Greetings laddingtons and welcome back to good old lustria. They have just released another DLC to this absolute masterpiece of a game. So I thought to just make a short let's play video to showcase the Hunt's Marshals expedition and I do this because I believe this game to be one of the best games I've ever played and I do say that because it invokes a certain Certain feeling and it has a certain aesthetics, which are Beneficial to our great cause of becoming forces of nature. So if you see in the background here, you can see the Empire coming in with ships to colonize the new world and on the right side right hand side you see the Verdant unconquered lustria so it's a game that invokes the feeling of epicness heroism and and Adventure so I am a great fan of this game and that's also because I'm a great fan of Warhammer in general And then of course also whenever I make a let's play I get the comment. Why are you making? Gaming videos. Well, that's because I believe gaming to be an absolutely brilliant way to Portray culture and to partake in a story and to get some inspiration And of course as I always say if you do game if you're a gamer be sure to game in moderation and because and be short only game when you have Taking care of the business for the day so if you have been to the gym if you've done your other work you can Relax unwind a bit and there is absolutely not a single soul in the world who can do work 24 7 everyone needs downtime and I believe gaming to be a good way to have some downtime to relax to recharge your batteries, so Keep that in mind Anyway, we have in this particular DLC. We have Marcus Wolfhardt nice name, of course and we also have another Mad cunt, which is called Nikai the Wanderer Now we will play as Marcus in this DLC But I thought to show this absolute unit. Look how juicy he is. He has not been skipping Deadlift today as you can see on his So anyway back to The monstrous shall be slain so we have an initial challenge of hard Which is which is fine and then some different bonuses primarily to Ambushing and an upkeep for archers, so I will play on legendary And battle hard. I think that's a good a good mix for a challenging Gameplay and I'll see if I will make more episodes on this This is mostly to showcase the game and to show this new DLC so let's get in to the game itself The jungle continent of Lustria lies west across the great ocean The first men to land upon these shores ransacked an ancient temple Filling their ships with golden treasures Words spread of their wealth and others were eager to follow Fueled by greed Men of the Empire ventured deeper into the jungle's heart The land of beasts Ravaged and plundered for its riches It Will not be without Consequence the jungle stares a cold-blooded fury rising to punish the invaders In the temple cities of Lustria the lizard men enact a ritual To call upon their mighty guardian for the wanderer Rome's Lustria once more The spirit of the jungle made manifest Reckoning has come Only the strongest will survive the coming bloodshed So yes, that's exactly what I mean with the aesthetics and the Feel to the game. I don't know if you feel the same when watching stuff like this Maybe I'm biased because I've always been a great warhammer fan But I do believe if you can draw inspiration from this type of settings. It's It's definitely a great thing so Yeah, I will do Glorious session after recording this and it will probably be at some sort of outdoor gym and it will be then to perform a 100 chin-ups infested continent and plunder it for the treasures it holds The near unimaginable wealth of these lands is dispatched home through the coastal colonies But recent raids by the lizard beasts have set the Empire back And I expect further attacks other enemies loom nearby Savage orcs no less who raid nearby abandoned cities These ancient places are sure to harbor more riches. So our prime locations for colonization But we must be aware that the lizard beasts dominate these jungles for our colonies to survive their threat Reinforcements will be needed from home The time of opportunity is now Lusty around its dangers await Anything that stands before me in the hope of defeating the Empire will meet its end by my bow It is the Emperor's will All right, as I said peak optics peak aesthetics, and if you want to look at Yeah peak Aesthetics man you can look at the Emperor Karl of France In this game also. So anyway, let's see what the crack is. We have how they play and also when I say the crack It's an Irish saying. It's basically saying what's what's fun. What's going on or what's up? So the crack is that the Emperor's mandate sent to the shores of lustria by imperial mandate Marcus will fart intends to protect the new world colonies from their lustriant predators With only limited supplies and troop numbers as further Reinforcements will not arrive from the old world for quite some time Okay, but we can get more things if we Do glorious things The beasts of this land must be removed if our colonies are to flourish The first blow must be swift and lethal It is vital. We act quickly before these monsters can move against us All right, we need to remove these monsters we have very Drury and it's I think it might actually be a halfling a hobbit that particular gentleman All right, let's get into The game itself then we're gonna first and foremost which I usually do when I play this game Look at the diplomacy see if we can initiate trade with someone and we have all the Lisbon factions Do not like us in the least then we have some Norsemen The Sterexon of the cool he doesn't like us either Can't trade these guys We have New World Colonies Helmut Nussbacher and this is An imperial as well, so he will probably want to be our friends can see if we want to be in defensive alliance as well Huh, how about just a trade agreement? Nice now we have increased our Income as always a nice thing and then we have Vampire coasts Mutineers do you want to trade with me? We'll probably not but we can have a Non-aggression pact and what happens now is that the longer we have a treaty with these guys? The more likely it is that we can have a trade agreement later on So now that's done. We have increased our income just a bit and we're gonna see We have a little army and We have a I don't know exactly what might be a feral pastel on can be quite hard to deal with But we do have a good good setup here as well What is the most reasonable to do in my humble opinion is to? recruit some units and we'll go with a Archer's I suppose Dun dun dun because we have some infantry to hold the line and Since he had some bonuses for archers. We're gonna focus on that and then of course temple of Tlecan Let's see if we actually need this building We can't really build anything else. So I suppose that will have to be the first step And then the technology Queen here mass produced small ammunition so 10% plus ammunition for all of our ranged Ladding tons Then we have colonial library like the different And things here colonial factors hunting advances recruit rank plus two for all imperial supplies units can be good too and See bone logistics, right? So we have some Different things here that might be good Let's actually go with this one missiles. So we Come a bit better in in battle I suppose and then we'll take the turn see what happens in the next Turn here, maybe they will actually Attack us and we have a battle on our hand in this episode Yes, we do have a battle and yeah, let's get into it Let's get this done and Yeah, we have some Some archers one two units then we have a war wagon missile chariot Haven't seen this before. It's a new addition to the game. Then of course Marcus himself Will be nice to see in action all right, we are in the battle and We will start by deploying This mad cunts about there Including our gallant Marcus wolf heart Which will then hopefully bring the listen when coming up to face them Which means that we can have these shooting them in the flank and The Empire and yours. Let's have a look at this. Oh, that's that's quite cool aesthetic barding on the horses as well. So a war wagon full of Full of ladding tones ready to shoot And we'll just keep our infantry there, I suppose And boom, let's start the battle And See what this lizard men might bring to the table. So we have the feral Bastilla don't Bastilla don't say it. I suppose Which might be a problem? So we'll have to keep our spearmen to fight off that That unit We also have a focused shot, which is a magic missile. So we're gonna shoot this This monster with this special shot. See what happens Boom. All right. Yeah, that's good enough Right, so they are coming to watch our archers I have to pull them back so they don't get into melee combat that wouldn't be Good at all Now, let's see. Yes, that's good. So we're Slowly but surely getting the HP down upon this This unit maybe we can actually engage our spearmen to deal with it as well and Right, let's see what's happening here Get this away from combat as well and no spearmen you were not supposed to engage there See if I can get them to break loose So we can engage the Bastilla don't right. We have routed this skin cohort nice And right if I'm not that talkative, it's because I'm Desperately trying to focus Winning this important battle Okay, if you can just break out there, I would be happy I think we can actually charge in to melee with these guys Boom. Yes, we could Good stuff. Good stuff Let's shoot this Where is it's there is the Bastilla don all right spearmen I encourage you to cut this Monster down and I have Skirmish mode on this. I suppose we don't really need to cause I think Marcus can Can take on Karak in single combat.  No, our war wagon has Has routed but yeah, they have rallied and I suppose this looks quite Quite good for us See if we can get away another shot here from our magic bow boom killing blow nice Well done Marcus Well done indeed Right, so I do believe we have this battle They are fleeing and yes, we do Do that will have to be a good and satisfactory conclusion to this episode I suppose so not the longest of Let's play videos, but again, I just want to mainly actually show you that intro because I was the first time I saw it, but I Suspected it was going to be great, which which it was Since it is autumn I will make more let's plays of some sort of game because that's How autumns should be and I know they are somewhat appreciated at least when it's getting a bit darker outside So do let me know if there is any particular game you would like me to make let's plays of and it will kill these Captives so they retreat there and we can recruit some more units. I'm just gonna take this This turn before I check out Right last thing is going to see What fun things focused shot cool down Boom, let's go with that. All right. Thank you for watching and I wish you all a Great weekend ahead xoxo boom


I've taken it to a couple of different people, no one can do anything for me so I've basically lost all of that footage and I've just been sitting these last couple of days just thinking right now what, you know, because I really really wanted to finish off that series nicely and wrap it all up for you guys as I said before for anyone that happens to care. So I've gone through all of my footage and I've got enough for three days out and I've also got enough for, there's a little bit of show day and maybe a little bit of the day after so I'm going to put together what I can and still bring them out and I've also got a new series that I'm really excited to start called Eat Big, Train Big, Get Big, whereas actually it might be Train Big, Eat Big, Get Big, I'm not sure what it is but it's basically going to cover my journey from last Monday when this bulk started, lean gains, clean bulk it hasn't been too clean though but I'll cover that in that series which I can't wait to make and I'm actually going to make the first episode today because as of Monday last week I've tracked all my workouts, I've tracked all my macros, I've tracked my weight and we're going to do this properly guys. On the road to 100 kgs, I'm sitting at about 90.5, about 91 kgs at the moment, my weight did shoot up but as I said I'll cover all that in good time. So that is the footage, what else?  I'm going to have my own space, I'm going to be able to be free in my head and my thoughts, be able to write things down, make lists and just get on with life and kill it so I'm really looking forward to that. One last thing I'm writing an e-book on flexible dieting, basically the basic principles of flexible dieting and as I'm going to be doing customized meal training plans they're all going to be based on the macro, a macro split and basically on flexible dieting principles so I want to include this little e-book with the meal and training plans so that my clients can really understand why they're getting results and why I'm giving them these macro numbers to hit so that is it guys, little apology, update on the future, you'll be seeing three days out from the WBFF show that'll be my next episode and then we'll see what happens after that.


So this talk is how AI gives your project superpowers. It was written as, it gives your site superpowers, but being that we're all digital experience creators now, not just website creators, this seemed like a better title. Quick reminder, code sprints are on Friday. If you haven't participated, you're interested in participating more in the Drupal community. That is a great way to get some kind of hands-on help get your first core contributed patch over the week. So I'm Frank Currie. I'm the CEO of HeliCore, all those business cards you got around this company that I'm partnered with. I've been a Drupalist for 10 years, so I've been around the block seeing how Drupal and the web has changed over the last 10 years, quite a bit.  I don't think the iPhone was debuted just yet. I think it was a little bit later in the year. So 10 years ago, there was no iPhone. Something to think about. So 2007 was interesting, but 2012 was a big year too. You guys might remember this movie. I don't remember if I ever saw it. I think it was terrible. But the whole idea was that in 2012, the Mayan calendar was running out and it was going to be some sort of apocalypse. People started taking this pretty seriously. I remember there were some things in the subway of like, come join our cult. So 2012 was a big year for me. I've left my position, lucrative position at Sony Music to go back to school, get a degree in machine learning and AI. And in the middle of my grad program, there's a program called ImageNet. It's a competition where different researchers try to best each other by taking millions of images across thousands of categories. Categories like different types of dogs, cats, a bottle of beer, and classifying them correctly using whatever technique they want, but generally machine learning. So what was big about 2012 was previously, people were using hand-coded techniques. Techniques were used to where you go in and you write some if-else statements. I'm exaggerating a little bit, but that's basically what they were doing. And this was a body of work that had been going on since the 50s to figure out what image features to use, how to segment them, and things like that. But at the end of the day, it effectively was not machine learning, but it was more statistics. They knew how to cut these things up and they'd shown what worked over time, but it was sort of human labor figuring these things out, not machines. And then in 2012, the winner dropped, this is the error rate on the left-hand side, the winner dropped the error rate significantly. So this has been going on for years prior to this and things were kind of plateauing. Humans were only able to improve this thing so much. In 2012, everything you see in purple is this new method. This new method was called deep learning. How many people have not heard of deep learning? Okay, so deep learning is a new methodology that uses a, it's inspired by the brain, let's say. It's not using neurons, but it's inspired by the way the brain works or the little bit we know about it. And it's a technique in machine learning that allows us to deal with very, let's say, noisy, difficult problems that have some sort of hierarchy. And it's proved to be very effective. So in this case, 2012, you can see how much the rate dropped. It dropped from around what, 30% down to 15%. And then each subsequent year, including now, it keeps dropping. What you'll notice is that the human performance is in red. So once we become superhuman at this task, and some of these tasks are hard, where it's like different types of dogs. I'm a dog lover, but I don't know all these different types of dogs. The AI was able to correctly predict the difference between a poodle and a dot sender, something like that. So it continues to be better. So these, I would say are superpowers that we're gaining. When it's better than human, it's, say, a human superpower. But even if it's not a human, and it's just a machine, I think of these as superpowers. Because even if it's not as good as a human at the task, it still can alleviate a lot of work that the humans would have had to do otherwise. So what are these superpowers that I'm talking about? So one thing to keep in mind is that you may already be using machine learning right now. And the goal of my talk is to say, hey, we should be exploring these things. You should be interested in these things because they're gonna become tools that you're gonna be using very soon. But you may already, most of you, how many are familiar with this logo? So it's Malim, right? Malim uses machine learning behind the scenes to figure out what's spam and what's ham. And it does it pretty effectively, and it learns over time. So just the idea that you may already be using some of these tools. So some of these superpowers, you could categorize them in a large swath, like interpreting images, or categorizing images, like we talked about with ImageNet. Natural language processing, so if you're working on some sort of bots and you want people to ask a natural question, they may ask it in a few different ways, and you wanna be able to figure out what are they really asking for it. Being able to listen, so right now, Google has technology where for the hearing impaired, I could speak, it could start typing, and people could use that right away. Speaking, it can generate speech, so you've used a Garmin or something, Google Maps, and the person speaking. That technology is getting much, much, much better than it was just a few years ago. And then translating, the traditional way Google's translating was taking two pieces of text that had been translated by humans and just sort of mapping them one-to-one, roughly. What the new techniques are doing that we'll get into in a minute is using deep learning to actually translate end-to-end. So it's able to translate between languages that it didn't have examples for. So maybe going from Swahili to Hungarian, or maybe that's a very uncommon pairing, but now it's able to do that because it's sort of like learning a meta-language in between. And then content creation and augmentation. I think this is a really exciting space, especially for the Drupal world because we sort of live with content all the time, that we're used to user-generated content, but what about AI-generated content, things like that? So we'll explore all these. So how do we create this? This Frankenstein monster. So we're gonna keep it very simple. We're not gonna dive in. If you wanna dive in, please come to the bof. We'll talk a little bit more in detail. But basically what you want is, you need to collect some data.  Here's what the right category is for that image. So you sort of need this pair, right? The input data that you wanna end up being able to predict in the future and the correct label that it's supposed to be labeled. And when you have the correct labels, you can know when the model goes and predicts something that it predicted it incorrectly. And you can say, how incorrectly did it predict it? And that's how it's learning. It's learning based on just like a child saying, this is a cat and this is a dog, right? And Drupal's great at this because it has all the structured data. So in this case, we've got a set of taxonomy tags. So this is a great example where you could maybe have a site that exists where you, let's say it's articles, news articles, and they're supposed to go in some category on your site. You can use the existing data on your site. The more data you have, the better. But you can use the existing data on your site to actually predict in the future when someone say creates a new article, what is that article supposed to be tagged with? So you can recommend tags that they should consider, for instance. So Drupal's really good at having this data in a structure that we can export. And you may export it through like a SQL query or something like that to get it out into a format that you can use to process by some other system. So you take these two sets of data, right? Your X is your inputs and Y is the, what are the correct outputs? You put it into a model, right? And this is, we're black boxing it. I'm not gonna get into details. But you put it into the model and you do this basically over and over and over again. And the model just like a toddler, just talking with Josh Kay about this, sort of like a toddler learning to walk or learning to speak. It gets it wrong first. It's not like it goes from zero to 100 right away. But it slowly improves over time as it figures these things out. So once you've built your model and you get it to a state where you like, you like how it's working, you're looking at the predictions it's making. It's say, making it 80% is good enough for your use case and you move on and put it into production. So how does this work in production? You can think of it as like a black box behind a REST API. It's probably how you're gonna do this, which Drupal. So you're going to say upload a body of a JSON, throw the body of your node into the model and then you're gonna get back a prediction, maybe here's a bunch of recommended tags. And that's how you would use this for Drupal. Right now, PHP is not a great language for machine learning. Python and Scala and some others are very popular. So what you're probably going to be doing in this case is writing this as a separate, service oriented type thing that you're gonna connect with. And it gets a little bit more complicated, but there's this idea of having different sets of data. So you take your bulk set of data, you're training on that data. You don't want it to just blindly remember the data, which can happen, which is called overfitting. You want it to actually figure out the data in a generalistic way. You want it to generalize about where these categories should be. So you keep aside a subset of your data and then that's the data that you're testing with. So the easiest way to do this is to forget everything I just said, right? And just use something off the shelf, right? So just like Mullum, it's a service that you have to use. You don't have to think about the machine learning going on. So we have face detection. Face detection's been around for a while. It works very well. So we'll move on. That's not that impressive of a superpower. Image classification we talked about. This is an example with Clarify. Clarify uses a deep learning model behind the scenes and they have a lot of categories. And so they come back and it's hard to see with the predictions on the right, but these are almost all in like almost 100% predicted. And we've got things like sunset, dawn, boat, reflection. It even says at the bottom that this is, there's no people in this photo. So that can be helpful. We've got not-safe-for-work photos. There's an interesting documentary on Vimeo that's called The Moderators, which looks at the people, has anyone seen it? It's basically the folks in India that have to look at all this smut that gets uploaded every day at all these sites and that it's really a human-driven thing right now. So with a not-safe-for-work model, you could think about having a lot of your content moderators job be handed off to an AI, but then they don't have to do with the obvious cases of pornography or whatever. They can just handle these sort of in-between case. So in this case, it's predicting sort of 50-50 accuracy between the not-safe-for-work and safe-for-work, which is probably good, right? It's borderline. I don't think Arnold could lose too much clothing here and still be safe-for-work. We can also do this with video. So in this case, it's looking frame-by-frame across this video and it's saying, what are the different categories in those frames? So it's very similar to image prediction, but in this case, we sort of get a continuous line of this. And this can be really useful. You can imagine where, if I'm a media company and I want to find what was the video that we had that had baseball in it? And it may have only been like a two-second clip inside a larger video, but I can search across my videos in this way. This is Watson. So this gives you text categorization. So I would upload an article. In this case, it was an article about sort of how AI is gonna take over everything. And it would give me back predictions on different hierarchies of categories. So in this case, they're, like I said, these are off the shelf. So you could maybe think about mapping some of these categories into your own taxonomy if that was appropriate for your site, or maybe just throwing them out your existing taxonomy and just using the sort of standard stock ones that they provide. Text summarizing, so this can be really useful. We have oftentimes a lot of legacy content, or we've imported importing content from other system. Drupal has a summary field that can be really useful or a pain in the neck, depending on your case. And what we may want to do is even have sort of a dynamic summary where maybe 500 characters was okay for our previous summary, but now we want to have it on Twitter or something like that, and we want to provide a 100 character version of it. This is an example of a site that allows it to do it. So I uploaded the same article that was all about how AI is gonna take over, and it cut it down by 98% and just gave me a one sentence output. And if you can read it, it's very impressive, very accurate, what it cut it down to. We talked about speech to text.  But believe me, we're at say 90, 95% predictability rate and we're getting better and better. So those last like nines, we all work on the web. You know how many nines maybe you have to worry about. The getting those last few inches can be some of the toughest to do. So in this case, I've just read something on the back of a book. I was pretty far away. I didn't have a very good headset or anything. And it picked it up pretty well. Some companies are starting to get smart with the environment. So they're taking their X, their input data. They're actually mixing in the audio with conference noise or outside noise or restaurant noise. And they're actually maybe able to make it handle those situations better because they're able to augment the data. We talked about translation. Let's talk about language detection. So this could be really useful if you say we're taking queries and you want to send it off to solar or elastic search. It might be helpful to know if even if people landed on your .com site and they didn't switch the language that you could detect the language beforehand to automatically provide the right queries. So that could be useful. So those are all kind of off the shelf you are available right now. Here's some ones that are a little bit hybrid. So you're using your own data or at least you can start with their model and then expand on it with your own data but it's still much easier than starting from scratch. In this case, it's a text classification. So if you're making say a chat bot or something like that, people may ask the same question multiple ways and you could sort of just think out or maybe you could look at your existing conversation data or search data and you could sort of hand categorize, hand label, well what are they asking for? Are they asking for movie recommendations or are they asking for product information and you have all these different permutations of the questions that they would ask. You can upload that data that X and Y data we talked about up to the Watson service and it will actually process do the learning for you. So it's this nice sort of a hybrid solution that is also available from the others, Google, et cetera, where you can basically just give them your data and they already have the model and they handle the training and then once it's trained you just hit up a REST API like you would with something else. So this can be handy. Here's an example with image classification. Now these are two different types of dingy sailboats or whatever. I'm not a sail person so they don't make a lot of difference to me. You can see they look very similar. In this case someone uploaded and labeled and what's cool is like because most of the training was done they only had to hand label maybe 10 different examples for each and they made their own custom classifier that said this is a Opti or whatever brand and this is a laser brand. So you can think about like product if you're doing like product related things or maybe you're automatically importing products maybe this would be something handy for you. So we get back to sort of the DIY the harder machine learning do-it-yourself but it opens up a lot of cool things like here's style transfer and I forget if I'm not an Instagram or a Snapchat person but I don't know if they have these things yet but if they don't they will soon. So in this case we're able to take the Mona Lisa and we're able to reimplement it in the style of other things, other paintings. Face detection isn't available as far as I know from a service but it's something that you could implement yourself. It's actually very good. You've noticed Facebook and other programs of how good they are at finding who you are and what faces are what. So this is basically how they're doing it. They find a face, they throw it into a neural net and they get some clustering and they say okay this person's likelihood is between this person, this person, this person and obviously if you have their social graph it makes it a little easier to figure out exactly who it is. Image captions. This is something else we could use with Drupal I think for visually impaired folks. It could be very useful for readers to be able to look at an image and say well what image is this? Give me an example of this caption. So here a man in a black shirt is playing the guitars on the far left and it's not perfect, right? If you look on the right hand side it says boy is doing backflip on a wakeboard. Well he's not on a wakeboard, it's like a trampoline but you can see the water in the background and you could see how it makes sense, right? So it's interesting when it gets it wrong, it gets it wrong in an interesting way, generally. And so you could see using this when people upload to the site it's always a pain to get them to put in the alt text. Maybe you just say screw it, I'm gonna have it, we'll still recommend them to do the alt text but I'll just provide it automatically and that'll cover our accessibility issues. Then we get to generation which I think is really interesting. So we think of user generated content but we don't think necessarily yet of machine generated content. This is an example where what's called a recurrent neural net was given Shakespeare and it just learned on Shakespeare over and over and over again and it was able to create this. Now all of these are words. It sort of gets the idea of IMB pentameter. It even predicts the capitalization for the names of the characters. It knows to put two carriage returns before the next person speaks. It learns how to put the semicolons. So it learns all of this just by learning how to predict one letter in front of it. So you can think of other ways that this could be interesting. Some people are using it for instance for image generation. So how many people have seen this? It's like took over the internet for a day and a half. So you're able to draw a picture of a cat on the left hand side and the model basically does its best to say okay this is what a cat would look like if that drawing was real and it can lead to some of these very scary, strange looking cats. These are actually some two that are, so I would recommend it. I think it's a, it's not cat to cat but something like that. So you can think about this in other ways. It's doing similar things with music where you can sort of give it a little riff or something like that and it's starting to put together other more nuanced predictions of what other pieces or motifs that you could put together. We're doing things with voices. So there's some pretty realistic singing voices that are happening. You can imagine where that could go. Like auto tune on steroids. We don't even need to pay the artist anymore. So here's another one, maybe a little more applicable to Drupal. It allows you to upscale images. So this can be really useful. The displays that we're using are going up and up and up in display size but you have a bunch of these old images and maybe you don't have access to the originals anymore to re-crop them. So in this way, what it does is the original images are on the right hand side, the down sampled images on the left hand side and you can see sort of how bad it gets. And then the one just to the right of it is just sort of averaging across. So you get this blurry image. But if you go one more to the right, so the third from the left, that is what it predicts. So it's able to go from an original image and you can see there's some differences, right? But it's predicting the reasonable outputs for these. So you could see this used for good for just say, okay, this movie or whatever was in VHS when it was originally made and we want to upscale it and make it look better. You could also see some sort of nefarious things happening, right? Where you see an image and it looks realistic, but maybe it's been altered in some interesting ways. So here's an example of something I did. We're often used to using search, solar, et cetera. This is implementation of an image search. So what I did was fed about 200,000 images from Yelp through a system and then got some features and then I was able to search by uploading a new image and saying, what are the closest images based on the image that I uploaded? So you could do this in Drupal with the help of some AI. So going beyond where we're at now, there's this idea that we are developers, we're used to constructing things, putting together if statements, where the AI is really different mode of thinking. You're growing something. So you may be tweaking the nutrients that you're giving it. You're maybe breeding two things together. And so it's a different mindset and I think it's a helpful mindset for us to start getting into now to at least know it's available, maybe start implementing those things on our sites and so that we're ready for the next things to come, which could be significant. So again, we're in the machine learning bof is gonna be today at 5 p.m. in room 312. Hope to see you there. If you wanna go into some more detail, we could talk more about like what is really going on with deep learning and so yeah. Follow me on FrankKerry and don't forget to do the session review. I'm sure you're getting that from everyone. So thank you. So we've got a few minutes. Any questions? There's a mic here too. I think we'll try to record it. I think that's the idea. Oh hi. So I was just wondering what... And don't go anywhere. There's another good talk right after this. All right. What kind of tools would you recommend that connect to Drupal the best? Would it be like some deep learning Java thing? As far as I know, there's sort of two types of modules. There's like specific modules that maybe work with Google's image search for instance. But there's no sort of like search API and that's something that I'm actually interested in talking to some people about at the BOF of being able to sort of create a standard API to do some of these predictions especially. Okay. Thank you. Could you both describe an average data set that one might be able to learn off of and then also what computational power like let's say in hours an average computer would take to process that data? Sure. So the first question was like what does a typical data set look like? And the second was sort of how long does it take?  So if you've got a website that has five pieces of content it's very hard to learn from those, right? Just like a kid.  So the more data the better. And the types of data you're looking at images, a lot of text data, you can get into more nuanced things but this sort of text and image stuff seems to be the most common. And how long does it take to train? You can train a model in as quick as, I'm talking like half a million images or something like that. You can train it pretty quickly. What's interesting, what helps to have is like a GPU. Big GPU helps. It maybe will save you like a fifth of the time. But it's not necessary. You could run this on your laptop. It just might take a little longer. So it depends on the model really. It's a very wide gambit. So the ImageNet competition, those guys were training it for a week, like 24 seven. What's nice is there's a thing called transfer learning where let's say I wanna do something image related. I can actually just steal their model and you can think of it as figuring out this hierarchical representation of the images. So low level, it's like edges and lines and circles. And then it starts to get more high level as you go sort of up the stack of the deep part of the deep learning. And with that you can train a new model very quickly with much less data as well. Because it's sort of already figured out vision. It just needs to figure out boat versus sail, you know, different types of sailboats like you saw. In that case, I think they did with like 10 examples. It's pretty impressive. There are some good course materials available for getting started. But I was curious if you could recommend some books where people would say, particularly people that have math stats background, what it takes to get from there to a working knowledge of the speed of learning algorithms. Sure, and there's quite a few. So like deep learning is its own sort of niche, but there are other more traditional learning algorithms that are available. I posted, if my buffer thing worked correctly, I scheduled it to post something to my Twitter account at Frank Carry. And that should, it's a blog post that I just wrote this morning with like some additional material, blogs that you could read. Some of the companies that we mentioned, some of the things that we mentioned in the slides. So if you go to at Frank Carry, I'm sure if anyone's gone there and doesn't see it, let me know. But it should be there now. It looks like deep learning is very different from the development, but what are debugging techniques are there? They're not easy. So it's just like, how would you debug a four year old learning to walk? Or I guess younger than four, hopefully. It's tricky, right? Just to think about it, it's tricky.  You say maybe they're not getting the right information. Maybe their balance is off or something, right? You start to figure out why, why aren't they learning when I think they should or something like that? Maybe their brain is wrong or something, right? I mean, see, the trick is though, because you don't have like a traditional debugger, right? Or you can step through the code. But some of that's changing. Like the, if you use a framework like TensorFlow, I think they just released like an actual debugger recently, but other things you can look at are sort of as it's learning, you think of as like, all these neurons and you can see the levels of the neurons, like what values they are. And if they all go to zero, then something's wrong. If they go to a billion, then something else is wrong. So you can sort of see the results over time. And when you're doing these called epochs, you're learning, learning, learning, what you'll see is like you're getting better and better and better. And based on how, maybe you're getting better and better and better, but you're not learning, like you're not generalizing, then you're overfitting. So you start to learn these techniques. And unfortunately, they're like nothing like traditional development. So it's not, it's not trivial to jump into it, but it's also not that scary. I mean, I guarantee you, if you have reasonable programming skills, you could get a deep neural net running in an hour on your laptop with a blog post. Thank you. Yeah. Do you want to jump up and I'll field a couple more questions while you're, you start in two minutes, right?


Hello. My name is Karel Szymon. I am a software engineer in Red Hat working on a project called OpenShift Virtualization. And I would like to present here a cool feature called Keyword Tecton Task. And long story short, with this project, you can automate the VM workloads. So you can easily start them, run some scripts inside the VM, then turn them down. Or much more, I will show you some examples of what you can do. It's pretty cool, you will see by yourself. So at first we will talk a few sentences about OpenShift Virtualization, what is it, what's it used. Then a few sentences about OpenShift Pipelines, then the project Keyword Tecton Task, then Keyword Tecton Task Operator, and then some example pipelines, what you can do with our project. So what is OpenShift Virtualization? It's in case you have workloads in virtual machines and you run it all the way, it might be hard to bring it to new systems like Kubernetes or OpenShift. But with OpenShift Virtualization you can bring your old workloads to Kubernetes or OpenShift and you can run it next to the containers. OpenShift Virtualization supports Linux and Windows. We have multiple features there, e.g. just a snapshot, it's subset, importing, live migration, snapshot ring, monitoring and many other features. Of course we have templates, it's called, the project is called Common Template and it's a set of templates for most of the modern operating systems. So for example, you don't have to find on the Internet how many CPU cores or how many memory each operating system needs, but you just look inside the UI of OpenShift and there you will see, for example, templates for Ubuntu, Fedora, for Windows and with just a few clicks you can have fully working virtual machine. And of course you have to provide a cloud image for it. But for that we have another feature called Golden Images and for example, for Ubuntu, for REL, for Fedora we are distributing these images inside the cluster so you don't have to care about anything, just a few clicks and VM is working. Now a few sentences about OpenShift Pipelines. OpenShift Pipelines is a cloud native CICD solution based on Tecton. It uses Tecton blocks to automate deployments across multiple platforms and with Tecton or Tecton introduce multiple CRDs for defining CICD pipelines. Before I will go more deeper into our project, I would like to explain some definitions. I will repeat these words a lot, so let's try to explain them. So first of all, task. It defines a building step. For example, you can imagine building some binary or building a container or running a test. So it's just the smallest piece of pipeline. Then we have a pipeline. Pipeline consists of multiple tasks. So with pipeline you can define, for example, prepare a disk for VM, start the VM, run some scripts inside the VM, then shut down the VM, delete the VM. So that's a pipeline. Then we have a pipeline resources and it defines an object that is an input for the pipeline, for example, a container or a git repository and it defines outputs. For example, again, some container or some change in a git or something. Then we have a pipeline run. Pipeline run starts the pipeline. So when you have some definition of pipeline, you will create a pipeline run object, which will then start the pipeline and Tecton will take care of it. And now about the project. Keyboard Tecton task provides a specific open-source virtualization task, which focus on creating a tool machine, deleting them, starting VMs, creating data volume, data sources. Of course, you can do some manipulation with the PVC. You can run, for example, disk customized, disk versus prep and many other actions. You can find the project under the link in the slides. And here is the list of all tasks which we are currently have and we are shipping with OpenShift virtualization. You can find tasks for creating virtual machines. We allow to create VM from manifest. So you just pass there a YAML manifest or you can create your tool machine from template. Then we have tasks for manipulating with metadata of templates. So, for example, you can copy the template, do some modifications. For example, like change the number of CPU, number of memory or add some devices inside the VM. Then we have tasks for creating or deleting data volumes slash data sources. There is a small note that in OpenShift virtualization 4.11, the task has named create data volume from manifest. But then we add much more functionality in 4.12. So it's name changed to modify data object. And as you can see in 4.11, it just know how to create data volume. But in 4.12, it knows how to create, delete data volumes or data sources. Then we have a task for generating SSH keys. So when you run this task, it will generate a new pair of SSH keys and store them into the cluster. Then we have a task for executing commands in virtual machines. First task executes commands via SSH. The second one just stops and deletes the VM. And then we have a task with libgefstool. We have two, this could customize and this could sysprep. And then we have a task for waiting for the VM. Like the VM can be in some states. So you just define for which state you are waiting and the task will wait for that state. And now about the project TectonTask operator. TTO or TectonTask operator is an operator which takes care about deploying of keyword TectonTask. So this operator is something like a box which consists of all of the previous tasks. And when you install OpenShift Virtualization, TTO will take care about deploying these tasks inside the cluster. TTO is a part of OpenShift Virtualization 4.11. It's marked as a dev preview. So it doesn't have any official documentation or test coverage. Of course we have documentation and test coverage in upstream but not in downstream. From OpenShift Virtualization 4.11, TTO is deployed by default. But by default it does not deploy anything. It's just a testing feature. And when user would like to use this feature, he or she has to go to HCOCR. HCO is like an operator which takes care about deploying any other OpenShift Virtualization components. And then user has to change or enable a special feature gate which will then tell to TTO to deploy its resources. You can see an example in the presentation and then there is a link to the Github repo. So before I will show you some examples what you can do with these tasks, I would like to speak a little bit about motivation, why we are doing this, why we are creating these tasks, why we are creating these examples. Imagine when you would like to use OpenShift Virtualization, you need to have some source data, some disk with operating system. When you are trying to run VM with Linux, it's quite easy to find a cloud image. With just few clicks, you can find an image for Fedora, Ubuntu, CentOS, RAL, but what about Microsoft Windows?  And for that, we prepared example pipelines which will take the URL to Microsoft Windows 10 ISO and then it will trigger the whole pipeline which will take this ISO, install the operating system, then stores it in a special data volume and then there is a second pipeline which I will explain later. So, as I mentioned, we have two example pipelines. The first one is Windows 10 installer, the second one is Windows 10 Customize. The first pipeline will take the ISO image and installs it and then stores it in the cluster and then you can use it as a golden image in OpenShift Virtualization OS Images namespace. Then there is a second pipeline, Windows 10 Customize. This pipeline takes the resulting result and then it does some modifications. EG, in our case, it installs Microsoft SQL Server and then, again, pipeline will take the image, stores it in data volume and you have fully working Microsoft Windows 10 with SQL Server ready for use in other VMs. So, as I mentioned, the first pipeline, it just needs ISO, the URL, specifically, and it will install this operating system and it, of course, installs virtio drivers for better performance and then it stores the image inside the... Well, in this case, it's keyword OS images. It's upstream name, but in downstream, OpenShift CNV Virtualization or something like that. In the bottom, you can see an image from which task it consists. Then there are special parameters. The only one which is required is a link to an ISO. EG, you can select from official Microsoft sites or you can do your own server which can then serve the ISO to the pipelines. Then, of course, you can specify some other parameters like auto-attent config map name, where it's a special config map where you prepare sysprep and according to this sysprep, the pipeline will then install these windows. Then source template name, base dvname. Here is the list of all tasks from which this pipeline consists of. So, at first, we have to copy template. We are copying the template from a project called Common Templates. Especially, we are copying windows 10 desktop large. Then there is modifying VM template which takes this template, do some modifications. EG, change the boot source. Then we are creating VM from the template. Wait for it. Create the new dv from the installed dv. And then we do some cleanup. And here is the demo. First note, this demo is cut. The whole pipeline takes about one hour, but it was cut to only three minutes. As you can see, there are two pipelines, Windows 10 Installer, Windows 10 Customize. You just start it, provide a URL for ISO, or you can change the pre-default parameters. So, start it. It will do some copying of templates, modifying. Then it will start the VM. And now let's see how the VM is going. As you can see, the VM was created. Currently it's starting. During the pipeline, the VM is multiple-timers started. It's fine when it's restarted. So now it's booting. In a few seconds, you should see the installation page. As I mentioned, this installation is going through sysprep. So everything what you define is sysprep. The installation will just flow the manifest. Now, as you can see, it's booted. And now it will do some generalizing, some cleaning. It's shutting down. Now let's go back to pipelines. As you can see, it's doing the last steps, like copying the disk. And when you click on virtual machines, you can select the Windows 10 template, and it will immediately show you that there is a boot source available. So you just click single button, and voila, you have working Windows VM. And now in this case, the automation stopped, because to do some extra steps, we create a special another pipeline called Windows 10 Customize. The purpose of this pipeline is to take the result of the first pipeline and then do some modifications. In this case, we are installing SQL Server, but of course you can install any other software or any other packages. In the bottom, you can see the picture from which this pipeline consists of. Again, we have some special parameters, but in this case, you don't have to provide anything because the pipeline will take results from the first pipeline. So you can, for example, define template name, config map name, where you again define the sysprep and, e.g., what you can install inside the Windows VM, and then the result name, with which you can then run another VM. Again, it consists of multiple tasks. First of all, we have to copy template and modify template. Then we have to create the VM, wait for the VM, then again do some modifications and then copy the resulting disk to a completely new disk. And again, we have an example. So as you can see, the first pipeline was successful. Now let's trigger a second one. As I mentioned, you don't have to specify anything in this pipeline, just hit start. Again, it starts the VM. So let's look inside. Again, I have to mention that this pipeline takes about one hour. And now it's installing the SQL server. Now it's doing some preparation, cleanup, shutting down. And in the pipeline, we'll take the resulting disk, copy it into completely new disk, and it will create a new template for you so you can use this new template with the new disk and create a new VM from it. As you can see, there is a new template. And just with single hit, you can launch a new VM with pre-installed SQL server. Okay. And that's all from this presentation. In case you have any question, don't hesitate to ping me on the email or you can ask here. Where to speak here? Cool. Do you understand that you're using PowerShell to install all the software inside the tool machine? Yes. Yes, we are using PowerShell script, which in the first pipeline it installed by IoT drivers. And then it installs my SQL server. And how the commands are invoked from the pipeline through the SSH, I guess? It's a part of a sysprep. So you define sysprep, then there is a special command to run or to mount the script, and the script is just below the sysprep. So it's quite easy to... Yeah, and the second step also done this way. Which step you mean? You describe you have two steps. First for installing Windows and preparation. The second one is for installing a SQL server. Yeah, both are done the same way. So with PowerShell script below the sysprep. And then invoked from sysprep. Thank you. Yep. Where this is all done on the back-end side, is it built locally on the machine? In the cluster. In the cluster. And can you connect multiple clusters this way? For example, around the tasks and builds, let's say Fedora S390 machine in IBM Cloud? Can you please repeat the question again? I mean, you built a x86 machine for Windows-based. Is it possible to, for example, use, let's say, my own IBM Cloud credentials and build the machine in the cloud? I think so. If you have pre-installed OpenShell virtualization, then I don't see any problem with that. It needs to be on the remote node in the cloud. Yeah, in your remote cluster, you have to have OpenShell virtualization, OpenShell pipelines or Tecton. And then it will work for you. Cool. Thank you. Yeah, I just wanted to ask if I can find source code of all the steps somewhere. Yes, yes. You can find them. So the source code of a task, it's on this link. So when you just write keyword slash keyword, it will find you the organization keyword, and then you just find the keyword Tecton task. But the source code is of pipeline. It's in Tecton task operator. Again, it's under the keyword organization. So just find reposts with Tecton prefix and you will find all source code. And of course you can ping me on email and I will send you the links. Thanks a lot. Hey, hello. So your solution is built on top of Tecton, right? Yeah. So in case your pipeline fails, how do you debug it? And in case is there anything missing, like because Tecton kind of builds on jobs, I think? No. When you run Tecton pipeline or when you create a pipeline run, it will create like a job pods. So each task is running inside a separate pod. Okay. And in case your pipeline fails, so you just directly check the logs of those pods or... Yes, yes. Okay. And is there anything else missing in those logs which might, like in case, is there anything missing that you would like to have, like additionally on top of those pods that would help you to better debug it? I think not because when you debug the pipeline run, it will tell you which task fails, which pod fails, and then you just go inside that pod, run OC log, and you will see, like, the whole log, what, what failed. But of course, when you would like to run a deep diagnostic, for example, when the logs are not enough, you have to build your own tasks, your own images, and then run the pipeline again. But I think for user usage, it's enough to debug from logs from pods. Okay. That's all. So then thank you very much. Thank you very much.


Tax season is here and it's time to start preparing to file. ActiveDuty Sailors will have access to their W-2s beginning January 21st for the 2016 tax year. The Internal Revenue Service would like to remind you that a new law states that the IRS cannot issue refunds before February 15th for tax returns that claim the earned income tax credit or additional child tax credit. For more information on the new tax law, visit the IRS website.  Those eligible for free tax services include ActiveDuty, Reserve and Retired service members as well as their spouses and dependents. For more information about Military OneSource tax preparation and filing services, visit the Military OneSource website.


Good afternoon, ladies and gentlemen. Today we pay special tribute to Colonel Roger S. Girol on the occasion of his promotion to Iraq, our regular general. The host for today's ceremony was the 10th general to lead across the director of the Defense Health Agency. Ladies and gentlemen, please stand for the arrival of the official party, and remain standing for the city of our national anthem by Master Carillo French, followed by the invitation given by Chopin Karen Beaker. For our ceremony today, when it can be almost too much to bear, but you are with us to strengthen us and encourage us to keep going. When we cannot keep going, you carry us. Thank you, Heavenly Father, for seeing the Girol family through such a season. It makes this happy occasion and all the more precious. And so, with humble gratitude, we give our heartfelt thanks and praise to Ian Maddy. May they keep in stride to contribute in meaningful ways to the Army and the nation. Bless the whole extended family, as their family business has been about decorated service and sacrifice in uniform for generations. May all of us gathered here today be inspired by their legacy. And on this Memorial Day weekend, we are reminded that our freedom as Americans and our freedom as people of faith has been paid in blood. Grant that we, O God, who yet remain among the living, be so committed to giving our lives for others. I pray in your holy name. Amen. Ladies and gentlemen, please be seated. Shopping meekers, thank you for those inspirational words. And ladies and gentlemen, let's please give a round of applause to Master Hero French for that rendition of the National Anthem. Call my friend Ryan Seacrest and see if we can get him on American Idol. We'd like to extend a special welcome to our distinguished guest, Dr. Andrew Centennial, Executive Director, Acquisitions, Technology and Logistics, Department of Veteran Affairs. Colonel Jero is joined today by his wife, Kelly, his daughter, Madeline, his brother, Mr. Ed Jero, his mother-in-law, Ms. Judy Hannon, his cousin, Lieutenant Colonel retired John Wink and his spouse, Deborah, and his brother-in-law, Dr. Michael Hannon. Thank you for being here with us today. We would also like to extend a warm welcome to the many distinguished military and senior civilian leaders, trusted mentors, dear friends, battle buddies, and esteemed colleagues, as well as all of the non-commissioned officers, soldiers, and DOD civilians joining us here today and viewing from both near and far. Colonel Jero and his family are honored and thank you for joining them for today's ceremony. At this time, ladies and gentlemen, it gives me great pleasure to introduce our host for today's ceremony, Lieutenant General Tolita Crossley. Good afternoon. What an amazing day for us. As I was sitting here listening at the introduction and I looked out, all the smiles and support just illustrate what today means to so many of us. So what is it honor to be here? So good afternoon, everyone. Welcome to distinguished guests, this is a 10-year-old family, friends, and most importantly, a dry family. Thank you all for being here today. Wow. Master, Kee-Rail, that was absolutely incredible. Absolutely incredible. It really was. Hi, Chap and Nika. Thank you for your inspiring words of prayer. And to everybody who had a hand in today's event, thank you for making it a ceremony that honors the significance of a promotion to the rank of Lieutenant General. Roger, congratulations. I am sincerely grateful to honor to have this honor today to host today's ceremony. Okay, let me speak to the potential women's out there right now. No, I did not reach back to my New York roots and talk with my connected friends who took a back to the 10-year-olds and me, the 10-year-olds and me, so that I could be here as today's ceremony. There's absolutely no truth to that. Because if I was to do something like that, I would have just put his name on the blacklist and called my friend Graventon, because he's much more discreet. In all seriousness, I am grateful to have this honor today. I appreciate that both you and Lieutenant General Dean will pass me. Before I talk about Roger, I want to recognize the members of his family as well. And as you heard today, his mother-in-law Judy's here, his brother, Ed, a former Navy SEB. Thank you for your service. His cousin, Lieutenant Colonel, retired John Week and his wife, Deborah, thank you for your service and his brother-in-law line. Thank you all for being here today. And of course, the two most important people in Roger's life, his wife Kelly and their daughter Maddie. Roger and Kelly met at the Great Place, also known as the newly renamed Ford Cavosa near Queen, Texas. And if you can believe it, they're celebrating 24 years of marriage. Congratulations on that. So Kelly's a former Army physician assistant and is currently working with the Veterans Evaluation Service. She's been an active member, you know, a soldier, a family registered in the world.  Thank you, Kelly. The daughter of Maddie, Maddie just turned 18, happy belated birthday and just graduated from high school as well. Maddie is headed to Colorado State University to study animal science and pursuing her veterinarian degree. So Maddie, so when I asked Roger about his greatest accomplishment, he quickly said it's his family. It's Maddie and Kelly. Maddie's not just a military brat dealing with the usual military upheavals, moving from post to post saying goodbye to old friends, making new ones, getting used to a new school. She's had to deal with some medical issues, some significant ones and has done so with the level of courage, grace and determination, keeping on track for the high school graduation I just talked about at 18 and going to her first year of college. And that's no small feat Maddie. You've been an inspiration to many, to include your parents. So thank you for what you do for our military. I know all of you are extremely proud of Roger today. He's not here without your love and your unwaiving support that is made today possible. The late General Odeiro, the former Chief of Staff in the Army always said the strength of our nation is our army. The strength of our army is our soldiers and the strength of our soldiers is our families. That's what makes us only strong. I would go further one step and say that our family's sacrifices are so that we are able to continue to serve. Kelly, Maddie, to the Drow family, you're Roger's heroes and we are all grateful for what you've done and for your faith in service. Thank you to the Drow family. As I said earlier, it is truly not an honor to host a ceremony. Promotion to the rank of General Officer is rare. To be specific, Roger is one of a handful of eligible 1,000, so it's not a handful. He is one of 1,000 eligible A-Med colonels. He joins the rank of approximately 230 General Officers in the Regular Army that has comprised of over 480,000 soldiers. Those data points underscore a rare privilege and honor of promotion to the rank of General Officer and the trust and faith our army has in him. I know Roger's humbled by his selection, might even be a bit overwhelmed, but you're absolutely more than ready for this next step. As you read his bio and his long list of duty assignments and decorations, it would be easy to miss why we are really here today to promote him to bring it in General. We're promoting Roger to serve as a General Officer, not just because of his intellect. To be sure, he is a big brain. Roger can assimilate an incredible range of issues and distill them down into impactful actions that make a difference. He is simply unparalleled in that effort. We're here today not just because Roger is an unselfish teammate and a great leader from any seat on the team or because of his ability to lead up. And I know this firsthand. I experienced Roger helping mentoring a newly promoted Brigadier General, getting her to pass as an operator as she served as a MedCom G357. We're not here today because of his moral courage or his commitment to the mission and the people. We're here today because of all of it and Roger has it all in spades. He has the character and the commitment to lead at this level and will absolutely continue to make a difference at the most strategic levels of our military. Roger, as you assume the inherent privilege to lead at this level, never lose sight of the people who got you here. Your family, your friends, they remain part of your journey and they will continue to sacrifice so that you can continue to serve. Honor and keep them. Remember that you're never alone. You are joining new teammates, other general officers, senior listed executives and leaders across the Department of Defense, both past and present. Finally, keep having fun, bringing the passion, the joy and the genuine commitment you have done so well to continue to serve and make a difference with the absolute most complex issues of our department. Roger, Kelly, Maddie, congratulations. Everyone here today is so very proud. So let's get to it. Please join me. Kelly, will you please come forward and join your husband on stage please? Ladies and gentlemen, please stand for the reading of the promotion order. Attention to orders, the President of the United States has reposed special trust and confidence in the patriotism, valor, fidelity and professional excellence of Roger S. Jereau. In view of these special qualities and his demonstrated potential for increased responsibility, he is therefore promoted in the United States Army to the rank of Brigadier General, effective to third day of May 2023 by the order of the Secretary of the Army. Please be seated. Kelly and Lieutenant General Crossley will now place the grade insignia on the shoulder loops of Brigadier General Jereau's jacket to reflect the rank of Brigadier General. At this time I ask Madeleine and Ed to please come forward. Madeleine and Ed will now place the grade insignia on the shoulder loops of Brigadier General Jereau's shirt. At this time I ask Lieutenant Colonel retired John Wink to please come forward. Lieutenant Colonel Wink will now present Brigadier General Jereau with his garrison cap reflecting the rank of Brigadier General. Let's give the family a round of applause. Lieutenant General Crossley will now present Brigadier General Jereau with his certificate of promotion. Brigadier General Jereau has requested Lieutenant General Crossley to administer the oath of office although not required by law. It has been a longstanding tradition that officers recite the oath of office upon promotion. Lieutenant General Crossley will now administer the oath of office to Brigadier General Jereau. Please remain seated. His family will remain in place. At this time will Command Sergeant Major Erano Booma please come forward. In the early 20th century the War Department initially authorized Army General Boak Flags for use when making official visits to naval vessels. In 1923 the authorization of flags was further expanded to include automobile flags and field office flags. Line officers had scarlet flags and staff officers only had branch colors and branch insignia. Army Medical Corps General Officer Flags were marooned with white stars. In 1947 the Deputy Chief of Staff of Personnel authorized all Army General Officer Flags except Medical Corps and Chaplain Flags to be scarlet with white stars and gold fringe while Medical General Officers kept the maroon flag with white stars. Lieutenant General Crossley and Command Sergeant Major Booma will now present Brigadier General Jereau with the Army Medical Department General Officer One Star Flag. At this time I ask Colonel Kenneth Lutz to please come forward. Colonel Lutz will now present Brigadier General Jereau with his General Officer belt. The history of General's belt dates back to World War II. In 1943 the Army Chief of Staff wanted generals to look in his words dressed up. So he ordered the issue of belts. The thick black leather belt with an 18 karat gold plated buckle with an imprint of an eagle was first made in 1944. Today wearing the belt is at the discretion of each general officer. At this time I ask Colonel David Zimmerman to please come forward. Colonel Zimmerman will now present Brigadier General Jereau with his General Officer side on. A six-solder P320M18 pistol serial number GO1075. Active duty general officers and promotable colonels can be issued a pistol on a loan basis. The pistols are procured exclusively for general officers and the serial numbers are prefixed with GO and are unique to one general officer. The loan of the pistol is valid until the retirement from active duty at which time the general officer can either purchase the weapon or return it. The pistol is destroyed. Ladies and gentlemen please stand for the rendering of honors. I present to you Brigadier General Roger S. Jereau. Please be seated. At this time Brigadier General Jereau will now present flowers to his family as a token of his appreciation for the love, support and sacrifice he has made in support of his career. Ladies and gentlemen the newest general officer in the United States Army Brigadier General Roger S. Jereau. Okay, we'll take a moment. HVAC system, General Dingell always talks about the HVAC system and the allergies. Pollen is heavy this time of year so we're going to get through this and hopefully the HVAC system cooperates. Lieutenant General Crossland, Mr. Centinio, Major General Mrs. Rubenstein, Major General Alexander and Colonel Hart, Major General Ferris and Colonel Weber, Mr. and Mrs. Bushman, Brigadier General McQueen, Brigadier General Mrs. Jones, Mr. and Mrs. Smith, distinguished guests, family, friends and I think Command Sergeant Major Greg, Command Sergeant Major Mrs. Greg, sorry. Thank you for coming today. What an awesome day to be a soldier. What a beautiful day for a promotion ceremony here in the historic National Capital Region right next to Hollow Ground. Especially as we head into Memorial Day this weekend. First and foremost I must thank God for this day and this grace. If you didn't believe in miracles, by God you can now design living proof. Likewise I'm also living proof that our Army is not zero defect as most of you can attest to as some of the stories were going on at the house last night. And that goes straight from my Army beginning as a cadet at Texas A&M. You can ask many of my fish buddies who are right that way, whom are here or on Facebook Live. My lieutenant buddies from America's first team are my fellow captains back from the days in the Big Red One. Judy first. They're here either because they're curious, amazed, flabbergasted or all of the above. Kelly, Madeline and I want to thank each of you for taking the time to come here today or attend virtually. Many from a great distance in different time zones as far as way as Australia. As I got texts from my buddy Ian Ford over there this morning. As we know most of you have busy schedules and lives of your own. But as you in this audience and many others, soldiers, non-commissioned officers, civilians, teachers, leaders and friends that made this day possible for me and my family. I'm humbled by your presence. Special thanks to all the folks that made this event possible. Let's give Kerala another round of applause please. I'll be remiss not to mention the G357 section. Captain Saraneo, my executive assistant, Sergeant Major Booma. Because nobody can pronounce your names, we all shorten it to Booma. The Fort Meier Memorial Chapel staff. Miss DeVille for the wonderful cake that you'll see as you process that way eventually after my hour and a half speech. Just teasing. And finally the excellence behind it all. The phenomenal Army Medicine Executive Services and Protocol Team. The voice of Army Medicine, Mr. Great Canty. A fellow healthcare operations alumnus on my dad. Miss Jane Houston, Miss Rose Jewett, Miss Nancy Sanchez, Mr. Adrian Morales. Miss Heidi Pampel, Miss Rosie Romiccio and Mr. David Watson. All superstars who coordinated all invites, set up the site, prepared scripts, programs and many things unseen by us all. My and my family's heartfelt thanks to all of you for making this day extra special. Please give them a round of applause. So I must thank and I want to thank Lieutenant General Dingle. He was the host on the original invite. But hopefully is watching, recuperating from his surgery and listening to his doctor's orders.  I thank you for the sage council advice and mentorship through the years. Thank you for answering my calls even though when I call it's not so great news most of the time. And I also thank you for not answering my call or taking my email back in 2015. I don't know if he knows this story. If he's listening, he'll hear it. If not, he may hear it later. It was right before I was graduating from the Army War College in Carlisle, Pennsylvania. This is when Human Resources Command was talking about presigning me for the second time back to the office of the certain general. See, I wasn't too excited about the prospect of coming back. I had gotten a picture from my first tour from 10 to 11 purposely with the Pentagon in a rear view mirror of the vehicle, hoping to keep it there. Clearly it didn't work. Then Colonel Promotable Dingle was coming out of command in the 30th Med Brigade in Germany and PCSing himself and family to become the Med Count G357 here in the NCR. I was convinced that I would talk him out of the assignment. He said we would talk. I'll chalk it up that he was busy with his PCS, and I'm thankful that we never spoke about the topic. After all, it was one of the most rewarding assignments that I've had in 29 years of service. Lieutenant General Dingle knew best. Lieutenant General Dingle's recent misfortune with a bum knee was my fortune, as I was able to ask another phenomenal leader and mentor to host this ceremony, Lieutenant General Crossland. Who, at her promotion to Lieutenant General, General Dingle described as the baddest woman in the Army. And that's no lie. My family and I are honored and humbled that you could host our ceremony today. You are a stalwart example of what a leader should be in our military, and you demonstrate the moral courage to tackle the toughest of problems, even when it's not the popular thing to do, but the right thing to do. I have appreciated learning from you and the positive example, leadership example you set. I thank you for making time for me, the phone calls, the office calls, and certainly today. I look forward continuing service to our nation, our military, and our military health system with you. As I look out at all of you, it is if I'm seeing my life flash before my eyes. No, I don't think I'm dying. There's just a lot of people here. You in this audience and on Facebook Live, and those that sent a note, are called leading up to this, are large parts of the reason why I stand here today. I see people that I grew up with, went to college with, and soldiered with. I see leaders that helped shape me and fuel my passion for learning leadership, all who helped shape a young Lieutenant, Captain, Major, etc. through middle-aged, Roger, and plant the seeds of leadership learning. I see leaders of various ranks, from very junior soldier, when I knew you, to Lieutenant General in this audience, from different points in my career that have helped shape and support me in good times, and not so good times. I see fellow Aggies, Brigadier General, Guy and Deb Jones, Colonel Dave Zimmerman, my son in the Corps, Steve Krippner, and some of my former fish buddies from Red Eye One or Company Eye One for the non-Aggies in the group who I learned through shared experience, the good, the bad, and the ugly, that you are stronger together, or as our Corps brass reads, per unitatum vis, through unity strength. And to be a part of something bigger than yourself is important. Important to always defend what is right and put others before self. So thanks, Ward. Thanks, Dave. I was fully expecting full-on Grizzly Adams look, so you kind of shocked me in the hallway. Joseph Lim, my former old lady, and if you don't know what an old lady is, just ask them. Dave Farr, who reached out, I think he's on Facebook Live. He was my longest old lady. And James Thomas, my fish doppelganger, who together we confused upper and underclassmen alike for the four years that we were in the Corps. I may need to talk to you later. I see many non-commissioned officers who shaped my life. My dad, his brothers, my uncles, God rest their souls, Uncle Ralph and Uncle Frank, a former Brook Army Medical Center Sergeant Major before the CSM rank came along. From my first platoon sergeant to my last Sergeant Major, Hernandez, Huffman, Robinson, Garza, Camp, LaFrada, Thomas, Jackson, Moran, and Booma. From my beginning of life through now, I have learned viable lessons from these and countless numbers of non-commissioned officers. I see former bosses, former battalion commanders, Colonel retired Larry Strobel, Colonel retired John Fristo, former brigade commanders, Colonel retired Bernard DeCuny, Colonel retired Todd Heisman, former commanding generals and other senior leaders, Brigadier General Arizona on Facebook, Major General retired Volpe on Facebook, Mr. Greg Stevens on Facebook, Major General retired Rubenstein, Gigham, playing Texas Aggie Class of 77. I think he's the eldest Aggie here. That's an honor, not an age jab. And maybe on Facebook, Lieutenant General Scott McKean, Lieutenant General Steve Gillan, who kept me saying at the great place, and Lieutenant General Nadia West, a shining example of humanity and leading with empathy. All of these that I worked for. Many mentors who provided me counsel along the way.  I thank all of you for that and the support you've given Team Jerome. I see a lot of folks who cannot be here today. Some distances a factor and have passwords and encouragement. Some who have gone on to their heavenly reward, like Sergeant Major Johnny Salazar, a high school instructor, Colonel Brian Aggie, who I had the opportunity to work for in Korea during my first tour. Two people that inspired me in this life lied in rest just behind us, not too far. In these sacred grounds of Arlington National Cemetery. When I was a second Lieutenant at the Officer Basic Course down in Fort Sam, my first duty assignment was the first Calvary Division at then Fort Hood and now Fort Cavassos. And I had to reach out to the Chief of the Division of Medical Operations Center, a then Major Gale Long, for whatever my assignment was going to be in that division. Now my buddy got to her first, so he went to 1-7 Cav. I got 1-12 Cav. It all worked out. I'd later work for her twice thereafter. She was probably the first mentor that I had in the Army. The HVAC pollen. Lieutenant Colonel Gale Long took the time to always listen and provide counsel up until a month before she succumbed to cancer in November of 06. She got that she was part of something bigger than herself. Likewise, from the day I was born, or at least the day I was baptized, my uncle and godfather, Uncle Walter, Colonel Retired Walter Rink, was there. Occasionally with his presence, because he lived in Florida and everybody knows I grew up in San Antonio by the dirt on the floor here in a minute. But always through letters and phone calls when I was growing up, always encouraging me, always remaining positive, inspiring me to become someone of good character, someone who I should strive to be. Also Class of 42, Texas A&M. All these people, these leaders, saw something in me that I did not see in myself. I am thankful that his son today could be a part of this ceremony. Thanks, John. If there's ever a point I get choked up so where the HVAC is really going to kick in here is when I talk about my family. Right? So I thank my parents, my dad who, as the Marine Hymn goes, is guarding the streets on heaven's seams, right? Currently, my mom no doubt still supporting them, nagging them up there, trying to keep them straight. A lot of sacrifice on their part and tough love. I must thank my mother-in-law, Judy, both Judy and Bill, my father-in-law, who's also watching from above. I've supported Kelly, Malin and I in moving to and from overseas and literally across this great nation of ours countless times. I do not know how we would have done it without you. My brothers and sister, as you can tell, they're older, much older, right, Ed? I know my sister Barbara hopefully has figured out Facebook. I talked to her back in the family room before. If not, it'll be on Facebook. Our brother, Richard, watching from the heavens, they've always been interested in their little brother. Special thanks to Ed for making the trek from Everett, Washington. I thank you for being with me during those special times in my life. It means a lot. Even driving with me in our little adventure posted my retinal detachment this summer in the surgery as I was one-eyed, going from what now is Fort Kevasso's up to here to get to this assignment. Okay, HVAC, don't fail me now. To my daughter, Maddie. There were a lot of people whom I thought were my heroes. My dad, former bosses, I'm not going to mention any names, there's too many of you in this room, so I don't want to offend anybody. Historical figures, even Mike Smith for writing the Med Ops handbook. Not much after that, though, Mike. Just saying. It took me 51 years in my life to realize that my hero is you. Six different elementary and middle schools, two high schools thanks to the wisdom of General Gilland asking me to stay another year in Korea, or it would have been three, at least. Her high school experience shaped by COVID-19 and on 13 October of 2020, a diagnosis of a brainstem tumor, low-grade ganglioglioma for all your medical types that would shape all of our lives, especially hers. The grit, the resilience, the strength, and the determination like no other. And she was going through proton radiation therapy at MD Anderson Cancer Center in Houston, and Kelly and I would take turns every morning for two months to get her to the radiation center at 6 a.m. That's when she wanted to be there, the first patient there every morning. Get in, get out. I stood there then and continued to stand in awe today of an amazing young woman who's a warrior. Please give her a round of applause for me. So thank you, Maddie, for sharing your dad and allowing me and pushing me to pursue my love for soldiering. She just graduated from high school, as General Crosslin mentioned, on Saturday, and will head off to Colorado State University in the fall. And probably many, many more allergy and air-conditioned moments to come. To Kelly, thank you for listening to me, the skill that you remind me often as recently as last night, that I don't do too well with. There was witnesses, you can ask them. Supporting me and being the best mother Malin could ask for. And being my best friend. Thanks for seeing this journey through and sticking by me. Thank you for encouraging me. Weaker folks would have quit a long time ago. I would not be here without you. To whom much is given, much is expected. The Army has provided a lot for Team Jero. From my schooling to part of Kelly's, I owe the Army a lot. And I can't think of a better way to give back than through Army and Military Medicine. From my being born at Brook Army Medical Center, the old one, not the new one, to my cousin John Week helping me being assessed into the Army Medical Department a couple of years back, to all the things Army and Military Medicine does from the Fox Hole to the Roll Four. It is, in my opinion, the most noble part of the profession of arms. I remain committed to what we are for, conserving the fighting strength. These are not just words. As many, as a couple of you have told me that are sent in this audience, words mean things. Words mean things. And I clearly understand the oath of office that I took again today. Before taking battalion command a few years back, Lieutenant General and our retired Dave Hogue, my former battalion XO and 112 cab, my first assignment told me, remember, you're appointed, not anointed. It is my honor to continue to humbly serve the greatest soldiers, service members, civilians, and our families on the planet. Again, to all. Thanks for being here today. It means the world to Team Jero. I appreciate it. Thank you. Lieutenant General would call this Omaha. I'll just call it a frago. I forgot, please sit. I forgot to explain why the dirt on the floor. I have been promoted, and some of you were there at one promotion where something similar occurred, on Texas soil for every promotion in this career. So from Second Lieutenant, certainly commissioned at Texas A&M, First Lieutenant, Captain Hood, now Kovasso's major at Fort St. Houston. Lieutenant Colonel was technically in Belot, Iraq, but somehow some Texas soil made it in through the wacky agricultural rules. And so I stood on Texas soil in Belot, Iraq. Colonel in the front of the Alamo, some of the most sacred soil for our state. And so thus, there are some Alamo soil and then there's some soil from our property out in the Hill Country that will have to be swept up later today. So that is why the Texas soil, that's why there's dirt on the ground. Sir, I'm glad you're explaining that so people wouldn't think I had the responsibility for that. Ladies and gentlemen, please stand for the benediction by Chaplain Meeker and remain standing for the playing of the Army Song. The words are printed on the program so that you are able to follow along. At the conclusion of the Army Song, please remain standing for the departure and family. Once the family has departed, please remain in place until a protocol representative comes to your role. Receive the benediction. May the God of peace grant you shalom always and in all places. May God grant you good health and help you to help others have good health and be strong of body, mind, and spirit.  And may we all be committed to the cause of freedom each and every day. I pray in the name of the Father and the Son and the Holy Spirit. Amen. Be blessed, Army Medicine. You accordingly invited to congratulate Brigadier General Giro and his family and stay for kick and light refreshments at the adjacent fellowship hall immediately following the receiving line. Thank you for attending today's ceremony. Have a great and wonderful Memorial Day weekend. Thank you.


This paper proposes an automated quality inspection system for aviation plug solder joints. It uses a two-phase approach to detect defects quickly and accurately. First, a fine-tuned YOLOV-5 model is used to identify the region of interest, ROI, containing the solder joints. This is then moved to the center of the image to improve clarity. A second fine-tuned YOLOV-5 model is then used to analyze the ROI and determine if any defects are present. The system's accuracy is tested in a real production line and found to be over 97.5%. Additionally, the system's speed is measured at 0.1 seconds per solder joint, meeting the requirements of industrial production. This article was authored by Junwei Sha, Zhuanpu Wang, Guanranhu, and others.


Traders in Ogun State have lamented low patronage of commodities by buyers, correspondent Habibat Ajayi visited some markets in the state. Here's what he found. Some of the things have skyrockets, you know, and we shouldn't be surprised, since the beginning of the year, we have been battling with inflation in the country. So we shouldn't be surprised anyway, but compared to last year, things have really gone on the ice side. In terms of customer patronising here, it's quite bit low than last year because due to the economy wise and we believe, and in most cases some people are even travelling with their own personal car. So it's a little bit low than the way it was last year. That's what I would say, the economy situation is very hard. That's what I would say and the transportation fare right now has increased. It's mainly the expensive because if you look at last year, things are not as expensive as there and right now, even the transportation and everything. Because, you know, when you want to get stuff in the market, even clothes are expensive, everything is just expensive. Expense wise, it's in lots compared to last year.


Hello and welcome to this session in which we will discuss section 351 specifically transfer of services. What is the big picture? What's the big idea here? Well under section 351 we have shareholders individuals that formed a corporation and what they contributed is money, cash or property and in return the corporation issued stocks they became owner in this corporation. Now if this transfer of property specifically was considered section 351 we don't have a taxable event simply put you contributed property in return you got stocks of this company the company that they formed the shareholders and right after the contribution these shareholders control the company and as a result section 351 kicks in and as a result it's not a taxable transaction that's fine this is what we learned so far about section 351. What happens now if some of the shareholder contributed services what does that mean? Let's take this individual here in this group and this individual don't have any money and don't have any property to contributed but this individual let's assume a young CPA motivated competent and they ask him to join but he does not have money so what they told this individual the CPA if you spend with our company one year will give you 10% of stocks so if you work for the company for one year we don't want you to contribute any money we want you to contribute your services what happened under those circumstances? Well this is a form of bartering I'm giving you my time you're giving me something in return well any form of bartering is taxable so when you provide the service it's a form of bartering and what's bartering bartering is when you exchange something for something else but we're not using cash for example these two individuals are bartering so it's a form of bartering therefore the service that this individual the value of the service is taxable so what we need to know is what happens when you provide services and property at the same time so what about if this individual they said yes I will work for the company but I do have some property some money some land some inventory I would like to contribute what happened under those circumstances would the transaction qualify under section 351 or not this is what we would learn in this session before we proceed any further I have a public announcement about my company foreheadlectures.com forehead accounting lectures is a supplemental educational tool that's going to help you with your CPA exam preparation as well as your accounting courses my CPA material is aligned with your CPA review course such as Becker, Roger, Wiley, Gleam, Miles my accounting courses are aligned with your accounting courses broken down by chapter and topics my resources consist of lectures multiple choice questions true false questions as well as exercises go ahead start your free trial today so let's go ahead and get started so the rules for transferring of services under section 351 it depends whether you are only transferring services under those circumstances the contribution is not counted under under section 351 simply put it's not counted toward the 80 percent control requirement because to have section 351 you have to have control after the transfer well if you only contributed services that percentages of the service does not count toward 80 percent control how about if you transfer both property and services you'd say okay here's my computer now I'm transferring property will my contribution now be be counted toward the 80 percent well the shareholder contribution will count toward the 80 percent if so you don't just contribute anything just any property well if the fair market value of the property that you contributed is a greater or equal to 10 percent of the fair market value of the service so the value of the property has to exceed a certain amount for the contribution to be counted toward the 80 percent control now what is that what is that amount well it has to be fair market value greater or equal to 10 percent of the fair market value of the service well the best way to illustrate this concept is to work few examples let's take a look at few illustration to understand this concept we have a individual a contributed property and received 60 percent of the stock right now owns 60 percent of the company b contributed services received 40 percent of the company stock and own 40 percent so a owns 60 b owns 40 after this transfer with section 351 applies under this scenario well remember that b transfer only service what did we learn about only service if b transfer only service this contribution don't count toward the 80 percent well if that's the case we're looking at a and b owning only 60 percent after the transaction well if they own 60 percent of the trend the transaction there's no section 351 therefore a will have to compute and recognize any taxes on the transfer of property and obviously b will have to pay taxes on the service provided on the fair market value of the service provided let's take a look at another trend transaction a contributed $60,000 worth of property owned 60 percent of the stock and received 60 percent and owned 60 percent of the company b contributed $1,000 in property $39,000 in service stock received 40 percent owns 40 percent so after this transfer a control 60 b control 40 well b here transfer both property and service does b contribution counted toward the 80 percent well let's find out b contributed $39,000 in service we have to multiply what's 10 percent of that that's $3,900 when it comes to the property the property contributed is less than 10 percent of the fair market value of service provided well as a result b's contribution is not counted toward the 40 percent therefore would back to square one a and b together own only 60 percent of the stock after this transaction therefore section 351 does not apply now remember b will have to pay taxes also on the service provided and the tax on the transfer of property is also applicable if there's a gain they have to pay gain on the property transferred let's take a look at another transaction a contributed $60,000 of property received 60 percent of stocks owned 60 percent of the company b contributed $10,000 of property $30,000 in service stock received 40 percent and owned 40 percent so after this transfer a owned 60 b owns 40 well a transferred property b transferred both services and property services is $30,000 well let's multiply this by 10 percent the 10 percent of the fair market value of services is $3,000 we see that the property is greater than $3,000 which is the 10 percent of the property what does that mean it means b contribution is counted toward the 80 percent well if b contribution is counted together they own 100 percent section 351 will applies and as a result a and b don't pay any taxes on property transferred however b will have to pay taxes on the services provided which is worth of $30,000 and that's considered ordinary income let's take a look at another transaction a contributed $80,000 of property received 80 percent of stocks owned currently 80 percent of the company after the transfer b contributed $1,000 of property $20,000 of service received 20 percent and after this transfer owned 20 percent so after this transfer is done a owns 80 percent of the company b owns 20 with this transaction classify under section 351 well a transferred property b both property and service let's take a look at the service 19,000 times 10 percent that's $1,900 well 1000 is less than 10 percent of the service of the property therefore b is not counted well it doesn't matter whether b counted or not after this transfer together they made this transfer a controls 80 percent of the of the company well they have control well as a result it does not really matter although b contribution is not counted that's fine a owns 80 percent therefore section 351 would apply therefore a and b don't pay taxes at any gains for the property transferred however b would still have to pay the taxes on the 19,000 of the service that's totally a different thing the 19,000 but for the property they don't have to pay any taxes now whether you are a CPA candidate enrolled agent or an accounting student i suggest you go to farhat lectures and work mcq's true false look at additional exercises that's gonna help you understand section 351 we're not done with section 351 we still have to look at when boot is involved we still have to look at when that is transferred with the property but it's very important to build your knowledge in section 351 step by step good luck study hard in the next session we would look at section 351 boot received section 351 liabilities assumed good luck study hard and of course stay safe