Good morning, John. I'm in a car. I'm headed to work. I'm stopped at a stop by right now. I'm being safe. And I wanted to take you with me to work. I wanted to show you some of the people who work on the things and the place where they do it. Here we go. Gonna start with Matthew. What are you doing right now? Financial diet. Hey, there's those girls. There they are. What's up? They can't answer you. How you doing? Good. How are you? Am I talking to the camera? I'm in the same spot as the camera, man. Yeah, I know. But if I look, I line, weird man. I line. Oh, Nicole's here? Yeah. I'll just pretend like she was here the whole time. Hey, Nicole. I have been here the whole time. Who are you editing? Myself. Yeah, I know what that's like. Sarah's here. Hello. What are you writing about right now? Uh, I'm actually editing Crash Course film. Alyssa's sad, empty desk. Cause she lives in New York sometimes. Kalen's here. Hi. How's it going? Good. How are you? I am reading about ways to start a new job. Not because I'm looking for a new job, but because I'm working on a script for How to Adult. Thanks for making that clear. Yeah. I'm coming in.  I am. How are you doing? I'm learning how to edit you right now. Well, more specifically, I'm learning how to animate on top of you. You wouldn't think there's anything happening in the darkness over here. There it is. The darkness. Look at you. This is the darkest I've ever seen it in here. Behind this door is the scariest part. Oh. Hey, it's Henry. Hey. Are you doing a tour? I am. So you don't work for me, but you work in my office. This is my office. I rented for you. You crossed into my office. This is the light that they turned purple when we're filming. This is Marianne, who is my assistant, assists me with all the things. Hello. What are you working on? Your emails. Thanks. How are they? There's a lot of them. Oh, look, there's a Julie. Hey, it's Julie. Hello. What's your official title? Director of Operations. Money maker. The vast majority of the pictures on my phone. Oh. His cheeks are coming in nice. Hi. This is Julia. How are you doing? I'm good. How are you? Good. Just maps of Amsterdam and Melbourne. Yeah, I got to think about them. We noticed yesterday that you haven't updated your calendar collection. How funny you say that. Oh. Calendar. Calendar. Cows doing yoga. Rivers. Ocean available on DFTBA unless it's sold out. Not being able to sell that now. Fontana Wildlife. And some Mormont. That's even more than you had last year. I know. What a cool room you guys have. What are you working on? I'm working on signage for Nerdfighteria. What do you have programmed there behind it? Oh, yeah, okay. Oh, oh. Sorry. Oh, dang. Okay, I'm going to take pictures of all of you and then put you in my video. You're going to have lower thirds. Oh, why are you on the floor? I think. Hello. Do that. You showed it. I've stopped for whatever this is. Now I'm going to the warehouse. I'm getting the feeling that our break table isn't being used very much right now. Oh, you're already in the video. It's pretty out. And now I go home. It's weird, right? I want to be clear that like Vlogbrothers still just me. But all the other things VidCon, SciShow, Crash Course, DFTBA.com, all that stuff. So many people are necessary to make it happen. I like doing the business thing and I like doing it not in the normal ways. So I'm going to keep doing that and I'm excited for what the future has to hold. There are a lot of people who work on the things that we do and I'm always amazed by them and really lucky to have them in my life. John, I'll see you on Tuesday.


Hello everybody, E here. Welcome back to day 3 of 31 days of Halloween. Today we are talking about No One Will Save You, a 2023 horror movie starring Caitlyn Devere as a character named Brinn. And when I say she's the only character you really need to worry about in this one, I actually mean it. Let's get into the review. No One Will Save You revolves around the main character Brinn. Brinn is a recluse, a hermit, a shut-in, whatever you want to call it, that lives in a very large, I don't know if it's a period home or what, but it's a large estate and she's there by herself and then there's aliens. And that is the entire setup, that is the entire movie, other than the fact that Brinn has some trauma that she has not worked out dealing with a friend of hers, a childhood friend, and this movie hit me in the gut hard. But before I go into why, I want to mention something that everyone else is going to be talking about too. There is almost no dialogue in this movie. When I say almost none, there is two lines spoken, one character says it and then the other character repeats it. And that's the only dialogue in the entire movie. It took me about 20-30 minutes into the movie to actually figure out what was going on and that this was going to be it. I read an article from an interview with the director that said that he was writing the script and he'd gotten so far into the script he realized that no one had talked yet, that Brinn hadn't spoken yet and he decided let's make this a thing. It is a unique premise and it 100% works here. I don't know, I'm shocked and I'm stunned. In fact, it works so well. My only criticism about this movie, period, my only one, is that I actually think that the two lines of dialogue that are spoken in the movie take away from the movie. I have never said that before, not with books, not while reviewing books, not while reviewing movies, no that stuff. I consider dialogue the grease that lets the wheels keep spinning. Any time you're getting bogged down in description or any of those things, too much is going on. You break it up with some dialogue, maybe some humor, maybe some drama, whatever, what have you to counteract everything else that's going on and just kind of ease people through the movie into the next scene. I'm shocked that this movie is as good as it is without much dialogue at all. I want to say no dialogue because even the dialogue that's in there is so, it's two words. One character says two words and the other character repeats those two words and that's it. The most striking, the most, maybe even the most upsetting part of this movie is at the police station. The director said in the interview that he'd gotten all the way up to that point and he went to write dialogue for that scene and that's when it clicked with him that there should be no dialogue.  So everything is body language and it just hits so much harder because of that. Not a single word spoken.  But yeah, there's aliens. It is a very simple setup. It was very cool to see Bryn fight back right at the beginning and what happened after that. And it just kept escalating and escalating and escalating. This is definitely a hidden gem. If you have not seen it, I believe it's on Hulu. If it is not on Hulu, even if you have to rent it, pay for it. I highly suggest that you do because not only is it a fantastically shot movie, acted, all that stuff is off the charts, characters, pacing, dread, all of that stuff is off the charts with no dialogue. It is also a very entertaining movie that doesn't have any downtime, well very little downtime, for emotional scenes like the dialogue that is spoken and the scene at the police station, but other than that it is balls to the wall. If you are a fan of movies or literature like Invasion of the Body Snatchers, even movies like Mars Attacks, not Mars Attacks, there's another one. Invasion, Invaders from Mars, something like that. I can't remember where they put the little spike in the back of people's heads. I can never remember the name of that movie.  The actress who played Brynn kills it throughout. In fact, the director said, I had such a great actress that she didn't have to say anything. And she didn't, which brings me back to my one criticism. I don't even think we needed those lines of dialogue. But I could be wrong if you watched it and you think the lines are perfect or unnecessary or whatever. I'd love to hear your opinion on that. But until next time, I have been E, you have been U. This has been another episode of 31 Days of Halloween. I'll talk to you guys later. Bye-bye.


Personal finance practice problem using Excel Home Loan Comparison. Prepare to get financially fit by practicing personal finance. Here we are in our Excel worksheet. If you don't have access to the Excel worksheet, that's okay. We're basically going to build this from a blank sheet here. But if you do have access, we've got the three tabs down below. We've got the example tab, the practice tab and the blank tab. The example tab in essence being an answer key. Let's take a look at it now. We have the information on the left-hand side. We're going to populate that and build our tables on the right-hand side. We have three different loan scenarios that we're going to be constructing amortization tables and then summarizing that data. As we think through it, we want to think about the practical use of this. Clearly, if you are thinking about different kind of loan structures, you might be running different scenarios and you might be changing factors, for example, with the amount, the number of years and the rates, for example. You can do that with online software. If you were to look up loan calculators such as this one, you can then construct amortization tables, for example, in this format. But you have a little bit less structure and if you want to do a side-by-side comparison, you can change the data over here to run different scenarios, but you can't see them side-by-side quite as easily. However, you can create different tabs and toggle back and forth between different tabs and try to do a side-by-side in that format. But if you can do it in Excel, you have much more capacity to make those changes a little bit easier. So we could, for example, have this information on the left-hand side and then just run one loan scenario on the right that ties into this data on the left, and then we can change this data on the left to change the loan calculations on the right-hand side. Or we might want to have the side-by-side. I might want to run two different loan scenarios side-by-side so I can see them side-by-side. So we might have two different loan scenarios so that I could put the amortization tables right next to each other. And we're going to hide some cells to show how to do that. We can also summarize this data on a year-by-year basis as opposed to on a payment month-by-month basis, which is another way that it would be very nice to do some comparisons, and we'll show how to do those kind of comparisons as well, building our table. So on the second tab here, we've got some pre-formatted worksheets. So you can work on this one and it'll be a little bit easier to work with because you don't have to format too much of the Excel formatting. And then on the Plank tab, we're actually going to build this from scratch. So this is the scratch that we have on the left-hand side that we're going to build from. So if you don't have the Excel worksheet at all, you can just build this scratch on the left-hand side. What I would first do is select the entire worksheet, format the worksheet on your underlying formatting, which I would usually make currency. Don't do this if you have this worksheet, but currency. And then I would usually have the brackets and I usually start with no decimals. And then I would build and add any more information I need, including making a percent type of cell here, a percent type of cell here, and adding decimals when needed. So that's what we have this time. We've got a blank sheet. Everything is formatted thusly, except for this tab on the left-hand side. This is going to be our source data that we'll then use to pull over. Remember that you always want your source data somewhere separate than your calculations. You don't want to hard-code the calculations so that we can change the source data on the left-hand side. Now I'm going to do a quick recap of this source data so we can see it again, and then we'll calculate the payment. So I'm going to say, let's say we have the amount, which is going to be equal to for one, two, and three. I'm going to say three loan scenarios. I'll just call it the loan scenario at the 168. And then we've got the amount over here at the 223. And then we're going to have the amount at the 199. And then we're going to have the years. So let's put the years. And I'm going to say this is going to be equal to the 15 years. This is going to be equal to the 30 years. And this is going to be equal to the 20 years. Now note, if you have this information on the left, you might just put like another, you might just construct it on the left here. If you're building the table from scratch, I'm just reworking it so that we can calculate our payment calculation on the right-hand side. So then we're going to say that the rate is going to be the rate for the R3 scenarios is going to be equal to the 6.5. I'm going to make that into a percent by going to the home tab number group and percentifying it, which isn't a word. But I like it. I think it should be a word and I'm working on it. I'm working on making it a word. I'm going to make it happen. I make stuff happen. So then I'm going to go to F3. This is going to be equal to the 7%. And then we need to percentify that number group percentifying it percentified. And then we got to decimalize it percentified and decimalized. I didn't really need a decimal, but we'll put one there anyways. So it has the same number of decimals as the other one consistency. That's what we shoot for here. Number group percentifying this one and we'll add a decimal 6.5. Now we got the new thing, which is the payment. Now this is the payment calculation that you can make. And this will just give you the payment. We want more information than that. Typically we want the actual amortization table because we want the breakout between the interest and the principle and to see that fluctuation at least on a year by year basis. So the payment calculation, I do it this way. Instead of hitting equals, I hit negative. So it'll flip the sign and make a positive number. It's probably more proper to put the negative sign in the formula, but this to me is the fastest way to type it. So negative PMT shift 9. Then I've got the rate argument, which is simply going to be up one. That's going to be that 6.5%. But that's a yearly rate because we talk about rates in years. We don't talk about like monthly rates or daily rates because they'd be really small. And so we usually talk in years. So I got to divide that by 12 to get the monthly rate because we're going to have the payments in months, of course, like normal. So then comma, the number of periods, I'm going to say up up is going to be that 15 in E2. Once again, that's in years, though, I need to make months because I'm doing this on a monthly thing. So times 12, so 15 times 12. And then comma, the present value is going to be up, up, up that 168,000 168,000 is it and enter. So we got the payment here. I could add decimals, but I'm going to keep it rounded at the 1463. Let's do the same thing. Now you could copy this formula to the right, but let's calculate it again. Because we're practicing our payment calculation and then I'll copy it over just to kind of show that we could do that too. But let's practice it again. This is negative PMT shift nine rate up once that's a yearly rate. So I'm going to I'm going to divide it by 12 to get the monthly rate comma to the next argument. That's going to be the number of periods. Number of periods is 30 years, but I need months.  There's our present value the loan amount and enter. So there's the 1484. And then next we have negative PMT shift nine rate up once that's a yearly rate divided by 12 for the monthly rate comma to the next argument number of periods up to that's the years 20, but I need months so times 12 to get to the months comma up up. And there's the present value the loan amount to get us to the 1448. So notice these two we both got the 1448 even though we have kind of substantially different terms in terms of the years and the rate. Now I could copy this across this way. So if I delete this one, delete it. What? No, it's okay. It's okay. And so I'm going to then copy this across put my cursor on the fill handle and copy it across. Okay, it's back. It's back. And let's make this let's make this blue. We'll go to the font up top and make it blue and bordered blue and bordered. So there's our information. Let's build our amortization tables. I need a skinny because I don't like to you don't want to build anything right next to the table over here. So I'm going to copy the skinny by going to the home tab skinny column that is and then the format painter and paste the skinny for a skinny H skinny H. Okay, now we'll build our amortization table amortization table construction time. So what I'm going to do is now note that I'm going to have a couple headers that are going to be longer than like the width of a column that I would like. We could wrap the text, but that makes these cells fat and we don't want to do that because it kind of makes everything else look funny. So I'm just going to predict that I need two rows, two rows. So I'm going to say the first one's going to be the year, the year, the month and the payment and then tab and then we've got the interest. And then you could say principal decrease, but I say loan decrease because it's easier to spell, but I even spelled that wrong. I noticed that I spelled it loan like that a couple times. So I mean, I am just spelling's not good. Spelling's not my forte, my forte, my forte. So this is going to be loan balance balance. And then we're going to make this black and white. So we'll select this and make this a header thing. We're going to go to the home tab font group and make it black and white, black and white. And then let's center it alignment and center. And then we'll make this a little skinnier. Okay, so we're going to add up the months now. So there's 15 years. So 15 times 12 is 180. So I need to go down 180. So 180, it's like a 180 degree like turn around one to 180. We're going to do 180. So here we go. This is a super cool move. So 180 kick flip. So there we, it's going to be right there. 180. And then we'll alignment and center it. That looks good. And then we're going to do our years with our fancy trick, fancy trick on the years, which is a roundup roundup. Roundup little doggies, which are really cows. For some reason they call them dogs in the songs sometimes. Roundup the little doggies. Roundup. And then brackets. I'm going to go to the right, divide it by 12. And then, and then I got to say what category do they want to round. So I got to hit comma and the number of digits is going to be point one rounding it. And that tells it to round it to the nearest whole number, a whole number. Don't give me any half or partial numbers. So then we'll, I used to add some decimals to make sure it does it right. And then if I copy it down, see how it all, this is all in the year one that helps us when we do the pivot table for example. And so I'm going to copy that all the way down, all the way down to 180, throwing up, throwing out the 180 kick flip. And then I'll send, we're not really kicking or flipping anything, but still sounds better when you throw on the 180 kick flip. And then we'll do that just to 180 is pretty impressive in and of itself though for me, I feel like. But I'm going to then format this one. I'm going to put the zero up top because that'll help us out with the pivot table. I shouldn't have a blank cell for the pivot table because that kind of messes things up. So I'll put a zero up top this time. Haven't done that in prior presentations and I was not optimizing what I should be doing by not doing that. I'm going to do it. So now this is going to be the loan balance of we're going to start with this one, this first one, the 168. And then you might put zeros up here because again, you shouldn't really have any blank cells. If you're planning on making a pivot table out of it, which we will do. So I'll put some zeros up top just to just to fill the space. And then I'm going to say this is going to be the payment, which is equal to the payment we calculated here. So there is the payment. And then let's say F4 on the keyboard so we can copy that thing down, copy it on down. And then the interest is going to be equal to the prior loan balance times the interest rate, which is the 6.5. That is a yearly rate. So I got to divide it by 12. I need to divide it by 12. That's a key component. Don't forget that. Don't forget that piece. And this is going to be equal to the payment minus the interest, which is the loan decrease or the principal decrease. If you would like to call it that Lee, call it that Lee, that bus Lee. And then what this is going to be equal to the prior loan balance minus the 553. There it is. Now we should be able to copy this down, copy it down. But there's going to be a problem in Houston. Houston will have a problem. Houston, we haven't actually the problems wasn't in Houston. They just telling Houston that we have a problem. It was in space when they had a problem, but they were just telling Houston of the problem. Houston wasn't the one with the problem, apparently. In any case, the point is that this interest item is outside of our data in the in the data set. It's not in our table. So we got to make that an absolute reference so that when we copy it down, it'll it'll it won't go down. This cell won't go down. So I'm going to put my cursor in E3 and select F4. So there's a dollar sign before the E dollar sign before the three. You only need a mixed reference, but an absolute is easy and it works in this case. We don't need to do that here because everything's inside of our area that we're working on. It's not in the data set, nothing in the data set here. So those will copy down and move down as desired. So I'm going to select these four. We're going to double click. We don't have to drag the fill handle. We just got to double click the fill handle button. Call it a fill button. They don't call it a fill button. It's still a handle, but you're really using it like a button when you do that. There's a zero at the bottom, which indicates that we have done everything was done properly, hopefully. And so there it is. Let's make it blue and bordered blue and bordered blue and bordered, not the letters. If you don't have this blue, you go right here standard and it's that blue. That's the Excel is fun guy blue. Excel is fun guy blue. So there we have it. So so now this one, of course, will flex if I change the change anything here, like the rate to to like 8% or something, everything will change. And that's the point. Now, of course, if I change the number of years, it becomes an issue because it's only 180. So you'd have to extend it down a little bit, but everything will basically populate and adjust with that. Now we could also want the year by year table. So I'm going to build the year by year table to see like a side by side thing. So and we also might want to see it broken out on a year by year basis. So first of all, I'm just going to build this another table right next to these two with these two scenarios. So instead of like instead of adjusting my data back and forth between the scenarios, I got a side by side of the amortization tables. So let's do that. So I need another skinny over here, the zero. So I'm going to put my cursor on the H. I'm going to format paint it. I'm going to hit that over here with the skinny. And so I'm going to try to do this a bit faster. So I'm going to copy my headers. That'll make it faster. Just going to copy that. And I'm going to put that right here. And then I'm going to hide this data from H to N, putting my cursor on H, scrolling over to N, and then right click and hide. And then let's do this again. This is going to be how many periods we got 30 periods on this one. So this will be 30 times 12, which is 360. This is the full 360.  But now we're doing a full 360 rotating all the way around. We're going to select these three. We're going to go all the way down to get that full rotation, getting that full rotation going right back to the same stance that we were in when we started the maneuver. We started the maneuver. We're going right back all the way around 360 instead of 180. So there we go. And I'm going to go to the home tab alignment center it. And then that looks good. We'll do our roundup, roundup equals the roundup little doggies, which are actually cows. And then we're going to pick up that one to the right and then divide it by 12 because there's 12 months. And then comma, the number of digits is going to be 0.1, which says rounded up to the full, a whole number. Poor Favore, please. And then I'm just going to copy that down double clicking this time on the fill button, which is called the fill handle, but we're using it like a button. So it's a fill button in this case. Fill button populates it all the way down to to the 30 years just like that. No problem. And then I'm going to put a zero up top fill in the blank space, put some zeros here to fill the blank space. The loan balance is going to be the three, three or the two, two, three. The payment, which we calculated this needs to be centered. That looks off. Something's off. I can't stand it. Oh, my God, that's so much better. Okay. The payment then is going to be equal to the 1484. And then we're going to say F4 on it, dollar sign before the F and the four, you only need a mixed reference, but an absolute one works. And then the interest is going to be equal to the two, two, three times the 7% this time. That's the yearly rate. So we're going to divide it by 12 divided by 12. And this is outside my data set. So that needs to be absolutized, which isn't a word, but it's what we're making it one again. We make what we make words here. It could be a mixed reference, but we're using an absolute. It's easy to do. This one then is going to be equal to the payment minus the interest. That's the loan reduction or principal reduction. If you so choose that terminology, the two, two, three thousand minus the 183. We're going to select those four sales and use the fill button. We'll just double click on the fill button, the fill handle button. And then all the way down, it should go down to zero at the end of the day. It's a long day. It's a 30 year day. But at the end of the day, there it is at zero into the day, the end of the day. So we're going to go back up top. And then let's make this home tab font group blue, blue ties it and bracken. My is it blue ties and bracken. All right, let's do it again. Let's make these a little skinnier. They should be a little skinnier. I feel like those are way too thick for this stuff. There's too much blank space in there. Okay, I'm going to take the skinny. Oh, skinny. Oh, we're going to go to the home tab and format paint it and skinny up the V skinny up the V. And then we'll take the headers again. We'll put that up top headers and then do a hide hide from O to you. Oh, oh, and then hide. Okay, let's do the same thing. This one's going to go to 20 years, 20 years, 12 times 20 is 120. I could have done. I could do that in my head. I'm not so dependent on computers that I couldn't do that one in my head yet. But I'll get there. This is a one. This is a 240 240. So we'll select these three. We're going down to a 240. Then she lands sideways. If you do a 240, but then you like finish the rotation on the ground. 240 is dangerous. They were going for a 180 but over rotated to the 240. I'm getting mixed up. 240 concentrate constant. There it is. Got it. Got it. Alignment center it. And then we're going to say this is going to be equal to the roundup roundup rounded up. And then we're going to say this is going to be this one divided by 12 and then comma to the digits of point one saying to the whole number. That's what that means. And then we'll just copy that down. There's our years. We'll do double clicking on the fill button fill button. And then we're going to say to fill handle, but it's a button center in it. They didn't know it was actually going to be a button when they called it the handle. But then it became a button. And now it's called filled handle. Even though it's also a button doesn't really look like a handle at all.  So we got the one. We got the 11199 payment is going to be equal to the 1484. And then we're going to say F4 on the keyboard so we can copy that down. You only need a mixed reference, but the absolute one works. Interest is going to be the 199 times the rate of the 6.5. We're going to F4 that one because it's outside our data set then divided by 12 to get it down to the monthly amount. We got the loan decrease, which is going to be the amount of the payment minus the interest loan balance. Then it's going to be the prior balance minus the loan decrease or principal decrease. You could call it the principal balance at the end. If you want to call it principal stuff instead of loan stuff, then I'm going to select those four. Double click the fill button fill button. And so now it's down to zero at the bottom. We're going to go back up top and just do some formatation blue and bordered blue and bordered. There we have it. Now if I was to unhide from going from G to W now we've got these three unhide and we can kind of see them on a side by side basis, which is something that it's a little bit more difficult to do if you were jumping back and forth from tab to tab. Although you could do a tab by tab jump back on here if you're going to use it like if you're going to calculate this on software. But what you also can do in Excel is to make these into a year by year breakout, which could help you with what you feel like your equity might be from year to year as well as your interest. So I'm going to do that on a side by side basis. So I'm going to first I'm going to hide some cells to the right to the to the right of this one and we'll break it out on on just the equity. So I'm going to put my cursor on O and I'm going to scroll over to this side to AB right click and hide. And so now we're here. So now what I'm going to do is I'm going to just try to break this out in a year by year breakout. So I'm going to I need another skinny in the AC. So I'm going to put my skinny here skinny H home tab clipboards paint it and skinny AC skinny. You can't even see the AC because the ASCII doesn't fit in the skinny because it's so skinny. But that's OK. And so then what we're going to do is take the same headers. These headers right here. Let's take those. I'm going to take those and then I'm going to delete. I'm going to delete the months. We don't need the months. Now we'll do this a couple different ways. I'll do it with a pivot table and we'll do it with formulas. So we're going to delete this and we'll just make a few of these on a side by side basis. So I need years from year one to and bring it on down to this one's. What was the first one? It was like 15 years 15 years fitting 15 15 fitting 15 fitting. OK, pronunciation, pronunciation, the loan balance. So then what I'm going to do is I'm going to say some if calculations. Then this is our some if calculations equals the sum. We would like you to some if and then brackets the range criteria. I want you to look inside this range. I'm going to select the whole column. And so be careful if there was something underneath it. You would want to not select the whole column but just the actual range. But I'm going to select the whole column because it's easier. And then comma and then we've got the criteria. The criteria is this one. So I'm going to say if you find this one in that column, then comma some the related range, which is the payment range. This range right there where my home is my home's on that range my home's on that range home on the range. And then we're going to copy that down. And so that that looks good. That looks good. I could have done that by just multiplying the payment out times 12 though. But I'm going to do it over here with the interest where she gets more interesting. So I'm going to say some it if some if brackets the range. We want you to take a look at that range. I range and then comma and then the criteria is that one again and then comma. So if you see that one in that area, then sum up the related item in this range, the interest range where my home is my home's on the interest range. Home on the range. And then I'm going to copy that down. And then so then if I sum these down to check it double check. There's the 10 7 19 amazing. Amazing. Let's do it again equals the sum if and then brackets the range the I range and then comma. And then the criteria is that one and then comma and then the sum range is now the loan decrease or principal decrease, whatever you want to call it. There it is. And if I if I add these up to check it double time double checking 6843 there it is. Now you could do this a little bit easier. Let's do it one more time by copying this across until you're going to delete it after all that work. It's okay because I'm going to do it faster this time. So I'm going to copy this across this one this I when I copy it to the right. I don't want this range to move. So I'm going to f for it f for making an absolute dollar signs the interest range or this one is the payment range. I do want that one to the move to the right. So I'm not going to do any f for stuff on actually know this one is the criteria that criteria I wanted to move down. This is the tricky mixed reference but I don't want it to move to the right. So that means that I'm going to put a dollar sign here but not there. It's not absolute but mixed. That's where the fanciness comes in. That means you could copy it to the right and down. And then on the this range I want that to move to the right to L next time. So I'll leave that as is so I could copy it down. It looks like it's doing the right thing. I could copy it to the right not to the loan balance but it looks like it's doing the right thing. It's doing the right thing. That's what we do here. We do the right thing. That's what we do. I'm always trying to do the right thing. That's what they that's what I that's how I was taught. So there we go. So now we're going to say there it is. That looks good. Okay. So now let's do the minimum loan balance here. This is going to be equal. This one's a little bit different. We want to take the minimum balance. So the minimum balance equals the men if little bit different on the on the criteria ordering here but we're just going to take the men range which is going to be the men. The men range which is this one first and then comma and then it wants the criteria range which is going to be this one and then comma and then it wants the criteria which is this one. So same kind of thing but they a little bit different ordering on there. And so that took the lowest one which is right there. I think I was right. I didn't really read it but I'm pretty sure it was right. And so then I'm going to copy it down with the fill button fill button. So there we go. Now you could also do that same thing with a pivot table which is a little faster. There's pros and cons to it. Notice that I can't pick up these two things for the header because I got two rows. That's the problem with with having these two rows and a header instead of wrapping it. So there's pros and cons of that. So I'm just going to use this as the header. That's okay. Copy that all the way down. I'm just going to do a pivot table this time pivot table. Same thing different way different way. And I'm going to put that right underneath here. So I'm going to say insert a pivot table pivot table. And I'm going to put it in the existing area. I'm going to put it right there. That's where I want it. Let's put it. Let's put it down one. I thought she wanted it. No, I want it. I want it there. So I'm going to say okay. And then I'm going to add my criteria the year. I got to pull this to the left pull that to the left. And then the other I don't want the months payment interest decrease. There we go. But now it's formatted ugly. That's so that's so messy looking. So what we do is we fix it up. We go into each of these. I'm going to hit the drop down value. Let's number format and make that currency brackets. Remove the dollar sign and decimals and okay and way better way better. Do it again. Do it. Do it again. Do it for the next one. So that one's not ugly either. So we're going to make brackets red and get rid of the decimals on that one. So much better. Okay. Two more times. The last one's a little bit tricky. A little bit more trickier. So we're going to say just doing the same thing here. Ultra vase. Ultra vase. Lo mismo cosa. And lastly this one. This one's the tricky one. We want to make that a min. Not a sum. A min. Not a sum. And then the number format. This part's the same. Lo mismo. And we're going to say get those. Get that out of here. And there we got it. So they're good. I'm going to skinny up the columns a bit. Skinning them up. Skinning up. Now these notice that these down here. Are rounded so so you know I could wrap the text. Now I might want a total column. The reason I did this is I might want like a total down here. We've got the totals right. So that gives us the grand total of the payments and the. And the interest and the loan balance. So that we could do that here. We could do that total here if we wanted to. Summing this up. It's not like we did. It's not like we. Couldn't do that here and then just copy it across. So that could be useful. A useful tool. And let's make this blue and bordered. So there we have it. So that's something you can't really see on the other. On the other. You know if you do it over here quite as easily. And we can update these now let's do it. Let's do the other ones for the other table. So I'm going to do it again. I'm going to unhide these cells. I'm going to put my cursor from N to 80. Nad. Right click my.  No one cares about your car. I love that car. It was a Volkswagen bug. I just told you no one cares. Okay. So now we're going to hide from the. On over. To a H. Right click and hide. And then we'll hide. Do I need to hide these? I don't need to hide that. I'll just keep it right here. We just need to add a skinny. I'm going to do this faster. We're running just going way long. This is way long time frame. Let's go to the O here. I'm going to copy the skinny O and put that on the AI. The AI now it's just an A because you can't see the eye. And then I'm going to take the headers. We're going to put that up top copying and pasting. I'm going to get rid of the months because I don't need the months on this one. Months are not what we're looking at here. Get rid of it. Years are going from one. How many years was it again? 30. This is the long one. This is the long one. So here we go. One, two, that gives us R. And then I'll take the fill handle and I'll get a good grip on that handle with my pointer finger. And I'll drag it down. Whoa, that's way to sick. I'm not going 360. I'm just going down to 30. Don't get carried away. Don't get carried away. All right. So then we're going to go to alignment and center. And then we'll do the same thing here. So we're going to do some if equals to some if summit. If I'll tell you, I'll tell you when you sum it. This is how it works. You're going to take this range right there, the P range and then comma, the criteria is one. If you see ones in there, then comma, you're going to sum up some range, which is the payment range. That's what I want you to do. And so let's let's actually copy this across. So how can I copy it across the PP? I don't want that to move. So I'm going to say F4 on the keyboard. This one's the tricky one. I need the mixed reference that one. I don't want it to move to the right. I wanted to move down though. So I got to put a dollar sign before the lettering, but not before the number. That's the trickiness. And then the RR is the resting and relaxation. You can just you can just sit there resting relaxation RR and then enter. So then we're going to say copy this to the right. Does it still work? Does it do what it's supposed to do? It does. It does do what it's supposed to do just the way we had planned that it would do what it was supposed to. How ironic. I'm going to copy that down with a fill button. So I think that works. And then we got the slightly different calculation equals the sum. Now this is the men if the men if and that one's for the last one where we're going to take. We're going to take this time the men range men range. There's men on the range and then comma. And then we've got the criteria criteria range, which is this one and then comma. And then we got the criteria, which is that number one right there. Boom. Bam. And there it is. Let's copy that down. So that's the men 20 to 20, which should tie out to the 227 35. Let's put a total down here this time. Total sum it up. Sum it up. Little darling. It's been okay. Stop. This one doesn't need to be some that doesn't make any sense. And then we'll make that blue and bordered home tab font group border blue, border blue, border blue. Let's make a pivot table out of it. Same thing. I can't copy the header up here just from here on down from there down. And we'll just construct a pivot table just like we did last time, which is doing the same thing in a different format. So you can choose whichever one's best for use, choose what's best for use. And so I'm going to say insert pivot. And then we're going to put that in an existing worksheet right there, right there. That's where we want it. I'm not changing around this time. I know where I want it. I know. And then I'm going to pull this to the left. I know where I'm, I know what I'm doing. So we're going to then adjust the formatting on these same kind of layout. Let's just adjust the formatting number format. And we want currency brackets. None. Decimals gone. Boom. Bam. Better. Boom. Bam. Better it is. And then do that here. Format. Currency. Brackets. Dollar sign gone. Decimal down down. Boom. Bam. Better. And again. Again. Do it again. We're going to say currency brackets. Dollar sign gone. Decimal down down. Boom. Bam. Better. Lastly we got the bit of a tricky one down here. We need the men. Then the number. And then currency brackets. Dollar sign gone. Down. Down. Decimal. Okay. Okay. And we have it completed. I'm going to make it skinnier. So there's another way. We've basically did the same thing in another format so we can see a side by side now between these two. We could do a difference if we wanted to on a year by year breakout between the two scenarios for interest in the loan decrease and so on. And then let's do it one more time. Uno, vase, moss, pour, favor. I'm going to unhide. I'm not sure where I need to unhide. So I'm just going to select the whole thing and unhide. One more round. Why? Because I didn't hear no bell. I didn't hear. I only stop when bell when there's like a bell that happens.  So then on this last one we're going to do the same thing. So I'm going to I'm going to hide the stuff to the right again. Hiding to the right to a in right click and hide. And then we'll do this one more one more round. This skinny right there skinny V. Home tab clipboard paintbrush it and the skinny AO. And then I'm going to copy the headers again, paste that up top. We're running long on the time. We're going to speed this up but not but do it precisely. So precisely and accurately and and fastly but not too fast. So people get upset. So this is going to be years one, two. We're going to this one is going to be going down to 20 years. 20 years you'll recall. So we're going to take that on down to 20. Don't get carried away. We're not doing an amortization table. We're just going down to 20. Just going down to 20. So we're going to go home tab and then alignment and center payments then are going to be. So we've got some if and then brackets. We're going to take the range which is going to be this range. I'm going to select all of W.  The criteria is going to be that number one. That's the tricky one. I want to make a mixed reference because I want it not to move to the right dollars on before the letters. But I do want to move down at no dollars on before the number comma and then the sum range in this case is going to be the payments. And so that and we don't need an absolute reference on the payments. Why why you might ask we don't need one because we're going to we want that to move to the right. So I'm going to say enter. And so there we got it. If I move that to the right and copy it over then looks good looks good. We can copy that down selecting these double clicking on the fill button and then the loan the loan is going to be equal to the men. If men if it's with an S and then the men range is going to be this one a B comma the men criteria range is going to be over here on the years and then comma and then the criteria is going to be the one again enter. Let's copy it down with the fill button fill handle button and then total it down here total and sum up total it and some it. Total some total some copied across this is going way long. I don't need a total over here that don't make no sense.  So I'm going to go home tab font group brackets and blue. Let's make our make our our our pivot table now do it fast because you're this is taken too long people got things to do. And you're expected them to go through this. We already did this. I know how to do it. So let's take this whole thing and go to the insert pivot table and then existing and we'll put that right there. That's where we want it and OK. I'm going to take the years down copy that to the left and then payment interest decrease balance. And then we're going to format this thing format the values number formatting currency brackets dollar sign gone decimal down down OK OK. Next one value field number format currency brackets dollar sign down down down decimal OK. Next one value field number currency brackets dollar sign gone down down decimal OK OK. One more time but a little bit more tricky on the last one because we don't want the sum we want them in number formatting currency brackets dollar sign gone down down decimal OK OK. So I think I got this everything correctly. I'm going to make a little more skinny skinny up top weight. Now I made that one wide. I don't want to make that wide. I want to make these skinny. That's the opposite thing. OK. So now I'm going to unhide everything unhide everything right click and unhide. And so now you can see this one's to do. I don't need this down here. So now you can see now you got these side by side kind of things which you can't. So now I can adjust the data over here on a side by side scenario. I could see the side by side in terms of the amortization tables and possibly more useful for longer projections. I could see the side by side and make these little skin here on a year by year breakout and I might even then get more complex and look at the differences make another column taking out the differences of each scenario on a year by year. Possibly then doing projections for taxes and you know what the equity value is going to be and so on. Given that information so you could do that once you get it set up. It's a lot more information that you could pull and run scenarios than just using the online table. It's easy to do the online table quickly but then you can't really tie it into anything else. You're always kind of bouncing back and forth to all these different resources and then trying to tie them together. If you can network your worksheets together for whatever you're working on in such a way that once it's set up you can just change your data and then do your side by side comparisons look at different scenarios that way. That's the better way to go in the long run typically.


My session today is going to be about delivering intelligent content using Drupal. One of the questions that we've been trying to answer for ourselves at our organization has been, how do we bridge the new technologies that are available for us and give more value to our customers? So before I get started with the session, I'll just introduce myself. I'm Shyamala. I'm co-founder of Unimity Solutions, and I'm also on the board of the Drupal Association as the community elected representative. Our organization, Unimity Solutions, is in Chennai, down south in India. We've over 10 plus years of experience in Drupal. We've started using Drupal with one of our largest media sites down there in India. And since I've been delivering a lot of enterprise solutions using Drupal. So before I get into actually answering the question of delivering intelligence, I just want to start with a short story. And this is a story of a Chinese philosopher, and he was having a chat with his disciple. He was actually showing his disciple a set of pots. He showed his disciple a clay pot. He then showed him a brass pot, which had very intricate designs in it, and a golden pot with gems embedded in it. And the question that he asked his disciple was, which aspect of the pot do you think is most valuable? So I just want to pose that question back to you. Any thoughts on which aspect do you think of the pot is the most valuable? Any thoughts? So, I mean, is it the color? Is it the shape? Is it the size? Is it the design? What makes it, what aspect of the pot is valuable? And of course, the student answered, saying that the golden pot was most valuable. The philosopher said that the value of the pot was in its emptiness. So it isn't the size, shape, or the design, but the value of the pot itself is in its emptiness. Coming back to content, enterprises have large amount of content that's already existing in the enterprise. Large amount of PDFs, words, documents, PPTs could be testimonials, client testimonials, could be blogs that are written, maybe real-life case studies. There is a voluminous amount of content that is available in the enterprise. Which aspect of this content is most valuable to the enterprise? And how do we make this content valuable? The value of the content itself is only in its consumption. So we need to make sure that people are using it. Is this content getting consumed? So the usefulness of content is in its consumption and we need to build different layers of intelligence to the content so that we can make this content consumable. So just, I think, like the philosopher said, a pot is useful in its emptiness. We need to correlate it that for us, the usefulness of content is in its consumption. I wanna get started with first defining what is content intelligence. And here, I just wanna segregate content intelligence to two parts. One is assigned content intelligence and another is acquired content intelligence. So if you see assigned intelligence, this is typically, I would say, you could classify it into the metadata, the keywords, the various attributes that we add to make our content structured, maybe even the relationships that we bring in. If you look at a blog, you have the author for the blog and the tags. So it's the structure that we define when we create the content, becomes part of the assigned content intelligence. The other part, the acquired content intelligence, this is more related to what is the value that gets added to the content as the content gets consumed. As we use this content, as our users start using this content, what's the value that gets acquired to this content as acquired intelligence? Here, this is typically probably the statistics in the number of times the content was downloaded or viewed. It could also be pieces like comments and reviews where the user interacted with the content to post saying that the piece of information was very useful to them. Today, there are far greater avenues in capturing the interactions and the intelligence that are available with the content. I'm gonna just, in the next couple of slides, just get into a little bit more detailed, starting with the assigned content intelligence. Here again, with the new technologies that are available to us, we can go beyond just the metadata and content. We have, we can come up with processes where we automate some of this classification and meta tag that gets created with the content. There are tools that are available where your images and videos could be further classified using these AI and machine learning tools. We can also integrate with translation and transcription services at the time of content creation and have the content translated in different languages and the videos transcribed. In the acquired intelligence, here, we have an opportunity to, at every time, the user interacts with a piece of content and when he actually consumes it, maybe we could call it a session. Every time that a user interacts, we have an opportunity to identify who consumed it, further define the profile of the user who consumes it, the attributes, his social attributes as well, and when this content is getting consumed. What's the context in which it gets consumed? Was it in the morning or in the evening? So you have an opportunity to identify when the content was consumed. The other dimension is how, was it in a device? How long did he spend on it? Attributes around how he consumed could also include the interactions he had with the content, the purpose for which he reached out to the content. Another dimension could be the sequence, as in what was the content that he see, did he see before and after?  So if you see at the end of each interaction with the content, we have the capability to identify multiple dimensions of the user and capture these as analytics. And if we run machine learning on top of this, there is a capability for us to then come up with recommendations which are far more real. That we've kind of understood what is content intelligence and how content intelligence gets classified as assigned and acquired intelligence. We move into understanding how can we maximize content consumption using this content intelligence. So this is our goal, is to see how can we make content consumable and how are we going to utilize this content intelligence that we have built in to maximize consumption. So making content consumable would mean, am I speaking correctly? Okay, so making content consumable, the user could interact with the content in two ways. One is he comes seeking for the content where he's actually looking for the content, he's either searching or he's on a page which he came through search or through a link that he received on his email. The second piece is when we push the content to him, we stimulate him to come to our content. So these are broadly the two ways in which we can reach out to a user or have the user land up in a content. And in both scenarios, when the user lands up in a content, we have the capability to customize the content based on the user's profile. We could make it presented in a language that he can understand through up certain sections of the content that are related to his profile and his personal needs. And there could be certain sections which we customize based on his needs. The second case where we stimulate content, where we push content either as text messages or as mobile notifications. Here again, understanding the user's profile, the way he interacts with our system, we have then the capability to actually throw up to him contextual content that is most relevant to him and we can do this real time. Of course, providing a consistent experience across the different channels in which we interact with him will further help us maximize content consumption. So I think kind of the main idea that I wanted to bring is how by building this intelligence to the content, we can then get greater value to our content and make it consumable. So what's the key difference between content intelligence itself is not entirely new. We've been trying to do this in multiple ways. We started earlier with probably creating meta tags indices. But the key differential today and the key power that we have today with AI and machine learning is that this is no longer programmatic. There are no predefined rules that we set to build this intelligence. We today have the capability to actually learn and with learning what happens is that these recommendations closely mimic what the user would require. So we are able to real time capture these interactions and come up with recommendations that are far greater and far more pertaining to the user's needs. Just want to, this is definitely a topic that is much in renaissance. Here is a quote by the Amazon CEO where he says that some of these problems in machine learning and AI is almost like it was science fiction. And suddenly today it is real and we're actually trying to identify how people interact with the content and try to mimic user behavior and understand user behavior. So just at this juncture, just wanted to understand if any of you had any specific scenarios where you have used AI with content that you would like to share. Okay, excellent. Chatbots along with Drupal content, okay. And this was for a customer experience, customer, what was the use case that you were trying to solve? Okay, okay. And anybody else who've used AI with content or Drupal? So some of the examples that I just wanted to bring to the table. Of course, shopping is a large area where there is a lot of opportunity for us to throw up real time relevant recommendations. Here I just wanted to take a shopper who's actually looking for probably, he's just purchased an iPhone. Typically when the shopper buys a particular product in our traditional shopping experience a couple of years back, we used to throw up related products and these could be probably either other phones or other gadgets that would play with your iPhone and probably a case or a head, your piece or anything that is additional to the iPhone that would add value to the customer. But today what we have is that a capability to gather data which is far beyond and supposing there is a user from Washington DC and he is actually shopping for an iPhone, we can actually present to him waterproof essentials because there are suddenly a surge in the number of people from DC who are purchasing waterproof essentials because of a thunderstorm that's happening there. And this is not something we need to program into the system. The system can automatically pick this up based on the learning that it does. It identifies that there is a surge in a certain type, there is a demand for a certain type of product in a certain location and it automatically throws this up as a real time, very contextual recommendation to the user. So which is just an example of how we could, which illustrates the difference between how we traditionally did recommendations and how we have the power to do recommendations today. Today at Unimity we are working with one of our largest newspaper companies where they have about close to 35 publications online. We're using what's called a universal recommender, which runs on the analytics that is getting collected in the back and using an Oracle system to throw up recommendations. And this machine learning tool has a capability to ingest many number of actions, events, profile data, contextual information and then in just all this to come up with recommendations, the power that this brings is that for a organization with 35 plus newspaper is not just recommendations within a particular newspaper portal, but actually across their platforms, they are able to cross pollinate content between their portals. The second example that I wanted to showcase here as a good use case of how we can use content intelligence today, is in using natural language processing to classify content. Project Feels Initiative is initiated by NY Times where they classify, they parse content and classify them into different emotions and they call or use what's called as perspective targeting, where they are able to throw up ads to users based on the emotion the particular article is supposed to evoke. And this emotions is dynamically built using natural language processing. Another use case is translation, where we have all the large cloud players like Google, Microsoft, Amazon, all of them having services for us, which uses machine learning in the back end and deep learning and machine learning techniques, which help us to, without having the inbuilt expertise in our teams, we can just plug into some of these cloud services to bring these capabilities. One of the examples is DB Corp, which is a very large publishing company in India, which used the Google Translations APIs to translate their interviews and publications. And they had 95% they had a 95% good quality translation into the Indian language Hindi. Amazon also provides a translation service and hotel.com, they have close to about 34 different portals and I think 34 languages, 85 websites and close to 350,000 hotels that are registered. It gives them a clear hedge edge when they serve across their 20,000 locations when they are able to personalize the hotels into different languages. So in all these cases, if you note, I just want to bring back to say that whether it was the recommendation, whether it is targeting of ads based on emotions or in the translation AI tools that are available to us, we are adding a layer of intelligence to the content to make sure that this content is getting consumed by the user. There is a more likelihood of the user consuming our content. So I'm just actually going to conclude the session with just a short note on, now that we've understood how what is content intelligence and what are the layers and how it's some examples of how it's getting utilized. What is it that we need to do to make sure that we can then deliver this content intelligence jointly with our clients? So I think it's important for us to understand this is not something that we can solve just by plugging in an AI tool into our system. It's not like just plugging in an Apache solar and then you have search ready. It's very important that we understand the business that our customers serve, the different points at which our customers can interact with their customers. Nike is a very good example. They have a Nike Plus app that is for runners, which helps them to track running history. They give content that helps the runners to stay motivated, train them better. And this app is a good example of how gamification and digital can help better connect with not just your customer. And in this product that Nike brought in, they not only connected with their existing customers, but they had an opportunity to connect with also their new customers. And so what this means is while we try to deliver this, it's important that we also jointly identify with our businesses. What are these additional touch points at which we can better connect, gather data about our customers and then better serve them. So here in Nike's case, they were actually not just selling, they were trying to help people reach their goals better with the products that they purchased by creating this running app. So in the how do we achieve, it's important we jointly understand and connect better with our customer's customer. We have like a unified analytics. We have a unified content publishing system where we can create ones and publish everywhere. It's important that we work with our businesses to understand the specific use cases where we can learn and create intelligence and of course create a unified experience. So how does Drupal help us do this? And here is where we can leverage Drupal's innate capabilities in the content space, increased emphasis and increased features that we are having in the content authoring space where content creation is getting better. Workflow and auditing, which is very important piece for us as we serve the enterprises. Structured content that is possible for us to create and this structured content is what we can use in creating the assigned intelligence. The interoperability of Drupal, the capability for us to for it to interact with the many systems helps us to integrate with AI and machine learning tools and the API first initiative, where it allows us to deliver to the mobile and the other, not just the mobile and the web, but also the other devices or channels in which we wanna reach our customers. Last but not the least, it's important that our applications are secure, scalable and agile. So with all this, we're then all ready to deliver content that gets consumable by building not just intelligence while we create the content, but we constantly acquire and make the content contextual, real time and relevant for our consumers and make content more consumable. That's it, thank you. Thank you for listening in and just wanna finish my session to say please, those of you who've stayed back to Thursday, I know there's always a, the first day has the maximum number of attendees and then it becomes half and maybe, maybe even less than one fourth of the last day. But the most exciting part of Drupal is the contribution spins that happen tomorrow. So any of you can contribute, please join the contribution spins tomorrow. And just wanna conclude that please share your feedback on the DrupalCon, the link that I've shared here and happy to take questions. Thank you. Yeah, sure. Do you have an example of a way that content was delivered in a personal way across different devices? Like a company that's done this and what it's meant for them? So in our case, the example across devices, I don't have one right away, but in our case, it was only across their different properties, the 35 different newspaper publications, they were able to give a consistent experience. Yeah. I guess some example of the cross-device personalization is many of the big players, I think Amazon, BeatAmazon or Google. I use Google's assistant and the tools for news reading. They give you a personalized experience across the devices. So irrespective of what I'm shopping on Amazon, on my website or on my mobile phone, there's definitely a continuity of experience. And they're also able to personalize it for me based on where I am and some of my past transactions. Shopping is where I think a lot of AI has been implemented. Though financial sector, they are, I know of couple of projects that we personally wrote proposals for in the financial sector in India, where we wanted to bring in AI and experiences where it can be shared across devices. Do you wanna come up here and share? I don't know how relevant this will be, but so we are currently doing an Alexa integration with Drupal and there, this is also related to shopping. So the way Alexa is connected to Drupal commerce, you have it on your phone, you have it on the laptop and you just tell Alexa to do things and then she adds products to your cart and it's just consistent across the devices which have the same set of base as an integration-wise, which are all consistent.  When you, for example, I wanna add four red wine to the cart, it might just ask, or if I say 10,000 red wines to the cart, it might just remind me, are you really sure you wanna add 10,000 red wines to the cart? And that kind of an experience it gives across the devices, consistency-wise, plus it's smart enough to tell you that you might be making a mistake. Okay, thank you. Any other questions? So thank you very much for being in here. Once again, just encourage you to submit your feedback online. Thank you.


GitLab provides scan result policies, enabling security teams a way to enforce separation of duties and ensure that vulnerable code is reviewed before it makes it into production. A scan result policy can be set to require approval based on the findings of one or more security scans jobs. Scan result policies are evaluated after security scans have completed. Now, let's create a scan result policy. We go to the security and compliance tab and click on policies. From here, we'll click on a new policy. Within the dropdown of policy type, we'll go ahead and select the scan result. Here we see YAML mode, which allows us to create a policy using a YAML. However, we're going to go ahead and go to rule mode, which provides a web UI, which makes it easier to create a policy. We'll provide the policy with a name as well as a description. Here I am creating a policy, which will require approval if any severity of SAST vulnerabilities is detected within the main branch. I'm going to go ahead and check the policy status to on, meaning that it will be active in our project and in the rules, I am going to select SAST as the scanner. So if a SAST scan in an open merge request targeting the main branch finds one or more vulnerabilities of any type that are newly detected, then we're going to go ahead and require approval. Here we can add who we require approval from. I'm going to go ahead and put Sam White as an approver, and I'm also going to add a group. I'm going to pick the analysis backend team. We'll require an approval either from Sam White or any member from the group if any SAST vulnerability is detected. We can see how the YAML was configured via the UI and I'll click on create merge request. And you'll see that a new merge request has been created in a new project. This new project is created to ensure separation of duties because it provides different access levels than the original project. Now, I'll go ahead and merge this. When going back to our project, we can go ahead and go back to policies. And when we click on edit project policy, we'll see that the policies are being grabbed from the newly created security policy project. Now, let's see this in action. I'm going to go to my merge requests and here is a merge request I have created to add a new file with global permissions which presents a vulnerability. You can see here one approval from the SAST approval policy is required to merge the code. And there is Sam White as well as members of the composition analysis team. Approval is required because SAST vulnerabilities were detected. Security approvals enable separation of duties and add additional security controls to ensure insecure code does not make it into production.


No? Here? OK. I feel like in a TV show now. OK. OK. We are Nadia and Camila. We are from Argentina. And we are talking about our experience in copper producing hydroclimatic knowledge in Argentina. I will present one project in which we are both involved, and then Cami is going to show another one. Both have things in common, but they're quite different. So we wanted to show you both. The first one is called, it's a project called Anticipating the Flat, in which we develop and apply a methodology to improve the understanding of flats at the Matanza River basin, which is the rural and urban sub-basin of La Plata basin, located in Buenos Aires. At the east of Argentina, where more than 7 million people live. In particular, there are between 1,000 and 10,000 people with high socioeconomic vulnerability, usually evacuated during flats, that can occur two to seven times a year. And they can be evacuated during five to 14 days. So it's a huge problem there. And the conceptual framework that we use is a copper production of knowledge framework, in which we as methodologists are working with oceanographers and hydraulic engineers, but also with anthropologists and geographers. So it's an interdisciplinary framework there. And we also incorporate local actors and government actors. So it turns out to be a copper production of knowledge framework. We build a space of permanent dialogue. This is super important, the permanent dialogue between the scientific and technological sector, institutions and local actors, and integrate the notion of climate risk jointly, which generates early warning systems knowledge and favors its appropriation from the local community. So, oh, sorry. So we are working with social organizations, local government delegations, schools, and community. We create a symmetrical dialogue between the scientific sector and the community. We also create a symmetrical integration of local and scientific knowledge. And we co-design a community early warning system. How do we do that? We have many activities that we develop there. Some of them are walks in flat zones with neighborhoods, local governments, students, and school teachers. We have some pictures of that. It's this one, but there are plenty of them. Then we construct flood risk mappings or maps with local community. That is what we are doing here in this photograph. Then we give some workshops to understand official sources of hydro-meteorological information through its exploration and use. And it's this photograph of here. And we also construct a monitoring network of rain and river level with community rain gouges and hydrometric rulers. Here we are installing a ruler. And here there is one rain gouge being installed in a school. And we design a digital community network to socialize all this information using a WhatsApp group. So that's the idea of anticipating the flood. And then Kami is going to talk about this other project. OK. And I tell you about the Climax Project, Climax Services Through Knowledge Co-production, which has all these institutions involved, government institutions, climate and national services, native births, communities, and a rural school. The next one. The region involved in this process is the Bermejo Department, a rural area located in the Grand Chaco wetland region in northern Argentina. It's an alluvial plain area with tributaries of the Paraná River affected by floods and droughts. This project, beginning in 2016, with the financial support of the Belmont Forum and JPI Climate, aims to underpin climate services in South America to develop innovative monitoring and prediction tools of regional climate and to co-produce climate-related knowledge of relevance for agriculture in an interdisciplinary and intersectoral way. So who are participating in this process? Climatologists, anthropologists, small farmers, teachers and students of a rural school, agents of state agricultural institutions. The theoretical framework of the project is the Implicated Science Approach, which consists in two premises. The first one is to establish communication between actors to recognize different points of view regarding a topic and distinguished coincidences and discrepancies between them. And the second one is to apply symmetry of the various knowledge on a subject to validate all points of view about the world, even if this implies contradictions. So a key point of the process was started with an ethnographic fieldwork by anthropologists in Bermejo in order to get to know the place and to generate truly relationships with local people. That allowed us to identify the most important worries of the people. For example, the nearest official rain gorge in south of Bermejo, you can show the, no, yes. Well, the nearest official rain gorge measurements were not representative of the rain that they experience in the department on the north. So we started to development precipitation, community monitoring network. After that, local people also showed their interest in hydrological monitoring. And until this moment, there are 22 pluviumeters and eight hydrometric rules in that area. These were strategically located in easily accessible places designated by the local community. Various workshops and meetings were held among the actors to devise possible monitoring strategies and systematized measurements and disseminating information to the population of Bermejo. Through social networks like WhatsApp, the social actors shared their observation and the impacts associated with all types of precipitation events and overflowed river events. And another kind of activity was a mapping activity with focus on the movement of the water. For example, small farmers identified the location of their houses, their stockyards, and other sites of interest. And they wanted to where the water reached in specific hydric extreme events. And also where flood occurred because of the rain or because of the rise of the main rivers. So some conclusions. Yes. Yeah. We have some conclusions now, but there are many. First, there are many co-production frameworks. And choosing one depends on the region and the problem. But if social scientists are involved, it is easier to choose them correctly. So we want to highlight the importance of having anthropologists in our groups. And also this kind of process allow local actors to appropriate the knowledge co-produced. Generating local community monitoring networks turned out to be a good strategy for risk knowledge and then reduction in both projects. And then this is quite important co-production approaches take long. Both projects started more than five years ago, and they are still in progress. So yes, we have been there for four years or something like that working on this project. And we don't have many papers published in this topic. So maybe the way in which the science is evaluated not well applied to this kind of processes that really takes long and a lot of work that can really have impact on society and on risk management and production. So yeah, that's it. Thank you.


I'm excited to be a guest host. This is gonna be a terrific show. So like the governor said, we're gonna go for an hour, discussed a lot of the people who shaped modern Hawaii and we're gonna talk about them as heroes, some rastals and some duds.


Deepcool is bringing displays to air coolers and they are impressive. The display seamlessly integrates into the top portion of the cooler and the slight RGB is a nice touch of color. Not too much to detract from the sleek black of most of the unit. These will be available by next month April.


Are you living for the weekend? Honestly, answer that question. Do you feel like day in, day out, every single week that you are just living to get to the weekend? Are you more excited about Friday than you are about Monday? I hear this phrase all the time. I'm just, I can't wait till Friday gets here. I'm just living for the weekend. If you live your life just wanting to get to the weekend, then you are wasting 72% of your waking days, your life on this planet. 72% of it is wasted Monday through Friday if you're just working to get to the weekends. If all that you're excited about, the only time when you're really, truly happy is during the weekend, then you are wasting 72% of your life. What about right now? What about this very second? I'm recording this on a Tuesday, right? Let's say that I'm just a person who just hates working during the week. Well, then what about now? Why am I waiting for Friday and Saturday and Sunday? What about this very second? What are you doing right now? What do you love to do? What do you absolutely love to do? And what can you do right now to get more of that in your life? Answer that question real quick. Think about it. What do you absolutely love to do? And what can you do to get more of it in your life? Whether that's spending time with your kids, spending time with your significant other, traveling, skiing, surfing, going on road trips, all of these different things. What do you love to do and what can you do to set yourself up to have more of it in your life? Think about that for a second. You owe it to yourself to figure out a way to get more of what you love into your weekdays.  Quit it. Do something that you love. Do you wanna start your own company? Well, if you have a job right now, why don't you work at night and on the weekends to build it and build something so that you can eventually replace your income at the job that you hate so you can wake up every single day and love what you do? I used to work for a company. Now I work for myself. I love every single day. I am excited. This is not some BS. I'm excited for Mondays. I'm excited about it because I get to go back and actually start working and doing what I'm passionate about. That's what I hope for you. I hope that you can get to that point. What makes you feel alive? What do you love to do? What makes you feel alive? And then consider this. What if you could do that for the rest of your life? Isn't that what it's about? Isn't that the reason why we're here? So that you can love and appreciate everything that you do? Monday through Friday, workdays, 40 hour workdays, those are arbitrary numbers and arbitrary days made up by people just years ago in the same society that you're growing up in. How can you find a way right now to start working towards doing what you wanna do day in and day out? I made in 2005, the beginning of 2005 in January, I put my goal was to start making income at my own company so that I could leave the job that I was at. 11 months later, I left the job that I was at and I was doing what I wanted to do when I was creating my own income and the reason why I wanted to create my own company was because I personally wanted to do something I was passionate about and that I could help people while doing and that I could travel while doing it as well. I'm excited to tell you something real quick. I'm gonna be moving to Rome with my girlfriend for six months because that is what I wanted to do. We're leaving in June to go to Rome for six months and then travel around the rest of Europe. I don't say that to brag. I say that because I'm nobody special. I'm just somebody who decided what they want, what they're passionate about, what they love to do and figured out how to get more of it in their life. In 2012, I quit my job and went to Europe for three months in backpack and I fell in love with it and I said, I wanted to move here and now it's coming to fruition. What can you do to do the same? Because I'm nobody special. You have the exact same opportunity in front of you. You have the exact same 24 hours that I do and every single other person does. What do you love to do? What are you passionate about? What makes you light up? What makes you feel alive and what can you do to get more of it in your life? That's a question you should ask yourself and it may be one of the most important questions you ask yourself because it could be the difference between you hating 72% of your life and going and working for somebody else and doing things you don't want to do, hating 72% of your life or loving 100% of it. Think about that and try to make a plan to start getting more of what you love to do in your day-to-day life. If you like this episode, please click the subscribe button and I hope that you have an amazing day.


Hi everybody, Joe for Jasper's case greats.com. Happy Tuesday. We've got some 2020 Do I have the right box? Yes 2020 panini immaculate football first off the line premium edition one box random team break number two One pack of box only six cards in here But a lot of first off the line FOTL first offline exclusives premium edition rookie patches emerald base Autographs could be numbered 14 or under so a lot of fun stuff here big Thanks everybody here for taking the risk on this High risk high reward randy with that last bottom mojo all 32 teams in let's roll it Let's randomize it five and a one six times for names and teams one two three four Five and a one six in the final time We got Marshall down to keel Five and a one six times for the teams one two three four Five and a one sixth and final time after six. We got the pat riots all the way down to the Leons Football is in the air folks mini camps well underway Preseason games are gonna be happening soon week one football before you know it Crazy I'm ready for it Marshall With the Patriots Joshua with the Texans Michael best with the Niners Paul with the Cardinals Nicholas with the Broncos Daniel with the Chiefs Sean Oh with the Panthers Harry with the Saints Randy You got the Colts Allen with the Steelers keel with the Giants Sean Oh with the Bears Lucas with the Dolphins Allen with the Jags Sean M with the Falcons Andrew with the Bills Allen with the Jets Michael Robinson with the Vikings keel with the Browns Sean with the Packers Allen with the Chargers Aaron with the Cowboys Corey with the Raiders keel with the Titans Paul With the Buccaneers Allen with the Washington football team Roy with the Bengals Sean Oh with the Rams Allen with the Seahawks and the Bengals Andrew with the Ravens and last but not least kill with the Detroit Lions Let's sort alphabetically by team Here's the box right here first off the line premium edition 2020 immaculate football We're gonna pause the video while we come back. We're gonna see if there's any trades Then we'll have the break stick around Alright, welcome back everybody Little bit of trade chatter, but in the end no deals were done Here in immaculate football first off the line. I should put the date there on a Monday August 3rd, 2021 Thanks everybody for giving this a shot See what we got here. I've got a blockchain card on the bottom and it's a marks of greatness Tony dorsett Now Tony dorsett in my head is a cowboy Could he possibly be on other teams? When you play for dallas his entire career except for one year as a bronco This has got to be dallas And that blockchain digital card will go to erin and the dallas cowboys.  It's pretty cool though Rookie relic for the bangles. That's going to be for roi Kind of hard to see in the lighting at this time of day, but there's a slightly more charcoal gray right there Two colors. We've got a remarkable relic five out of 25 lamar jackson That'll be for andrew and the ravens and the top loaders want to hit the bell Our top loaders Our first autograph is joe thomas nice five out of 25 all-time greats on-card autograph for the browns keo lamb with that cleveland. This is for you Two more to go. We've got cooper cup nice two color patch And autograph silvery and auto auto on the eye black It's 49 out of 49 eye black jersey and auto for the ramaly Sean O'Leary with the rams And the last one excuse me Getting choked up over this hit here and finally Oh nice four out of 14 Three color patch and on-card autograph tea higgins nice Joe burrow is going to have a decent amount of weapons this year That is for Cincinnati roi with the bangles Nice since any bangles once again roi And there you go boys and girls That was 2020 immaculate football First off the line premium edition We've got another one box break in the store. Let's keep chasing the monster hits. I'm joe. I'll see you next time for the next break. Bye. Bye