Welcome everybody back from break and thank you for your participation in the trivia poll, more than 1200 people participated in the poll. 81% of you experts picked the winner of the only US gold medal in 1968 as Miss Peggy Fleming figure skater. Interesting factoid Peggy Fleming moved to Colorado Springs, Colorado to go to high school to train at the Broadmoor Figure Skating Club and and then 52 years ago won her gold medal in figure skating. So we are jumping into our next session. Focus on strength and conditioning and biomechanics and I am honored to introduce our first panelist Dr. Matt Jordan. Matt has been a strength and conditioning coach and applied sports scientist working with international athletes over six Olympic winner games. He's currently the director of sports science at the Canadian Sport Institute in Calgary. Matt has consulted with more than 30 Olympic and world championship medalists. Dr. Jordan, thank you for joining us. Hi, my name is Matt Jordan. I'm the director of sports science at the Canadian Sport Institute Calgary, which is one of four Olympic training centers in Canada. And it's a real pleasure to be here today to share some outcomes from a paper that we published recently in frontiers and sports and active living, looking at monitoring the return to sport transition after ACL injury in an alpine ski racer. So over the next 15 minutes, we're going to talk about why it's important to have objective metrics to support the return to sport transition for ski racers, the importance of not adding to the uncertainty around ACL injuries, the importance of a team approach and how we use monitoring to help support the athlete in their transition back to health and to performance. So why this matters? Alpine ski racing is a high risk sport for traumatic injury in general. But ACL injuries are the most common injury type. And what we know is that 20 to 40% of these athletes will go on to suffer an ACL re-injury, often to the other side. These athletes are constantly managing risk. It's a very demanding environment, fatigue, high forces. And it's a very technically and tactically demanding sport. And as previously mentioned, ACL injuries occur frequently. Injuries often happen like the video you're seeing on the screen, a very high energy injury mechanism, the athletes landing in the back seat and suffering a catastrophic right knee injury. When you talk to skiers about this, oftentimes they downplay it. Sounds like, you know, getting your wisdom teeth pulled like everybody goes through it. But what we know is that it's much, much more than just an ACL injury. There's often trauma to other knee joint structures. These athletes often go on to have arthritic knees within a few years after their injury. And it's about restoring confidence and function to help them make this transition, you know, not only back to health, but back to sport in this high risk environment. What we want to avoid is what's often been referred to amongst our team as the regrettable cases from the past, you know, where athletes have been potentially cleared too soon to get back to snow and then suffer a re-injury. This athlete that you're seeing on the screen right now had a left side ACL injury and you see him now holding the right knee. So he's just suffered a knee injury, a contralateral knee injury. And this happens all too frequently in Alpine ski racers. And it's at this transition back to sport where mistakes happen in our judgment. It's very easy to get bought in emotionally to the athlete's journey back to sport. And oftentimes, you know, we want nothing more than to give them the green light to get back on snow doing something they love. But it's here that it's critically important for us to be able to have measures, to have objective measures to help support our decision making account for our confirmation bias and make sure that we are doing everything we can to support this athlete back to sport in a healthy and safe manner. So we gave in the paper, we talked about this idea of a bucket of blue chips and red chips that we could boil down a risk profile for an athlete in a really simple conversation using an analogy or a picture of a bucket of blue chips and red chips so that we could help manage discussions around when an athlete should return to sport. And this is critical because, you know, after an ACL injury, what's the first thing that the athlete says? When am I coming back? And, you know, they might look to the media and hear stories of athletes coming back at four months and five months post-surgery, these very aggressive timelines. And obviously, we have to be able to contextualize this to the athlete. So how do you contextualize uncertainty? This case study was built around the athlete that you see on the video here. And she's given me permission to talk about her case study for the purposes of science and education. Here she's suffering a right-side ACL injury and actually a shoulder dislocation. So the question would be, you know, how are we going to contextualize the uncertainty around when this athlete's ready to get back to sport? Well, if we use this idea of a bucket of blue chips and red chips, the bucket on the left side is the rough risk profile for an athlete who's not had an ACL injury in ski racing. It's the rough risk profile for suffering an ACL injury, roughly one to two skiers per 20 skiers per season. What we know is after that first ACL injury, the risk for a second ACL injury goes up about 14 times. So now, instead of pulling out of the bucket on the left, the athletes who's had an ACL injury is actually now pulling out of the bucket on the right. And based on the pictures, what you see is you get a blue chip, you're all good, you get a red chip and you've got an ACL injury or re-injury. So should I get back early? You know, should we go back after four months, six months, eight months? Maybe we should wait 24 months. Well, what it boils down to is being able to contextualize this risk in a productive way to an athlete and within a performance team that's there to support them. So imagine we're talking about an early return. Well, we might be pulling from the bucket on the left. Here, represented on the bucket on the left is the notion that the athlete had a limb symmetry index of less than 75%, which means that their asymmetry and quadriceps strength in this example is more than 25% from side to side. So, you know, there are blue chips in the bucket, meaning if the athlete reaches in there, grabs a chip, there's no chance they could pull out a blue, but we just see a whole lot of red. Now imagine that we wait until the athlete clears that 75% limb symmetry index. So now they're above that threshold. We see that the risk profile has changed looking at the middle bucket. And then let's take the bucket on the far right where we wait till the limb symmetry index is more than 90%. So less than 10% different side to side and quadriceps strength. Now we see the athletes pulling from a much more favorable bucket, but it's important to know that there's still red chips in the bucket. And that's one of the challenges around contextualizing risk is sometimes that we feel that, you know, if we do everything right, everything should go right, but it's just not the case. You know, the reality is that even on the bucket on the right where you've tried to check all the boxes, there are still red chips in the bucket. And that's an important thing to contextualize when we're talking about the risk of ACL re-injury and how to manage a transition back to sport. So the question becomes, what bucket do you want to pull from? The bucket on the left or the bucket on the right? Also, in addition to sort of having this conversation around risk of re-injury, it's important to have a multidisciplinary team that can help support the athlete. In this case, we highlighted the role of the nutritionist, the strength and conditioning coach, the psychologist, the sport medicine physician, the orthopedic surgeon, and the physical therapist. And we proposed this idea of it being a holocracy or a flat leadership structure, which would mean that at any given point in time, any of the team members could step up to voice an opinion or lead a situation, depending upon what was called for. And that this was one way that we could sort of support and avoid, support the athlete and obviously avoid making a poor decision around when an athlete's prepared to get back to snow. The other idea with this performance team is being able to create alignment and purpose with the use of data. And this is just one example that we used. And what you're seeing on the screen right now is data from our database collected at the Institute on athletes with ACL injury, in this case ski raisers. And we're looking on the left-hand panel at the asymmetry in the concentric phase of a counter movement jump and the symmetry in the late phase of a squat jump shown here on the right panel. The black horizontal line represents 0% asymmetry. And in this case, asymmetry was calculated as an average between five and 10 jumps. And we can see here, when we look at on the x-axis of days from surgery, that there is a recovery in the functional asymmetry as time progresses. So here, early on post-surgery, some athletes are approaching nearly 40% asymmetry in the counter movement jump. Some athletes had asymmetries of more than 50% in the squat jump. And we could see that there's a recovery in the functional asymmetry as time progresses. So with this data, we're able to now contextualize what the recovery rate looks like for an athlete. So rather than having returned to sport be sort of like a final exam where the athlete crams for months and goes and tries and goes to try to pass a battery of tests, we propose this notion of monitoring. So here, we can now track the trajectory and the recovery rate of the athlete to be able to have a conversation around, is the athlete tracking according to expectations, behind expectations, or maybe they're tracking rate on what we would expect. And this was a way that very early on is the athletes recovering that we're improving the quality of the discussion and improving the team's ability to support the athlete. This example looking at vertical jump functionally symmetries is just one example of metrics that go into this idea of a risk profile. But the important thing is having the capacity to monitor these simple things consistently over time. And in the paper, we did highlight the importance of making sure that we are considering the time from surgery. That's another important factor in a successful return to sport after ACL injury is ensuring sufficient time for tissues to heal. But blending this idea of a time-based approach and also a functional milestone-based approach for the athlete. And we propose this idea that in this environment where decision-making is often comes with added pressure and added anxiety, that we could communicate this timeline and milestone-based approach for return to sport in advance, like many, before an injury even happens, at the start of the season to a team of non-injured athletes. To discuss the idea that not only are we going to be considering the time from surgery, which will be guided primarily by the orthopedic surgeon and the sport medicine physician, but also the functional milestones. And then at that point where we see a transition back to sport, that it would involve not only just a medical viewpoint of how the athlete was adapting, but also their physical and mental performance status as well at that point. And importantly, we use this word transition. Transition meaning that in this phase as the athlete makes her way back to snow, there's the possibility of both progression and regression as they make their way back. And then at the very bottom here, and we'll speak to this in just a couple of slides, is the important of having monitoring. So rather than, again, this sort of clearance approach where a bunch of testing happens at a discrete time point, how do we monitor the athlete to support them in this journey back after injury? So with our case study, we have here on the screen a counter movement jump, which was one of our core monitoring tests that we used in our return to sport testing battery. So we had plenty of pre-injury data for this athlete, but also were able to get multiple time points as she was recovering after her injury. And you'll see here on the left hand panel, a representation of her vertical jump profile at about five months post-surgery. And here on the right, the vertical jump profile at seven months post-surgery, right where she was about to make a transition back onto snow. And you know, in this case, the green and the blue line represent the ground reaction force from the right and left limbs. In this case, the blue line representative of the ACL reconstructed limb. And we were able to use this data to build a risk profile for this athlete along with other data points. So take a moment just to consider her data from vertical jumping. Again, we have the asymmetry index shown on the vertical axis and all of her jump tests going back to, you know, May of 2012 all the way to May of 2019. The black horizontal line represents 0% asymmetry calculated over at least five jumps. The black dash line is plus and minus 10%. And what we have here in panel A is the eccentric deceleration phase of a counter movement jump, the concentric movement phase of a counter movement jump in panel B. And then the early and late takeoff phase of the squat jump shown on the bottom two panels. So the squares here represent her pre-injury data. And so these are all the tests that she would have done before the injury. Here we have is the black dash line, where the injury occurred. The second black dash line shows the return to sport transition. And the solid black line shows where she is at 18 months post-surgery. So this is an 18 month post-surgery measurement shown here on May of 2014. And, you know, this data shows a couple of important things. First of all, if we just take, for example, a look at her concentric phase of her counter movement jump, you can see here flirting with just about 10% asymmetry after her ACL injury, which isn't horrific. But we can clearly see that the profile, even though the asymmetries are low, she's not looking like she did before until she's about 18 months post-surgery. And that's an important concept. Because in this particular study, while the functional asymmetries that we measured were low in this athlete, we did see some very interesting trends surrounding her quadricep and hamstring strength. So on the left panel here, panel A, we see quadriceps and hamstrings maximal strength. And on the right hand panel, we are showing rate of force development or explosive strength. The solid line is her knee extension torque. And the dash line, which you'll see in a second, is her knee flexion torque. Now importantly, we see a small gradual recovery in her knee flexion torque. We see a nice robust increase in her knee extension torque for her ACL reconstructed limb at 18 months post-surgery. But the really important part of this case study was the de-training that occurred in both quadriceps maximum strength and explosive strength over the post-injury period. And as you meant, as I said earlier in the presentation, 20 to 40% of these athletes will go on to suffer an ACL re-injury. And very often, that's to the contralateral limb. So the important message in this case study is the critically important viewpoint of measuring strength not only in the injured limb, but also the non-injured limb. As we come towards the end of the presentation, I just wanted to briefly touch on another part of the case study that was important. We talked about measuring workload. And in this case, we did that through the Session RPE method. But what I wanted to point out is the fact that in her return to sport training plan, it was periodized. So we had periods of recovery and unloading shown here, in this case here with a circle around the dot. And we talked about the importance as this athlete was coming back through the return to sport transition that prior to getting back on snow, we had ensured she had restored her physical work capacity to comparable values that we would have seen in previous seasons to support the return to snow and the on-snow training environment. So just to kind of touch on the final point here about some of our losses, I just wanted to point out the importance of debriefing. That was a comment that we made in the paper is how important it is not only to focus on the things that we've done well, but also on the things that we could do better. And debriefing is a critical part of this process when it comes to supporting athletes after ACL injury. So with that, I just want to wrap it up. Thank you very much for your attention. This sort of gives us a summary of where we came from today. I'd like to acknowledge all of the individuals who helped support me with this presentation today. And a big thank you to all of you for your attention. And hopefully now we can open it up to a few questions. Thank you.


What's up guys? Mine is Michael and welcome to my YouTube channel today. We are going to go over this problem called hangover This is actually not a difficult problem I'm not actually going to read the story to you because I think it's kind of useless, but basically You're just adding the number one half plus one third plus one fourth up to one over n plus one So this is like you're the function one half one third and up to n plus one So now what they're saying is that given this C? Number C you want to find the number n such that the summation from one half to One third to one over n plus one is going to be just greater than C So that's basically that boils down to the problem. So so n is like a n is a number that you're summing from one half one third one fourth up to one over n plus one and They give you a number C and you just have to make sure that You find the number that's just greater than Find us the n that is the who's sum that's just greater than this who some of the series is just greater than the C Value so I'm there's not much to it actually so you could just brute force this So I'm just going to explain the code to you guys because there's not much to it so the difference between spodge and the and code forces is that spodge Code forces give you gives you the number of test cases a spodge What they do is that you have to if you input zero Then the program should stop. So because of that. I just used to do what would do while loop So do while C is just the input C value which is a Each of the input values here of one One dot zero zero three, but dot seven one Right, and I just check if it's not equal to zero, right? And then if it's equal to zero then the program would stop. So that's what this would do while is okay So to brute force it basically we're just going to keep looping We keep looping and we're going to keep calculating the value and once it's greater than our C then we stop So that's basically the gist of this problem. So yeah, I create a value called zero Float value and I said to zero and I create a value of n I said to zero, right? Then what I'm doing is that a while while this current our current value is less than C Right the input value. We are going to add one to a value at our value n and then we are just going to plus equals to one over one plus n plus one Where we're gonna add one over n plus one to our value. So that's this part. So that's this part Right because we're just summing up one half plus one third plus one fourth up to one over n plus one And what we're doing is we're just gonna slowly increment n until we get to a point where the sum of one half one third one fourth up to n plus one of one over n plus one is going to be Greater than C greater than or equals a C. So that's what this while loop is. So yeah, so every time We're going through our values We're just gonna keep adding plus equal to one over one plus one over n plus one We're gonna keep adding that and then we're gonna add one to n Right because we're gonna we're just keep trying the value until it reaches it then at the end of the loop We just display n because that'll be the number of cards That'll be the end it will be the card number that is that is displayed So yeah, that's pretty much the gist of this problem once it gets to the end We just display it display and and make sure you guys put a space and then had add cards because That's what the input statement requires it for But yeah, that's basically the gist of the problem Basically, um, if I could explain the test cases If you guys want me to because I could just show it to you guys what I mean by that so like I Could explain what it what the test cases mean. So like let's say we add our C is equal to 1 Right our C goes to the one dot zero zero So basically in our in the equation one half plus one third up to One over n plus one. We want to find the value n such that this sum the summation is going to be just greater than C So basically what we're doing in our code is just we're just gonna keep adding one by n So we start n at zero Right and then it would add up one one one plus n plus one zero plus one would be one half it would add one half Right and then after this it'll add one third add one fourth and then sooner or later After this sum, you know, the sum is going to be greater than C and when that happens We just break right we end and when that happens this while it would be finished And then we would just have our value of n in which the case this this summation occurred and then we just display that Okay, and I check if C is not equal to zero because if C is equal to zero the program stops Right, so then then you know what you're not supposed to print anything. So yeah, that's pretty much just the problem I hope you guys understand this video is pretty short Raycom subscribe. I'll check you guys later. Peace


It's about 8.30pm. I haven't had anything to eat. I've got two scoops of amino energy and some some water over there. So that's 100 milligrams of caffeine and five grams of BCAAs and I'm just gonna sip on that whilst doing some morning cardio. So my shift starts at 9.30pm today and I'm gonna go to work right now. I'm working in town.  So I'm gonna park at work, I'm gonna walk into town and I'm actually gonna pick up a parcel from the post office as well. So kill two birds with one stone, get some cardio under my belt, go and get my package which is from Massive Joe's which I can't wait for. I think I've got some BCAAs, a singlet and something else that I can't remember what I got. So that's exciting. Everyone loves packages, especially sups and yeah I'll be at work by 9.30pm. Lunchtime's at 12, 12.30pm and that will be when I have my first meal. I'm feeling not too bad today. I only had about 13, 1400 calories yesterday because you know I fasted so long it was like by the end of the night I sort of well after I trained I had some Greek yogurt and I had 360 grams of Greek yogurt which is two serves and one scoop protein powder and I had a serve of oats as well. So you know protein was only at about 120 grams yesterday which is not enough but today I'll certainly be hitting that 200 gram mark and trying to keep calories under 2500 which I don't think I'll have a problem with though I am just about to park up and then we'll be hitting the streets and heading to the post office. So I don't know about you guys but I certainly have that entrepreneurial sort of spirit. Always have, always will and so one of the things I like watching the most is interviews with people who have become successful through you know their own entrepreneurial ways and at the moment I'm actually listening to a guy Grant Cardone. I only just found out about him but he is very successful financially and he is in the real estate game which is what I want to be in. So I'm getting some good inspiration from him. I got great inspiration from Greg Plipp when it came to my physique and when it comes to real estate investing I'm getting awesome inspiration from this guy Grant Cardone but there's so many awesome like interviews out there. You know people have gone from rags to riches, wicked stories, no luck involved. These guys have knuckled down and put principles in place put yeah I can't really talk too much about it right now because I'm learning but one day I will know and I'll be a real estate guru and then I'll be telling you guys what to do. We are back. See what we got.  TMJ all day repping that natural bodybuilder and we got some more core ABC. I've tried watermelon and so we've gone with white appletini which I've been recommended from the boys at Massive Joe's so that'll be going in my new shaker. So that's an hour's cardio in the books feeling good.  I might have to put that sleeveless on right now but either way I will go into work now and I'll see you guys at lunch time. Alright guys just got home we are on lunch and I gotta put my new sups away. So this is my so-called supplement shelf. We've got protein powder down here now my current protein powder I'm using is MTSW. I've been using MTSW for probably a couple of years now. Cinegram can't go wrong with that. It's pretty pretty awesome flavor. You can mix it with you know anything you want chocolate banana freaking oats you can mix it with anything it's pretty it's awesome so that's my current protein powder of choice and we've got core ABC that's BCAA's two different flavors of amino energy which is caffeine and BCAA's watermelon and grape I would have to recommend. I've got gold standard pre workout and pineapple when I want like for pre-workout I'll either use a fat burner if I'm using it basically I just need something with caffeine in it that is that's really all I'm looking for in a pre-workout as far as pump supplements you know I'm not too sure about them.


The flight line at Naval Station Rhoda lies along one of Europe's most active bird migration paths. The Bird Aircraft Animal Strike Hazard or BASH program have been conducting research all year long to find the best ways to keep our runway safe. The migrants are the ones we're worried about because when they come here they're not used to airports, they're not used to airplanes. August-September we formally began our experiments and conduct our experiments to see if the tube man actually works well as a bird deterrent. The work the tube man has done is we're putting him near some of these airfield equipment and that's really made a big difference with the raptors, the hawks. And what we found was using this 20-foot tube man that you see behind me, we had on average about a 67% reduction in the amount of wildlife was sold. No matter how wacky or wavy the solution safety is always first at Rhoda's Flight Line. Petty Officer Christina Brewer, Rhoda, Spain.


Hello, everyone. Welcome to my talk. The title of this talk is Optimizing Speed and Scale of Real-Time Analytics Using Apache Pulsar and Apache Pino. And I actually have both data stacks, which is the company I work for, and then also StarTree, which is supposed to be my co-speaker Karin Wallach, but she can't be here today. So I'm doing also covering her part and also just a note that this talk is only 30 minutes, so it's going to be a bit compressed. And then I welcome you any questions afterwards as well. And also not just here on site, but it can be offline too. So, okay. So thank you very much for coming. And oh, first of all, if you're interested in this slide deck while I'm talking, it is here, the QR code, if you're interested. Just a very quick thing is that, well, data stacks is the company that the flagship product is Apache Cassandra on the cloud, Astra. So they've been in business for 10 years, based in California. And recently, a year and a half ago or so adopted Apache Pulsar. And it's now also managed cloud platform called Astra Streaming. And that's Pulsar underneath the hood. And then with StarTree, they are startup company. And if you're familiar with Confluent, Tim Berglund, who was the DEF-REL director at Confluent before, he's now at StarTree. So they are open analytics and they are the ones that power pretty much LinkedIn of their online real-time analytics too. So that's StarTree. Okay. So with that, let me start. Very quick. I don't need to introduce myself as much since, presumably, you were here this morning when I did my keynote. So I'm streaming developer advocate at data stacks for those of you who didn't come to this morning's session. So I'm, I was an engineer for 20 years before, 20, over 20 years, actually, in more Java. And then prior to that was some CN, Unix and then Java. And then started becoming an advocate in five years ago at IBM. And now I'm at data stacks. So, and I'm also Java champion and based in Chicago. I also run the Chicago Java users group. And this is just a quick thing since Corinne isn't here. I told her I would just kind of introduce her to, you know, to you here because the slides to from StarTree is from her. Corinne is from StarTree. She's head of developer community at StarTree. And yeah, she's just a very energetic person too, but too bad she isn't here today. But yeah, so just introduce you to her. Okay. So today's agenda. Basically too, I wanted to start by kind of understanding the problems that we are trying to solve here with Apache Pinot and then also pair with Apache Pulsar. Although I don't necessarily now have a use case to show you, I will have future talks that will actually have demo too. But for now it's just more about the talk. You can use Apache Pulsar as a source data source for you to ingest data. So then it feeds into Apache Pinot to do real time analytics kind of work. So we kind of try to understand the problems first and then giving some examples and giving some quick background of the evolution of real time analytics too. And then basically too, how can we use, you know, and how and what can we use for solving the problems is basically an open source solution using Apache Pinot for real time analytics and then also then Apache Pulsar for real time data ingestion part. So that's pretty much a thumbs up for the next 30 minutes. But let's first start to talking about the types of analytics use cases. I think what we are more used to these days when we talk about think about analytics is, you know, from the, let's say, you know, 20 years ago or something in the IT industry, most of the time too, we are dealing with statistics, right, being displayed on dashboards in your company, maybe website, you know, for marketing for business decision makers. They were using like BI business intelligence tools and a lot of times too, they may be doing, you know, analysis from data warehouse. So very much kind of, you know, not real time and also batching up all the information and processing them, making sense out of it. Those are kind of the, you know, what we're maybe come, we have come from a bit of an older way of doing analytics. And then now with the, you know, times have changed now, we're kind of talking about machine learning artificial intelligence. So now too, they're also the machine learning part that's ingesting like real time data. And also, you know, essentially to defining your model data model as the data comes in, that requires kind of real time, huge volumes of data kind of processing too. So that's machine learning. For example, even like machine learning ops by ML ops too, they are essentially helping it's like DevOps, but then it adds in the machine learning data part of doing, you know, real time analytics and immediately turning out the model and immediately doing rapid deployment. That's the theory. Okay. So that's machine learning. And then, but then today too, this particular example we're talking about is more about user facing analytics.  And that's actually utilizing real time and analytic software. And they actually at LinkedIn, they are using Apache Pinot. So and, and in fact to Apache Pinot is kind of came from the LinkedIn engineering too. So now this company is called Star Tree that's working on developing further. Okay. Okay. So then this is just a diagram explaining to you again, kind of going back, right? The dashboard BI tools, they are kind of more dealing with data that's already in your warehouse. You're drawing them out and doing analytics and drawing out pie charts and graphs and all sorts of stuff. That's kind of BI tools. And then again, well, this, this one is actually machine learning too. As you can see, how many of you actually are working with machine learning? Maybe I'm just curious or maybe some, yeah, maybe you're then familiar to having to ingest huge amounts of data. But I think my understanding is that I think a lot of the machine learning kind of, you know, production, so to speak. And they are not actually using real time because of the huge amount of data that they are explaining. I've talked to some, some folks who are in machine learning engineering, they said just cannot, you know, like ingest like terabytes of data, for example. I think right now, maybe the streaming systems are still a little bit like short on being able to, to ingest so much data. But theoretically though, once, you know, kind of reach a point of maturity, you can actually do real time, huge, you know, really like huge, humongous set of data to at the same time. So, okay, so then this one is the user facing analytics. For example, here too, I already talked about the, you know, like your page and your items and, and all of the real time like messaging, all of these things, as you can see, it's kind of immediately analyzing all of your activities and then print out who view your profile impressions of your posts and they are kind of near real time, not quite exactly real real times, you know, by some definition. So, okay, so then in this slide too is kind of basically talking about why should I care, right? So we're looking at, first of all, right, in a business too, you have like business monitoring used to be to is, you know, you have an ops team that are kind of doing monitoring of these things. And then the thing is that as business getting more sophisticated, then you get into analyzing business insights, all of these things, and you get into the, the analyst side of things, right over there and over here and analysts. And then essentially too, the goal actually of Star Tree from what I know from Corinne's explanation too is that we want to basically shift the power, essentially having the power of the data in your hands for the end user is what they're trying to do because previously you do all these BI tools and analysis is really for corporate big teams like they are the ones that have, you know, access to those data only. But now you want to kind of get into all the insights and also monetization too for companies that are business entities trying to, you know, make more money and all that stuff. You basically want to shift the power to the end user, essentially. So it's it's that's what it's kind of like giving kind of importance to this area of computing is you are now able to actually analyze your data and basically monetize it as well. So so kind of like this whole chart is basically saying the business has evolved over the years. So we want to kind of shift to doing more, everything more real time. Okay. So this one too, I think it's just an example and it's showing you the LinkedIn as such where I already mentioned about who viewed your profile. So like over here, it's very much near real time. And it just does all the analysis on your profile as it happens too.  So over here to actually Karina already told me that the total number of users right now is showing 700 million, but LinkedIn already has reached higher than that at this point because she took this picture like a month or two ago. And all of these to the query per second, all of these are kind of also like increasing. And also the latency to that they want to have like less than 100 milliseconds, right? And the freshness of your data to is in seconds. And that's what this is. Okay. And then this is also another example of user facing real time analytics. As you can see to over here, I think it's kind of probably same, same kind of information in here too. It's just basically also showing you to who view your profiles, view of your posts, all of these other things and the messaging, everything is being done essentially like very much a real time thing. Okay. And then this one too, actually another usage too for these user facing real time analytics would be useful, would be for like recruiting firms, right? They are out there searching for candidates at any time. So they need to have more like a real time analysis, right?  And so these talent scouts out there are constantly be watching your status change. Once you are open up, they may they are going to reach out to you for whoever they are looking for the skill set and all of these things. So okay. And then this also is another example too of this user facing real time analytics would be like Uber eats, for example. So say, for example, right, you, you want to be able to have real time service, especially when you are doing food delivery. And let's say, right, if someone, you know, ordering everything's done online on Uber, and then they have some orders that they missed, or maybe they receive an order the delivery and they found out they missing some dishes and they wanted to report it right away to Uber. So the thing is too, and that's when you want this information to come to you in real time, because you don't want to wait now. The food is fresh and they deliver something, they forgot something you want.  So that's kind of, you know, very, you know, a use case for this type of system too. So, okay, there's also another example too is from Stripe, which is the financial company. And hope over here too is basically they are using like real time analytics use cases in financial statements and reporting, and then also the bugs and problems analysis, detecting like financial risk and also like managing essentially their business operations, their liquidity, you know, their financial line to are they doing good. So you want to have that kind of financial information at your hands, you know, really up to date to an act on it immediately if something goes wrong, something. And also as well as like auditing too, there are past actions too that happened, you want to be able to audit that and give you very tangible kind of analysis and results so you can again, you react to it rather than waiting for it and it becomes too late, you could be sued if you forgot about something in your procedure, for example, things like that. Okay, so, okay, so this one is just basically saying what problem are we solving is basically teams like executing like money movement, those are kind of prime candidate to use this kind of real time and analytics type of software. Financial data consumer of these are kind of prime kind of candidate for this type of software. There are also unique challenges and opportunities too. So you want to make sure especially financial data has to have high precision and accuracy too.  And so basically there are also like many small unit transactions and also like small currency units can vary too. So you want to have very accurate kind of calculations very precise as well. And also granularity has get onto the transactional level granularity and reports too must be reproducible and and also then requires like frequent manual action to all of these things are meeting compliance security. So as you can see financial data and requirements especially, you know, for analytics, it's, you know, analytics can be applied to financial applications, you know, heavily in this case. Okay. And so now let's then kind of take a look further into user facing analytics. On the left side is internal analytics. So these are maybe like company internal analysis. So the latency can be you can tolerate up to seconds in latency. A freshness that can be seconds to minutes and concurrency, maybe hundreds of users. But whereas if you look at like external analytics, and these are like user, like your customer facing side of things or potential, any kind of external analysts, right, you want to have super fast latency of milliseconds. And the freshness have to be in seconds too. And concurrency, you don't know how many people are going to come to your site to look up information that type of stuff. So it has to be really kind of very robust, you know, especially in the external analytics side. Okay. So now then this one is about evolution of real time analytics in here. So essentially we're talking about it's this landscape is rapidly changing. It used to be the OLAP right online analytical processing system that are older, doing like data warehouse and dealing with data. That's kind of already data at rest and you pull them out and do things with it. But these days too, we want things to be done much faster. You want the data comes, you want to analyze it right away and turn, you know, into like a shopping cart recommendation, for example, things of that nature. Right. And all of these things, as you can see from internal facing analytics, we're now going to user facing analytics. And then structured data has become like going into semi structured data too. And then over here to approximate data query consistency in the past. Now we want strong data and query query consistency. And there's also there used to be the slice and dice queries to that is in the past with your data warehouse, slice and dice, all of these things. Now we're kind of want to support like full SQL semantics. And also in the past to maybe gigabytes to terabytes of data and now terabytes to petabytes of data. So we're handling much more data right now in today's kind of economic climate, right? The market out there. That's how it looks like. So now we go kind of talk about, we want to build a user facing real time analytics system on the left hand side. We know it comes in, we need to ingest. That's very important. You know, the whole essentially the whole pipeline needs to be all real time, real real fast, real time ingestion and high dimensionality and the velocity of ingestion has to be very high. So, and then essentially to it has to be highly available to and very scalable operating in the cloud environment. And also the cost to you want to keep the cost down very effective. And on the left side, as you can see, these are we're dealing with these user facing real time analytics. It has to be seconds of freshness and thousands of query per second and milliseconds latency. So, so now the question mark is who can help us with doing real time ingestion. So now this is where a pulsar we're kind of like to suggest to you. And of course there might be folks already using any other kind of ingestion right streaming kind of ingestion like for example, Apache Kafka. And Apache Kafka is fine. It does its job and everything. But the thing is I want to introduce to you a page pulsar because over here too, as you can see, it is a using a traditional pops up architecture in is kind of a, you know, a quick introduction to you is it is using pops up as an architectural kind of approach to developing, you know, we had this broker that helps with distributing messages right in high volumes, high ingestion very fast too. And then there are brokers that will be handling all of these messages. It's much like you produce your messages, pops up, producer consumer kind of approach, you send the producer will produce messages, send it to the broker, but label it as a topic, right? And it's like a post office. Think of it broker is like postmaster. I get the messages and it's labeled as such. And when the messages comes, then I'll deliver to whoever is interested in receiving the messages. Those are the consumer. The consumer must subscribe to your topics. And pulsar too, by default, it uses one broker, but you can also define multiple brokers as well as you can have topics that can be partitioned across like different brokers as well. In a cloud environment, it's actually very efficient because Apache pulsar itself, it separates out the compute and the storage too. So it pulsar doesn't want to deal with all the log messages, distributed log logging messages in such high volume. So it lets bookie, which is Apache bookkeeper to do the job. And then there's also zookeeper that's in the picture. Zookeeper is there to help with monitoring and managing all your cluster, all of your configuration data, more like kind of really managing keeper of the zoo kind of so to speak. So we'd like to introduce to you Apache pulsar, but basically let's kind of take a look too. Now when we talk about Apache pulsar, it is actually a unified messaging and data like streaming platform. If we kind of, this is a reactive summit, I would say that this actually, it is actually you know, helping to do things in a reactive fashion. And let's take a look at it, right? So what is driving the change, right? It's basically real time, we need real time data to enhance customer experiences. We don't want things to be like, you know, you can batch up your processing, but then in that case, your data may not be as fresh. But in this case, we want real time data is basically when data comes in, you want to immediately ingest it and put it to work, essentially real time. And then another thing is that there is also essentially, I mentioned about machine learning kind of cases, you can use it to build data pipelines to kind of essentially ingest huge amounts of data and then push it into your data pipeline to do machine learning type of analysis right away and then immediate turnaround, then you update your machine learning model and be able to deploy it right away. So that's the idea, you want to have that constant kind of streaming in of data, huge amounts and being able to do that really quickly. And then the third thing too is that we need to have systems that can handle scalability too, that will meet the demands of large volumes of data generated by application that's operating at the edge too. For example, like IoT devices in a huge field, you're collecting data, maybe like weather changes from your huge amounts, the thousands of acres of land, you want to install all these IoT devices, you want to collect all the data, you use this kind of approach, like a PubSub type of approach, it can scale very well too in this case. Okay, so now kind of take a look to again summarizing why event streaming, because we want to watch for the events with the system or the application and we want to be able to subscribe to those topics that are only of concern to you, you don't need to subscribe to all of the messages, you can select the messages that you want and then you can in this case you get the data in real time and not after the event, you can also ingest high frequency of messages with very low latency. Okay, so here too, let's take a look to get into event streaming. So basically too, let's kind of take a look at the times of before streaming, right? And then now we're talking about event streaming. The one below here is that when we're, it used to be too, is that we're doing things not real streaming, maybe there, you know, we think we're doing streaming what used to be, but you still need to maybe ingest data over here. You get some data from somewhere maybe using ETL load, right? The extract, transform load kind of older process, you load them, you ingest the data, but you actually have to persist the data first, right? You kind of write it to disk. Anytime you need to involve any disk IO is going to increase the time, even though if it means a millisecond, nanosecond, it's still, it takes time to read and write. So the IO is going to increase your, your, the time, right? It's kind of decrease your performance. Okay. So then what we used to do is ingest data, persist the data, and then you, you then have to read the data back and then do any kind of processing on it. After that, you write it back to your database to some, some data store, you persisted back and then you do more selection. So it, it works too. Not that it's saying not working, but it's just slower because of this extra layer of your persisting to, to the database, right? Sometimes it may not be necessary too. So if you look about here, we're talking about streaming and everything to you ingest the data and it's in memory, you process the data in memory. And then once you kind of, after you've transformed your data, then you output it to a sync is some kind of destination where you write it to. And then from there, you can do all the selection. Everything is being done kind of faster using this approach. Okay. So now let's get introduced to you a patchy pulsar. So pulsar too, what is this? Right? It's an open source project created by Yahoo engineering back in the early 2010s. At the time they were dealing with Yahoo, you know, all the finance, all kinds of Yahoo services. And then they realized that it's, you know, not able to handle a situation in which, you know, you're doing things on the cloud. You need to add another cluster to your cloud, all of these things. And they find that there are no, you know, library already out there to handle how do you actually deal with the scalability aspect of your infrastructure. So then they decided to work on pulsar and develop pulsar. So over time, it has added quite a number of features to it. And in 2016, they contributed to the patchy software foundation. And then in 2018, it quickly became a top level project. It is very much of a cloud native design, right? I call it like it's born with the cloud native DNA because it takes into account, I'm going to run this event streaming platform in the cloud native environment. It has to be very efficient and it takes care of, you know, kind of the infrastructure dealing with the cluster is all cluster based. And also it's a multi-tenancy to this architectural approach. And I'll show you in a few slides about this multi-tenancy kind of approach it takes. And also too, because of a pops-up nature, you can actually develop your client APIs relatively simple and using different languages too. You are not only confined to using Java, like the broker is written in Java, but you can actually have C sharp client, Python, Go, and any other kind of, yeah, you know, what you call a community contribution like Scala it also supports too. And also the message delivery part is guaranteed too. So the broker, basically your message is reaching the broker, the broker will guarantee that it gets delivered to this intended target even after the network has gone down, for example. And there's also a serverless functions framework called Pulsar functions too, that you can do message transformation as the data is traveling through your pipeline too. So then you don't need to rely on yourself writing another function layer or maybe another external library too. And then there's also this concept of tiered storage offloads. So basically too, your messages are on your system, but it may become like a stale, it's aging out the data, then Pulsar itself is smart enough to know that okay, this data is kind of becoming aging out. So I'm going to move it off to code storage so that it won't take away storage space from your hot storage. So okay. So this is again just a summary. Apache Pulsar is distributed messaging and streaming platform open source, very cloud native in nature too. And as you can see these graphs is showing is increased in popularity and GitHub as it reflected in a number of contributors and the number of GitHub stars. And then these are just a sample of companies that are using Pulsar. It is still kind of growing and importance at this point. And this one too, I'm just going to talk over here actually already talk about that. Oh, this one too. I just wanted to say right in it takes on a very traditional multi node architecture. They're common challenges like, you know, when you need to scale your system, it's actually very nice because it separates out the compute and the storage part storage is handled by Apache bookkeeper. So when it needs to scale like all of your topics to it Pulsar will take care of spreading out all of your topics accordingly. So then you don't need to worry about it. For example, if you are using Kafka, you know that how hard it is to do scaling. You need to do a lot of manual process to make things shift things around. But Pulsar is already built in. It knows how to kind of rebalance all of your topics. And that part is really important too. And so everything is very loosely coupled in this structure. And okay, I know I don't have as much time, but I wanted to quickly kind of highlight right separation between compute and storage is one big thing. And also that supports like geo replication is that geo replication quickly saying is that you can have data center scattered throughout the world and you can, you have to do different replication. You can do it like actively. And also to it, you can do selective message replication. For example, some region of the world, you don't want data necessarily to be replicated everywhere else. Right. For example, like GDPR in Europe, you don't want to like replicate those datas to regions that are not, you know, allowed to have those. So it's all built in. And this one too, another differentiator is it being having the multi-tenancy kind of way of organizing all of your data. So in your cluster, it's basically it's already built in, you can organize your data like using different tenants too. You can have different departments that are managing your own namespace of your data. So it is kind of already built in with all of these things. And it's basically helps you to organize all of your data better too. Another thing too is with the message processing model on the subscription side, you can use an exclusive subscription mode that will turn essentially pulsar into like a message queuing because it becomes like one producer only sends data to one consumer in this case. Or you can have failover, which is have one primary and many consumers backing up in case the primary goes away. And then there's also shared subscription in which you can have more than just one consumer in that subscription. But the shared mode doesn't guarantee your message order. So if you want message order, you want to use like a key shared type of mode to do it. Okay. So let me kind of real quick, this one is just data pipelines. I think we already understand what it is. I'm going to just quickly go through but pulsar functions is essentially it kind of takes on this spirit of AWS Lambda, very lightweight, allow you to do message transformation and it travels through the data pipeline. And there's also pulsar schema. If you want to define your data without worrying about serialization and deserialization, you can use pulsar schema. They can also keep track of the change of your data too. So also there's a concept of pulsar IO, which is an SDK. You can actually write your own source connector or sync connector if they are not already preconfigured. For example, elastic search is already a preconfigured sync. Then if something else you want to do, it isn't there, you can write your own IO pulsar IO connector too. Okay. So data stacks just real quickly is that we have Esther streaming, which is the managed pulsar that actually is pulsar in the cloud. And also Luna streaming is the one you deploy yourself, but you can use our enterprise support pulsar or you can use it completely open source too. Okay. So this one comes back in here. We'll use pulsar as the ingestion is we like to suggest you to kind of combine with the Apache Pinot. So, and over here to just a quick summary is that Apache Pinot, as you can see, right, it can take sources from many sources too. But I want to kind of highlight we have pulsar being added in addition to Kafka. And then basically too, as you can see, it takes care of everything. And the thing is wanting to point out Apache Pinot has this star tree index. And that's what it's kind of like their algorithms that is real, real fast in analyzing all of the data. And then also essentially have very give you use cases of, you know, business intelligence, data products and normally type of detection too. So all right. So I think this one I probably won't have as much time to go through. Sorry. Is it I only have, I don't have much time, but over here is just wanted to say, oh, actually, what's going to show you that that too is basically star tree index is the one that does the index optimization in Pinot. So if you want to read up more about it, you're welcome to do that. I basically have to skip over now and over here. So this is like the link that some resources for you if you need, like to look at Pinot and they also have a slack channel that you can join to is all over here. And then there's the resources for Apache Pulsar. So these are all the links to it, but I want to highlight to the middle one this extra data sectors.com. You can get a free $25 credit account to try out our extra managed cloud platform and you get it for a whole year, more than a year to every month you get $25 it get refreshed to so you can develop like personal projects and try this out to our extra managed Cassandra and managed Pulsar. So that's that. And this if you're interested, there's extra credit that you can get and you can visit that link and give that code. And then also we have five minutes about Pulsar on YouTube. These are just a little bite sized nuggets. If you want to get information, visit our data stacks developers.com playlist. You can find those and also I also do a Twitch stream every Wednesday to usually if I'm not traveling. So if you want to follow me or join me to on my Twitch stream, and that's that's how I do my stream. I invite people in if you're interested to and share your projects. So and then join us at the hood. And this is we have Apache Pulsar neighborhood is a wiki page, the meetup.com. The meetup groups is a little bit quiet right now. So and then with that, I want to thank you for coming spending the time with my on my talk. And then this is my contact information, my LinkedIn profile, my Twitter account, and also my discord. I also have a discord server too. And this is just a picture that's Karin. And then we were at Zurich when we went to a Fox days conference. So that's Karin's connection information. If you want to get more information about Apache Pino and Star Tree. So with that, I want to thank you. And then I hope you enjoy the rest of the conference. Thank you. Supposed to be asking question. But if you have question, please feel free. Also, too, I have some Apache Pulsar stickers. If you want some, yeah, I forgot to mention about, yeah, so it's up here. You can take more than one to if you like. So please feel free.


Do you think there is a crisis in the world and could be an advertising world solved? First of all, if there is a crisis in the world the job is to define it. The second thing I think, which is where I am optimistic, the reason I'm optimistic for the world in a sense, is that really in a way progress happens not so much by the generation of new ideas but by the abandonment of old assumptions. And a few of the things we're beginning to understand now are for example complexity in general. Now if you look at a complex system which is closest to say a meteorological system than it is to a simple mechanical system like a clockwork mechanism such as a watch. It's more complicated to model emphatically. It's far more difficult to change. You can't use simple Newtonian physics in meteorology nor can you use it in economies or in psychology for example. It simply isn't that simple. That's the bad news that actually working out how to fix it is harder. The one piece of good news is that sometimes fairly large problems can be solved by fairly small interventions, butterfly theory if you like. And that's the one area where I'm optimistic. If we start to understand that complex systems are difficult and different from simple systems and that treating economies as if they're like some sort of mechanism involving a couple of cogs and a lever is fundamentally fallacious. Once we start to realize that then first of all we'll stop this business of always trying to have big effects by creating wholesale change. There may be very very small interventions, very small ideas that can have absolutely massive effects. Here in Holland there's a very interesting case which I always regard as just a small example of that where the typical mechanistic view of the world says if you want people to slow down when they're driving down a particular stretch of road you place a speed camera there and that's the kind of logical Newtonian incentives, disincentives, economic model for how you change behavior. To some extent it doesn't work all that well for reasons I won't go into now. What they found somewhere in Holland was with an apparently illogical intervention simply removing the lines painted on the road causes people to slow down instinctively without even being aware that they're doing it. So Buckminster Fuller talked about this idea of trim tab which is the point on a ship or a plane where the smallest movement creates the biggest change and actually on his gravestone it says call me trim tab. That showed an early understanding I think of complexity. This kind of understanding that two things. One, it's not easy, it's not simple and predictable and mechanistic. Therefore we should stop trying to change the world necessarily through grand interventions that cause considerable disruption and we should spend time looking for and incidentally failing in the search for smaller interventions which may achieve greater things with far fewer unintended consequences. So that's where I'm optimistic. First of all we need to accept that actually this is an imperfect science and actually experimentation and failure and modification and so forth. There is much part of the process as having a grand vision. The second thing is to understand that actually it isn't necessary to seek to change the world in order to change it. I'm sure there are people now dead, some people now alive who have significantly changed the world and yet we don't even know their names. That assumption that in order to change the world you have to stage a revolution or achieve massive political power or some enormous sort of upheaval in the way things are ordered and organized. Maybe one of the great misconceptions we're starting to abandon that trim-tab interventions as Bucky would have called them are actually much, much more interesting. In order to make those succeed, first of all politics has got to understand that first of all its own sense of self-aggrandizement often requires it to do massive, high-profile, high-budget interventions. These may not actually be the best use of politicians time and the second thing politicians have got to do is learn to get less embarrassed about failure and say we tried this small thing, it didn't succeed very well, the ill effects were relatively trivial, relax about it. If you look at the business world it really does work through, at its best, Silicon Valley is one example, through stochastic tinkering and experimentation. That's not my phrase, it's Nassim Taleb's I think, stochastic tinkering is how it works. And one of the great things about the business world is that when a new idea comes along, entrepreneurs will try and implement that idea and indeed market that idea in six very different ways and maybe only one of them succeeds. That to some extent is why capitalism works because actually the rewards for trying something different in capitalism are quite high. If everybody else is wrong and you're right, the rewards if you put money in the game for being proven right are really pretty high. You might argue that cultures like politics, cultures like the public sector and academia, there's much more reputational risk involved and actually the price of descent is very high and the potential reward is very, very small. So the great thing about business is if you actually just, there is this extraordinary reward for actually looking at the world differently.  I think you know there is quite a lot that academia and politics can learn from how free markets actually work. I don't mean the deluded sort of neoclassical view of the perfectly efficient market. I mean the kind of Schumpeterian view of creative destruction and entrepreneurial activity. The fact that actually this isn't actually an unstable thing in constant desic disequilibrium which is forever just searching for relative advantage over a competing company or a competing idea. To translate that, not that boring bit about the perfectly efficient market what they've done in trying to introduce markets into say the public sector is actually to introduce some of the less attractive and less useful aspects of the public sector into these businesses but if you can actually understand that there's a kind of dynamic competitive market for ideas approaches and indeed for marketing approaches. Here's my most radical suggestion which will seem to you very weird if you believe that value is subjective there's no reason why the next big revolution couldn't be psychological not technological. If we simply better understood what people valued how they behaved and what made people happy that could actually raise the quality of human life just as significantly I would argue far more significantly than some new widget or battery powered device. They may be slightly interconnected. That's the first point. And so far more intelligent effort needs to go into understanding what you might call intangible value not just how to make material stuff. After all, we're materially quite well off in the developed world already our appetite for stuff isn't infinite apart from anything else you run out of storage space. So understanding the value of intangibles and services and so forth I think could lead to some really important innovation and I think that's a dangerous thing about innovation that it tends to be conflated with a particular kind of technological progress whereas actually innovation takes place in all manner of different places in distribution but also in marketing. If you can work out new ways of understanding consumer needs in a way that's much closer to the grain of human nature then business efficiency can significantly improve without necessarily needing to change all that much what it actually makes or supplies. Does that sound too weird? A lot of people look at this and go it's dangerously close to either propaganda or to kind of brave new world where we're drugged into being content with our own circumstances. I'm just saying there's an awful lot of wasted effort. The other, the final question is how many technological problems are really marketing problems or psychological problems in disguise? So I'm quite a keen fan of nicotine not a fashionable point of view I accept the terrible thing with nicotine was the delivery device and the electronic cigarette seems to be a very important invention it's quite a lot of the pleasure of smoking but with perhaps a small percentage of the risk. The problem isn't the technology that's already there and existing the problem is a whole load of social pressures and frames around the fact that it's just embarrassing to smoke electronic cigarettes in public. The driverless car, Google's more or less perfected that the problem with the driverless car is no longer technological in principle it's legislative how do we legislate for this for blame in terms of software that goes slightly wrong and causes a minor accident equally it's also psychological how do you design cars in such a way that gradually gets people to accept that you can be walking down a pavement and a device with no human in it passes you at 30 miles an hour and that's the real challenge of the driverless car it isn't the technology anymore.


coupled with the fighting skill of the American soldier stands ready on the alert all over the world to defend this country you the American people against aggression this is the big picture an official television report to the nation from the united states army now to show you part of the big picture here is sergeant steward queen a proud tradition is a must for a fighting army past deeds of glory serve as an example an inspiration for the soldiers of today an army post which almost breezed tradition is fortman row in virginia headquarters of the continental army command and incidentally an attraction for tourists from all over the country to give viewers of the big picture our own quick tour of historic fortman row not long ago we flew down to the extreme tip of virginia's lower peninsula from the air it's easy to see that fortman row is really a fort within a fort begun in 1819 it is the largest enclosed fortification in the united states covering 63 acres of ground around the fort is a mole 60 to 150 feet in width but that it as it may be in the face of modern weapons of war in its day when a stone wall was still the answer to gunfire fortman row was a brilliant concept in seacoast defense yes the surroundings may have an aura of bygone days but that's all there is about the past at connor the words of commanding general willard g wyman highlight the present and future of the continental army command i'm very happy to introduce you to the headquarters of continental army command located here at fortman row on old point comfort virginia it is significant in this respect that we are located in the shores of hampton roads where during the civil war the first ironclad vessels of war challenged each other for the first time in battle new weapons in a wartime laboratory now in peacetime we endeavor to look still further ahead fortunate too are we located within a few air minutes of the tactical air command at langley field blood brothers of ours on the battlefield that powerful air force that opens the way for the army victory no less important is the navy which keeps the army alive on distant shores just across the bay at norfolk there's a commander in chief of the atlantic fleet with his headquarters three services of the utmost mutual importance to each other the army the navy the air force your team for national defense my appointment with a public information officer was for later that day and there was time first for some sightseeing around historic fortman row known first as fort algenorn the original fortifications were started by the english in 1609 a good many years before our country was founded and that's the first thing to strike you about fortman row how long it has served so well from 1609 this defense point later named fort george and still later fortman row after the nation's fifth president has quartered fighting men from near and far the fortifications were destroyed once by fire twice by storms at one time the fort was rebuilt by men commanded by a young lieutenant later to become famous as general robert e lee there is a sense of history in every corner of fortman row and to help visitors understand its role in some very stirring events a small museum has been set up within one of the old walls of the fort the case mate museum here a sergeant from the public information office answered my question what are the main sightseeing attractions at fortman row well sergeant queen that would be difficult to answer because so many things have happened here at fortman row historic speaking but uh i just couldn't quite concentrate on one point uh huh i noticed that a great many tourists visit this post they do from all over the world coming in uh when did uh this tourist popularity here at fortman row began sergeant queen i don't think i would care to answer that question because there are so many things about fortman row that have to do with america's past you know this area has been a resort area since way back in 1832 by 1832 sergeant simpson that was the end of the black hawk warrior remember and at that time chief black hawk and several of his chiefs were brought here to fortman row and held prisoner and people came from far and wide to see these uh well they were downright celebrities here and uh then they told their friends about how interesting fortman row was and thus it was built up as a resort area listening to sergeant simpson i realized why this post is most fascinating to those interested in our civil war period fortman row was a union stronghold throughout the civil war even though it was deep in confederate territory it served as a staging area for thousands of union troops in other words the union troops were right here within almost the confederate lines that's right and just across the bay at norfolk was the confederate troops i think sergeant queen that if you were coming to our museum you'll learn a lot more about fortman row than i could tell you thank you very much sergeant simpson i think i will just look around the casemate museum consists of a series of small rooms hewn out of the fortress wall of particular interest is a room commemorating the sea battle between the first iron clad ships the union's monitor the famous cheese box on a ramp against the confederacy's marimat the battle took place on march 9th 1862 at hampton roads just off the walls of fortman row and on the walls of the room was a drawing of the famous battle which turned back to confederacy's bed for naval supremacy next along the wall were other drawings of highlights and personalities in the fortman row past robert e lee as a lieutenant of engineers a recital of his poetry by ed garland po in 1849 po was a former sergeant major at the post and the memorable day in 1862 when a famous president stepped ashore to visit a strong point of his nation's defenses these and other mementos of a storied past lined the walls of the casemate museum the adjacent room is simply furnished a bed a table a chair a bible the cell where jefferson davis president of the confederacy was brought after the defeat of the south in the civil war a chair next to the court of jefferson davis a tribute to the memory of dr craven chief medical officer at fortman row who befriended the captured confederate president and helped him win better conditions close by the casemate museum is another hollowed building linking fortman rows past with their present the lovely chapel of the centurion serving as a post chapel for fortman row it is open daily for prayer with me on my visit with chaplain mills post protestant chaplain i understand that the chapel was erected almost 100 years ago uh yes sergeant queen it was built in 1858 by lieutenant julian mccallister a young officer at fortman row was a thanks offering a thanks offering yes lieutenant mccallister and two other officers were working in a fortman row laboratory there was a bad explosion mccallister escaped unharmed but his two companions were killed in recognition of the divine providence which had spared his life a lieutenant mccallister sponsored the building of this chapel with his own funds and money collected from france i kept thinking of the story of lieutenant mccallister as we walked on and a moment later we were inside the cool quiet of the chapel of the centurion the chapel is dedicated to saint cornelius patron saint of military men who was converted to the christian faith by the apostle peter cornelius was a roman centurion an officer commanding 100 men and that's why the name chapel of the centurion from the walls of the chancellor naïve are the flags and colors of old regiments of the united states army these flags faded and worn over the years have rustled quietly over many a national leader who has come here for moments of spiritual repose among them was president woodrow wilson who more than once left washington to spend weekends at fortman row where he worshipped in this flagline chapel the stained glass windows are dedicated to the military men who have served at fortman row all good and faithful servants whose memory will always be cherished by a grateful nation they served in the watchful quiet years of peace and in the rumble and thunder and sacrifice of war some fought in the early battles that long ago entered the chronicles of american history and some died for their country in recent years still fresh in memory died in korea so kids next door may live the spirit of the chapel of the centurion is best expressed by these windows and the gallant men whose memory they revere so the kids next door may live fittingly enough just opposite the chapel of the centurion is the chapel center which provides religious training for all age groups with emphasis on the young there are three youth chapels here in an atmosphere that is pleasant and spiritually uplifting they worship regularly the post has always been a leader in the field of soldier and dependent education watching a bible class at the center conducted by one of the many volunteer workers you get an idea how moral training is emphasized here in a wholesome interesting manner no wonder then religious classes are among the most popular activities at old fortman row and for that matter there's many a reason why it is a popular post with the men stationed here the blend of the old as an ancient canon set against the new of a luxurious off post hotel where many visitors stay all this gives Monroe a certain something a unique only place like it quality that men appreciate long after they've left whether he wanders up to the old lighthouse looks across the water to where the monitor fought the marama or whether he enjoys an hour of relaxation at the officer's club set in the coolness of an old case mate a room cut into the actual wall of the fort or whether he spends a lot of his free time at the enlisted man's club any soldier stationed at Monroe will tell you life at Monroe can be mighty pleasant and the outdoor swimming pools don't hurt one bit dependent housing is available with plenty of room for kids to play and a wonderful view of the Atlantic to boot there's even an unofficial dog cemetery where Rover and Fido and company are laid to rest impressions mingle one with another as you walk through fortman row there are the old quarters built in 1819 still in use the churches so that men and women of every faith can worship in their own way there is the impressive grandeur of generals row from where by 730 every morning senior officers have left for work on sunny sunday afternoons the thumping beat of a brass band sounds out from Chamberlain Park as the soldiers offer a concert Monroe to the other the stirring music can be heard it washes over the empty gun emplacements and flares across the water where sailors on freighters bound for europe and south america come up on deck to listen do you suppose these ancient moat walls have echoed to the music of the fort Monroe band almost a countless number for these stone barriers were built to ward off the musket and the cannonball and still stand today in the era of the rocket and the guided missile surely the fort is no bulwark of defense today it is more a symbol of the unwavering unfaltering past of a great nation but the everyday work at Monroe the work of Connor concerns itself with the past only as a lesson for the present and a guide to the future and the future of our honor that is the business of Connor as i soon learned in my interview with one of fortman row's public information officers how do you do sir now you sit down please major gordon andrew's is one of the public information officers of the continental army command major would you outline for our big picture audience some of the important functions of conard well as you know the soldier forces within the united states are divided into the six armies and the military district of washington the six armies covering a section of the country the commanding general commands the six armies and the military district of washington along with this command function he is also responsible to the chief of staff for many of the other functions would you mind spelling out the more important ones for us sir it is the job of the continental army command to create improved weapons and develop doctrine tactics and techniques for a modern defense force conard officers must look into the future planning for new weapons and uniforms of war together with the know-how to use them to the greatest advantage working with its six field testing agencies known as boards as well as an arctic test branch conard's development and test section keeps tabs on how theory works out in practice at board one for example in fort sill oklahoma conard men have participated in many tests to improve the honest john a rocket capable of delivering various types of warheads at long range fort Knox kentucky is the headquarters of conard's board two here the dust and grime of operational use test the latest in armored vehicles and automotive equipment as the m59 armored infantry carrier or the t101 self-propelled gun every piece of rolling equipment gets a rough going over as conard men watch and report on the need for possible changes the t101 shows a lot of balance as it goes through one obstacle after another to prove it's good enough to join the army's armada of mobile weapons at fort benning is conard's board three its primary function is to review the performance of infantry weapons like the 106 millimeter recoilless rifle which displays its effectiveness for conard men who stand by on the range during fire for it bliss texas headquarters of conard's board four which is primarily concerned with the nike guided missile now being used in many defense locations throughout the united states board four men constantly analyze the procedure for moving the missile into firing position trying to streamline and speed up the operation without in any way sacrificing the safety factor for operating personnel the force field of interest also extends to target drone planes pilotless machines hurtling through the air under complete control of men on the ground anti-aircraft weapons represent another important area of board four activity they are put through rigorous firing tests regular at fort bragg north carolina conard's board five test communication and electronic equipment in cooperation with the signal core conard officers travel to all parts of the country to examine new developments like combat television as when put through tests at a recent combat demonstration in fort mead marily the advancing troops may be way up ahead but the television screen tells those at headquarters how things are going field radar installations and other electronic equipment are run through constant operational tests under the supervision of conard board five fort rucker alabama a name and a place synonymous with army aviation here conard's board six tests army aircraft and air support equipment which covers a lot of territory a lot of different types of late model light aircraft used by the army fort grily alaska home of conard's arctic test branch in ice and snow battling sub-zero weather conard men watch and report as men and equipment go through performance tests across the frozen arctic just part of conard's extensive program for observing how material meets the test of combat conditions through its six boards and the arctic test branch the scene any one of many army installations throughout the world a projector is turned on for a training film conard is concerned here too for another of its functions is to prepare army instructional material training aids that result in quick learning of army skills conard also supervises the training of individuals and units of the reserve forces conard prepares plans for the ground defense of the continental united states and also maintains liaison with appropriate canadian and mexican defense agencies and lastly but a vital interest to areas hit by disasters as the floods that have raged over wide stretches of the country in recent years conard prepares plans for and is ready to assist civil authorities in securing immediate relief when a disaster suddenly strikes a widespread area that's a very abbreviated very much simplified run through of some of the important functions of the continental army command thank you major by the way where's that band music coming from that's from our parade ground you're just about to get in on the awarding of the soldier of the month here at fortman rome a few minutes later a parade was taking place on the carpet green braid ground i stood on the sidelines watching the ceremony soldier of the month received his award we've all seen parades with louder brass bands with more marching men and women it's impressive just the same on this parade ground surrounded by the mementos of the army's proud past one got a real sense of the continuity of the united states fighting forces atmosphere of the old where continental army command is planning the army's new look you realize of our country's founding there has always been a proud fighting army ready to defend america home of the continental army command still plays a prominent and vital role in the national security of the united states now this is sergeant steward queen inviting you to be with us again next week for another look at the big picture is a weekly television report to the nation on the activities of the army at home and overseas produced by the army pictorial center presented by the united states army in cooperation with this station you too can be an important part of the big picture you can proudly serve for the best equipped the best trained the best fighting team in the world today the united states army


Hello and welcome. Today we're going to be creating a very basic repeating seamless tile pattern to be used in video games. We're going to go kind of low resolution here, but a lot of what we're going to do is going to apply to higher resolution stuff as well. Right here we have a texture. It's just an image I took with my cell phone of a close-up of a tile out in my living room. It's not the best for what we're working with. When you're doing this, you want to try to get your lighting even. As you can see, it's darker on the right side than it is on the left side because of where the window is in my living room. But we're going to make this work. We're going to use some tools to make this a seamless pattern. So we have that. That's going to be our texture. Let's go ahead and start creating our first tile. Control N to create a new image and we're going to make it 64 by 64 pixels. Under Advanced, we're going to go fill with transparency. Okay. Again, our tiles are going to be rather low resolution here. We're working with video game stuff, so you don't want to go too high unless you want to hog of a game. And what we're going to do is we're going to select our rectangular tool here. And I'm just going to eyeball select one pixel on the right side and then shift select one pixel on the bottom side. This is going to be where our grout is. If we were going higher resolution, we would probably create a grout texture to put in there. But since we're going so small, it's only one pixel wide, you're not going to see that texture. So I'm just going to use this gray color I already have picked and select my fill bucket tool and make sure I have foreground color fill. And then I'm going to click in here and now you can see we have this gray and that's going to be our grout. You're actually not going to see it very much, but that's where it's going to be. Now I control A, control C to copy that. And you may or may not know this, but in GIMP, once you select something, that can be used as a fill pattern for your fill bucket as long as the resolution isn't too high on it. And again, we're only working with 64 pixels by 64 pixels here. I'm going to hit control N to create a new image. I'm going to go 640 by 640, which will give us 10 tiles by 10 tiles. And we're actually going to trim off some later on. You'll see, but I'm going to make that background transparent, click OK. And here I have this blank image. So there's nothing to be confused. This is the one we just had with the grout. This is one 10 times that size. I have my fill bucket tool selected and I'm going to go down here to pattern fill, click on here and I'm going to choose this top left one and it should say clipboard image. And now if I click in here, you can see that we have a 10 by 10 tile grout that we have created. Now we're going to go back to our texture here, control A, control C to select all and copy. Go back to our grid pattern here and control V to paste that. Now our image, our texture is much bigger than what we're creating. So we're going to zoom out a little bit and I'm going to hit shift T for transform and I'm going to hold down shift and I'm going to scale this just so it's just a little bit. Hold down shift so it keeps its aspect and ratio here and we're going to scale down until it's just a little bit larger than our grid transform. We can zoom back in now and I want to get rid of the excess here, which would use our crop tool. And over here we can select our crop tool, which is supposed to look like a knife of some sort. And I have no clue where it is because they've changed these monochrome icons, which a lot of people seems really like. I think they look great, but they're annoying because everything's the same color, which makes it a lot harder to find what you're looking for. But I use keyboard shortcuts most of the time. Now that I got my little rant about the icons over with, what I'm going to do is I'm going to hit shift C to get our crop tool up. And then I'm just going to select around the outside and hit enter and that crops away all the excess. We're also going to check our floating layer here and make that a new layer. And now we're going to make this a seamless pattern because again it's darker on this side and lighter on this side and it's not going to match up with the pattern. So with that, we're going to control A to select all filter and we're going to go down to map and we're going to do tile seamless. And you may have not noticed it changed, but it did. We're going to click OK. Basically what it did was it took a feathered copy of this image and put it in each corner of this image, making it seamless. You can do this with a texture like this. Obviously you can't do that with something that actually has detail that you would notice. But something like this is just like a random pattern. It does it. It's not perfect, but it's a quick way to get it done simply. Let's go ahead and label our layers. I'm going to call this one grout and I'm going to call this one texture one. And I'm going to move texture one underneath our texture two here. And what I'm going to do now is I'm going to select our grout layer and I'm going to choose this tool here, which is select. Actually I'm going to select this one, the little wand. And with the grout selected, I'm going to select one of the empty tiles. Now I'm going to hold down shift and I'm going to select every other tile. So let me show you the first thing I tried when I was trying to do this. I selected this tool, which selects all one color. I selected all these. Then I went to our texture here and I said filters, decor, bevel. And I clicked OK. Thinking it would add a bevel to each one of these. And it does add somewhat of a bevel, but then it's not what I thought it would do. So there's a little bit of a bevel in there, but not very much. You'll see a difference. Plus we have this right white at the top, like lights hitting it. And we're going to still get that in the other pattern, but not as bad. And we're going to crop it away anyway. And we're going to hit control Z to undo that a couple of times. So now I'm back to our plane. We have our texture here, which is a seamless pattern and our grout layer. I'm going to choose my grout layer. I'm going to choose this wand selection tool and click the top left square here. This part's the most tedious part.  And we're going to do that for our entire image. A little daunting, but not too bad. And you'll see doing it this way for whatever reason it is, gives us a much better tile look to our tiles. Now we're going to go up to filters and we're going to go back down to decor and bevels. I'm going to make sure I have unchecked, worked on copy and bump layer. I don't want those things on this. Click OK. And now controls Z to undo that. We have to check our textured layer now before we add our bevel. So we have all our every other square selected our texture. And now we're going to go down to decor, bevel. Click OK. And there we go. We have these nice bevels. If I select all, you can see it very nice. And that's a pretty cool looking pattern right there if you want to use that as a texture. But we don't want every other tile to be higher for what we're doing. So what I'm going to do now is I'm going to select our grout again. Again our wand tool. I'm going to select this second tile here and then shift select every other tile to choose those. In reality I might have been. I haven't tried this. After selecting all the other ones and adding the bevel, I hit control A to select all to show you what it looked like, you might have been able to hit control I to invert the selection. And that might have saved you from this second little clicking every other pattern. But now we have that. Not forgetting to choose our texture first. Going to filters and again decor, add bevel, OK. And now we have our tile pattern. And the grout that we put in there originally is almost unseen but we have this nice tile. It looks like small little tiles you might have in a shower or something. And it is seamless repeating except for this bevel again. The top layer of the bevel seems to have more lighting if you want to call that than the other one. So if I was to take this and control shift E to export it and I'm going to put it inside here I'm just going to call it TT1 PNG just to give it a name. Now if I was to go over to my shell and you can see that I'm in that same folder and what I'm using as a part of the image magic program is I'm going to say montage and that what that allows you to do is to put images together. I'm going to put that same image in there four times. So it's going to give us a four, a two by two grid of the image we just created. Geometry plus zero plus zero background none so that there's it's filling a color. And we're going to do an output called tiles dot PNG. So I'm going to do that should only take a second. And now I can go back to GIMP and control O I can open up that image. And you can see this is now this image as a four by four. And actually I was worried that you would see where the pattern was repeating and I was going to crop some off but it looks like that's not an issue. I think that might have been an issue with the old way before selecting every other tile technique. But yeah as you can see this is a repeating pattern because if you look at like this tile here you can see that's the same as the tile over here and this tile here is the same as that tile there and of course this tile, this tile, this tile and this tile are all the same tile. But I think it's pretty good because you can't really tell that it's repeating too bad. So that is a technique to creating a repeating tile pattern. I will save this and put a link to the files in the description of this video if I don't forget. I do thank you for watching. I hope you enjoyed this. It was pretty simple and you can use this. I use the one tile but you can should be able to do this with a lot of different textures so you can make a repeating tile like this with different textures on it and it can be used in 2D games or as textures in 3D games. If you want you can go higher resolution than what we did but for a simple little 2D game this is definitely a pattern that can be used or even a lower resolution 3D game. I do thank you for watching. Please visit filmsbychris.com. That's Chris the K. Check it out. There's a link in the description of that and as always I hope that you have a great day.


Hello, my name is Michael, and in this video I will be demonstrating four new features of the Gaffer interface. The first feature is that you can rearrange tabs in a panel by clicking and dragging them across the panel top. The second feature is that you can drag a tab from one panel into another. So if I click this primitive inspector, drag it over here, and release, it becomes docked into this panel. The third feature is that you can detach a tab and make it into its own window. So if I right click this animation editor, click detach, it is now its own window. I can reattach this tab into a panel by again clicking and dragging it into the other window. The fourth and final feature is that you can also detach an entire panel. To do so, you click the panel layout button, detach panel, and now that panel with both of its tabs has now become its own window. And those are four new features in Gaffer.