Yeah. A lot of refugees, Saturday too. Oh, there's my son there. Look at that. There's your son? Yeah. Oh, okay. That's his son. Told his friends. Everybody slid out. Okay, got it. I'm not going to lie. Like the last three Spanish videos I've watched. No, no, no. Not three. No, three. Alice Springs, the one I just posted today, which is Tuesday. And then this one, it seeming to be the most lit places. But it's the biggest spin-out jumping out in hoods and, like, just hundreds of people freaking to see me. So is there a suburb called Logan, or is that just the... The multiple of... It's the whole CDA. Yeah. Marvel cousin there, the tall one. Yep, yep. You saw it. It was on the news in that, like a race war, Aboriginals and... Oh, do you remember? Yeah, yeah, yeah. So then my cousin was inside prison at the same time. Yep, yep. And then it kicked... It wasn't... It didn't really go, but it does cause tension in prison too, a bit. You know what I mean? Oh, so the Islander lads fighting the... The Murrays, yeah.  The Murrays, yeah. Yeah, Murrays, yeah. Oh, and it spills out into the streets. Yeah, like, it was just... They shut down the whole neighborhood too. Some people, it's not a big, gang war zone, but to have that in a city in Australia, like, it's big... Ethnic tension. Yeah, yeah, yeah. Like, down Gold Crows, you'd never get that. Yeah. You know what I mean? That doesn't even seem legit. Like, what happened in that situation? Like, what's the backstory behind that? Because Australia is so small. It seemed like everybody would get along unless they were real ips. Like, racial tension in Australia is kind of rough. That's crazy. What I never thought. They wouldn't even feel something like that existed. Yeah, yeah. Yeah, you're right. There's not a lot of places that have ethnic tension. There's a police park up there, so back in the day there's been a few murders up there. Oh, yeah? Just punch-ons, you know? You know, a lot of bikey cubs around here, if they had, you know, recruiting and that, like, gangs... I always knew that Queensland in general was like a heavy motorcycle club, like, state. Some states don't really have it. I knew that Queensland... Legitimately, the only gangs I ever heard coming out of Russia, Australia, before Spain and before any of this, was motorcycle gangs. Like, I've never had any thought that there was, like, street... Maybe one, four or two. But, like, they were like... I heard, like, a little bit about them, not too much. Specifically, Gold Coast, I thought. Yeah. But, so, it's in Brisbane, too. Yeah, well, bikings, it's not so much now, because ages ago, there was a big fight in the surface paradise, and then the government just went down. Oh, they went hard on them? Yeah, yeah, so... Yeah. I think that's what happened, and started not allowed to wear y'all. Oh, so, like, the same in Sydney? Yeah. Not allowed to be to get, like, not allowed to talk to each other? Yeah, I think it started from that.  Yeah. So, it made it, like, impossible to exist, pretty much. Yeah. Is this place that we're going? Bourke Street? Yeah. That's, like, the spot? Well, one of the younger lads, you know, ran a muck, and that, and he died on there, and the boys want to show true blood to him, too. Oh, yeah. All right. Mother. Ha! Ha! Ha! Ha! Ha! Ha! Ha! Ha! Ha! Ha! Ha! Ha! Ha! Ha! Ha! Ha! They are comfortable. Comfortably. Let's hold. I want to say it like, cool, you know what I'm saying? Oh, yeah. That's awesome. Is that? Yeah. Choppers, bro. Choppers? Choppers? Bro, you're the neighborhood superstar, bro. This is Marsden. This is Marsden. So, not long ago, um... The road just hit Choppers? Yeah, that mate back there, Junkie was trying to hold it up. What is that, boss?  The cop has killed him here? Yeah. Was that on the news? Yeah. What was he doing? Was he robbing everything? He robbed the McDonald's. Oh, he robbed that? Yeah. How long ago was that? It was probably, what, last year? Yeah, last year. Oh, yeah. I don't know how you can blame Spain. Spain is huge in Australia. Like... Like, he doesn't tell anybody he's coming. He doesn't get on social media and advertise it or anything. He just shows up with his contact and walks the street and shows everybody the neighborhood. Like, how could the local authorities with the government be bad at them? He's not doing anything. He's not inciting it. He's not... You know what I'm saying? He's not, like... Oh, meet me here, here, here.  We were shooting last night. Logan Lee. Whoo! There was a shooting last night here. What, just up the street?  Oh, yeah? That's why he's shooting, bro. Like, he's not shooting. Oh, that's it? Shoot, not too much on the news, you know what I mean? Yeah. Yes, gun violence. Hey, that's crazy. I didn't actually know that. Yeah. A lot of gun violence around here. Wow. So, I read that in the last year, 2023, the climb around Logan has, like, skyrocketed. It's almost doubled statistically. Yeah. What's going on in Logan, then, for it to be doing this? There gotta be some type of war behind the scenes. I am curious about the gun laws in Australia. Is it like the UK? No, or is it like America more? So, have you sensed that? Because we're just immune to it. Like, it's like... They don't even notice that. Yeah, it's just... Yeah, they don't even notice. Like, if we go to Scotland... I say the crime's double, he's just like, it's the same. Like, if we say we're from Logan, it's like, ah, you know what I mean? Yeah. Also, in other parts of Queensland, you say you're from Logan. Yeah, yeah, it's no. And people are just like, ah, these kind of things. Yeah.  Yeah, yeah. Let's go walk in time. Oh, is it up here? Yeah, so we're going to walk here, too, so... This is the centre of the hood up here in Marsland. Don't. Don't. Don't. Don't, don't, don't. Hey, he's got my bandana. I want you to sign my book. Yeah, come over here. I'll sign it. What's going on up there? What's going on up there? Hey, they got the books here, bro. I love that. I love signing books, bro. That's the best. Bro, this is like a state fair. What is going on? This is like a carnival. Spanning is the main attraction right now. Like, the whole street is blocked off. You see this? No. We're only 10 minutes in. This normally happens like 30 minutes in. Hey, they got the books here, bro. I love that. I love signing books, bro. That's the best. It's always easy. There's like 100 people up there and just all police lights. The coppers are probably freaking. Don't lie, don't lie. Don't lie. Don't lie. Don't lie. Marsden, lad. Logan. That's all. They're getting up here. I'm going to get some good out, eh? The coppers are shutting down. Yeah. They have a photo? Right. There's so many. Yeah. Somebody put in one of my videos, they was like, I don't like what Spanian's doing right now. What is Spanian doing? He's just bringing light to areas that have no light to them. Maybe local council, local whoever come through and make a change. You know what I'm saying? Like, this is the hood. This is everyday stuff. Like, I don't like, to me, no hood is different than any other hood. It's still got the same like, it ain't, okay, hold on now. All right. It ain't the same. But you can still see the nuances of similarities across the world in all hoods. You know what I'm saying? Chicago hoods are, I want to say they're more aggressive by looks. They look more aggressive. You know what I'm saying? They calm at the moment, you know, because the spotlight been on it for so long. But you know. It's like Spanian out here like Thanos. My bro is missing a tooth. Yo, what is happening right now? The whole hood, nobody's at home. If you're not here, what's, what's, you, you, oh my God. What happened to the pavement? I know for a fact that is an amazing feeling. I know for a fact that this is hard. I know Spanian feel this right here. Like a lot of people will be like, man, bro, why are you bringing all these people? Bro, these people have some of these people got literally nothing to look forward to all day. Some of these people probably sitting in this is the hood. Don't forget. There's mad depressed people in the hood that don't get to voice their depression all the time. And he's just giving them a moment. Simple as that. W hat. Let's not forget Chicago's everywhere. How are you going to complete the walkthrough video? We got 32 minutes left. What are we going to do for 32 minutes? All generations. We got mom and son. I never understand why people be gangbanging and other people videos. Like, bro, you got real ops. Go step outside.  Why are you in this video doing it? This is insane. I've never seen this many people in it. Bro is still here. He got his book signed and he on his back from that point on. This is crazy, bro. How many Adlai slads? How many Adlai's in here, bro? The seats. Look at the compass here, bro. They're going to be breaking. If he get new, he's... Bro, Spain is one man AMP. Y'all know who AMP is out there in Australia? He's like his own AMP. He can show up anywhere and it's just going to be crazy. Can you even go outside anymore? Like, without having this type of situation happen? Like, especially in Australia. I enjoy it. Good luck. What do you do? Second year. Oh, man. Oh, man. Oh, man. Oh, man. That's right. Second year. Second year. You know what's crazy? Like, most towns he be going through. The police don't even be showing up. But this town? Like, you got to really be catching stuff. This town, the police is outside. They're like, nah, we got to show up. We don't believe that the neighborhood can stay calm in situations like this. The other ones, they were still calm. Police wasn't even pulling up. Police is out here today. This is the first time I've seen the police, like, firmly present. Oh, you're in a four tours. You about to blow the engine out there. Coppers are spewing, like. All the coppers' faces, they're full dirty. He got everybody out there, from the moms, to the kids, to the iceheads. You know, from everybody. They're going to put this there in everyone. Oh, the one. Don't worry about selling out rap shows at night. I sell out streets in the hood, like. Don't worry about that, brother. Don't worry about rap shows at night. Talk about it. Talk about it. I sell out streets in the hood. Talk about it. Thank you. Thank you, brother. Thank you, brother. No, Loki, he can't, like, if he was to do, like, a papal, does Spain have merch? Like, he's... What's going on? We made a break. We caused a riot. We made a break. That's right. That's right. That's right. Spain! Spain! Look behind us, son. Look behind us. The fact that you just said, look behind us like he had a cameraman is insane. He was, bro, look behind. Look. Oh, I got the camera. My fault. Look. Just put it there. Just keep going. I can't get a photo of the Coisines. Sorry, sorry, sorry. Okay. Good, brother. Thank you, brother. Normal day in Logan, ain't it? Normal day in La. Every afternoon's like... What's going on? I had to come outside, like, at this point.  Like, if I was a dude, I'd be outside. I'm trying to pull something. I'm trying to riz it out. Everybody outside. Yeah, the boys. What point does this get overwhelming? Never, you can't.  Because they're going to sense that out. Like, you being phony, like, no, you can't. You just got to rock out. All right. Signature's photos galore, lad. This is the old gunfire. Woo! I love it, my like, in city, baby. The car that's picking us up can't get it because the coppers are blocking all the roads. Oh, that's the docker. Docks will not jump in. Docks will not jump in. I'm going to cruise. I'm going to cruise. You literally have to. There's no way you can continue to walk. You've got to separate yourself. They'll catch back up. 100%. They're going to catch back up. Michael, shorty ink is crazy. I know this hurt. He got his whole rib tattoo and his chest. That's tough. That's it. Oh, is he? Sliders. Sliders. Hey, look at the coppers there, bro. Look at the coppers. They're going to drop us. Don't turn right. Don't turn right. Don't turn right because of my leg.  It's a little bro's fan. It really come through Australia any hood. And this is parade inside my city. Yeah. What? That's it. Every time every episode just double spot. Yeah. 100%. I feel like every episode not saying that I have every episode since I've been watching it went from like nobody showing up. Then I'm like, okay, it's a few people here. Okay. Now it's a lot of people here. This is the most I've ever seen. Because I was in Melbourne last week and I thought that was big. I thought that was big. This is 420 a mile, bro. That's your legend, brother. It was like 400 people there. Can deal.  What do you mean? You get better than a Sylphie. You get to be in the vlog. He's just sitting there waiting for someone. He's Brisbane's most famous Uber driver now, lad. Yeah, so that street is chaos. This is an Uber driver that was just waiting on his ride. Instantly canceled. No, I'm waiting on a ride. That would have been solutable, but like, no, you got to cancel that. Yeah, it's like a written down apartment. Yeah, because I'll see him. I didn't have no time to say it, but on the left and the right of that street look like all the houses and that. The area that you were coming up, they're all houses.  Going through it. When you're walking, if you turn left, there's a lot of crackheads. It's really disgusting. Nobody looks after the place around there. We're proud to be from Logan, too. You know what I mean? It's a very tight-knit community, too. For instance, as a young kid missing, everyone was just now looking for him. I forget. Australia is bigger than America. I could believe that. I could believe that, but is it more populated than America? That's the question. Are there more humans in Australia than there are in America? Because Australia, it seemed like it's just a lot of, you know, outback, a lot of land everywhere. It comes together and just... Hey, Siri, how big is Australia? Australia land mass is 7,600,017,938 square kilometers. All right, but I don't know if I read that number right. L-Math. Hey, Siri, how big is America? You capped. You capped out. Sorry. It's not bigger than America. By 2 million, there's 9 million America. 2 million, 7 million there. Third largest country in the world. Hey, Siri, what's Australia's population? 26 million? Okay. Hey, Siri, what's America's population? 331 million. Okay. That is true. Australia is a continent. That's fine. Okay. Do we want to do North America then? Because the continent of North America is... That's smart. It's like a good sense of community. Yeah, it supports each other. That's what's good about the Hood Bar. Yeah, we need local heroes. Like local people, we can look up to James here in the day, him in Fortify. Yeah, yeah. And the boys fighting from here, you were saying, James was saying before? Yeah, yeah. These are famous fighters from here? Yeah. Smart. Yeah, I like to live for World Champion. Oh, yeah? No way. Yeah, like from Logan. I will tell you, man, man, listen, a lot of people, like, go elsewhere from America to go get love. You know what I'm saying? It's like, it's like... America's not supportive. I just want to let you... Like, it's not. We're not supportive, 100% at all. It's rare to find an American and be like, oh, man, I support you and everything you got going on. And you know what I'm saying? Like, the UK, when I first showed Mad Love, even till this day, Mad Love. Australia, Mad Love. You know what I'm saying? Ireland, Mad Love. Never... Everywhere, Mad Love. But America, man, maybe. You know what I mean? You don't see me at the Woodish Market. America's got this complex. Like, they the best. Like, chill. But you know what I mean? Like, I enjoy the players' moves. Yeah, foot of Geary's from out here. Lottie to Geary. Is he? Camera Smith, Boston boy. This is his foot. No way. Camera Smith. All I've got out of prison are any of the cameras. She's the league of superstars from here, lad. All right, we're back at the shops where we started Woodridge Shops. Having a coffee. Recovering from that. These shops look good as even. Even the shops. Yes, I what? This just popped up. Woodridge Police, mate. Yeah, about three years, yeah. About three years. Look, it's at night time, bro.  Yeah. Even after dark. Yeah, it was bloody.  Yeah, yeah, yeah. Stuff you don't even know of. You know what I mean?  What about drugs around here? I haven't even asked you. Is there a lot of drug users around here? Yeah, yeah, yeah. Very heavily drugged. Ice. Ice. Even heroin? Yeah.  What's this place? They aren't. Same vineyards or something? We'll talk in before about the other parts of Brisbane. There's another dangerous part of Brisbane, Inala. Yeah, Inala, because back in the day, I don't know about it like these days. Bro, they literally got dropped off, spun, walked around because there was too many people. They got a ride back to the original spot where they got dropped off so he could continue with the video. That's insane. Maybe the young fellas are all like... Good plan. All about it. You should be Woodridge versus Inala. Oh, so this place versus Inala. Yeah, yeah. Inala's like in the western suburbs, 20 minutes from you? Yeah. Not long ago, some Ifrich boys, I don't know what they were on, but they ended up killing a granny. Yeah, that's a really sad day. Far out. Yeah. So it seems like it's been an ongoing thing for a while since back in the days, and even now, like generally that part of Brisbane, rivalry with this part of Brisbane, in some form or another. Precious crimes are not needed. Yeah, yeah, yeah. How do the boys all the way from that part of Brisbane even come across this part like... Stolen cars. Stolen cars. Stolen cars. Those are the boys that get in the hotties and drive in over here. They're all the young kids. Yeah, yeah, yeah. They started knocking down... Yeah. Housing. All they have.  Yeah, yeah, yeah. Because that's happening, like that's like a common theme everywhere that I go.  Doesn't matter. It's called gentrification. But, you know, at least in Chicago, you could never really fully gentrify something. Like, it's hard.  You can knock down these buildings, you can rebuild nice little complexes, but listen, some people ain't just going to let go. Yeah, the chopper's always out, man. Oh, yeah, you got police choppers here? Yeah. Boons still in car joy rides, you know? Yeah. People do look after their house and maintain the gardens and well-being of it, you know what I mean? Yeah. Yeah. It's pretty nice. Needles. There's needles back there? Yeah. Wow. Needles with exposed teeth. Wow. The ones we've got the caps on? Yeah. Oh, no. I'm always dodging syringes. Don't worry. Needle packets everywhere. Bro, what the?  What's going on in these flats, laddie? Yo, dude. Yeah, bro. Hey, what do you like? Say, word. Trying you, man. Look at you. Look at you, bro. What are you doing, lad? What's doing woodchairs, bro? And that's all that we needed to see. One person find out, give about 10 minutes. It's back to normal. Woodchairs, I'd like. You from here? Yeah. Woodridge, yeah. Man, what's your name, bro? Hey, MC Tricks, bro. Ronald, bro. He grew up here, lad? Yeah, in my whole life. Tell us the yarn, bro. What's Woodridge, lad?  I lived here my whole life. Yup. When I was a kid or when I was younger, there wasn't that many nationalities here. Yup. But I watched all the migration happen. Yeah, yeah. So this is now one of the most multicultural places in the- They'd say. In Australia, brother. The boys were saying that, yeah. The difference is, is everyone would say they're from Logan. Yup. But where you at now is Logan Central. Yup, yup, yup. It's not really, they used to call it Woodridge, but now they call it Logan Central. Oh, yeah. They call it that, but there's like 70 suburbs here, brother. So in the last 10, 20 years, it's gone very multiple. How's that? Yeah. Every nationality's here, I think. The boys were saying that a lot of African lads. It's pretty big, this area. Afghani lads. Everything. Everything, huh? Every food's here. It's a few examples. Yup. Yeah. So y'all got good food, huh? That's a good thing, right? Yeah, good guys just have to run down the hood that much, eh? Ate's right. Ate's right. Ate's right, brother. Ate's right, brother. Later. We were at the train station waiting to go home. Yeah.  Yup, yup, yup.  I'm about to do a suicide attempt just at the train station right there, sir. Just now? Right now? Just now? And then like, I'm standing by one, nah, don't, don't.  She was going to jump off the train bridge. Yeah, she was just about to jump off, not the bridge, like onto the tracks. Oh, onto the tracks? Yeah. And you stopped her? Yeah, I picked her up and everything. And what happened? Where'd she go? She went home? She ran off crying, but then like, I'm waiting for the police to come. Yeah, she told the ambulance, turned into a superman, Oh, so that just happened just there, the station? Yeah, even a couple of months ago, cops actually shot him at a black fella at the radio bridge. Did they? Yeah, because I was living in the apartment up here. Yeah. And, yeah, I was in my, just playing games. Everyone's calling me you're up, you're up, man. Nah, do you know what happened? Nah, do you know what happened? Nah, I was like, apparently he tried to come grab a plank and come, come back to them and they just, they just shot him? Yeah, six shots. Seems like the cops are shooting these people nowadays around here. Yeah, Australia, huh? Yep, they're dirty ones. Yeah, you see straight into that house, that house, that's full exposed. It just seemed like an old lady sitting on the lounge, watching TV. This street looks like, I don't know, maybe I'm wrong, the worst street we've been in so far. Even, this is, like Alice Springs was lit, but like this is like, it's giving me, it's giving me like flashbacks of certain areas in Chicago for sure. Oh yeah? Like Alice Springs was lit in the turn up, like in the terms of, like it was, like it looked fun. Like, you know what I'm saying? Like in Chicago, you can go on certain streets and it'd be like the midnight or like the middle of the night and it'd be teed up like that just on the street. You know what I'm saying? Like Alice Springs was, but this like, it's real remnant of what's going on. It's giving, it's definitely giving the vibe. How you doing lad? You from here? Yeah, yeah.  Lad, tell me. Probably the murder down at our footworks. Murder of footworks? Yeah, just down the radio. What am I saying? Was there a murder there? SES, come to our yard and whatnot? No way. Yeah, I think so. What was that? Some guy who worked from the Irish Delan and got stabbed down there in the middle of the sun. I've got a lot going on over here in Logan. Yeah. At footworks. NYCS right for you. It's crazy. It's a neighborhood called Logan in Chicago too. It's like a party area though. It's cool. I mean, yeah, it's got some hood to it. Like, but it's heavily gentrified now. But like I said about gentrified spots, you know, it's not always, it's not too gentrified when you dig too deep. I used to live in Logan. And there's a lot of Hispanics over there, Hispanic gangs. So I know. I would know. No way. Looking for a knife. Stubbings coming here? There was a murder here on Norfolk. A couple years back. Someone got put in the bin here. Yeah. Around. Yeah, the truck driver noticed it. No way. All right. It's all right. Thank you, bro. What's going on in there? Nando. Oh, a church or a match? A church, yeah. There's been a few meters on the streets even looking up. Let me say, a lad in a bingest with a family in a bingest here. Look up there, lad. Yeah, which is trapped out here now, ay. Everyone's happy here, at least for the cameras. The cameras. Yeah, which is trapped out here now, ay. Everyone's happy. Is that 32 people? Yeah, at least for the camera. Camera's off. They aren't showing on. Wait, they're not just seeing. They're happy here, at least for the camera. Oh, yeah. I'm seeing stuff. Okay. Camera's off. They aren't showing on, lads. But I've seen some rakes. I mean, what was going on? And this is why you do it, man. Kids, make kids' days, man. This is something that they could take forever. Might change the trajectory of a child's life meeting you. Hey, how are you doing? I was bringing one at the moment. Oh, you're mad? Well, you're going to be one of them. Yeah. Fitness person. Hey, there is two. PlayStation going, everything in there. This is man cave, lads. Doing well. Nice work. Thank you. I was looking in your little man cave in there, bro. Let me see it. Yeah. What do? Come on. Hey, doing. Hey, look at that man cave, lads. Hey. I don't know if I'd like, or if I'd like. What's this? Nice little man cave, low key in the head, like, you know. Right in the garage, you got the, what is this? What game is this? Hang on, I forgot the name. What's this? Forza? Forza. Oh, Need for Speed. Need for Speed. Little hood sound system, lads. Little hood gatorade. What do? PS5, too.  Local crackheads, just yelling and streaming up and down the streets. Yeah, yeah, yeah. Breaking into the houses. Yeah. These are drug addicts around here? Yeah, man. Yeah. What drugs are they on around here? Mostly crack or fentanyl. Fentanyl? Yeah. Really? Yeah. In Australia? That didn't hit Australia? That's, I feel like that's rare. I've never really heard of it that big anywhere outside of America. I've just heard of it coming to the UK, but Australia? Fuck, you mean ice? Yeah. Yeah, yeah, yeah. Get it, one, two, three. Forza fentanyl's a thing here. Yeah. Wow. Didn't even know that. All right, it's all about thank you, ain't it? This is for sure the most rundown place he's ever been in in I've seen. In Australia. Yeah. Yeah, boys. All right, man. Can you jump in the car now? Yeah. Change your plan. We're getting a half-time feed, lad, sunshine kebabs. Yeah, let's go. That's a kebab spot? Yeah, yeah, let's go. Best kebabs in Logan, lad? Free advertisement for sunshine kebabs? Let's go shut it down. Swen on kebabs, lad. Sunshine kebabs. All right, this place looks legit. The mixed grills? Yeah. Yeah, we gotta get a mixed grill, lad. Look how the feed comes out. See, yeah, I don't feel like there's no places like definitely not in Florida. 100%. I will hold it down. I will tell you all this to the death of me. Florida don't got no good food. I don't care which, no, no, there's no good food. Not coming, like, a lot of people say, like, I'll be, oh, you come from Chicago, so you think Chicago got, yup. They damn, yup. Ain't no food better than Chicago, in my opinion. Because there's everything. There's authentic everything there. You know what I'm saying? So like, I just don't be believing in stuff. Like, I believe, if they had this in Chicago somewhere, which I'm sure they do, I just never ran into it. I'm ready. Look at these. Well. Sought out the boys. Well. Thank you. All right, look at these. Thank you. Thank you. Wow, bro. What is it? These. What is that? These are lamb chops. Lamb chops. Adana kebabs under there. Well, bro. Very good. Let's get into these. Amen. Ektik. Lamb chops in the tomb. Let's go. But that's a gun. It's good. It's good. It's good. It's good. It's good. Bro, I haven't phase. Let's go. You said there ate the whole meal. They gon' find you. I was ripping that. We're gonna have to get guests. We're gonna have to get some of the people doing burnouts to come here. Oh, you didn't eat. Oh, really? The boys went off-stay, lad. They went chai bar. They smoked the whole restaurant out, lad. Where'd he go? They caught on a discipline. Oh, he did eat. Okay. Well, he's doing cut scenes. He's going up from old footage too. Here and out, lad. Ladders. Thank you. We're only halfway through the shoot and we're already on the news. Look, Oisiz. Fans of controversial Australian rapper, Spanian turned on officers who were there. He's not even there. He left before any of this stuff happened. But that's why the officers was there. You know what I'm saying? For crowd control, they turned on officers. They turned on vehicles and set off flares as local hoods turned the surrounding streets into a crime scene. We're already on the news, but... Oh, they got it. Busser. These notorious for visiting some of the world's most dangerous neighborhoods. Yeah! Let's see it, Oisiz. Where's the photo? That's just, that's just adding to the, adding to the legacy, man. Being on the news, it gets different. Four on the news already, lads. For the people that aren't from Australia watching this, I'm on the biggest national news in the country. Right now as we're talking. And we're still shooting the video. That's crazy. Bro, they didn't even leave yet. They're still on the news. So this is the spot, brother? Yes, this is where I can talk. This is where the big punch-ons were? Yeah. Is that the fence? Yeah, yeah. Oh, because in the video you see them smashing like, ripping apart a brown fence? Oh, I might have been down there. Do you see when the farts happen? Hey, what up? Where was that? Can you tell us about it? Yeah. Yeah, it's a mess of bulls. What was that, 2011, I? Yeah. And it happened just so long. The whole bunch of dogs inside. You know what? Never mind. This is your dog, y'all. This is his abode. He's doing the right thing. Nice to shut down. That was crazy. We went for days. You know what it means? Oh, we went for days? Yeah, because I got out like a week later. It's all right, bro. Yeah, bro. I'll see you this time. What are you guys up to when the farts happen? We were actually drinking in the house because the mission was too loud. Oh, these flights here? Yeah. Yeah. What's it going on for days, you were saying? They're punching on all the time? Yeah. Pa, real. They just shut Logan down like he good like yours. But the question everyone wants to know, who won the fight? I've got to ask. I've got to ask who won the fight? I think I won the fight. Oh, you won the fight? Yeah. So the girls were saying that the Tongan lads lived up one side and the Murray lads lived down there and they were just meeting here, punching on every day, bro. What was the point of it, though? Like, why? It seemed like what the situation was. Yeah. Like, heaps of people? Yeah, yeah, yeah. Gangs are like 30 people. More than that? Yeah, yeah. No way. Yeah, yeah, yeah. So like how we had today? But violent? Yeah, it happened, bro. Because I got out and they were like Woodridge alert. Can't be walking around here. Yeah. On horses, patrolling the streets. That's craziness. Yeah. Well, you were here then. I got out like two weeks after it happened.  Like just punch on. Yeah. That's mental, lad. Yeah, get two out of hand. That's mental. That's mental. See, I'm still thinking about this. The news has a strange way of making you feel that something is happening that's not happening. Like when they were showing it on the news, even in the beginning of this video, I thought he was actually there. He's not even there. Got it. Got it, y'all. He's not even there. Like he's in the city, but he's not at that particular spot no more. He's laughing. Hey! Hey! Hey! Hey! Hey! He's talking to the boys, lad. They're going to... He's trying to chuck fishes. The boys are hanging on for a little bit, Lord. Let's see. This is crazy, lad. What are you doing? That's not me, bro. You too, bro. You too. Boys, did you see the news? See, I got PTSD, man. People hopping out of cars. Like, you've got to get past that, I guess. But I don't think I'll be... I think in the UK, I'd be past it. Like, all right. It's not there. For me, it's not in there. Oh, spinning brother. Shoot. It's only half done. It's in the news already, lad. Anyway, that's the center of the Logan riots, lad. So, some islanders gate crashed on my party and then later on it extended. He got ran over here. So, African kid ran over. My bad for pausing, but I like how he doing it. Doing a little bit of the scene, then moving around and doing a little bit of a more than getting in a car and moving around. He can't really walk right now because this one is too hectic. It's a lot going on in Logan. Oh, really? Yeah. From a beach, from gate guys in the party? Yeah, yeah. Is that so long? Yeah, around here. It was just like literally just around here. We just tried to pass it. Yeah, that escalated too, bro. You know? Yeah, yeah. So, things here, like the common theme is a little thing will kick off and it escalates. Yeah. That seems like the everything escalates really deep, y'all. And then it gets racial. So, like, then that's the... It's because they're bored. That's what happens when you're in the hood and you ain't got nothing to do. Any little thing will go from this to this. Just go straight bored them. They want it to last as long as possible because it's something to do. Yeah. Africans versus Polynesians. Yeah, yeah. But then, yeah, it just blows over and just, you know, communally they just have to get involved. Where we going now? Kingston. Kingston. The detectives flying around. I'm thinking at some point they're going to be looking for us. They're on the news. They're probably going to put a call out. Just go and get these people. Just stop them. Pulling up with the icky slag. Watch out, it's raining. Don't get wet. Mad, brother. We just see you're supposed to fly. Oh, no way. Follow us. I'll sign it for y'all. You got to text us. Get a pen. I'll pay my book with me. Disarray that because I've nearly finished it. Dead set. Wait, I'm jumping out. It's full pissing down now. My biggest fan, Adelaide. Are we going inside? Yeah. Wow. Ah, what's up? What's up? The gorilla pit, lad. Let's hoge. What's up? What's up? What's up? Okay, what are you doing? You working long? Yeah. What's it like as you get rough yards? Calm down. What is this? Is this a casino? Yes, calm down. Yeah. I did it? Yeah. Full dramas all the time. Bar out. Who's going to ring up Workland? Oh, yeah? Tell him. Is this a hotel? Same another day. I'm waiting for your food truck. Yeah, hectic. I can taste the man for this. Yeah, lad. What a blessing day, brother. I'm in, brother. YouTube. Put me on television. You want to be on YouTube? That's it, brother. Tell him, brother. What's going on? Yeah, Woodridge is great, man. Woodridge is great? Woodridge is great. Good stuff, brother. What's the Gorilla Pit like? This your spot? Good spot. Yeah, good spot? Yeah. Good stuff, my brother. What's your name? Glenn. Glenn, good to meet you, brother. Cheers, brother. All right, my brother, later. Cheers, Glenn. Hey! What's going on? Let's go. We're just sussing out the Gorilla Pit, lad. Yeah, we're just the employees, bro.  Oh, yeah? Look how common. This is the second, like, little store, like, drive-thru. Get out. Get into what you need. Hop back in your car. Ride in the little drive. Look at this, look at this. Yeah, yeah. Show me, bro. We got the whole, the fainter part. Look at that, look at that. Next day, he showed up to work. He was fired. What are you doing, bro? Yo, yo, yo. On the regs, bro. What are they doing? I hit you tight. They hit you tight. They hit you tight. Bro, this car is threatened. It's half smashed windows. I don't like it. Yeah, I don't like it. What's they doing, bro? Incredible salt, bro. Incredible salt.  That's all I am a liquor legend himself. For real sweet. For real sweet. Yeah, cut it. Let's crack up. I am a liquor legend. Assaulting patients. Property damage threatening staff. We got problems on Australia Day. About, like, some 14-year-olds. Did y'all? Yeah, they bit Yakin on the arm, bro. They bit him on the arm. Yeah, they bit him on the arm, cuz, like, bit him on the arm, bro. Like, really, even to... Like, with teeth. With teeth to arm? Is that what he said? Two bucks on your boat.  Two bucks himself. Two bucks on your boat. Yeah, yeah, yeah. Look, look, look. It's just the most he preaches the moat. Two bucks not dead by those alive. Logan City. We were just joking about you coming through, too. Yeah. I drove through Berks Street about four hours ago, bro.  Yeah, almost. It's on the news. Oh, we'll probably see it later. Check seven news. Yeah, yeah, seven news. Yeah, word cards are very word. Oh, this is absolutely those things. This was threatening us boys. Was he?  It sounds like full drama is working here, though. Bro, it's a win. Our seckeys, bro, they leave.  It looks like, like, anything that's too close to outside, like, your job is essentially outside. Like, anybody could walk up to it. They don't gotta go through a double door or nothing. They just in there. Like, every two weeks. Yeah, they leave, bro. Oh, they can't handle it. Bro, they cycle through seckeys every two weeks. Big seckeys, too. Yeah, yeah, yeah. I just met one of them. Yeah, yeah. He's gone in two weeks. I bet, bro, he's... No, no, no, no, no, no, no, no, no, no, no, no. It's a hole. Oh, that's the hole. Oh, my God. Oh, my God. Sorry, sorry, bro.  Wow, that's crazy.  She's local way.  That was my little buck. She don't care. Ban for life don't really mean you ban for life. Like a store, like, you know, there she go right there in the blue. That was her. Guy, he took us back there. That was mad. What are you up to? You've been in my hometown, Darwin. Yeah? Yeah? Is that where you're from? Yeah.  Yeah, I was in Alice Springs a week ago. Yeah? Yeah, yeah, yeah. What's the reason why the whole poppers was going down there? It was. We're in the news. They're shutting down the streets because of me, lad. It's not my fault. I'm not telling them to do anything. They saw it as you would you just mad? No, I don't. What's up? What's up, man? Hey, hey, hey. What's going on, man? The news that make you think is him, though. Like legitimately, like. I'm pretty sure like half of Australia or half of that area thought it was genuinely he was there, causing the road came and left in like 30 minutes. Hold on, hold on. One more. Hey, man, hold on. All right, all right. Hey, the whole of fame or the photos up. Those up those cracker we just pulled over there was like four car cars down there with four officers in each car Like a whole bunch of officers we thought I'm gonna pull us over, but I think what they're doing a raid So we're gonna go down here and see what he sees exactly what they're doing Yeah, I'm just worried about the files. I'm just ready for the SD card when we turned over I'm like I was about to pull the SD card at the camera and check it. I swear Joustals like what are these food tribes? I don't think you was about to do it. Wait a minute now You about to put this SD card You know what I wouldn't blame you honestly at this point That's a million. That's $10,000. You got to check it. I'm pretty sure his rate is a $10,000 for a million views Maybe more 10 to 20 easy Oh, yeah, I'm definitely cheeking that pause No, it's a bit dark, but we've come to like some of the worst traps a And those coppers that we just drove past that were doing a raid are just like just over that crest there Maybe 80 meters up the road We're walking through the worst worst up trays full middle of the night pitch black with a spotlight It looks hammered down here sirens See this behind me I seen him do this stuff all the time during the daytime, but at night now now you really Wait, she getting chased I Thought she was getting chased they coming around I So you're going to choose everywhere Sirens everywhere as people run them So this spot is full red odd I not gonna lie this town deserves a like a like a cameo and grant that photo for sure I can tell already. Yeah for funky J. Fine. Yeah. Hello Yeah, but this place is this place is full proper. It was for the parking only sketchy Hey, just be be careful. Why because you got thumbs on to love that looks red. I'd bramble walking through that land I'm a lot for back Is that a door this is a random door sitting here who The hawk ripped it off or something walking through their land They're gonna I've a my life for backpack of murderers up there lad What are the coppers doing The coppers are there creeping in people's houses There's two coppers just there creeping down someone's house. We spotlight so They're looking for that girl Yeah, you will say I'm just guys done. I'd say yeah, I say I'm just yellow is done a snotty. Yeah, I see kins They're going in yeah, but he's flat off these flats off again ghetto. Yeah, we're hurry These flats are ghetto Yeah, these flights are full ghetto Coppers creeping around now. They're right in some town So what happened is they're looking down the side and the coppers went to the door the lady that lives there would have willingly Let the police in they would have said we think someone's like in your backyard and she would have said yeah come through like They're not raiding the house, but they're like clearing her premises. Yeah with her permission. You know what I mean? No way what he's doing Thank you I just got a gun pulled on me to have a night brown. What for can we walk it up in the top complex coppers or someone else? No, from someone else. No way word someone trying to run.  Okay, anyway, I'll be our something Word Now they're going into the is that your house They're going in yeah, they're going in a house They're going in a house the coppers are just walking in everyone's house So what are they doing looking in your backyard? Oh, look at the right Oh You see in this that's what I'm talking about they talk about that's a possum that ain't no possum I never seen that What is that a wombat possum no, no, we're not we're not done.  It needs more discussing We're not done Go back to This the most Australian thing I ever seen in my life shorty get up now you need 20 shots in your stomach To make sure you don't got rabies like what are you doing? And That is the stuff that I come that I would want to avoid You know I'm saying that's what I be talking about when I be like man, Australia to nature even me I'm what y'all said that's a possum. I doubt it never seen it That don't look like a possum to me What's it called maze of yeah, it's crazy down here police. Oh, yeah, is it always like this? Soon as we got here police are like raiding houses Yeah She clearly what's our list what you doing? We're trying to signify some Well, it was so like living here. You live here. Yeah For years. Yeah, what's in what way in what way? Drugs knew it knew it No offense, that's a rough path to go down. She wanted to say it but her kids there I was four years clean and I moved here and it's everywhere and But I Yeah, yeah It's hard to escape it here.   How'd you get it back? Oh, no, they're enjoying riding in it. Nah Yeah, yeah, all right, thank you for talking so yeah, so it's not just the arts It's all down there, but she's saying like that's that part up. There's the worst Yeah, but like yeah, everyone there was clearly clearly addicted to drugs Yeah, 100% 100% bro, see all the kids all of them. It's it playing around that Yeah, yeah, that's sad bra. Oh, that's an undercover cop card. He's too. Hey, yeah Yeah, yeah undercover cop car those flats were crazy That was sad bar like you were saying like all of those kids running around I looked in the grass There was like syringe packets in syringes. They had no shoes on or nothing in the grass.  That's why I'm sure you touched that possum like that She probably just you know what I'm saying that ain't nothing to her possum like that's those flats like awesome and drug-addicted parents Yeah And then the other kid comes down and goes on he goes like someone put a gun on him You know it was so normal like they didn't even care that the police running around it's just the they went into her house She was like why you going in there? All right, brah?  We're already famous James brother was grouse. Thank you boss. I ain't even there and I'm stressed out I'm tired. That's tough till a little like comment subscribe turn up post notification bells man Span keep doing what you're doing man. I enjoy it fully all the time pause


I got us into all public supermarkets and then Kroger supermarkets, and when that happened it was game-changer They brought us into full distribution overnight, which doesn't happen. That's insane. I was like, how many stores and they're like, you know, all doors. People got cookies.  Getting that distribution I knew we were gonna be a real company.