Jumping on again, I will give my pitch one last time for those that have cameras and you feel comfortable. Turn them on. It's great to see faces rather than empty boxes. So I appreciate those who turned them on. If you're uncomfortable or you just want to be kind of passively on that is okay. You can still join in via the chat. And when, when it's time, you can certainly unmute and certainly ask questions as we go. So, Kate, or sorry, Lily was just reminding me that a few years ago, she was, I don't know if this is considered lucky or unlucky, Lily. But the, the course that I teach IST 195 introduction information technology, it's a big course at the high school. It's all of our high school freshmen are in it. So usually about 110 or so. Freshmen from the high school and then usually around you another 140 or 150 from around campus take the class and we'll talk about why in a minute. So it's a class of somewhere between two, 250 300 students, which is abnormal for your high school classes, I would say, but it's by design that we do this one that way. When, when Lily took it, what, when was that was that fall of 23. It was fall 2021. Sorry, fall of 21 that's when it's after the semester. Yeah. So, so Lily took the class and at that time at Syracuse. We were socially distancing. Right. If you remember those great old days of COVID. And I was adamant that I didn't want to teach online that I wanted people back together. But the problem is when you have 300 students, how do you socially distance 300 students. And there's only one place at Syracuse University that I could think we could do that. And that was in the dome, the J may wireless don't formerly known as the carrier dome where our football team plays and our basketball team plays. And because I'm involved in athletics and I know some folks I went to them and said, Hey, I want to teach my class in the dome. And they thought I was joking until I wasn't. And that's what we did right Lily, we had class in the dome. We socially distance 300 students. The lectures were on the big center hung video board that was our projection screen. They built me a little stage. Yeah, built me a little stage I had a mic and look at it. It was certainly an experience it's the only class ever taught in the dome and something I'm sure Lily will remember for me as a professor. It was great and better than being online but it didn't replicate a classroom as they could hear me really well I couldn't hear them as they asked questions. So they would text in their questions I had a little texting platform. And, and we we got through the semester. So fun fun times maybe not so fun times, but you make the best of it. So I'm going to go ahead and share my screen. We can talk. Let's do this. Okay. And I'm just going to just give me a second as I rearrange so I can see some stuff. And you can see some stuff. All right. So, and you might see some of your faces on here and I'm just going to kind of go like this real quick. Feel free to ask questions as we go. And just because of the way I'm sharing my screen. I may jump a couple times back to the chat just to see what's going on. So, first of all, you know, even if I, if I go back one slide for a second, sorry. You know, thought it would be fun to generate an image in AI. Why not. So I just fed it. Hey, this is kind of what I'm talking about and what I teach. Can you build me a image and and this is what it generated earlier tonight for this class. So, I am Jeff Rubin. I have a few different roles. In the eye school in fact I'm going to stop sharing for a second I'm just going to do this different so I can still see you. I'm going to just share the PowerPoint. So then I can see you at the same time. Okay, now I should be able to see you and I can. You can see me. All right, much better. So, I do have a few roles in my life and that's probably because I've never been able to figure out what I want to do when I grow up and even though I'm 50, I still feel like I haven't grown up yet. So, I have been teaching at the eye school for 27 years. And before that I was a student at the eye school so as Lily said I did my undergrad in my master's work in the eye school. And while I was getting my undergrad long time ago, the internet was just commercializing web browsers were just becoming a thing. And so I started a company, as I was doing some web development and thought it was fun. And I started a company called sidearm sports. And I'm still the president of sidearm but I sold the company to a much larger company called Learfield. That's the logo on the top there. I sold it to them in 2014 but remain on as president of sidearm and executive vice president of digital for for Learfield for the last year and a half or so. And then, if three jobs wasn't enough, about three years ago the chancellor of Syracuse University came to me and said Jeff would you help advise me on digital transformation so he's really looking at Syracuse University and really the student experience and how do we grow from our digital experience from what we have in 2023 to where we want to go in 2030 right like and it's not going to all happen at once but kind of this this transformation. And that was supposed to be six months, but now I'm on three years and still doing that and it's like another full time job but I absolutely love it. I'm going to be working with him and the executive team at the university, and we'll talk some of what those transformation pieces will be, and maybe what you can expect if you come here as a student. All right. And so I'm just bringing up the chat in case there's any questions. Okay. So, welcome to to 2023. Right and this is scary, but it's all true. Facebook knows who we are. Right. And what I mean by that it doesn't know that I'm Jeff Rubin, they probably know more about me than I know about myself, or at least that I'm willing to admit about myself. Right. And again not sure how many of you are on Facebook I get it, but take the word Facebook out and put Snapchat or tick tock and it's the same thing. Right. So, so they know who our friends are. They know what we watch they know when we zoom in on something they know and we're stalking they know what what we're looking at I mean they know everything right. Google knows what we want, because it's it's constant right it's trying to predict what we want even when we don't even know we want it. But but Google's trying to help us with that. Amazon course knows everything that we buy in Netflix knows what we watch Apple knows how we operate right. I assume most of us have iPhones maybe not all of us, but it doesn't matter it could be Google knows how you operate if you're an Android user, Apple knows how you operate. If you're an iPhone user and me when you think about that, the point of this is, you know some of these companies right now Google. They're under, I hate to say federal investigation but the Department of Justice is doing an inquiry right and saying like, is this is what they're doing ethical. Is it fair is it right. Is it a monopoly. Right, these are questions that will probably get answered by the time you're in kind of college or in your college life. The other side of this is just recognizing that what is privacy what does privacy mean in 2023 and beyond what should privacy mean. And what if things changed like some people say well I don't want these companies to know everything about me. But then on the other side of the mouth you're saying, well wait a second where did all my great recommendations go of what I'm supposed to binge watch on Netflix. Right and so it's like, we don't want them to know but we want them to know when it benefits us. And so it is not an easy thing to think about. When I look at generative AI, and when I say every software company is leaning into gen AI in every business that I know is working on an AI strategy and if the business isn't working on an AI strategy. I question what kind of business they are and how they plan to operate in the next decade. Now, AI doesn't necessarily just mean generative AI we're going to talk about that a little bit more tonight. There's many aspects of AI of course you know the big one right now is chat GPT and barred and Claude and in the generative AI models. But but we're going to look beyond that. And just like up above there's this ethical approach to what these companies are doing with our privacy. There is an ethical approach to AI we don't know what that is yet. And my gut is the United States won't be the first to figure it out. It'll probably be European Union, or some other group of countries or country. But we will get there. Then we look at data breaches. It's every day, right companies every day it's so and again maybe right now the only mail you're getting is from universities. But I promise you if you ask your parents some of the mail they get in the last year how many notices have they gotten that says, We're sorry we had a data breach and your name and email address or so and so was compromised. Don't worry we've signed you up for a free year of credit reporting. Yeah, if I could bank these credit reports they would last longer than I'm going to live because it's constant data breaches. And then you go into data strategy. How do we manage all this data right all these companies that are collecting data on you has that manage some massive issue even and again you might be wondering how does this all relate to sports and I promise you on the next slide we're going to start making that connection. And you see chat GBP barred Claude more generally AI is changing everything and it will right this this is this is what setting up is when we look at the future it is AI we've got a lot to figure out here it is not going away. And we see how it's being used both ethically, unethically misinformation disinformation. A lot of issues. All of these are things that we talked about in the high school. I get pretty excited about these and I could talk for hours just about this one slide, but you don't want to, because you want to talk about sports. So, let's, let's go forward. Alright, and do me a favor in the chat. Can you all just kind of type in where you're from. Where's home. And so in the chat just throw in where you know you can just write it to everyone you don't have to write it to me. So we have Maryland and ten of fly New Jersey New Jersey Boston, another Maryland Connecticut another Jersey, Rochester right west of Syracuse. New York 10 or I don't know if there's that New York City area New Jersey Toronto Strat Stratford is that Connecticut. New Jersey Washington DC another one from DC, LA. This is why we do it at 8pm so you'll a folks it's only 5pm. People like me I'm ready to go to bed. And I will write after this Connecticut Syracuse Angelina I love it with a nice heart. New York, New Jersey, Lexington mass love this. Alright, so we've got a lot of folks kind of in the East Coast side. We've got at least one from LA, which I love to see we've got one from Canada. Great to see. So, thank you just like to know and that person Maya and Lexington I grew up in Wayland, Massachusetts. So it's pretty close to you. I was just back there last week. Okay. Thank you for doing that with me. So, talking. I want to talk about AI for a minute and in relation to sports. Right. So, when we look at it again at the point this isn't to give you a lecture, but hopefully have some fun. I know it's going to sound like a lecture, but when we look at what AI is, right, it's just, we are making machines think and act like humans, right and perform tasks that humans used to do. And sure, some people might say but you're killing jobs and then there's the other argument. Sure, we are killing some jobs but we're creating other jobs, right because computer scientists computer engineer cloud computing security privacy ethics. We need jobs for all of those right that didn't exist prior to the AI and so we are creating much higher paying jobs for a much more educated workforce is what I would say. When I look at sports and I did this tonight just about an hour ago I was saying like what am I going to talk about with AI and sports and so I jotted down the first five things that came to mind. But there's many others of how is AI being used in sports today and analytics. By far number one, and we'll talk about this in a few slides I'll talk about money ball I don't know how many people have ever seen the movie money ball. I don't even know how many of you know Brad Pitt who was the actor and money ball, but he is a famous actor. But anyway, we'll talk about that in a minute but but the idea of analyzing data to help teams make decisions right and we'll talk about what the NFL is doing with this in a minute. The NBA is doing what college sports are doing injury prevention is a big one even at Syracuse if it during all the practices and and in certain games. The players are wearing sensors, right and this is pretty normal and they are monitoring biomechanics so measure and measuring heart rate, measuring body temperature. Right. And they are what the goal of this is to be able to identify injury before it happens like when is it time to pull somebody off the court when is their body at the point of too much strain or, you know, to get scary for a second. It is not uncommon, almost on a yearly basis I feel that I read something where a high school football player passed away from heat exhaustion, usually down south, because they were doing two a day camps in their body overheated that shouldn't happen in 2023. Right. I mean you could argue it should never happen, but it should not happen in 2023 because we have the technology to monitor the body and be able to have somebody say hey, you're too hot, get to the sidelines cool down drink some water. So, officiating you might love this you might hate this, but you know you wonder what are what are officials going to be in 1020 years, we already see it with minor league baseball. And it's going to soon be with major league baseball, right where we don't need the umpire behind home plate, right because he or she doesn't call balls and strikes. They do it with their own mind what they think versus what is really the strike zone right which which should be the same for everybody. And, and so we can have an official deal we see it in tennis, where we can see if something was in bounds or out of bounds right. If you watch Thursday night football on Amazon, we see it where they have kind of their next gen stats, and you can see all this analysis of what's going on so fantasy sports. I don't know how many of you play fantasy sports. I'm going to pick them league, because I would get addicted if I tried to actually do a real fantasy team. And I don't need I don't have time for another job, but I do do a pick them league. And I spend way too much time trying to figure out. But but right it's all data. It's all data and AI that is helping to generate this in chatbots, which I put this in here just because some of these sound really hard and then you get to a chatbot. We implement. So my company we implement chatbots on a lot of sites, and they're not humans chatting right it's it's just a bot.  Sometimes the people don't know their humans but the idea is you a fan could ask a question and just normal natural language like, hey, can I bring a pet to the game or can I bring my purse to the game or where can I buy tickets to the game or do you have kosher food or gluten free food at the game, whatever it is they want to ask. And the idea is that the chat chat bot just like some of the bots you've used with AI should be able to learn as more questions are asked and also be able to respond not from just looking it up in a key word, but being able to to truly learn from what's being asked and previous information. I'm just going back to the chat real quick see if there's questions nothing yet great feel free to ask away. And let's go forward. So when we look at other technologies that are part of sports it's, I mean I could go on and on and on right my company which I'll talk about for a brief minute. We're in the web space. So, I'll get to that in just one second but we do college athletic, we do college athletic websites for almost every university in the country, college athletic program so whether it's qs.com and that's really the only one you know because it's the best qs.com I'll say again see us.com. That's that's the best but whether it's them or Ohio State or Michigan or Duke or Georgetown or whomever we do all those we do their mobile apps statistics. We were just chatting about that so somebody's we're going to talk about more in depth over the next 15 minutes or so. Broadcasts right I mean just how many of you put it in the chat if you don't mind how many of you still have what we call linear television meaning cable TV versus over the top, meaning like YouTube TV or something else so so does anyone still use cable. Right, somebody. We did get a question from Jack about. All right, perfect. The a I'm going to read this and you guys look at you all these people with cable. Look at you. I'm very tell your parents to get rid of it cut it go outside right now just cut the cable. Do it. Okay, don't do it. We can't afford that. So, the AI proposed fantasy trades through things like IBM Watson are extremely one side with flawed background thinking. Why don't we help these AI platforms get to a common sense. Jack, come to the ice school and do this. That's exactly right right so look some of these models are flawed and and IBM Watson I'm not going to say you know it's bad technology it's incredible technology but what I would say is is look at some of the newer platforms that are coming out there and what some trained to be able to do things like some of the other platforms that could be trained on statistical data. So yeah, Jack, it's a great insight cable cable cable. I'm taking an AI machine learning at the graduate level right now where we're learning about things like one sided like AI machine learning type things and it has a lot to do with bias and you know when people hear I sometimes they think. As Professor Rubin was saying before that it gets rid of jobs but really AI needs human intervention to make sure the models that they're training or working properly so this one sided thinking you're thinking of actually has to do with bias of the people who are creating the model and so whoever's telling Watson to to read these statistics read this data might have their own bias towards what teams they want to see succeed or when or what players maybe are better in their fantasy league and they don't want to lose to their friends. That's exactly right. Thank you, Lily. And this is where it gets really scary because what happens when AI starts training itself on disinformation. So in other words, if you start feeding an AI model because I'm posting on x formerly known as Twitter. I'm posting disinformation meaning information that's truly wrong. And I know what's wrong, but I get these large language models which is what this generative AI is these large language models. I get them to train on that data. It is going it doesn't know the difference today between what's real and what's fake and that becomes a real problem. Real real problem. Anyway, too many of you have cable tell your families, they can save money by going to YouTube TV. I will give you my code so I get $5. Not joking. But if I had a code I would do that. But you anyway you don't need cable. It's silly. I watch all my sports on YouTube TV and I get much more of them than I did on cable. We're going to talk about sensors we're going to talk about that analytics of it social media really. Here's the beauty of the eye school. You can mix technology with any discipline you want. Right. So for me, I love technology, and I love sports, but I knew early on in my life I wasn't going to be an athlete. My kids are now in high school I have a son who's who's your age, a senior looking at colleges. I invited him tonight he didn't want to come. But, but anyway, the, the idea of going into school and knowing what you want to study. Right. So if it's if you like technology. That's fantastic. For me I love sports as I said I knew I was going to be an athlete, but I was able to take technology take sports and find that intersection and make a career out of it. But if you're on tonight because this lecture maybe intrigued you but you're not a huge sports fan. Take out sports and put in any other discipline. Entertainment, music, arts, government, nonprofit, automotive. I literally take any other field in the globe. And that field cannot be successful in its future without technology. I don't care if it's a for profit company a nonprofit company if it's government sector. There is no one that can tell me an industry that can succeed without technology I don't care if it's trash collection. I don't care if it's lawn mowing I was driving through the university yesterday and we just had a robotic lawn mower mowing the lawn it was the coolest thing. I absolutely loved it. So, everybody is being transformed with technology. My love is the intersection of sports. All right. So we talked about sidearm. Oops, somebody had some audio listen to that. Just make sure your microphone muted if you could. Thank you. Thank you. I have a question in the chat. I have a question lots of a my models are in their infancy that is true suffer from hallucination that is true. And thoughts on how we can prevent this as AI gets more embedded into sports and analytics. Here's the thing is, we have to train the models. And I think what you're going to end up with is a lot of specialized large language models that different companies run that. What do I mean by this, you know, my company has a lot of sports data. Right. I don't necessarily want to feed this all into Claude or bar or chat GPT because then it's part of their model but it's my data. Right. And this is one of the this is one of the issues at hand which is, do we want all these. The AI models being trained on our data where I'm not making any money on it, but it's my company's data. I think what you're going to see is sports analytics as well as other niche areas will have their own large language models and perhaps there's going to you have to pay for some of that data. Perhaps it's just part of a subscription model perhaps it's free but you have to log in. We'll see. All of everything you just said downhill is 100% correct. We're at the infancy of these models and you will look back in 10 years and be like, wow, can you believe when I used to ask chat GPT and this was the response I got. Right. But it will change. All right, I got to stop sharing and reshare just because I'm going to do a different screen for a second. So, so I'm sports. Right. I just I thought this would be fun just to show real fast. Let me just share my full desktop. Okay, and I'm going to go over to a web browser. And let's just see what we've got running here. Let's see.  So, what I am doing right now is looking at. Right. So what this is showing me is in the last 30 minutes, there's been 103,000 people on our websites is what this is showing and so that's in the last 30 minutes. This is looking at and I don't know September 17 so the last month 69 million users who are who are on our websites. And this I don't know if this is really going to be helpful what I'm looking at right now. This is just a quick snapshot of like where are people right now. And we can sell know why this is this looks really odd to me but we're going to go with it. Nonetheless, we can begin to see, you know, not only where people are, but this is looking at really since football started. Division one schools we've had 105 million users division to 17 million more on division 319 million. We then can break it down by which conference is getting the most traffic big 10 sec not surprising football big football conferences. We can then look at schools. You can any any sports fans here know why Colorado would be the number one traffic site this year. Go ahead and throw that right in the chat. Why is Colorado got the most traffic. I promise you they did never had the most traffic and any other year there you go for coach prime coach prime coach prime coach prime now everyone's catching up. Yeah, right so this is the coach prime factor. They had 7.7 almost 7.8 million page views since the start of the football season. Next up is Texas then Michigan and Ohio State Florida Penn State Wisconsin all these are clients to sidearm. This data is really useful because on every one of these pages we have ads ads make us money. And also obviously the school just trying to push out their their brand. Right so not only can we see at any moment from an analytic side. What is happening and where is traffic. And again it's it's getting late on a Thursday night and there's very few games going on right now. But if you look at this on a Saturday. It'll be you know 10s of thousands of users on the sites and they're hammering and they're looking at like we can even probably see what they're looking at here. Let's see what content they're looking at. We could go in and say right they're looking at James Madison looking at West Virginia actually I think West Virginia might be playing a football game. You can see West Virginia they're looking at schedule pages they're looking at rosters. They're looking at where she rice raw she rice roster page so we can see what they're doing where they're coming from I can see from where in the world is this traffic. Coming from and you can see most of it from the United States, but you know in the last five minutes we've had traffic from all these countries as well. Right and then we could dive in into the United States and be able to see where in the United States is this traffic coming from so forth and so on so to me this gets pretty exciting and important again I'm going to stop sharing just for a second. I can go back to seeing all of you go to the chat. Alright we're still in coach prime. Cool cool. Alright I'm going to share back to the PowerPoint. So the point of that was just to show from a data side. We are collecting a lot of data. Right on on all these sites on all these users. When people come to a site. Sometimes you know who they are not necessarily by name like I don't know it's Ford or Rahel or any of you folks, but I do know that it's your browser, and I know what else your browser is interested in so I know hey this person's interested in Nike sneakers, or they're interested in a certain brand or a perfume brand or whatever it is and we can push out ads based upon what we know about that that fan right that's the advertising works. The mobile apps. Which we do for most of our schools. This is right mobile app is critical in that it's oftentimes the ticket to a game. Right so while we don't do the ticketing we integrate with ticket master and pack your own where the two biggest ticketing providers and college sports. If the ticket shows up to the stadium, that's their ticket in if our app doesn't work, fans cannot get into the stadium. You don't want it like Saturdays during football, or anything but relaxing for me or anybody on the on the staff. Right because we are responsible for every football fan getting into every stadium. It is stressful if there's a technology issue, you know for you, you don't think much about it you just go into your app and it works and it should work, but there's a lot of stress on the system. I don't know if you've ever been to a stadium where you can also instead of it also being your ticket it can be for concessions, much like if you've gone to Disney, if anyone's been to Disney and you have your magic bands and you can pay for things. You can do any type of thing where you can pay with your phone using the same technology. Right. We can do predictive play on the apps so fans can engage answering questions kind of like a precursor to sports wagering that's out there. So RFID in the NFL right and we all know T Swift right what would a lecture be without Taylor and what would an NFL game be without Taylor being mentioned in the broadcast. Yes, we'll just leave it at that. She is right now. But this is when Travis Kelsey scored the touchdown right and so we could go in sorry I've got to just stop sharing and share one more time as I go back here and share this if I went to NFL next gen stats. Right. And we go in here. So if I go in, let's do stats, or we can even do highlights. And we go in and we say we're looking some of Bill's fan. Right. So we're going to go to Buffalo, and maybe well not this last week as they lost. But maybe we'll go to week four. And here. Right. So here's a play. And you might look at this and say why is this interesting well if I just hit play here. Right. So we're looking at this animation and here's Josh Allen and their step on digs. And there's the touchdown. Right. And buffaloes up 34 to 20. This so this gets really interesting when you think of the technology that's behind this because if I play that again. Right. There is. Oh, this is the next play. Sorry, that's not going to be super exciting. Let's go back in here and let's just search for digs. And we can see every play that we want. Let's do the 50 yard 55 yard touchdown pass. This will be a fun one to see. I'm going to hit play. All right, so back goes Josh Allen. There are RFID tags in every player's shoulder pads. And so essentially what's an RFID tag it's it's just a sensor. By the way this is so much fun to watch isn't it, especially if you're Bill's fan. There's sensors and so what you're looking at is where every player was on the field at that exact moment this isn't just like in precise it's it's completely precise it's it's real time data. That allows you that that generates this it's the same technology if you're watching Thursday night football, which is tonight on on Amazon Prime, right. So really cool stuff when we're talking about sensors and what can be done.  And so you could almost officiate a game without an official, whether you think that's good bad in different. I'm going to I'm going to go a little faster just try to wrap this up in the next few minutes.  I'm glad I created chaos, but it is true the Giants do suck. Okay, so has anyone ever seen Moneyball. Yes, no throw out the chat. You've watched. Okay, look at this. I love this. Yes. Look at all these yeses. Maybe the same people that have cable because it's from shirts on one of those old cable channels. So, I've read the book. I look at you studious Ryan I like that I have not even read the book, but I have seen the movie several times. Let's talk about Moneyball for a minute. So, Moneyball was was based on the GM of the Oakland days, right, who way back when in the 90s, basically said hey, I don't want to put together a baseball team like they've always been put together. I'm going to stop sharing just for a second just so we can we can talk. I don't want to put the baseball team like we always have. Why is that because baseball teams in the past were put together based on gut gut instinct saying like hey I think this person's really good or they've hit this many home runs. But the reality is what happens is we all have biases, whether we admit it or not right we have biases we look at somebody and we say they're too tall they're too short they're too skinny they're overweight. I don't like the color of their skin I don't like their hair they're wearing glasses they're not wearing glasses, whatever it may be they're from this area of town. We have biases, right we judge people just I judge people you judge people we just do that we judge people. What Moneyball did is said hey let's cut through let's take all that out let's just look at the sport from an analytical standpoint from a statistical standpoint. Let's look at it from a statistical standpoint says, these are what you need to earn runs, these are the players that are going to get you to earn runs. And forget, I mean, Coach Prime says this right he's like, what's this culture thing you're talking about right and I've got some issues with that but what's this culture thing like we're here to win. And so if we do it from a statistical side, what are the components we need to win and they did this and they made it to the world series right with the lowest if not one of the lowest salaries and baseball. Which was unbelievable. That was the start of a trend with the Oakland days. Today, there is not a team in the NFL NBA Major League Baseball. Whoever else I missed soccer and college sports that doesn't have data analysts. It is a full time profession where every team is hiring data analysts, because what they are looking at is, I mean even in Syracuse. What are the practices and games, it's where were you on a court what was the if in football. What was the distance between a safety and a wide receiver, right and and all those dots I showed you with NFL next gen. They can calculate exactly where somebody was and tell them precisely why they missed the play. Right, we can see acceleration speed. So all this data that that you can get. I feel like the Phillies are currently disproving the money ball strategy they show important intangibles and love and the passion of the game matter numbers don't account for all that that's fair jack. That's fair right numbers won't account for everything but I would also argue if we don't use data analytics as part of this. Then you will be at a disadvantage right so I agree it's not everything, but I also wouldn't agree to say you can throw it out. And so what I'm saying you've got to have right, you got to love what you do, and you've got to have passion for what you do, but you do need data to help it be the same thing of, I have a store but I'm not using data to know what products are most successful. Right, you need data, regardless of what industry you're in. Does AI also assist coaches and teams create game strategies. Yes, absolutely it does. I've seen the models. I've seen what coaches use for college sports and professional sports where you can go in, literally get to show me this player every pick and roll that you've ever had that resulted in a three point play from this corner of the court with less than two minutes left in the game I mean you can get so specific, and it'll show you, literally within seconds, every play from an entire season, where you can go through and watch it. I mean, so this is what coaches have at their fingertips. Yes, yes, absolutely. Right, the concept of film is 100% changed. And, and that used to be more videographers people who are great with video who could cut film. Today it's about the data. Right, it's really about someone who can who can get through the data and look at film and from an X's and O's. Absolutely. All right. I'm just seeing if there's, I'm going to just jump what I'm going to pause here is I've taken 47 minutes of your time. Questions, thoughts. Feel free to ask, ask anything. What, let me ask, ask you question. Let's go with a favorite sport, favorite team. So you can, you know, what's your favorite sport. What's your favorite team. By the way, Syracuse is always a good answer. No, let's see, Liverpool and soccer. Love it. Okay. Football in the Rams. I was at SoFi last year watching a game with them Bruins and hockey. Hot and other hockey New York Rangers hockey lot of hockey hockey black box football giants. I'm sorry. I'm serious. We all can't be winners.  Don't don't don't hang up on me. I'm not mean, I mean, football bills Lily's right. She's got a winner football Ravens. It's fine. Lamar is good. NHL Montreal, I'm a tennis player, but I like watching football giants fans stick to tennis. I love basketball and wizards hockey, but the Bronx hockey, but Broncos. Okay, Liverpool and soccer Manchester United. Alright, love it. Guys gals. The point is whatever team you love. If you do start looking at the game also from a data side from it from a sports technology side. The like these stadiums today when I tell you like we have cameras. And those cameras can count people like we know where anybody is in a concourse at any time, not necessarily where Ford is right we don't necessarily care where Ford is. But we do care is what are the wait times at concession stands what are the wait times in bathrooms, what are the wait times at certain entrances, how can we disperse crowds. Like we even can get to the point I was I was working with a firm the other day, where they have sensors in the seats that can, they're measuring sound, right noise. And what we're trying to do is say, does a section that creates certain noise increase or decrease ticket sales. I mean just think about what we can do there right so do fans like to attend more in a certain section because it gets really loud, or do we see when we have sections that are really loud. People to people say no I'd want to sit elsewhere. The amount of data we're collecting and things that we're doing are, you would be amazed at the data collection with you just bring your phone and yourself to a game. But Lily I'm going to kick it over back to you. Well, thank you so much for that. So great to have you on. Um, we still have some time with about 10 minutes if anyone has any questions about anything in admissions anything about life it's your accused clubs classes organizations, anything you can think of I'm happy to answer. I have some information if you guys are looking for it for upcoming events other mock classes we have. I can drop that link in the chat now. And yeah, if you have any other questions feel free to ask me or Jeff. And I'll say this. I'd love to have you all come to Syracuse love the place if you can't tell. I got Syracuse stuff behind me. But the, if you come to Syracuse if you come to the high school, I'll be lucky enough to have you in your first class. So the first class you take in the high school is my class. IST 195. And the idea is, yes, there's a lot of references to sports because it's, it's what I do. But every class is a different topic in technology. So every week we're covering some different aspect what could be social media, web development, networking, security, privacy, cloud computing, internet of things, etc. So, team, you're the best. Thank you for participating. Thanks for putting up with my, my humor or lack thereof. Your giants will get better someday. Maybe before you graduate, it'll be okay. I love the look. I love the look. All right, team. Thank you. We appreciate you feel free. If you have any questions, I'll stay on for a few minutes. If not, we are, we are good and you can hop off. Have a great night. Justin, great question. I saw what you asked about a sports analytics major. So we don't have one in the high school. There's a sports analytics major in the Falk school. But they work very closely with the high school and you'll probably take classes between the two schools. Yeah, so we have three different minors. I'm answering your question now. We have three different minors in the high school. One is our information management and technology minor. One is our data analytics minor and the other one is some more entrepreneurial minor that we most recently started. You will be able to take classes and get a minor and any of those as long as it works with your, your new house scheduling. So as long as you're taking your major classes for new house.  You will have free reign of high school classes to take to fulfill those minors. Does anyone else have any questions? Thank you crew. Have a great night. Appreciate you jumping on. Have a great night everyone. Thank you. Right, Lily. Bye all.


I've got five really nice free plugins to show you today and I'll be using them all on just one demo. Hi folks, I'm Mike and I hope you're well. I'll be running through how I've used these five free plugins in my demo stroke groove in just a moment but first of all I'd like to thank the sponsor of this video DistroKid. If you follow the VIP discount link in the description down below you'll get 7% off an already amazing price to distribute your music to the world. Now let's dive in and use these free plugins. So first up I have Delay 11. I think they're called Platone Studios the makers here. Now before I switch this on and I demo this let me just play you the thing we're going to be applying it to which is this piano. So I'll bypass to begin with. I think you get the idea then I'll turn bypass off. This is initially set to quarter beats. Now you can either sync this to your door or you can set it to milliseconds down here. I'll have it sync to my door and it's currently going to be sounding like this. Okay so we've got some delay happening there but it's not the most interesting delay in the world so I'm going to change this to eighth notes and then dotted a bit of a classic delay setting. Have a listen now. Getting interesting now. I'm just going to turn the mix down a little bit so we've got a little bit more of the original and then the next thing I'm going to play with is a little bit more feedback meaning we'll just get more delays. That's working nicely for me and the balance control I'm not going to be using but as you can imagine it either pushes the delays to the left or to the right. I'll skip that and let's add some width to this. Nice I like it. Now we've also got sort of two tone controls if you like brightness and darkness. I'm not going to add any darkness or sort of low into this. I'm just going to add some brightness so we get a sort of a tiki-taki feel to it. So note that these controls get applied to the delay not to the original signal. And then finally my probably my favorite part of this is I'm going to add in a little bit of well quite a lot of drive. Some grit which again is only going to be applied to the delays. Have a listen. Okay I think we're off to a good start. We have another plug in here from Platone Studios. This one is called Flex Reverb. Quite a straightforward reverb to use but again has a few tricks up its sleeve. Now I have applied to the piano but I've switched off the delay for just a moment so we can hear just what the reverb is doing. Have a listen to it and it's more or less default setting as you may expect. Okay now what I like about this is when you push the size control up so we sort of make our room bigger. There's a nice amount of modulation on there which I rather like. Have a listen. You can just hear some pitch modulation happening there on the on the reverb which is rather nice. We've got a width control. It's already up pretty wide. We can make it more narrow but I like it wide as you can see. We've got a dampening control which sort of suppresses some high frequencies and then we've got a pre-delay as well. If you don't know what pre-delay is, it creates a little bit of a time delay between the initial sound and the reverb coming in. You get some pretty interesting effects with this pre-delay as we push it further up. Have a listen. You hear how it sort of makes some of those notes really stand out. I'm going to leave it like that because I rather like it. Now as you can see at the top here we have a low pass filter happening. We can move that around. Low pass filter is super super handy on a reverb plug-in because you can cut out all of that low end build-up that you tend to get with reverb, especially on full range instruments like a piano. But also we can add more nodes in to control this EQ. So if we do one towards the top here, I'll just double click, that automatically creates a low pass filter there. This one's a high pass, that one's a low pass. Or you can add in some sort of regular EQ nodes in here as well. You can control some of this with your mouse. I'm using my mouse wheel here. Or you can just use the controls at the bottom. So you can just change the frequency, change the cue like so and adjust the gain for that node as you would with a lot of EQ controls. So it's super nice that it's got that in there. I think it's really well presented as well for a free plug-in. So we've got that now applied to our piano. Let's turn our delay back on and see what we've got so far. I like it, but there's a lot of top end information. Let's have some bass in there. A simple man with simple taste, which is why I like this AI bass mini. This is a cut-down version of a full product. You'll find out that some of the features aren't available in the lower half of this piano keyboard. If you play them, it gives you a message to say they're only available in the full blown product. But it is still useful as a free plug-in. If you just want a straightforward electric bass sound, which sounds like this. So that's what you want. You'll get that right out of the box. Now in the demo, I have used some octaves together and played those. And there are some small tuning discrepancies, I reckon, between some of these notes, which I rather like to be honest with you, because it adds that little bit of sort of imperfection to it, which I kind of like. So let's have a listen to it in the context of the demo so far. Now we do have a few controls available here. We've got ADSR, which is a Tacticay Sustain Release. So if you want a sort of a really slow attack on this bass guitar, you can make it sound like this. I didn't want that for this demo, so I'll put that back down here. There's also an overdrive section here. Have a listen. Which could work in this demo, but I've opted to switch it off and also a chorus. You can't beat a chorus on a bass guitar. Have a listen. Haven't said you can't beat a chorus on a bass guitar. I actually had it switched off for the demo. So I actually used it in a very, very simple way because I enhanced it a little bit with one of the other free plug-ins we're going to be looking at in a moment. By the way, don't forget when you're ready to release your music, follow the link in the description down below and use our sponsor DistroKid. They're very cheap. They're very easy and they get it out to all of the major platforms like Spotify, Apple Music, Amazon, Google Play, etc., etc. Just follow the link in the description down below. EQ1979 is pretty much a Neve console strip emulation. There's two main sections. You've got your sort of drive section here, which we'll have a listen to in a moment. Sounds pretty nice actually. And then you've got your main EQ section here. Now I could add some drive to this piano. Let's have a listen. But I sort of feel there's enough on the delays already. It's gritty enough there. I could just put it down on a low setting, I think. Now the other section, as I say, is the EQ section. A little tip for you, a couple of tips for you, actually, if you download this and use it, you need to make sure you switch the EQ section on by clicking on EQ over here.  Nothing will have changed unless you switch that on. So I've just used this to boost a little bit of a high, the high shelf there, and also the mid frequencies. I haven't touched the low end on this. Well, I have, but not using this low end. We'll get to that in a moment. Now another quick tip. When you make adjustments here, you need to set the frequency with this mid and low, these mid and low controls. I played around this for a while and I just couldn't get anything to change. You know, I was dragging things around. I was trying to type on there. I couldn't. What you've got to do is left click on there and then drag up and down to select your frequency. Okay, not all that intuitive. I have to say that it's free, so I'm not going to complain too much. And as I say, let's have a listen to what it does if I sort of push these high and mid frequencies a little bit. Now I wanted to get the low end of the piano out of the way of the bass guitar a little bit. So that's why I use this high pass filter over here, set to 50 Hertz there. So that's sort of just, you know, getting it out of the way. It's cutting out those lower frequencies. That's what I use that for. I also use this on the bass guitar just ever so slightly. And if we go over to that instance, you can see that I actually added some low frequencies in here around about 60 Hertz. Okay, just give it a bit of a boost there. Just to give that bass guitar sound a little bit more meat. So I added some drums to my demo and I wanted to mess them up a little bit using this plugin, which is called Rust. This is great if you want to make things sound a little bit more lo-fi, kind of like they're sounding, that they're on a vinyl LP or something like that. Okay, now I'm going to start off by using this age control here. I'll play the drums. You'll hear exactly what it does. Have a listen. Yeah, instantly sounds really lo-fi and nice. I rather like that. Then we've got his control here, which sort of sounds like any tape or electronic hits. Yeah, and we can modulate that using this movement control here. Yeah, that's pretty good. And then also we can add the effect of sort of dust on a record. Have a listen. So obviously you can combine all of those things together. But what I actually wanted to do was only apply this to the snare. So I was just using these rather simple settings for that. And I was also using one of the earlier plugins that we used, which was this delay plugin. So the final effect of all of that using rust on the snare with the delay is this. The best way for me to know which types of plugins I should recommend to is via the comments down below. Which of these plugins are you going to use?  I'd love to hear from you on that. If you want to find out about a whole heap more plugins, a whole heap more, I'll keep that in there. Then follow this playlist down here. You can get more there.


This past weekend, the world's largest hackathon took place right across the bay in San Francisco. I'm Parker Lishroy with CalTV News, and to truly understand the experience of this year's annual CalHacks hackathon, CalTV decided to send a team to compete against thousands of other Bay Area hackers. With CalHacks claiming that all levels of experience can compete at the event, we wanted to see how a team of almost all amateurs would fare. But more importantly, we wanted to get to the bottom of why thousands gathered for a weekend of non-stop debugging, caffeine drinking, and problem-solving. Although hacking conjures the idea of someone writing malicious code to break into some system, to hack at the hackathon means to build something, usually using existing frameworks and solutions to tackle some unsolved problem. But beyond the competition, there were workshops hosted throughout the day that helped beginners start their projects, as well as social events like cup stacking, Smash Bros., a 1am wash party of Shrek 2, and a Rubik's Cube contest that our teammates smile and found great success in. I think you won. But to make this all happen, top companies sponsor the event and even give away massive prizes, ranging from an iPad mini to a $10,000 grant. So companies want to be blown away by our solutions. Looking forward to really see what ideas people are bringing up and how passionately they are building on that. At the end of the day, hackathon is all about the passion, and ideas, so very keen to look forward and see what comes out. We knew our idea had to be good if we wanted a shot at winning, so we sat down and brainstormed until we landed on an idea that would streamline the video editing process. Our app would simply take in a video in a key phrase, and it would return a clip of the video that includes that key word or phrase. And safe to say, it had great reviews. That's so good! You're being humble as f***, this is like a million dollar idea. This is actually amazing. One of the best things I've seen is the soccer ball. Thank you. Excellent. We didn't pay this guy. But we asked others what they were working on to see how it squared up to our project. Like, our project in specific is more of like a social good product, so we're trying to create like a charging, an autonomous charging vehicle for unhoused individuals. And I feel like there's not a lot of other places where you just be able to like make something that you want to make without having to like appease anyone per se. I really like my girlfriend, and my idea is that I'm going to make a focus app. Like it helps me focus. Yeah. So what it does, it'll use the webcam to track my eyes. And when I'm looking at my screen as a reward, it'll flash a picture of my girlfriend every minute. And it'll kind of like condition me into keeping my eyes on the screen instead of like looking at my phone or... Yeah, so I'm building a virtual reality marketplace for NFTs on Solana, which basically is a way for people to trade digital assets that are Reddit and 3D and a virtual environment. Dude, this is unbelievable. That's what I was looking at. And so to challenge these projects, we needed to start strong. And luckily we did, as Abhi and I started to get some basic functionality down. So a little update. We have our video transcription software. Next, the next step is just to get our editing done. So use the timestamps of these words to help edit our videos. OK, next step. But completing the next step is never as easy as it seems. And as the night went on, progress got slower. And whenever it was next to implement, we were going to have to learn on the fly. Learning. OK, folks. That's number one here. But Adi and I were determined to deliver something to the judges the next day. So we did what any good coder would do. And that's drink a lot of energy drinks to stay up all night. But running into problems is an essential part of the hackathon experience. And so we were certainly not alone in our struggles. Is there any like pitfalls you've hit? Any, you know, any unexpected things that have happened? Constantly, because that is coding. I think progress is OK. Biggest hiccup is probably the Wi-Fi thing. That was really tough, especially because like everything needs even my like CAD software for designing the print requires Wi-Fi. So while we were waiting for that, it was pretty hard to get things done. We've tried probably four or five different ideas at this point. All of those sponsors provide a lot of starter code. The problem is now it's 2 a.m. And they're not around to help you use it when you run into problems. All of this seems like frustrating late night work, and it is. So why does it attract so many participants? You can watch like the Warren Miller ski movies, wherever and see the people throwing themselves off like gigantic mountains. That's nothing that the adrenaline rush of that. That's nothing like the people who are base jumping. That's nothing. I tell you what the most prime adrenaline rush is at 3 a.m. When you finally get a bug worked out. Yeah, I mean, it's it's it's like nothing you can get in the excansion or anything like that. Hackathons are the one excuse to have like the worst health habits, like procrastinating on a project till you have only 24 hours to do it. Stay up the whole night, drink energy drinks at 3 a.m. Like nowhere else is that going to be like, good job. That's right what you should do other than like the hackathon. I originally joined more of like as a social thing. And it was I did my first hackathon like right when COVID hit and it was more of like, oh, I have nothing better to do. I might as well like meet some people and try to learn something. And then I made like some of my closest friends through it. So I've definitely continued doing it because of that. And so while some grind it through the night, others use this as an opportunity to be with friends and meet new people. How's your guys's idea going? We just we just dropped it. What are you doing here? You're just continuing? I mean, we gave up like. We are here because we wanted to get out of Berkeley for a night and hang out for a couple of hours in the place. Yeah, we were going to go to Denny's in a couple of hours. Oh, that is actually a great idea. It's all that late last night and since there was so much fun to be had, sleep was not a top priority for most people. Yeah, it's been like four hours since I saw you guys last. Any updates? We've learned a lot about ourselves and each other. We think it's true. We think it's true. Although it felt like two years, we were really only at the hackathon for two days. But we were pleasantly surprised with the event and ourselves. It's true that all levels can compete. And although Addy and Akil had no programming experience, they were able to use their marketing abilities to make a great pitch for our product. So here's our 10-page. Running my money. Although it wasn't enough to bring home the $10,000 prize, we definitely didn't feel like we left empty handed. We left with the confidence in our ability to make something from scratch in just a day. And that's what the hackathon is really about. I'm Parker Lishway, Cal TV News.


two events A and B are independent if and only if probability of B given A is equal to probability of B. Now probability of B given A means we are talking about the conditional probability the conditional probability of B given A that is equal to probability of B then we can say that A and B are independent that means whether A has occurred or not there is no effect of this on B so that is why they are independent or we can say that A and B are independent if probability of A given B is equal to probability of A now probability of B given A is equal to probability of B implies probability of A given B is equal to probability of A and conversely. So here we can talk about multiplicative rule what is that if in an experiment the event A and B can both occur then probability of A intersection B will be probability of A into probability of B given A. So this rule is coming from the definition of conditional probability which is already covered because we know that probability of B given A is equal to probability of A intersection B divided by probability of A provided probability of A is not equal to 0. So from this we can get probability of A intersection B is equal to probability of A into probability of B given A what is this probability of A intersection B what does it mean it means that probability what is the probability that both the events A and B will occur what is the probability that A and B both the events will occur. So this is equal to probability that A will occur into probability that B given A so probability of A what is the probability that A will occur into what is the probability that B will occur given that A has already occurred. So this is the meaning of this thus the probability that both A and B occur is equal to the probability that A occurs multiplied by the probability that B occurs given that A occurs since the events A intersection B and B intersection A are equivalent it follows from the above result that probability of A intersection B is equal to probability of B intersection A which is equal to probability of A into probability of B given A and this is same as probability of B into probability of A given B. So they are all equivalent next we consider one example suppose that we have a fuse box containing 20 fuses of which 5 are defective if 2 fuses are selected at random and removed from the box in succession without replacing the first what is the probability that both fuses are defective. So let us try this example in this way if A denotes the event that first fuse is defective and B denotes the event that second fuse is defective here we have to find the probability of A intersection B so we have to find the probability that both A and B will occur and that is we know that probability of A into probability of B given A now what is that first among 20 fuses 5 are defective. So according to the problem we know that among 20 fuses 5 fuses are defective so that is why the first fuse is defective probability of that will be 5 by 20 so probability of A is nothing but the probability that the first fuse is defective so that will be 5 by 20. Now once the first fuse is defective it is now taken out and kept aside now another fuse is randomly chosen from the box so the probability that the second fuse is defective will be that is probability that B given A so what is the probability that the second fuse is defective given that the first one is already defective. So this probability will be 4 by 90 because one defective fuse is already chosen so the number of defective fuses will be 4 and there are 19 fuses remain in the box so that is why the probability that B given A will be 4 by 19 and so the resulting probability that is probability that A intersection B will be nothing but 5 by 20 into 4 by 19 which is 1 by 19 now two events A and B are independent if and only if probability of A intersection B is equal to probability of A into probability of B so this result is coming from the fact that probability of B given A will become now probability of B so let us see here because we know that probability of A intersection B is probability of A into probability of B given A so since A and B are independent we know in that case probability of B given A will be probability of B and that is why in this case probability of A intersection B will become probability of A into probability of B so that is why we can say that two events A and B are independent if and only if probability of A intersection B is equal to probability of A into probability of B therefore to obtain the probability that two independent events will both occur we simply find the product of their individual probabilities. Let us take one example here what is the probability of getting two heads in two flips of a balanced coin now we know that flipping of a balanced coin twice so if we flip it twice they are independent so two flips of a balanced coin they are independent and as the coin is a balanced coin the required probability will be half into half that will be 1 by 4 so this is the probability that first flip will give a head into probability that the next one is head that is also half so that is why probability of two heads will be half into half and that will be 1 by 4 because they are independent. Now suppose there are three events in an experiment event A event B and event C so in an experiment three events A B C can occur so if we have to find the probability that A intersection B intersection C that is we have to find the probability that all these three events will occur A B as well as C so this will be probability of A into probability of B given A into probability of C given A intersection B so that means the probability that A will occur into the probability that B will occur given that A has occurred into probability that C will occur given that A and B both have occurred so how is it coming this very simple A intersection B intersection C now A intersection B can be taken as one event so I can write it as probability of A intersection B into probability that C given A intersection B so I am taking two events here A intersection B and C so these two events now if we consider these two events by the definition of conditional probability we can write probability of A intersection B into probability of C given that A intersection B has occurred so this can be written as probability of A into probability of B given A into probability of C given A intersection B so in this way this will come now if we have more than three events then what should we do if in an experiment the events A1 A2 to AK can occur then probability of A1 intersection A2 intersection so on intersection AK so intersection of A1 A2 to AK so that I am considering the probability of that event can be written as probability of A1 into probability of A2 given A1 into probability of A3 given that A1 intersection A2 has occurred dot dot probability of AK given A1 intersection A2 so on intersection AK – 1 so this result is coming by extending the case which we have already considered that is if there are three events so the way we have done it the same way if we extend number of events then we can get this result very easily now if the events A1 A2 to AK are independent then probability of A1 intersection A2 intersection dot dot intersection AK is equal to the product of their individual probabilities that is probability of A1 into probability of A2 dot dot probability of AK so this can be written as probability of A1 intersection A2 intersection dot dot intersection AK that will be equal to probability of A1 into probability of A2 and so on probability of AK now let us talk about total probability if the events B1 B2 to BK constitutes a partition of the sample space S such that probability of BI not equal to 0 for I equal to 1 to K then for any event A of S probability of A is equal to summation I equal to 1 to K into probability of BI intersection A and that is equal to summation I equal to 1 to K into probability of BI into probability of A given BI and this is called total probability now let us prove this result for proving this result we consider a Venn diagram partitioning the sample space from the figure it is clear that B1 B2 to BK are mutually exclusive events the event A is seen to be the union of the mutually exclusive events B1 intersection A B2 intersection A up to BK intersection A so this is so A the event A is the union of all this events B1 intersection A B2 intersection A up to BK intersection A so that is we can write the event A as B1 intersection A union B2 intersection A union not that union BK intersection A now since B1 B2 to BK are mutually exclusive events we can say that B1 intersection A B2 intersection A up to BK intersection A are also mutually exclusive and that is why probability of A can be written as probability of B1 intersection A plus probability of B2 intersection A plus dot dot plus probability of BK intersection A so this is nothing but the summation I equal to 1 to K of probability of BI intersection A and this probability can be written in this way that probability of BI into probability of A given BI so it can be written as the summation I equal to 1 to K probability of BI into probability of A given BI now let us talk about Bayes rule if the events B1 B2 to BK constitutes a partition of the sample space S where probability of BI not equal to 0 for I equal to 1 to 2 K then for any event A in S such that probability of A is not equal to 0 then probability of BR given A is equal to probability of BR intersection A divided by summation I equal to 1 to K probability of BI intersection A which is equal to probability of BR into probability of A given BR divided by the summation I equal to 1 to K probability of BI into probability of A given BI for R equal to 1 to K so this is called the Bayes rule and this Bayes rule is very very important and it has lot of applications so how to prove this rule by the definition of conditional probability probability of BR given A will be probability of BR intersection A divided by probability of A then using the above result that is the result of total probability we can find the expression in place of the denominator so probability of BR given A will become probability of BR intersection A divided by summation I equal to 1 to K probability of BI intersection A which is equal to probability of BR into probability of A given BR divided by summation I equal to 1 to K probability of BI into probability of A given BI and this completes the proof. So in this way we are getting the Bayes rule and what is this actually so if in some experiment it there are some steps so we are doing something in the first step and doing something in the second step like this so and so if it is asked in the other way that is the final event we know final event will occur that is given then what is the probability that before that it has occurred so this kind of question is asked so in that case we can use Bayes rule and we can find the probability of the conditional probability that final event has occurred then before this this event had occurred so this kind of question can be tackled by Bayes rule.  One ball is drawn from the first bag and placed unseen in the second bag what is the probability that a ball now drawn from the second bag is black. Now we have chosen randomly a ball from the first bag and we have kept it in the second bag and then we are choosing a ball randomly from the second bag now we have to find the probability that if what is the probability that this ball drawn from the second bag is black. So let us try this solution in this way W denotes the event that a white ball is transferred from bag 1 B denotes the event that a black ball is transferred from bag 1. So these two events W and B they are mutually exclusive either W will occur or B will occur A denotes the event that a black ball is drawn from bag 2. Now the required probability is probability of A and what is that probability of A can be written as probability of W intersection A union B intersection A and since W and B are mutually exclusive events W intersection A and B intersection A are also mutually exclusive and that is why this can be written as probability of W intersection A plus probability of B intersection A. So this can be written as probability of W into probability of A given W plus probability of B into probability of A given B.  Now we have to find probability of A which is probability of W into probability of A given W plus probability of B into probability of A given B. So now probability of A given W so we have to find the probability that if a white ball is transferred from bag 1 to bag 2 then what is the probability that a black ball will be chosen from bag 2. So that probability and this is the probability probability of W is nothing but the probability that a white ball is chosen from bag 1.   So this probability will be 5 by 9 plus the probability that a black ball is chosen from bag 2. So that will happen with probability 5 by sorry it will be 3 by 7 because there are three black balls in bag 1 among 7 balls.  So now we can calculate this probability that is 20 plus 18 divided by 63 so it will be 38 by 63. In a certain assembly plant 3 machines B1, B2 and B3 make 30%, 45% and 25% respectively of the products. It is known from past experience that 2%, 3% and 2% of the products made by each machine respectively are defective. Now suppose that a finished product is randomly selected what is the probability that it is defective. So let us try this solution in this way the event A represents the product is defective, B1 is the event that the product is made by machine B1, B2 the product is made by machine B2, B3 is the event that the product is made by machine B3. So we can write probability of A that is probability of B1 into probability of A given B1 plus probability of B2 into probability of A given B2 plus probability of B3 into probability of A given B3. Because B1, B2, B3 these 3 events are mutually exclusive so probability of A can be written as probability of A that is probability of B1 intersection A union B2 intersection A union B3 intersection A since B1, B2 and B3 are mutually exclusive B1 intersection A, B2 intersection A and B3 intersection A are also mutually exclusive and that is why this probability can be written as probability of B1 intersection A plus probability of B2 intersection A plus probability of B3 intersection A and this can be written as probability of B1 into probability of A given B1 plus probability of B2 into probability of A given B2 plus probability of B3 into probability of A given B3. So that is what is here this problem can be represented by this tree diagram also if we have this kind of diagram see probability of B1 is 0.3 so it has 3 branches probability of B1 probability of B2 probability of B3 these 3 possibilities are there either B1 will occur or B2 will occur or B3 will occur. So probability of B1 now from this we can go to probability of A given B1 which is 0.02 in this way if we go along this line we will get probability of B2 that is 0.45 and from this we can go to probability of A given B2 which is 0.03 and along this path we have probability of B3 which is 0.25 and from here we can go to probability of A given B3 which is 0.02. So from each of this path we are going to A so this represents the problem here so probability of A will be 0.3 into 0.02 plus 0.45 into 0.03 plus 0.25 into 0.02 and this if we calculate we will get 0.0245 now with reference to previous example if a product were chosen randomly and found to be defective what is the probability that it was made by machine B3. So now we can apply Bayes rule to find the solution using Bayes rule we can write probability of B3 given A is equal to probability of B3 into probability of A given B3 divided by probability of B1 into probability of A given B1 plus probability of B2 into probability of A given B2 plus probability of B3 into probability of A given B3. So the values are already obtained so we can substitute this values here so it will be 0.005 divided by 0.006 plus 0.0135 plus 0.005 which is the denominator is 0.0245 and the numerator is 0.005 so it will be 10 by 49 so that means if a defective product was selected the probability is very low that it was made by B3 and that is all thank you.


Another summer has come and gone and with it the changes of the seasons. As I sit here editing this vlog, it's another very wet, very rainy day here on the coast. Autumn has definitely begun and this has meant much cooler days and nights. It's been another very rainy season with lots of storms and winds and rain, particularly as we went from February into March at the beginning of the season. As I live further up the coast of Australia on the Gold Coast, we don't really get the beautiful changes in the trees when they change colour from green to orange to yellow to red. This is one of my absolute favourite things about autumn, so I really missed this change happening up here on the coast. And that's one of the things I missed most about Sydney is being able to see the changes in the trees, watching them go from summer to autumn and the changing colour. I flew back home to Sydney during the month of April and stayed for about 5 weeks. As I was leaving the Gold Coast to fly to Sydney, I looked out my window and I could see patches of flood waters over areas like Byron and Ballinau where they'd experienced tremendous flooding just weeks before. It was really devastating to see these areas underneath metres of dirty water. This is the second major flood event we've experienced in just 5 years in Australia as back in 2017 we had another major flooding event happen as well. It was so wonderful to be home again and I find that's one of the hardest things about living so far away is I don't get to see my family as often anymore. But when I do, I try and make the most of each moment with them and cherish the time I have before I head back home again. The flight is only 1 hour and 20 minutes but to drive it takes around 8-9 hours so I much prefer to fly. One of my favourite places we visited while I was home were the Mayfield Gardens past the Blue Mountains. It was a 2.5 hour drive to get there along windy roads and through mountain ranges. But when we arrived it was truly one of the most beautiful gardens I had ever seen. We picked to go this time of year as the autumn trees were changing their leaves so there was so much colour. They had what they called the Valley of the Five Pools which were five waterfalls that ran along the length of the garden and a little stream that connected them. I went with my twin sister Meg and younger sister Emma and we just spent the afternoon wandering through the gardens soaking up the beauty and tranquility there. And we also took a heap of photos. I also house-sitted for my cousins while they were away on a camping trip so I got to look after these beautiful water collies which one was six and the other was only eight weeks old and she was so cute. She'll be happy with a stick for a while. Come on. There they go. See? This is what happens. Stop biting my shoe. Come on. Let's try and intervene. You can't keep biting onto my shoe. Ella! Everything, the time they come back, I am not doing very good at house-sitting. They'd only got her recently so the older one could train the younger one. On their first night with the puppy she did cry all the way home but as soon as she met Archie, the older dog, she immediately stopped and has been really content ever since. She doesn't cry at night and has even been toilet trained by him so in the morning she will just follow him out the back and they'll do their business on the grass. It was really wonderful being around dogs again as it was only just under a year ago since we lost our dog Ari. I made sure to soak up every minute with them and just bask in the presence. I miss having a dog so much. So I am house-sitting for my cousins. They're away camping and while I'm in Sydney I was like, oh my gosh, I get to house-sit. It's like a huge house. It's so cool. So I get to house-sit this huge house with my sister while they're away for this week. So five days.  Both, one's a dog, one's a puppy. One is, they've only had her for a week. Her name is Bello. That's the one that kept biting my foot and has an obsession now with my sock. So I'm going to have to come here more prepared in joggers next time because these shoes aren't going to last. These are my socks. I could hear it tearing and I was like, ah! It's not going to end well. So I've bought my laptop to do some assignments for my uni. Got it all here. I'm going to probably be doing that this afternoon and then when my sister gets here, she's coming a bit later because she's coming from her boyfriend's. We're going to take them for a walk, or actually take Archie for a walk because he's older. Bello hasn't had all her vaccines yet. So my sister will probably stay here with her and I'll take the older dog for a walk, taking for a walk and that'll be nice. Since our dog passed away, I miss her so much. It'd be nice to sort of go out walking with another dog again. That's something I'm looking forward to, just to have those walks and have that company again. On my second night home, I went to a paint and sip night with my friends. We bought our own drinks and snacks and just chatted the evening away while we painted a picture of a boat floating on this crystal clear lake at sunset. My best friend Sarah had actually just recently come up to stay with me in Queensland for a week just before I flew back down to Sydney. So I got to spend a lot of time with her and I showed her all my favorite places and cafes before she had to fly back home again. And it was really nice because I hadn't actually got to show her my new place since moving. As a surprise for my cousins, we took them to this Harry Potter themed high tee. I swear I was more excited than them. I just love Harry Potter. It was really cool. They hosted it at Sydney University in one of their conference rooms and set up the tables to mimic the Great Hall. So we of course sat at a Gryffindor table and they had these actors going around pretending to be characters from Harry Potter. So Dumbledore, Luna, Professor Trelawney, Harry, Hermione and Ron and others. It was such a fun day and really cool experience actually. They even brought out the sorting hat and I had Professor Trelawney come and read my tea leaves which was pretty cool. While I was home, I also caught up on some gardening which I've really missed being able to garden since moving out. And I plan on actually sitting up some pot plants back home which I'll fill with herbs and greens to use in my cooking. So I have a plan to do that. I'm hoping to start that within the next few months. But while I was at home, I planted some lettuce, spinach, beetroot, carrots and coriander in our back garden so that they'd be ready for winter. Now I've learned from past experience to plant them early on in the season. Otherwise by the time they're fully grown and it starts to head into spring and the weather becomes warm that they begin to bolt so they don't become as nice anymore. My dad and I also salvaged some papaya trees that were growing in our vegetable garden out the back which they'd self seeded from our compost that we use in the garden. So we transplanted them next to our shed around the back where they had more space to grow and then gave them some water. So time will tell and we'll just have to wait and see if they take to the new location and continue to grow or not. Fingers crossed that they'll be there when I get back home. For one of my pracks for TAFE, we did a beach cleanup and this was just before I flew down to Sydney. We walked around Burley Beach and picked up around 30 kilograms of rubbish. You wouldn't think there would be so much to pick up when you look at the beach from afar but once you start searching, it just doesn't end.  It's too late. I'm in Baratech.  So there's about like 30 of us going around and cleaning. At the end of our cleanup, we pulled out all the trash we found onto a huge tarp and wrote down what we found on a data sheet to log online later on. Everything was separated into categories. So there was like plastics, glass, metal, wood, clothing and things like that, which we noted down. Then once everything was recorded, we had to properly dispose of it all. So some things could be recycled like the glass bottles and aluminium cans but other things like the bits of old clothing, plastics and lighters had to be thrown away. As I flew back into Gold Coast Airport, it was really nice seeing the ocean and beach from up in the plane like I was coming home. I'd really missed the sea and the sand since being away. As the days get cooler, I won't be swimming as much but I still love to ride my bike to the beach and walk along the sand on the rare sunny days that we have or just sit under the shade of the trees and watch the waves roll in and out. Thank you so much for watching this vlog. I hope to see you soon. Take care. Bye.


Assigning work one task at a time? Do this instead. In list view, hover over tasks to select them with the toolbar. To select multiple tasks, hover over the status and then click this icon here. Or to select the entire list, click on the list name here and then go down to select all. Okay, so here we have the entire list selected and now we can access the multitask toolbar located at the top of the screen. So to assign somebody to all these tasks, we navigate to the set assignees icon right here and then select the person we want to assign. And just like that, you've saved so much time.


Hey, this is Brett, and this 2006 Ford F-150 SuperCab 6.5 foot short box is stock number 24T16B. I am here at Summit Automotive in Fond du Lac, Wisconsin, your new and used light duty truck headquarters. This 2006 Ford F-150 has the 5.4 liter V8 gas engine. This one has been fully safety and inspected by our service shop as a fresh oil and filter change all the fluids have been checked and topped off. It is mechanically very nice and this truck is 100% ready to go. I'm going to go all the way around in this video inside, start it up, take a look under the hood, show you all the options and just give you the most accurate representation that I can of the vehicle. Black clear coat is a color. I showed all my videos in 4K. If you like the video, subscribe to the YouTube channel, click the bell notifications, get updates on the videos I do each and every day as well as having access to one of the largest catalogues of vehicle light duty truck walk-arounds on YouTube and stay current on our ever-changing inventory here at Summit Automotive. This one comes with the painted and polished aluminum wheels. They do have a little bit of corrosion on them, that's because this 16-year-old truck or 18-year-old truck has been in Wisconsin its whole life. Cooper Discover AT3 tires. These are LT27565R18s. I would say that they have probably about 50 to 60% of the tread left on them. The frame and underbody is in pretty nice shape for being a 2006 vehicle. Front fender, I didn't see any major dents or dings. There are some scuffs and scrapes and scratches on this truck. It has been used as a truck. Headlight lenses are nice and clear. It does come with the factory fog lights. The front bumper is in pretty nice condition. I didn't see any major dents or dings on there. The grille is in nice shape as well. And the hood is in excellent condition. No major dents or dings on there. Passengers side front fender is in pretty nice shape. Is just a little bit of corrosion at the bottom there. Passengers side wheel, about the same condition as the driver's side. As you go down this side of this 2006 Ford F-150, take note of how clean the body is, how reflective and mirror-like that paint is. Pretty nice shape for a 2006 with 100, I think it's got 137,000 miles on it. This one does have a rolling tonneau cover. This is a, I believe it's a Pace Edwards. Really nice tonneau cover, works nicely. Pretty clean on that side. I didn't see any major corrosion on the doors or anything. This side of the box is in really nice shape. Take these HD videos, so if you're far away or close by, just want to come take a look at the truck, but you can't. You can see the truck here, the truck end up confidence in the vehicle that you're looking at before you even get here. So back tires have just as much tread as the front tires, frame and underbody, not too bad. A little bit of corrosion on the box rails, but nothing terrible. Pretty typical of a truck that's been in Wisconsin for about 18 years. Has a nice factory chrome step bars, they're in pretty nice condition. FX4 Off-Road Suspension Package, you get the bed rail covers. Coming around to the back, the rear bumper does have a big dent in it. Full towing package, which includes receiver hitch, four pin and seven pin wiring. The tailgate is in pretty nice shape as well, it is a locking tailgate. And there is that tonneau cover, it does work quite nicely. The rules like that, you've got to keep it unlocked, but you can see it is working really nicely. It does come with a nice drop-in bed liner. So ready to do all the work, shots nice and solid, and that closes like so. I didn't see any major damage to the tonneau cover, and yes, it is a pace at words tonneau. Coming around the driver's side, just as nice as that passenger's side, like I said, there are some scuffs and scrapes and scratches on it, there is just a little bit of corrosion on the box side here, but nothing terrible, back wheels in about the same condition as the rest. And the driver's side doors and cab all look pretty good. Does have the driver's side door code entry. We do have the code for this truck, if you ever want to figure out what your code is for your 04-2007 F-150, the upper right hand part is going to show you how to do that. Inside the FX4 package gives you the gray cloth bucket seats. No rips or tears in here, they're in really nice shape for 137,000 miles. Power driver seat, factory all-weather floor mats, power windows, locks, and mirrors. These back doors open up 90 degrees, and it does have a power back window which was pretty nice back in 2006.  We'll hop inside, check out the miles, the radio, and everything that this one has to offer on the interior. As you can see this one has 137,239 miles, you do get a compass and outside temperature display and the instrument cluster is nice and clean.  The headliners in nice condition as well, you get map lights and that's your button for your power slide rear window. We'll start it up, take a look under the hood, starts right up, no check engine lights or anything like that, and the big thing that I noticed on this truck is how smooth it runs, no exhaust leaks or anything like that. Also, you don't hear any ticking, which could be a sign of cam phasers on these 5-4s, this one sounds very nice and smooth, so I don't think you have any issues there. Under the hood we have the 5.4 liter V8 Triton gas engine, engine base is very clean once very smooth. Once again this truck has been fully safe and inspected by our service shop, has a fresh oil and filter change, all the fluids have been checked and topped off, runs really smooth, there is the emission sticker, and this truck is 100% ready to go and see more pictures of this truck or one of our 550 new and used cars, trucks, SUVs, minivans, wranglers, half tons, three-quarter tons, one tons, you name it, we've got to go to the website right there, summitauto.com, full pictures and descriptions of every single vehicle, all at summitauto.com, if you want to check out more HD videos you can go to youtube.com slash summitauto, click the bell notifications, get updates on the videos I do each and every day, as well as having access to one of the largest catalogs of vehicle walk around on YouTube, and stay current with our ever-changing and vast inventory by hitting the subscribe button and bell notifications, you can stay up to date on our inventory as it comes through the picture studio. In fact, in a second you will see a link to subscribe to my YouTube channel in the upper left, a link to all the F-150 videos that I've ever done in the upper right, link to this vehicle on our website in the lower left and a link to one of our latest YouTube videos in the lower right, click those check us out, we're super excited to help you with this ultra clean 2006 Ford F-150 SuperCab 6.5 foot short box FX4 in black clear coat, thank you so much for checking out the video, remember to like, subscribe, and share on the YouTube channel, I really appreciate it, thanks again.


Hello and welcome to the session. Let's work out the following problem. It says using quadratic formula solve the following quadratic equation for x. So, let's now start the solution. The general form of quadratic equation is given by A x square plus B x plus c is equal to 0. Now the given equation is p square x square plus p square minus q square x minus q square is equal to 0. Comparing this with the general equation we have A is equal to p square v is equal to p square minus q square and c is equal to minus q square. Now the discriminant d of the quadratic equation is given by b square minus 4ac. You must write this. Now we find d for the given equation v square that is p square minus q square whole square minus 4ac. A is p square and c is minus q square. Now we will apply the formula of A minus B whole square. So, it would be A square that is p square square plus q square square minus 2ab that is 2 into p square q square minus p square into minus q square and we know that minus into minus is plus. So, this becomes plus 4p square into q square and here we have used the formula say x minus y whole square which is equal to x square plus y square minus 2xy and this is very important to write the formulae whichever you are using. So, this is now equal to p square square is p to the power 4 q square square is q to the power 4 minus 2p square q square plus 2p square q square is equal to 2p square q square. Now this becomes the formula of p square plus q square whole square as we know that x plus y whole square is equal to x square plus y square plus 2xy and here x is p square y is q square. Now we can find the value of x, x is given by the formula minus b plus minus under the root d upon 2a. Now we substitute the values of b, d and a in the formula now v is p square minus q square plus minus under the root d that is p square plus q square whole square upon 2a is p square. So, now this is equal to minus of p square minus q square plus minus square root gets cancelled with this square. So, we have p square plus q square upon 2p square. Now we have two values of x, one is minus of p square minus q square plus p square plus q square upon 2p square and another value is x is equal to minus of p square minus q square minus p square minus q square it is plus here. So, we have plus here upon 2p square. So, we have x is equal to minus of p square plus q square since we have negative sign outside the bracket when we will open the bracket sign will change it becomes minus p square and this becomes plus q square plus p square plus q square upon 2p square and again x is minus of p square plus q square again we have negative sign outside the bracket. So, when we open the bracket sign will change. So, it becomes minus p square minus q square upon 2p square again we have now minus p square gets cancelled with plus p square and we have q square plus q square that is 2q square upon 2p square and here we have x is equal to now here plus q square gets cancelled with minus q square and we have minus p square minus p square which is minus 2p square upon 2p square now 2 gets cancelled with 2 here also and here p square gets cancelled with p square. So, we have value of x as q square by p square and x is equal to minus 1 since 2p square gets cancelled with 2p square. So, x is equal to q square by p square or minus 1. So, this completes the question while doing the question do take care of all your calculations that is very important. So, bye for now take care have a very nice day.


Today, I'm going to show you how I would teach counting by tens to the students in my classroom. To begin with, I would have three students come to the front of the room with their fingers extended so the entire class can see. Student one, student number two, and student number three. I would say class, we are going to count their fingers. We're going to count together. Ready? Count. One. Two. Three. Five. Six. Seven. Eight. Nine. Ten. Eleven. Twelve. Thirteen. Fourteen. Fifteen. Sixteen. Seventeen. Eighteen. Nineteen. Twenty. Twenty-one. Twenty-two. Twenty-three. Twenty-four. Twenty-five. Twenty-six. Twenty-seven. Twenty-eight. Twenty-nine. Thirty. That's right, boys and girls. There are thirty fingers in the front of this room. Is there any quicker way to count these fingers? Well, by now they're probably going to say counting by fives. I say, oh, boys and girls, you are so smart. Let's count by fives. Five. Ten. Fifteen. Twenty. Twenty-five. Thirty. Oh my goodness, boys and girls, that's right. There are thirty fingers. Is there another way we can do it? Any quicker? Hmm, what can we do? And if no one comes up with counting by tens, I would give them the idea. Oh my goodness, we can count by tens. Let's try that. Both hands together are tens. So we're going to say ten. So ready? Count with me. Ten. Twenty. Thirty. Wasn't that much quicker? We did such a nice job. Boys and girls, how many fingers do you see? Thirty. You are correct. Now I'm going to bring some more students to the front of the room with us. Here's student number four, student number five, and student number six. We would go through the process again and we would count all their fingers one by one. Boys and girls, count with me. One, two, three, four, five, six, seven, eight, nine, ten. All the way over here to 56, 57, 58, 59, 60. Oh my goodness, that took us a long time. What can we do? Well, they will say now, counting by fives. So we'll count them by fives. Five, ten, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60. Beautiful job. Can we do it quicker? Hopefully they will now come up with counting by tens. So we're going to count the entire set of hands, all fingers. Ten, 20, 30, 40, 50, and 60. Boy, that was a lot quicker and we got our jobs done faster. Nice job.