What's going on you guys, welcome to the Single Guy channel. I have a very interesting, this might be intriguing, subject today and that's why women love psychopaths. So I know I said this in the title, women don't love psychopaths, they actually try to avoid them actively. But a lot of insecure, sometimes troubled women do, they end up falling for them. Okay, the perfect example of this is like guys like Jeffrey Dahmer and Ted Bundy, very frequently you'll find prison inmates getting love letters from women who start fantasizing about them. Ted Bundy received dozens, maybe even hundreds of love letters from women. He was a national figure that people find out about.  Now the average woman is usually intrigued by it but doesn't really, is actively looking to avoid people like that. Okay, but I'm going to describe why women find it intriguing and also why some women find those very reprehensible and despicable human beings appealing. Okay, so we're going to get into some dark stuff today but hopefully by the end of this you will not be so suspicious of women and you'll end up seeing kind of why they do the things and you know be able to spot women that you know might be falling into that category. Okay, because men do a lot of bad things and then there are a lot of women that go after these guys that do a lot of bad things unfortunately as is with everything. So we'll get into the video right now. Okay, so let's talk about why women love psychopaths. Psychopathy as defined by Wikipedia so it's probably accurate. Sometimes considered synonymous with sociopathy is traditionally a personality disorder characterized by persistent antisocial behavior, impaired empathy and remorse and bold disinhibited and egotistical traits. So a couple key words there antisocial lack of empathy and disinhibited egotistical traits. These are serial killers, these are rapists, these are people that in society we have decided that they do not belong because they harm people and rightfully so. They should not be a part of an acceptable society that we live in. We cannot have people like that in there. But why are some women drawn to these types of people? Well psychopathic behavior is very very common among men. You don't see it as much in women. It does happen but it's a lot less. Serial killers are usually almost always men. There have been some women serial killers but not quite as many. Men when it comes to the masculine. The masculine a lot of people like to especially in today's day and age they like to hijack the term masculinity and define it whatever they want but masculinity is neither good or bad. There are very masculine men that do horrible things and there are very masculine men that do amazing things. Masculinity is not good or bad but what it is is it is an ability to do things that maybe aren't necessarily part of the traditional grain of society.  They tend to fantasize about these guys and when young girls look at them and they're riding a motorcycle or whatever like they're doing some bad boy stuff like they're into that because it's a very very masculine trait. Now as women get older they learn that these bad boys aren't necessarily like good to get with and so they don't get with them anymore but even farther down than that you find women that are even more troubled or disturbed or they don't have a good they don't have they have no father figure within them. They tend to gravitate towards these like very aggressive kinds of men and it's because it's hitting them at a biological point and because they have these unsatisfied needs they look for they're looking for them in the wrong area.  Now I hopefully I wish I could think of a more aggressive or worse example than a recess piece for the first psychopath but I could so that's the general idea behind it is that it's very very hardcore like masculine traits that women are going for to a ridiculous extent okay. Now there's also the side that women see that's you know not very anti-social they can't fit in this is actually unattractive for most women okay but if they don't understand social cues too if they don't understand societal things then it's not a detriment for them they see it as fine or maybe oh he's anti-social too like maybe he's like me that's kind of what they go for so women will get suckered in to a lot of these kinds of guys like Ted Bundy, Jeffrey Dahmer, Charles Manson was another one a lot of the women who joined his cult were of this category you know they were very anti-social they didn't understand social cues and they were very very troubled they were women who you know didn't grow up in very good environments yes they came from households a lot of times they were like middle-class households but they were basically neglected like they didn't have parents in the picture at all so they have this insatiable need to find someone who will lead them and the only person that they could follow or go for was a very anti-social person who fit outside of the grain. Now I am not saying that to get these kinds of women you need to be this kind of guy and by the way you don't want to get these kinds of women but is there anything that we can learn from psychopaths without necessarily being a psychopath hopefully hopefully for the love of god I hope nobody watches this video and thinks being a psychopath is the way to go because it's not like I said there's a lot of bad traits that psychopaths have that women are not into okay almost always when the women find out that they actually murdered people they're not into it okay what we can learn from psychopaths is that we can learn that going against the grain of society is sometimes okay okay it's okay to do it in certain in in in in measures it's okay to do it's okay to be yourself you don't always have to fit in you can't embody those bad boy traits without necessarily being a bad boy by going for what you want to do and who you are if you're also a kind social and caring person but you're not all you're not afraid to go against the grain of society that is the most attractive guy that you can be that guy beats the psychopath any day of the freaking week okay and for some of you guys what I invite you to do is also don't be afraid to be disliked by some people you know for a lot of my students I find that they're so they're so afraid to upset other people that they don't do the things that they want to do a psychopath has no problem with that all right too much so but I would like some people who are watching this video maybe and you know who you are if you're walking through life and you're feeling scared constantly about upsetting others you have a lot of permission seeking behaviors what you need to do is you need to not like I would invite you to to actively go out there and express yourself and be okay with people not always liking you because if you try and be liked by everybody you're gonna be you're not gonna be loved by anybody okay no one's gonna really go for you you're not gonna be desired so women recognize this and although the troubled women go for the psychopath a healthy smart intelligent beautiful woman is going to go for a guy who is like what I described not the psychopath but someone who is also like able to go against the grand society and is someone who goes on their own path and is not always looking to other people to try and be a certain way okay so don't be a psychopath psychopaths are terrible but take some of the going against the grandest society and doing your own thing and I think you can add it to your game I think you can add it to your life and it's going to make your dating life a whole lot better cool well thanks for watching you guys hopefully you learned a little bit from this hopefully you've learned why women you know wrote all those love letters to those crazy guys and why they're obsessed with those kinds of characters you know there is a sexual component to it but it's something that you can all have and not be as dislikeable and reprehensible as those people that we just mentioned so thanks for watching


Kremlin accuses Ukraine of planning dirty bomb attack in Russia.  No, we have no assessments. He told reporters when asked as to how the Kremlin was assessing information obtained by the Russian Federal Security Service.  It stressed that the agency obtained additional data on the involvement of Ukraine's special services in planning and preparing acts of international terrorism. The TASS agency said it received information that Ukraine's military intelligence had set up a special unit using light aircraft to supply sabotage groups within Russia and drop bombs on fuel and energy infrastructure facilities. It was also noted that Ukrainian pilots, detained by members of Russia's special services, provided details of the planned terror acts involving a dirty bomb in Russia and deploying small portable nuclear warheads.


Worthless house progressives retract mild peace advocacy under pressure from warmongers. The Congressional Progressive Caucus has retracted an extremely mild, toothless letter its members had written to President Biden, politely asking him to consider adding a little diplomacy into the mix to help end the conflict in Ukraine. The retraction followed a deluge of public outrage against their slight deviation from the official imperial narrative. If you actually read the letter signed by House Progressives including Alexandria, Kassio-Cortez, Ilhan Omar, Ayanna Presley, Rashida Tlaib, Jamal Bowman and Ro Khanna, you will quickly see that it's as innocuous and anodyne as any statement could possibly be while still containing words. It opens with effusive praise for Biden's interventionism in Ukraine and condemns the Russian government unequivocally throughout, offering only the humble suggestion that he, quote, pair the military and economic support the United States has provided to Ukraine with a proactive diplomatic push, redoubling efforts to seek a realistic framework for a ceasefire, end quote. Its authors make it abundantly clear that they support making sure such diplomacy is agreeable to Ukraine at every step of the way. This impotent nothing salad was bizarrely spun by the Washington Post as a call on Biden to, quote, dramatically shift his strategy on the Ukraine war, end quote. Despite nothing that could be remotely construed as dramatic existing anywhere in the body of the text, the letter received backlash from warmongers in both parties, including from House Speaker Nancy Pelosi. It was personally slammed by Bernie Sanders, the pope of American progressivism. Trolls and warmongers swarmed the social media notifications of every account which posted the letter in an official capacity, mindlessly bleeding the words appeasement and chamberlain in unison. In a statement on the retraction of the letter, CPC Chair Pramila Jayapal says she accepts responsibility for the publication of the offending act of peace mongering while in the same breath blaming its publication on her staff. The letter was drafted several months ago, but unfortunately was released by staff without vetting. As chair of the caucus, I accept responsibility for this, Jayapal said. Every war ends with diplomacy and this one too will after the Ukrainian victory. These statement reads, ignoring mainstream reports that US officials quietly believe Ukraine stands no chance of outright victory in this war. The letter sent yesterday, although restating that basic principle, has been conflated with GOP opposition to support for the Ukrainians just defense of their national sovereignty. As such, it is a distraction at this time and we withdraw the letter. Empire critics were quick to highlight the obsequious nature of this retraction. For progressives, I didn't think it could get more pathetic than voting for a disastrous proxy war that the US provoked and prolonged, handing billions to arms makers in the process. In retracting their tepid calls for diplomacy and blaming staffers for it, they somehow surpassed it, tweeted Aaron Mate. Certainly speaks to the insanely hawkish atmosphere in Washington that pressured the progressive caucus to withdraw a totally reasonable, responsible and necessary call for diplomacy in a conflict that risks escalating to nuclear armageddon, tweeted Rania Kallik. Imagine being elected to Congress based on promises of challenging the establishment or whatever, then being so petrified of anger from bipartisan DC establishment mavens that you can't even wait 24 hours before meekly retracting the only mild dissent you've expressed, tweeted Glenn Greenwald. I don't know what pressures were the ultimate deciding factor in the CPC's decision to retract its feeble advocacy for a bit more diplomacy, or how much of that pressure was brought to bear behind the scenes by bigger political monsters in the Beltway swamp, but ultimately it doesn't matter. The important take home from this lesson, once again, is that progressive Democrats are worse than worthless at opposing the mechanisms of oligarchy and empire.  Aside from the occasional empty soundbite about healthcare or debt forgiveness, they're not doing anything to advance progressive agendas which make American lives better, and they're certainly doing nothing to impede the expansion of the U.S. war machine. The progressive Democrat is a myth, like the good billionaire or the righteous American war. The squad is nothing more than the social media savvy branch of the Democratic establishment. The United States has two warmongering oligarchic parties, and a tremendous amount of narrative management goes into manipulating, cajoling, and coercing Americans into staying psychologically plugged into that fraudulent political paradigm. This comes at the same time the Defense Minister of Romania was forced to resign for saying peace talks were necessary to achieve peace in Ukraine. It just reveals so much about where we're at and where we're headed that the most incendiary and outrageous thing you can say in our society is that we should probably attempt to diplomatically deescalate hostilities between nuclear superpowers. The fact that the Overton window of acceptable political discourse has already been dragged that far in the direction of warmongering insanity prevents peace from ever having any space to get a word in edgewise.


than three of you. I have given this talk in a room of three people. So hopefully, no, they had a lot of trouble. But we got to work back and forth and figure it out. Anyway, so you're here to learn Elasticsearch. I've got 50 minutes, I believe. So we'll see if I can fit an hour-long talk within 50 minutes. Hi. My name is John Berryman. Just to do a quick introduction to myself, find me on Twitter. A lot of my self-worth is derived from my Twitter followers. So growing up, I was a pretty, pretty nerdy kid. Started reading programming manuals when I was in the first grade. Ended up getting into aerospace engineering. That was my first career. Decided that satellites and all that stuff were pretty cool. But I liked the programming and I liked the math. So I moved after about four years in the field. I got into search technology. And I was consultant. I wrote a book. That guy right there wouldn't necessarily recommend doing that with your life. But it's a good calling card. And now I work at Eventbrite. I am a discovery engineer. So search and recommendations and stuff like that. So to give you a little preview of what we're going to talk about, this is not really an advertisement for Elasticsearch. But what a lot of what we're doing involves my mental model thinking through the Eventbrite problem. So just to give you a little shared background. Historically, the company I work at, Eventbrite, has been a very organizer-focused startup. We allow organizers who want to put on their own events to come to our website. You can build a nice little web page with little effort expended. You can sell tickets. We take care of all the credit card mess. You have a platform for messaging attendees. And we gather metrics. So after the event is done, you get to look back and make sure that your next events are as good or better than this event. But after years of actually nailing down this side of the market pretty well, my company realized that, look, we've got all this inventory. Everyone, we're basically white-labeled. But everyone is plastering their events on our website. If we can turn around and sell our inventory to everyone else, then organizers are happy. The customers are happy because you can find something to do over the weekend. And we're hoping to generate the so-called flywheel effect. And this is exciting for me because this is where I belong. Creating the marketplace is all about building search and browsing and recommendation features for Eventbrite. And of course, this technology is based on elastic search. But we're talking about it today. Can you guys keep it secret? So I know we're supposed to talk about elastic search today. But I got to tell you, I'm actually more interested in talking about my new startup, EventDark. Yep. So don't tell anybody, but I am going to directly start competing against Eventbrite.  I know we're supposed to talk about elastic search. But elastic search is hard. So I'm going to focus this new startup, and you guys can join me if you'd like. It's going to be focused on MySQL because everyone knows how databases work. Databases are easy. And let's just build on a tried and true platform. And let's not overthink it. And our specialty, because I found a free data thing online, is cat-related events. We start at cat-related events. Good. So we have some attendees already. And then we'll expand other fields. All right. We have someone who will lease by our ticket. So we have a marketplace. Excellent. All right, so building this new website is going to be pretty easy. There's not really too much to an event. So here's our schema with MySQL. We're going to have IDs, an integer, name, description, city, start date. You can look at all that. That makes pretty good, simple sense, right? And my hypothesis that I know will play out well is that we can build a website based on this. And I'll demonstrate it. So here is our event search. Select star from events. That gives us all the details we'll need back for the website. We have date range search. Obviously, you'll need that to find something this weekend. We have geo search. Not hard. Why invest in all that stuff? We can just do string matching. And finally, it's easy to search for events that you like. So I wanted to find an event where the name equals cat. The results are nothing. Oh, so this is interactive part. Why do you think there might not be any results for that particular MySQL query? Oh yeah, okay, so that's a little problem. I could spell cat with misspellings. These are all, you guys are overloading my brain, but I think we can still make this work out. Now you guys can't spoil all my slides before I get to them, all right? So the particular problem here is probably no one's gonna, to the first answer, no one's probably gonna name their event cat. Would you like to come to see cat? So, okay, so MySQL solves this for us. We can use a like query, like percent cat percent. And the results come back is, yeah, teach your cat to niche an evening of cat bowling and BYOC cat dance party. This is, we're on board. So, okay, so that was just a silly thing, just to show you that we can probably accomplish this. Let's get more serious with a more serious query. Someone's likely looking for a cat farming seminar. So we're gonna help them, what? Not in a bad way. That might have particular meaning to you that it doesn't to most of my audiences. No, not that event. So anyways, so how do we look, how do we search for this? If someone comes to our website and they look for cat farming seminar, select star from events for name like percent cat farming seminar. Results, well, it's in red, which that's the thing I would like to match, but it doesn't match. Interactive time, what have I done wrong now? Case, that's right, right, right. MySQL is all uppity about case, so this is also not hard. All we have to do is whatever the people type to us, we lowercase it and it'll still work. Cat farming seminar, so okay, great, that matches. But seminar for farming of cats, not such a match. Anyone have any ideas how I can deal with this one? Cats or farming? Well, let's try and, I want to make sure. Yeah, so okay, so let's do something like this. Good idea, good idea. And, well, it's starting to itch me a little bit because I heard that like is not as efficient of a query as just like a pure match, but surely not, right? And we're doing it three times, so it's kind of like scanning every document in the database three times, right? But we'll probably shard it and that scale will be fine, I'm sure. So anyways, we do indeed match that. Seminar for Farming of Cats, but we don't yet match making a cat farm the seminar. And now you're totally in my head because I didn't realize that this was a potentially derogatory thing. Making a cat farm the seminar. So why does that one not match? Farming and, well, but they're the same thing, right? Yeah, so it's like, with search technologies, they do a pretty good job about understanding language and I guess we'll have to like cut off the ends of the words. So farming, farm, at least, that'll match farmer, farms, that'll match other stuff. And we indeed do get back the results we want. I'm starting to poke some holes in my little theory here, though. This is an old presentation. Are you telling me I should retire my presentation after this time? Oh, yes, you're right. Okay, so I should have updated the dates on my examples on my slide. For Mr. Michael Handler in the front row. So next one, cat farm class. Doesn't match either. It's a class. It's kind of like a little mini seminar. In order to make that work, I'm gonna have to do, what am I gonna have to do for that one? Oh, okay, okay. It doesn't match all the terms, but at least if it matches like a couple of them, that should be good enough, right? So I replaced my hands with oars to someone's suggestion earlier. And what happens? I do indeed match everything I want. And I match all these things I don't want. And since there's no notion of which match is better than the other match, all the stuff with a cat event goes to the top and this is the whole thing about cat events. So guys, I think we're sunk. I apologize for taking you through this startup with me, but databases are very good at some things, but search engines and search technology are very good at a different set of things. In particular, search engines are quite good at finding documents that not only just match exactly what you have, but contain specific tokens and phrases of the tokens in different mutations of the tokens. They understand English in a way that I think you'll understand when you leave here. Scoring and sorting of documents. MySQL finds the set that matches, whereas Elasticsearch, as we'll see in a little bit, you can put into it an understanding of how good or bad a match is to particular search terms. And finally, this is something that both MySQL and Elasticsearch are good at, but it's become an interesting, more recent use case with search technologies. Searches are actually really good for filtering, grouping, and aggregating data. So search engines came out of information retrieval field, but they're being used more and more for like log analytics and stuff like that. And we'll touch on that right at the end. All right, so now since we've failed, let's go ahead and get back to the main talk that you guys got came here for. We're gonna teach you about Elasticsearch, and in the next 30 minutes, we'll do a really quick and dirty application. I'll show you how to pull down Elasticsearch, create an index, index stuff, and retrieve it. We'll take a peek under the hood so that you can see the data structures and algorithms in place. Fortunately, the data model for Elasticsearch is simple enough that you can leave with a basic understanding of it. And we'll get, as I promised, we'll get into some of the data aggregation stuff that Elasticsearch has been used more recently for, and then we'll have hopefully a little time for questions. What in particular I want you guys to get out of this is a couple of meta goals. One, I want you to see me using the very basic implementation of Elasticsearch, and I want it to be approachable for you guys. So it's a tool on your shelf that you can grab for and learn more about when you need it. The second thing, and I encourage you to do this with any technology, any data store technology that you want to use, I want to impart an intuition about how these data structures work and what they're good at, and a little bit about what they're not good at. This means that when you reach the shelf to get your tool, you actually get the right tool. So building a basic search app is not that hard. And you can get, I'd say for, there's a lot of tuning that comes with Elasticsearch and getting the behavior and the relevance, notion of relevance, just right. But getting the thing out of the box and turning it on, it'll actually get you about 50% of the way there. So it's a real quick technology to get up and running and get some good results. In order to install and run Elasticsearch, this is pretty easy, you all probably know what WGATE is. So you can pull down the, find your favorite mirror, pull down Elasticsearch. In this case, I do need to update my notes here. It's a little bit older version of Elasticsearch. But pull down, unzip it to whatever, wherever you want it to live, CD into that directory, and then start the binary, bin slash Elasticsearch.  Like in case you forgot that it was for search. But Elasticsearch is now up and running. And just like with MySQL, with Elasticsearch, you will want to think in advance about the type of data that you're gonna be interacting with and build a schema for it, or as they say in Elasticsearch, a mapping. Now, Elasticsearch is interesting here because early on they advertise that they were a schema-less data store. In the age where MongoDB was rocketing off, everyone was kind of tacking on to this. And it was true to an extent that you could just start dumping information into Elasticsearch, and that's gained Elasticsearch a lot of popularity, but it's still kind of an anti-pattern. So in my opinion, over years using this technology, it's still very important to think through what you're getting ready to do with this thing. So setting up the mapping is simple. Everything in Elasticsearch is a JSON interface. And in this particular, this is a Python conference. So every example that you'll see here, I am using the Python client, but it's really nice. It's really a fairly thin layer over the JSON interface of Elasticsearch. So when you're setting up the schema, all you have to do is specify the fields that you're going to have, in this case, ID, name, description, city, start date, price, and you get all of the things that you would typically think of existing in a data store. So you have numbers, integers, floats, strings, dates. So you can start to get more complex things, like dates, you can get locations that are a little bit more aware than just two numbers.  But one thing I'll be focusing on is not only can you have strings, but you can say that your strings are special in some way. For example, an ID is a type of string, but it is a string that is not analyzed. That means that we're not going to do any special massaging and trying to understand this as a string from natural language. However, both the name and the description here, I've marked as having an analyzer that is English. So this is me giving Elasticsearch a hint that not only is this blob of bytes actually text, but it's text of English. And I'll show you what that means to Elasticsearch in a little bit, but it's interesting because you don't have to put English here, you can put Chinese or Japanese or any language, most any language that you'd want, and you can make up your own stuff. So there's interesting things that you can, extra rules you can put in for like if you have camel case strings because you're indexing programming languages, you can break it up and make your own analysis chain for it. And then of course, here's me using the client. You create event rights with that mapping structure. Okay, so we have an index set up ready to receive events. Actually adding the events at that point is pretty simple. You have an array of events and it's just JSON blobs again. The client is nice because you can do, you can use date times and it does the right thing. And then the simplest version is for just an iterator, for every doc that you have, then dump it into Elasticsearch. This does make an HTTP request for every doc so there are batch methods once you actually really want to put this into production. That's an easy way to get up and running. Okay, so now we've got a bunch of documents in the index, the next bit is to pull stuff out of it. And the easiest way to explain this, oh yeah, sorry for the microscopic text. How horrible is that to people in the back? I'll just speak louder. So the simplest building block for pulling stuff back is this match all query. And it does exactly what you think. It's effectively the select star from the events table. It gets everything back in the order that you indexed it in. And you don't have to understand what is on the screen here, but I'll provide these notes on my Twitter account later. You can see it, but it gives you back what you'd expect. It tells you how much time the query took. It tells you if there's any errors and obviously importantly, it gives you all the hits back. All the documents that match the query sorted by how well they match the query. In the case of match all, there's no notion of relevance so you just get them back in the order that you index them. All right, so that was like the hallow world of making a query, but there's a lot of different things you can do to craft the notion of relevance. What is an important document? What should match? What should not? And the smallest building block for these is the so-called term query. So if we have an index document, it's in an event in Nashville, if I wanted to make a filter over all the documents and only hit documents corresponding to the city Nashville, then that's a term query. I say this is a term, the field of city, the token is Nashville. The special thing about a term query is just like earlier where I said not analyzed, term means that this is just a token. It has to be capital N-A-S-H-V-I-L-L-E. Doesn't do anything special. And so that's a match. But where it gets interesting and where you really get a benefit from a search engine is when you start incorporating this notion of, hey, this is not just a string, this is actually English text.  And so rather than looking for sort Dilbert, the exact tokens there, it knows that it can be lowercase, we can split on spaces. Sorting and sort should be basically the same information. And so that's a match. So compared to what you think about how you'd have to do that in MySQL, you would have to make a horrendous query to make that one simple match right there. And it would also be very poor performing for reasons that I'll get into in a little bit. Getting more and more complicated because your application has to have a lot of different ideas mixed together. You can do phrase matching. So not only do we have the notion of matching documents that have these terms, but we want a document that has the term sorting and Filbert in it in that order. This is not a match because the original document had Filbert sorting. However, if we search for Filbert's space sort, that is a match despite the fact that it's different from the original document. Original document has uppercase and has different parts of speech. But think about as a user looking for something, you don't quite remember the name of the movie, but you're probably gonna get something like this. So getting these type of fuzzy matches is a specialty of search technology. Filbert fun won't match because there's space between Filbert and fun. Just more example of how match phrase works. But you can add this notion of slop and everyone chuckles when I do that one. That's what it's called. You can add slop and it'll find any document that has these two words within a space of two. And you can go nuts with this. I once had a gig with a US patent office and their search technology that they were getting rid of and moving to a different search than the Elasticsearch Solar, they really wanted to know, I wanna find this word within the same sentence is some other word and I wanna find it before or within some number of words. And so you can take this same behavior and overload it and get some really complex search behavior. But everything I've showed you to this point is just like atomic. It's like I want this thing or that thing. You have to have a way of gluing these things together. In Elasticsearch, that is a Boolean query. In normal notions of Boolean queries, in normal notions of Boolean, you think ands and ors and nots. Elasticsearch has that but using different terminology. Rather than ands, we say must rather than should or we say should and then not is must not. So that one makes pretty good sense. But the idea and if you play around with a few queries, you see why they moved to this terminology. Usually you have an array of things that must match. So in your Elasticsearch query, you have a must key and so you stick everything that must, all these sub clauses that must match there. And additionally, you have several things that don't have to match but should match. If they could match, if you could find documents that also happen to have these other things, it should boost a little bit higher. So that's yet another array of things that if it matches, then you get a better score. Each one of these pieces, you have the ability to also adjust weights. So we're starting to get into a notion of how search understands what's important to your customers and to your business. You can not only match documents that match their queries, but you can also boost documents that we need to sell quickly because they're expiring inventory or something like that. And that leads us to our next big topic, search relevance. I'm curious, how many people here have heard of the notion of TF IDF? Okay, only this half of the room, that's interesting. You guys should have mixed in a little bit more. It's not a hard concept. And so I think it's intimidating at first, but I can break it down pretty easily. This will be a little bit of a mathy slide, but not too bad. First off, TF is really, just means term frequency, and I'll get into that. And IDF means inverse document frequency. And the best way, rather than giving you the Webster's definition, the best way of explaining this is through an example. And let's say a user comes to your website and makes a search for the diddle. Now that seems odd until you realize that one of the matching documents in your index is hey, diddle, diddle, the cat in the field. That's actually a pretty good match for it. So let's do a little practice round and see what this document would be scored as from the search engine's perspective. Term frequency is simply the number of times a term occurs in a document. So the TF or V in this case is two. The occurrence of V is twice. Similarly, just by coincidence, diddle also occurs twice. So TF for both of those guys is two. So far so good? Inverse document frequency. Sometimes I just wish they called it document frequency and just put a one over it. It's basically how many number of times, so the document frequency is how many number of times the term occurs not in this document, but across the entire set of documents. So document frequency for the, pretty high. So the inverse document for the is just about zero. Makes sense? And the document frequency for diddle, not a very common word, is about it's only occurs in seven documents. So it's actually very important and it gets an inverse document score of one over seven, which is a lot, lot, lot higher than zero. So when you finally are figuring out the total score of this document against this query, you put all those pieces together. The score is the TF IDF score for the plus the TF IDF score for diddle. And you probably make sense, but just be a little bit redundant. TF of the is two, IDF of the is zero goes away. TF of diddle is one seventh, there's two and IDF is two seventh. And so you get the final result of 0.2857, but the idea is every document is going to go through the same process and be sorted. And so the way that you craft your query informs the way that this math works and the documents that you have about 10,000 matches, but you wanna make sure you do the right thing. So the top 10 search results are what they want. Okay, yep, so that was a pretty overloading slide. I always like to take a break after heavy slides like that. And I think play work is really therapeutic. And in particular, I think that this, this is, this is my favorite one. That's great. We're gonna watch that one more time. I love this part of this talk. Okay, service is a good break. So to this point, how much time have I got left by the way? So at this point, we've done a lot to get you in the mind space of how search works from a mechanical perspective, how to dump stuff in, how to pull stuff out, what it can do as compared to other data stores like MySQL that I was picking on. The next thing that we wanna do is dive inside the data store and give you a little of intuition about how the pieces inside work. And what you'll find is it's not that complicated. So after this section, you'll have a little better understanding about when it's right to use Elasticsearch and when it's not. So getting data in, in any data store, there's two main chunks that you have to understand how you get data in and how you get data out. So that's the outline for the next bit. The first step of getting data into Elasticsearch is a step called analysis. And basically we're gonna take a document and in this case, I've got just one field out of a document and I will show you how it effectively gets shredded and rearranged and shoved into the data structures that make search technology so fast. Our example in this case is the, send it's the conspirators conspire conspicuously. I chose it so that I could almost not pronounce it at a conference. Tokenization, that's the first step. In this case, we have told Elasticsearch, hey, this is English and that gives us some interesting things that we can play off of. We know that English is split on white space and also punctuation, we can basically throw out punctuation. An interesting side note that I always like to make here is this is not true of a lot of languages on the other half of the earth, right? So like my wife is Japanese and so there are places where you could have symbols right next to each other and they're different words and the same thing, doing the same thing in Japanese, which you still have to do, you have to have a really complex algorithm to know where the best place is to split these things to make a logical sentence. So tokenization itself is a fairly deep topic. Next step is actually a fairly shallow topic, lower casing, pretty easy, but if you have someone type in lower case, you better make sure that it matches a document that has uppercase letters. Stop wording, a lot of the words in English are just noise words. They help us understand where things are placed relative to each other, but they don't really change the content. So we can throw away words like the and is and was and stuff like that. And perhaps my favorite step of analysis is stimming. This is another place where, because we've given Elasticsearch the hint that this is English, it knows some interesting tricks to do. If you want a document for farming to match a query for farms, which is often the case, then effectively what stimming does accomplishes that. You can take a word and using a statistical technique, you can effectively chop off and sometimes modify the end of these words to make tokens that are easier to match no matter what the intent was of the people searching. All right, next step after analysis is indexing. So our example sentence has turned into these three tokens, conspire, conspire, conspicue. Sounds like Latin. Let's say that this is document one. The secret sauce of Elasticsearch for being so fast is effectively during the indexing process, it takes these sentences, turns it into a bunch of tokens and then it effectively transposes that. So instead of document one has these tokens at the end of the analysis, when you've gone through all of your documents, you say these tokens have these documents. So document one had these tokens, but in the end conspire appeared in document one as well as these two other documents. Conspicue appeared in document one as well as these three other documents. And so effectively from a Python point of view, you could implement this with a dictionary where the keys are tokens and the values are an array of IDs. Now under the hood, this is actually implemented in Java and they do a lot of sneaky stuff. They shim extra information in the keys. So all the notions of document frequency, which we use for scoring, get shoved over into the keys when you look stuff up. And all the notion of term frequency, that's the other half of the TFIDF, are basically hidden into the values on the right as well as other information like the positions of the words in the documents so you can do phrase matches and stuff like that. But effectively, a simple search engine is just a Python dictionary like that. All right, so we have now gotten all the information into the index. The next half of the equation is getting information out of the index. So our inverted index looks like this and make this interactive. How would, given that data structure, what's the easiest way to find all documents containing conspicuous and aardvarks? Anyone? Yep, that's all you have to do. Effectively, you have, these are lists, but they might as well be sets or iterators and you find whichever one IDs occur in both. And you can build arbitrarily complex things on the same idea or just a set union. And if you combine a more complicated search, it's a set union followed by a different set or set intersection. Pretty easy. So, but that's only half the puzzle because my SQL is really good at finding documents that match. I just showed you how Elasticsearch finds documents that match efficiently, but Elasticsearch has to turn around and do a sorting algorithm that is part of the important aspect of search. When Google gives you back the 60,000 results it supposedly says you have for your query, you only see the top 10 and they're usually pretty good. If you scroll down 50,000 pages they would probably be less good. So it's important to know how that works. Effectively, what happens is when your user gives you a query you have an iterator of all the documents that match. And so what you do to find the top 10 is you initialize, you have a priority queue. Do you all know roughly what a priority queue is? We can talk about that. But effectively what you do is every document that comes through you take it off of that iterator, you look at all the other secret stuff we've hidden in there and find the score for that document and now you put the document and that score on your priority queue and there's something there that's just iterating doing that with every single match that exists. The interesting aspect of this priority queue though is that it doesn't keep up with every document it ever sees. It's only of length 10 or whatever you tell it to be. So as soon as you get past the top 10 documents you've got one that scores lower than the documents then it compares itself to not even 10 like it's log, order log in or whatever. It compares it to a few of the documents and says I'm lower than all of these. Never think of me again. And so the action is actually pretty efficient. Now there's a little side note. This is another intuition that might be important for Elasticsearch. If you're doing some sort of relevance but you also want to return 100% of the documents think about how you to implement that.  If you've got a robot scanning your website for the 10,000th to 10,010th most fun event then this means that you have to have a priority queue that is 10,010 long and you sort all the documents in, throw away the first 10,000 of them and give that chunk back. And guess what happens when the robot goes the next page carelessly? It just gets worse and worse and worse. So that's one important intuition to think about search technology. Elasticsearch allows you to turn that off so if you don't care about relevance but if you do I would recommend not letting anyone get past about 500 results. All right and then Ari said it returns the most high priority contents for that queue. That's effectively what we do. Like after top 10 they go away. The data structure is only 10 items long so it can't hold anymore than that. Oh yeah, yeah, that's not a bad idea. I don't know how I would implement that in Elasticsearch. I don't think they make that easy for you but yeah, that totally checks out. All right. Okay, so I need a little transition slide here but effectively that gets us through everything that a search engine has been until about three years ago. But Elasticsearch came out of information retrieval, library, technology type stuff, finding whatever I wanted to find. But Elasticsearch has started to prove the point really strongly that the same data structures that serve search results are actually really good for online analysis, log parsing, stuff like that and a big chunk of that is its ability to do aggregations. And I think I can convince you that it's basically what we're doing before just one extra step and you get this nice ability to do aggregations for free almost. So just like before whenever we're aggregating we wanna find a histogram of the ticket prices or something like that. We have all the results that we had from before. We do the sorting like we did with them before but while we still got that document in hand we push it through an aggregator. It's basically just a little in memory thing that says, okay, how many documents have I seen in from $10 to $20? And it just increments those counters. For every document it does this and at the end of it you pass back this aggregator thing and you have these really nice results. And it was just something that you did almost as a byproduct of the actual search itself. So with the building blocks that I've given you right now you can see how we have the ability to easily filter just what a search is. You can group stuff because you can see as the documents are coming through you can already figure out which group it belongs to. And within each group you can do calculations to do running averages or anything like that. So to give you a little more intuition about how you might use aggregation here is how I encountered it for the first time. Let's say you go to Amazon, you're chuckling. Have you seen my, that top book by the way is a really excellent book. So anyway, if you go to e-commerce sites you see a lot of the original use for aggregations. They were called facets, faceted search. You have a list of subcategories on the side. You have the counts for how many things are in that category you can click on it and it serves as a filter. It gives you a little bit of what I call relevance feedback so you can understand what's actually happening. But people have taken the same data structure you turn it on its side and you've got really nice histograms which at event right, we're making them prettier now but you can use them to feedback good information about how many tickets are sold from a particular class. You can take exactly the same information but a different data set and give spark charts for how many tickets were sold in a particular day. And you can take again counts over buckets and you can plot it on a map and you've got a really nice geo information console this to give you intuition about where things are happening in geospatial relationship. And finally it's, I don't know exactly how to make a picture for it but analytics, log analytics in particular are great with Elasticsearch. Building Elasticsearch, building aggregations in Elasticsearch is easy. I'm gonna kind of fly through this so I have a couple of questions but effectively all you have to do is you have your normal query. You keep asking your query like normal but you add a new section to your query to Elasticsearch called acts. And in this particular case it's gonna be hard to read so I'll blur over it but you can say things like my aggregations I want you to do counts for how counts grouped by city. So that's a term aggregation where the field is city. And I also want you to do a histogram aggregation for the prices with an interval of 10. So that's the second thing. The results come back and you have the normal search results at the very top but you have a new section that has these aggregations in it. In this case I've got the city bucket right there with my Nashville and Dallas and BFE events. And I've got my price buckets for what distribution of events occurred. But a neat thing that you can do so right now I really needed a graphic for this. Right now I've got two separate aggregations. A neat thing for us to provide back to our users is not only the histogram of all the events but we can do a histogram per each city. And you can do this with elastic search. Aggregations can be arbitrarily nested. There's performance issues after some point but I can say at the top level do a terms aggregation so we bucket everything by city and I get the counts back. And then within that aggregation do a histogram so that we can show our users here's the price distribution within the city that you're interested in. The results turn come back. Very similar structure except it's appropriately nested so that for each city bucket you have the count and within that you have sub-buckets for the histogram so that you can draw it on the screen. That's effectively it. I've been doing this a while so I have a lot of things to learn but a lot of other things that I would enjoy talking about. Also if you're interested in learning more on your own I know of some reading material. And find me on Twitter. Tell me what I did right and what I did wrong. Anyway that's it. What have you guys got? Any questions? So repeating questions I guess right. The question was around how do we deal? We can specify English or not but how do we deal with unknown terms, different languages, jargon terms, stuff like that. The easy answer is you still just say it's English if it's basically English and you still get the ability to split on white space and all that stuff because that's presumably where you might come from. I'll go to the extreme in a second. And you still do stimming which means if it's like maybe a verb but it's a verb I haven't heard before stimming actually does pretty well for English like things. I mean but if you're willing to put the work in it you have an arbitrary amount of control over what you can do. So at the other extreme end of things I mean I guess you could write your own Java. It's all pluggable. It's just Lucene, Java Lucene. You could write your own classes to do whatever custom logic you want. If you don't want to go quite that far there are other kind of middle ground things like synonyms. You can say as a preprocessing step before you do the stimming chop off and throw it into the words you can say here's a file of every jargon word you might see and you can either say don't touch it for the downstream stuff or you can say this maps to three other words or these three words map to one word. So there's a lot of flexibility about what you can do to tune that relevance notion but it might be a lot of work. He had a question first. You, yes and no. Part of that is the not only do we hide the term frequency that counts for each one of those terms that they occurred in the documents but we also hide a few other small things that we stick next to the tokens. We hide its position in the document which gets to your answer about phrases and you can also hide, there's a couple other things that aren't used as often but like you can hide part of speech there if you have that set up and you can hide a payload which you can do whatever you want to if you can boost on documents that have certain words in it, a little bit higher but it's still there. One thing you can't do though is make a search and reassemble it into the original document from this data structure. That's why whenever you store a document elastic search it gets shredded, turned into that and at the same time you have a different file on disk that's holding the memory that reads the original document out. So you're effectively storing it twice every time. A document at Eventbrite is an event and it has what I call the boring fields that are expected, the name, description, the date, geolocation which actually that gets interesting. But we also have, this is in progress but we're working on interesting fields like machine learning things like event cluster that we can later match up with a user cluster that comes in or event quality which is another thing that we're inferring from the metadata around it. So those are all things that elastic search is happy with dealing with and then there's not too much more than that that's mind blowing from departure from what I showed here. It's elastic search. This is a data search. It's a, yeah, JSON record that's, we do exactly that thing with it. Hand it to elastic search and make it variable. Elastic search stores both, like connector type things. We rolled our, when I was in solar land, the predecessor sort of to elastic search, there was a lot of plugins where you could connect them. I forgot what they called, pipeline thing, ETL. There are some of those for elastic search but we ended up just rolling around because we wanted to control over it. So not a very specific answer, one more. I think he had his hand up first but please talk to me later. So James, really cool question. A really cool benefit of elastic search is it's a write only index. So segments on disk effectively are never touched again but the caveat is when you actually change a field what you do is you go back, find that record where it used to be written, read out the entire document, change that one field and write it to a new segment file and the only place you can change the old file is you mark one bit is dead. James done it. So not great but it's a trade off. You get benefits for treating it that way. Definitely not a table scan. It's still pretty quick. Cool, so I have exactly zero minutes left. Please come back, talk to me later and thank you very much for coming.


Hello, I'm Charlie and welcome to Authentic Mental Health, the channel that offers advice and friendly support within our like-minded community. Today's video is coming up right after this.  This isn't authentic mental health anymore, you've got one more chance. Hello, I'm Charlie and welcome to the rewired soul. Chris is still away so you're stuck with me, unfortunately, sorry, can't help it for another couple of days. So what I want to talk about today is how the lowest point of my life made me who I am. So the lowest point in my life was in 2016. I was 22 and I was at rock bottom, literally I couldn't go any lower in my life. I couldn't reach a lower point in my life. At that time I didn't want to be alive anymore, I was considering ending my life, it's just how I felt.  I wasn't getting any better and I wasn't getting any worse because I was literally at the bottom, that's how I felt anyway. My mental health was declining at an absolute crazy rate, it just kept going down and down and down, I was getting more and more depressed, I was getting more and more anxious, I didn't want to leave my house, I didn't want to socialise, I lost a lot of my friends, my family didn't understand what was going on with me, I got out of a relationship where she didn't understand anxiety or depression, she judged me, she called me nasty names, like her family, they also, her mum was horrible to me, she said you need to man up and all these other things that had a negative effect on me and I was kind of like, I can't help the way I'm feeling yet these people who are supposed to care about me and love me are being horrible to me and they're not really understanding how I'm feeling, I just didn't know what was going on with my life. Well anyway, one morning I woke up and I realised I need to change, something has to give, I'm at the bottom, I can't go any lower so no matter what I do from here, no matter what change I make, it can only go up, my life can only move forwards and get better because it couldn't get any lower, I didn't want to be alive anymore, it can't get any lower than that, so I literally for the whole weekend I got an A4 book and I started writing everything I wanted to do down in life, everything, you name it, where I wanted to go, what car I wanted to drive, how many children I wanted to have, how long I wanted to be married for, where we wanted to go on holiday with the kids, where I would get married, literally you name it, I wrote it down in this book and I filled it in a weekend of goals for my life, what I wanted to do, then what I did is I started to figure out and write down how am I going to achieve those goals, how am I going to do it, how am I going to go on holiday, how am I going to afford a car, how am I going to meet my future wife, how am I going to achieve my career goals and what I want in my life and I started to make steps towards that and the only way that that came about was from me being at the lowest point in my life, like I've already said 15 times already in this video, I was at the lowest point of my life, I didn't want to be alive anymore and then authentic mental health came along, the opportunity arose for me to create authentic mental health and it was created, now that's what I'm doing with my life, so I turned a negative, the lowest point in my life, to a positive authentic mental health where I'm reaching millions of people a month and helping them change their lives and what I always say to people who ask me advice or say hey Charlie how can I create a community like authentic mental health etc etc and I say good things come out of bad things, when you're at the bottom there's only one way up and I personally went through that change and I experienced it myself, I have a piece of advice for you and I'm sure Chris will totally agree with me and I'm sure Chris has been through similar situations to myself, as you all know he was an ex drug addict, now look at him, he's done a fantastic job in changing his life and as Chris knows, I'll tell you on camera I'm so proud of Chris and what he has achieved in his life, the odds were stacked against him to even be alive and look at him now, he's more than alive, he's making a positive change on the world, so from his negative the drug addiction has turned into a positive helping people on the rewired soul and he works in an addiction clinic, so well done Chris, but he's just another example of no matter what you do or the mistakes you make in your life you can turn that around, if you have the willpower and you want to change it yourself you can turn it around into a positive, turn that negative turn it around and turn it into a positive, make a change in your life, my advice to you would be evaluate your life, write down everything about your life, what you hate currently about your life, what you dislike about your life, what you want to change about your life and then after all that create a new page, a new book how you are going to change those things, how are you going to change them, are you going to change your job, are you going to change the course that you're doing at college, university, are you going to change your friends, are you going to move out of your house, are you going to rent a new house from a new tenant, are you going to get a mortgage, are you going to buy a new house, are you going to sell your car, buy a new car, whatever it may be, write it down, Have a plan and plan your life and then you can stick to the plan and picture what you want in your mind all the time. Have your goal in your mind. Little secret. When I first started YouTube I never expected, I'm almost at 90,000 subscribers and I never ever imagined when I started YouTube I'd have like a thousand subscribers. That wasn't the goal. The goal was as you already know from yesterday's video if you watched it, the goal was to help people and help myself become less depressed by doing authentic mental health and try and connect with like-minded people. And then I got to a thousand subscribers, then I got to two, then I got to ten and when I got to ten I wrote down in my A4 book I still have it when I write down my goals, my ambitions and how I'm going to achieve it. I wrote down 100,000 YouTube subscribers and every single day since then when I wake up or I go to sleep I picture 100,000 YouTube subscribers in my mind and I think about how amazing it would be and how of an exclusive club you'd be joining if and when authentic mental health gets to 100,000 YouTube subscribers. I picture it in my mind so it's always there. I know what I'm working towards, I know why I'm doing it, I know what I'm doing, I know what I want. That's what you need in your life. You need a goal, you need a plan and you need to stick to that goal and that plan.  But when you get to the end point that doesn't mean you stop, you just write new goals and assess your life again. Anyway that is how I turned a negative in my life into a positive. That's how the lowest point of my life changed to who I am and where I am today. I am who I am because of the lowest point in my life I decided to make a change. If you're at the lowest point in your life too you can also make a change and you can make a change. Look at me, look at Chris, we both made positive, positive changes in our lives to be who we are now. Anyway guys and girls thanks for watching, take care, I'll see you tomorrow.


Hello, my name is Avery, and today I'm going to be talking about the viewer app. To begin, open up the application. This application demonstrates low-level, real-time data streaming, using the structure SDK. The app displays a camera view on the top, a depth view on the bottom left, and a surface normal view on the bottom right. Data is displayed using iOS core graphics APIs. Source code for this application is provided as part of the structure SDK. I hope this video has been informative and helpful to all of you, and until next time, we're all died.


What's good y'all support Ross back again with another video? So I'm gonna be checking out WWE wrestlers who hit their finishers in music videos There are times where Wrestlers end up in different artists music videos. So this should be an interesting one I'm looking forward to this video man. Appreciate all Love and support you guys been showing on the channel man. You guys have been running it up We're almost at a hundred K and I'm very thankful for all the love and support you guys been showing So let's get right into this one should be a good one Cane wrestlers hit their finishers in the ring, but have you seen them do it in music videos during the Hulkamania era Hulk Hogan was so famous He started a music video with Dolly Parton called headlock on my heart The story is that Dolly falls in love with Hulk Hogan who is a wrestler named Starlight Star bright She goes to see the Hulk's turn action during Hogan's match He performs a psychotic finisher the leg drop this allows Hulk Hogan to get the one two three And not only does he win the match, but he also gets the girl Yeah, Hulk Hogan back in that time period. He was so popular He was in movies, you know most of them weren't that good. He was in like on talk shows He was on radio shows. He was guest appearance on other game shows like he was Everywhere because wrestling was so big back then and he was the face of wrestling now This is just awesome We all know that the rapper bad Bunny has gotten into the debit b-ray and beating people up However, wrestlers have appeared in bad bunnies music videos and done the same thing in the song key in two arrays Oh, yeah, and I believe I think he I believe Rick flair was in one of the bad bunnies videos I'm not sure. I want to say he was I could be wrong bad Bunny is a trucker and makes a stop at a diner with his friend They end up getting some beef with a motorcycle game and leave the bad guys decide to chase them down Which they soon regret bad bunny pulls his truck over and confronts the motorcycle game Just as bunny starts to get surrounded out comes stone cold Steve. Wow Nick acts like it's an episode of Monday Night Raw and begins cracking open a can of you know what? The best part is when he nails one of the guys with a stone cold But just like what Donald Trump learned at WrestleMania 23 You can't trust a rail snake and stone cold hits bad bunny with a stunner to end the music video That's cool, but check out the unedited clip Oh That is a bad bunny is a fan of wrestling He's had multiple wrestlers in his videos and he's wrestled at a WrestleMania He is a fan of wrestling. I think that's dope.  I'm a rapper, bro I'm definitely hitting up like a stone cold of the Rock King Please be in my video it can only be for like it can be for five seconds like that's if you're a fan of Wrestling and you know saying you you still watch it or you still support it, bro You happen to rap or do music. I think that's pretty tough He's WCW teamed up with the band stuck mojo to produce a music video for the song rising the video features several wrestlers And the whole thing takes place in a wrestling ring Well, you know some moves are gonna be hit during the song Billy Kidman hits his finisher the shooting star press to the outside of the ring I hope someone caught him later diamond Alice Page steps inside the ropes and begins beating everyone up in slow motion Several moves before nailing a guy with the diamond cutter Oh, not only that but right after hitting one cutter the WWE Hall of Famer hits a second dude with another cutter to end the music video When Rob Van Damme joined TNA for impatch wrestling in 2010 He needed some new entrance music a musician named Cushionator create a song called the whole effing show And it also got a music video in it This guy Cushionator smoke something that makes him pass out and hallucinate that he's in the ring with RVD There's also a small army of other wrestlers who want to beat up mr. Monday night van Dam them proceeds to bust out his signature moves That's one thunder the monkey flip split-legged moonsault and just about everything else However at the end RVD gets on the top rope and executes his finisher the five-star frog splash Luckily Cushionator snaps out of it at that point. This one's kind of interesting That's no music video for a song called the endless Tommy dreamer is trying to chill at his house But his next-door neighbors are jamming as loud as they can when they refuse to lower the volume Dreamer takes matters into his own hands and starts beating the crap out of everyone and I mean everyone What the hell the fans and the band the lead senior tries to crawl away But Tommy dreamer isn't done He and the poor guy end up outside and dreamer takes out the musician with his finishing move the death Valley driver Do it by some padding the only thing crazier than all this is seen WWE wrestlers hit their finishers In public to watch that hit the video. That was cool, man That's that just shows how powerful Like the love for wrestling is man and for me is one of those types of things where At one point, you know, I lost the passion like I wasn't feeling it but I was able to come back and it just it just brings me to the moments when I was a kid when I used to Watch wrestling all the time and and used to just be amazed at what I would see in the ring And it's it's not as popular as it used to be I don't think wrestling will be as popular as it once was but if you're able to still enjoy it If you're able to like really, you know, appreciate the craft and appreciate the work that's done in any ring Doesn't even matter if it's WWE AEW impact, you know, New Japan wherever you love wrestling at even it could be at your local gym What night if you love it, you have passion for it. Don't be ashamed of it, you know, just you know, embrace it You know, like love what you love in this world And it's cool to see some of these artists show their love for wrestling in their own music videos I don't have to but I think that's just a cool thing to show a I'm still a fan of wrestling So comment down below. Let me know. I want to ask y'all kind of a different question When did you become a fan of wrestling? If you can remember your earliest time and saying, oh, this is cool I gotta watch more of this. Let me know for me. I became a fan of wrestling. I want to say It had to be like when I actually understood what it was I want to say I had to be maybe Seven something like that. I had to be like seven years old or something like that. That I was relatively young So man, but that's the earliest moment. I can remember of me being a fan of wrestling Comment down below. Let me know that but I appreciate all the love and support roll two I'm honey. I appreciate y'all kicking with me. See y'all next one. Peace


As of elevated stress, there can be pretty challenging impacts on an individual's physical, mental, and emotional health as well as on their relationships. And if there's anything I could suggest to people, it's to remember that you have a wide range of assets on any farmer ranch operation. Typically, we talk about land and livestock and seed and, you know, buildings and things like that as being important assets. But actually, I would argue that the most important asset on any farmer ranch operation is the health of the individuals who are working in that operation. You rely on your health to help you be resilient during times of elevated stress, and so it's very important to take the time to slow down, maybe to get an assessment of your health, and just make sure that you're taking care of yourself and the people around you so that you can rely on your health as a critical resource during times of stress. I encourage people, if they haven't done so recently, to begin with a visit to a healthcare provider. Healthcare providers deal with a wide range of issues, not just physical health, but mental health as well. And so you can ask for a baseline checkup and assessment of your physical and mental health. Self-care practices that are very important include trying to focus on getting healthy sleep on a regular basis. Sleep provides that energy that we need to handle tasks on our farmer ranch operation, paying attention to your diet, and particularly taking some time for exercise on a daily basis if you can get it. And then accessing sources of support in your life, just taking some time to identify who do you trust, who are some individuals in your circle that you could maybe talk with on a regular basis. That might be daily, it might be every few days, but someone with whom you can share your thoughts, your worries, your your plans, your anxieties, and by doing that it allows you to process some of the stress that you're experiencing, and also think about ways that you might handle those stresses, maybe other resources that could be available to you and just get some encouragement and support from people around you. Fortunately, there's a wide range of great resources out there. I think people can start with our NDSU Extension Farm Stress website. The state of North Dakota has a great website called ndresponse.gov. Again, that's ndresponse.gov and that has specifically a lot of resources related to dealing with weather impacts, behavioral health type of resources and programs, things like that, so I would encourage people to use that website. If you have a need for talking to someone immediately, the Organization First link handles the 211 hotline in the state, which is available 24-7. So through that hotline, if you call 211, you can get 24-7 counseling, crisis counseling, but they also offer referrals to a wide variety of different types of information and programs that are out there to assist people. So if you're looking for a counselor in your area, if you're looking for help with a substance misuse issue, or if you're looking for some kind of financial assistance specific program, they can help connect you with all those resources through that 211 hotline.


Hey everyone, welcome back to another Counter Side video. They were going to be featuring my free to play account after 21 days or after three weeks. Let's see what I have for you guys and more or less if those, no I've had questions regarding free to play, what units to start with, how to do things and more or less add three weeks.  So let's take a look at my units first. Okay, so as you can see here, these are my units, most of them are, you know, I have around six, oh no seven who are at level 100 already and it's been a rough time leveling them up because most of the time you need to level them up during battles and resources are actually very scarce in terms of leveling them up. So again, I only have seven. What's new with this account? So there are two units that are actually I'm proud of and very lucky to get. First is the administration sword fighter, which actually I got through, where did I get it? Through our free one pull every day. So if you notice that we have a free pull every day and I got her there, both of them. So again, I was kind of lucky there. After that, I was actually during the time I was pulling that I pulled for the administration sword fighter, I was actually pulling for Ainz and Zwei. So both of them actually I got from their banner, but it took me a while because I had to pity this banner. Imagine that free to play and had to pity it because I need them because I'm not sure when I'm going to get another, you know, chance at their banner. So I was able to get a lot of recruitment, what do you call this, recruitment contracts in counter case.  So those are my most notable add-ons. Also, I'm trying to level up administration riflemen because to be honest, guys, I actually lack rangers. So let's filter through my stuff here. And if you can see here, the rangers that I have are kind of good because you have Kyle Wong, you have Elizabeth, you have Zhuxun. But the core for me would be Geon, would be Rosaria. Those two, I don't have them. I'm also missing even Xinjiang. So at this point, I am really missing a lot of key rangers, especially because right now we have a lot of awakened defenders like Hilde and Naubin. So I really need a lot of firepower in terms rangers. So for the meantime, I'm actually stuck with them. I'm trying to level up again, as I mentioned, the admin riflemen because they're cheap and they're very good. So that is my, you know, they are my pet projects now. And more or less what I'm looking for down the line, what I see in terms of banner would be Rosaria would be near nearest that would pop out. So more or less, I'm going to pull for that banner. Hopefully Geon will come, you know, around the corner. Hopefully another rerun for Geon because again, I really need Geon in this account. Okay. So what is actually slowing me down as well? Let's take back this filter. Okay guys, so what is actually missing? And I'm, you know, I'm farming for is is going to be prime training data. I actually lack this and the basic one I also lack, but most most that is missing in this account is going to be prime training data. And also for your limit breaks, I don't have enough. If you can see if you can see here with the with the other units, let's go to Anson's way. So I really lack counter ATP cores. It's really a grind and I'm already crafting them or in terms of just converting from other currencies. So I'm actually crafting from this from from mechs or from soldiers going to counters. And it's not really productive because again, if I'm going to use them in the future, then I'm going to farm for them again. So that is my problem right now. But it's going to be slowly but surely guys, after three weeks, I'm actually happy with with what I have. So again, as you can see here, I'm happy with my lineup so far. I don't have any awakened units thus far. The next that's that's going to be projected is going to be Seoyoon, which I hope I'm going to get because again, I'll be I've been eating a ranger. So she's a ranger. So she'll probably be the best ranger that I'll ever have if I get her. So I'm praying that I could get her by that time. And also for my gear, I'm already let's say for Kahlua, I'm already kind of upgrading my gear from either for Tier 4, Tier 5, and Tier 6 gear. Because I'm already farming certain stages working certain molds to the Tekkencraft and the Tier 4 gear. So again, I'm trying to take out my Tier 3 gear already. And as for the summons, guys, as of the moment, I'm not any more summoning for any banner. I'm actually just waiting for for Seoyoon to come to come by inner banner. And also I'm waiting for Rosaria's banner. So those are the banners that I'm looking forward to to augment my lineup. So in terms of my ships, guys, let's take a look at my ships. For my ship, basically, I still have Glypnir. I'm actually having trouble farming for material for Lake Superior. If I'm going to go with Lake Superior, which most probably is the scenario, let me go to HQ first. So ship construction. So I have a lot of options, but most likely the one that's going to benefit me more would be Lake Superior. So I lack these materials. So special ships, schematics, that is the one that I'm lacking. I'm lacking 26 pieces for this one. So more or less, it's going to be a done deal. Unless you guys have any suggestions for me, you may put them down in the comments section below so that I might choose another ship. So I have other choices here, including New Ohio, your armored type, Kamizumi. I'm actually veering away from Kamizumi. So that's it. These three are more or less my options at this point. So again, put down in the comment section below which one should I get next for operators. I actually have an interesting operator. It's actually the most recommended for beginners. So actually, I got Lena Mackenzie. So it's a simple buff. So as attack, attack speed plus eight to all allies for 12 seconds. So again, I opted for her instead of instead of Sigma because for me, I think for a beginner account which doesn't have that variety, this one is very all around. So I'd rather go with her at this point. Okay, in terms of the event, I'm actually farming this event right now. I'm farming this together with supply operation either or depending on what I need. If I need more materials for gear, I would usually farm here the 1-4 in military supply acquisition. So this is where I would go. This is where I would spend time in farming for better gear at this point. Also for side story, I'm already here at SWAT 4. I haven't opened this yet. I'm actually, it's okay with me because I'd like to farm Kangso Jung first. I actually need her more than Maria at this point. And for simulation, I'm already unlocked up until level 90. So again, I'm farming those every day. All three of them are actually at level 90 already. Then as we go to the world map, so for world map, I actually have three bases already. I'm doing great actually with in terms of the bases that I have. So I have two things to do today. And also for danger clothes, I've been struggling a bit because I don't have the right pieces sometimes to clear the boss. So this one I will be struggling, I'm sure. So I'm at top 88%. So it's very low. So it's okay guys. Eventually I will be able to climb this content. I'm actually just, I'm not sure if I completed it. I don't remember. I don't think so. I don't think so. And also for dive, I'm already at 35. So this runs up to 45. The problem is the third ship or the third squad that I have isn't that good yet. So if you can see, sorry, squad, yeah, I'm here. But for the third squad, it's not really that good. It's just a band of misfits that I've put together. Squads one and two are pretty much okay. Some of, I'm still leveling up. And this squad standing by is actually kind of okay. Third squad is not okay. Again, I've been struggling on leveling up and developing our training skills for my units thus far. But again, what do you expect? It's free to play and it's only been three weeks or 21 days. So I'm actually, again, I'm happy with my progression so far. And lastly for Gauntlet, for strategy battle, I'm not really struggling here. This has been good for me. I've been able to choose the right match for me. So I'm at Platinum too. But my only gripe actually is with ranked battles because it's really funny that I seem to find a lot of players in bronze, take note, in bronze that have a lot of awakened units, but they're still in bronze. I'm not sure why. It's not really expected that they're still here. They should be probably in silver and gold, at least or vying for Platinum. I'm not sure why they're still here. So that is actually my problem because most of the time, if I run into awakened units, let's say I have a 66% chance that I'll lose that game. 33% is more on if I can deploy the right kind of unit for that awakened unit to take it out. But again, it's a bit tricky and it's actually a mystery why I keep on encountering a lot of awakened units even in bronze. So if you guys have an idea why that's happening, be my guest, put your comments down below. So that is it guys. Well, what can I say? At 21 days or at three weeks, I'm happy with my progression. I'm just actually banking on a little bit more luck in progressing forward, hopefully in summons. Because again, if I don't summon the units, at least a copy, sometimes it's really, really hard to progress, especially in PvP. And also in content, some of the content need a specific hero to clear or at least have a high score. So again, I hope I would have better units to show you probably a week from now. So we'll see, we'll see, we'll see, we'll see what happens. Anyway guys, for those of you who have stuck this far, please consider subscribing, click that bell icon, and also put a like to this video. Thank you guys, stay safe, this is The Warden, and I'm out of here.