Is this thing on? All right, the audio visual guy was not wrong. We're just gonna keep this going Okay, um, so thank you first of all David for Giving me the opportunity to do this. I love sharing learning lessons. It's a part of my job and it's a part of me So this is fun to do again The story I'm gonna tell you today is Kind of all about how I didn't know what the hell I was doing for most of my career But that it oddly prepared me for what I'm doing now a job that I'm really excited about at Acquia that I just really adore and All those wrongs Turned into a big right. So that's where I'm going with this in case you're like, why is she telling me so many things? so When I started out as a youngling many moons ago, we won't say how many I wanted to be a developer. I was like Love making things and I want to be an architect and figure this out and oh my gosh my thing works And this is amazing. I felt really excited about it. I thought that's gonna be my career By the way, I should say before that I wanted to be a professional floutist and a French teacher So on the spectrum of things that I'm interested in it's very wide But in this case I wanted to be a developer. I was really passionate about it and I was Really into it and I decided I'm gonna go to school for this And I went to college and I started, you know Learning how to do things learning Java and all this stuff and I realized I was terrible I was that person who was like at 2 in the morning working on their thing and their little program And just calling up all of my guy friends because I was the only girl in the class by the way And calling them up me like, I don't know why this won't run.  I decided all right. That's it. I'm giving up on this But I'm staying in this field because I like IT. So I'm gonna do design. Maybe I just was in the wrong Maybe I was like, you know in the wrong fields. I'm gonna do designs that I did design. I Was not so great at that either Didn't do the most beautiful things there were better than some other ones But I wasn't talented in my own opinion at that time I didn't realize that I had to like actually do tons and tons and tons and tons and like really train and learn and Study in order to become a good designer because I was young and naive Then anyway, that was another thing I was wrong about So then I moved into Information architecture and I realized that that was really boring to me. It just wasn't interested in it at all so that was another thing I was wrong about and then I moved into Project management and that kind of stuck like I really liked I did that for about 10 years and All of those things like having done I did UX and UI as well, but I wasn't super great at that either By the way, so that was another thing. So I was like wrong wrong wrong wrong wrong Pretty good. That's a pretty good fit and today I am a program manager and I realized why this is such a good fit for me In one part is because I learned about all of those things all of those wrong decisions all those years wasted in career paths that were not for me Clearly ended up being super valuable to me today when I talk to developers I can understand where they're coming from when I talk to designers I know how hard their job is to get someone to describe what they want It's really really hard UXers and UIs how underappreciated this like career is and how Immensely valuable it can be and how great it is So I can come at those people and the project managers how they just feel like secretaries. Oh my god. Do I get it? So now when I'm cross-functional and I'm talking to different groups in different parts of dealing with all these things I am so grateful that I screwed up so bad so many times because now I have this beautiful perspective on Everyone's problems and now all their pain points and what they care about because I've literally been in their shoes For a short time when I was just wrong.  You might feel God.  And I understood for myself what I cared about and what I liked I think it was maybe kind of a kiss a kiss a lot of frogs to find your prince situation and I hope that everyone in this room When you screw something up Feel bad about it, of course because then it motivates you not to do it again But also just like learn from it. What can you learn about yourself? What can you learn about other people? How does this enrich your life and for me? That was the best lesson that I could take from failing at like five careers So that's how I was wrong That was only five minutes Hi, my name is John Ferris. We're for ad-design group David's not here, but I did want to thank him for Thinking to reach out to me for a session entitled I was wrong Appreciate that that vote of confidence So I thought a lot about what I wanted to talk about today I've I've made a lot of mistakes in my life. I've been wrong wrong a lot Thought about talking about You know developer issues. I lead a team of front-end developers. So, you know talking about testing your code or When did when to deploy when not to deploy anything like that? But I kept coming back to Something that happened. I think I was maybe a senior in high school I Used to I come from a very I guess joyful or A family that laughs a lot. I'm the youngest of five We like to to make fun of each other.  So I assume, you know other people like to get made fun of too So I do that a lot just trying to make people laugh And then one day I was sitting with my friend Mike He's a friend of mine, I've known him since I think we were four We grew up a couple houses down from each other. He's just an amazing person like he was Balaviktorian of our of his class He actually got an award for perfect attendance for all 12 years of school Like a letter from the president. It's just that the kind of guy that he is he you know graduated From the University of Arizona and like three years with dual majors in microbiology and like Choir directing or something like that.  Don't Don't say that about other people and Like to me There's something I think back about a lot you Know I met I was actually visiting him in New York a few weeks ago and I actually told him this story and He didn't even remember it like didn't even like, you know, it's just an insignificant moment in his life And I'm like, I'm even saying it now. I'm getting choked up Because it like really affected me So now I think about like, you know if I'm on Twitter or something and I'm about to say something snarky because that's all I have to say and Like I'll check myself. You're like, what would Mike do or not really but you're like, yeah, I'll just keep this one to myself You know be taken out of context. This might hurt someone's feelings It's not worth the joke Even happened, you know a few years ago when I first started with that and we had a I don't know a client left a message in base camp and for some reason I thought like The actual words that they wrote taken out of context were hilarious to me and I thought it would be funny for everyone else to see it too.  He's like Don't don't say that like don't ever like we have a standing rule like one don't ever Put anything bad about a client and writing and in general just like don't talk bad about a client in general we're on the same team and You know, of course I saw that email and I was like Oh What did I do now super apologetic and he's like don't worry about it. Just don't do it So I guess the lesson for me is not so much, you know, you know, yeah, don't be snarky.  Just kind of without really knowing it testing our own boundaries like pushing things and it takes people to You know say You know, don't do that. It's not You're wrong So I guess I would tell you to or encourage you to you know, tell other people they're wrong Like don't do it publicly just take them aside and be like you know that People might take that better, you know, you're hurting people's feelings or whatever and That's it. Hi, thanks so Mine My name is Batty and I come from Iceland. I live now in Germany. So I didn't we don't know what we are actually going to be talking about here, but actually Yes Because this is exactly what I was going to say so Actually, my story or what I've been thinking about a lot It's actually personal for me because it was actually difficult at that time So it was like this that we were or I've organized a lot of camps and in in Europe and And we were like organizing this camp Drupal Europe And it's gonna take place in September and we've been doing this basically from September to December or January and we're working really hard every single week and Then finally we it comes to the time and moment that we announce Where it's gonna be and when it is gonna be so we announce it really like hey It's gonna be in Darmstadt in Germany on this time in September and then people start tweeting And then came one tweet from a friend of mine, and he said oh damn I can't get to that one and I was so excited about our event that I immediately just wrote him like hey, just reschedule And I made like a this here, which is like a blinker for those who are listening And then actually a friend of mine He wrote me on a privately.  What do you mean? And then I noticed that there was a long tweeting list after this and I'm like, oh no Did I do a mistake? You know I actually asked somebody to reschedule something. That is a religious holiday and I felt terrible and I felt so bad that I just like it was public. It was on Twitter and So I started to think about like well, I did a mistake, but then I actually realized we did a mistake And that was actually You know that I think the first thing first to think about like I did a mistake of doing something like that But then I realized it was something much more bigger than that, you know We actually did a mistake of not thinking about May having an event at a time that didn't fit everyone So you can imagine what happens to to you as a person or if I just take it on a personal level Yeah, like I didn't know what to do. I Started to like talk to friends and I had really good friends that have been actually going doing stuff like that themselves And and I was like, you know delete the tweet, you know, it's like no that doesn't you know What's it that do and I wish I had like a some kind of a A training book or a helping book like hey, what what should I do now? You know, should I start apologizing personally? But then I actually have to do it on a much bigger level because we actually have to apologize on a you know, because so You get my point For me personally, I didn't sleep for a whole week, you know, I felt like terrible and and that's why You know, it's really difficult to say it because it was just it was a terrible five days in my life So yeah, so I never said it before I think so Where's the water? So basically What I wanted to share is that? You know, we all make you know, if I had been in a In a party with all of you and I had said the same thing I think that you probably would have said like hey buddy, you know And you would have corrected me correctly But this is something that just sticks and is online and I think like the biggest lesson for me is of course Think about what you say in public just generally Just like you think about what you say to a person in person And I think we all have to just learn from that and that's probably one of the biggest thing that I really learned from and Then of course apologize for the mistakes that you do So I think it is also really important that you just you stand up and you also say hi at data mistake so that's maybe the next thing that I learned from that lesson and And just to add to that because I have two minutes because it happened again the other day But not in this level and I didn't lose sleep for that, but we all had the security update and Me as very many other people we were just tweeting like triple get them triple get them and putting the hashtag and then Tim actually tweeted Hey guys think about what you're actually saying because it could potentially hurt people That were back then involved for those who potentially Made that you know that are responsible for that security leak That it actually hurts the people that were involved in that process And now we are doing like security update parties and we are putting this hashtag to that So I didn't think about it at all when I tweeted and put this hashtag in but after Tim actually Talking about and he's writing a blog about it. I heard then actually you understand that that could actually there are people behind it and So therefore just think a little bit before you you know take your time Before you say something or if you want to be especially if you want to be funny and I think like Then especially you have to think One more time. So yeah, thank you for listening to that one And I hope that you know, we all can learn to be a little bit more where is a nicer to each other and most important come to us in person to each other and Let's have that conversation and let's try to help to educate each other, right? Thanks, I'm not gonna use the mic or I'm gonna like wander into the wall somewhere Yeah, so I'm Tim Plunkett and I am a senior developer at aquia working on Drupal core pretty much full-time now so About seven and a half years ago. I started like my first foray into core Working with Bartek theme and about maybe a year or so after that Became what I called a core developer for the first time When I was invited to participate in the views in Drupal core initiative And so after you know after we successfully got views into core I thought maybe I'll stick around and do some more core core work going forward So, you know, I got working in my free time spending lots of nights and weekends working On things after about a year, you know, I felt really comfortable with the way things work And how you go about you know achieving change and and making progress and in core Which turns out is awful It's largely just the person who is the most stubborn and has the most time to spare gets their way And it took me a long time to learn that so that's what that's what I'm gonna talk about So yeah, so if anyone remembers during the Drupal 8 cycle they once they announced feature freezes happening Drupal 8's coming soon in 2012 so a year after The feature free feature freezes came and gone and now we are then there was a API freeze and That was early 2013 Drupal 8 was right around the corner that came and went so now we are in an API completion phase And by this point with each independent like successive date you know the stakes got higher the pressure got higher and There was a sense of a real sense of urgency that this was a very important thing that we must get done in 2013 and not wait, you know two years till 2015 to actually get it done so so You know working in the issue queue became a very stressful place For for the people who had been working on this for for many many years and I've often thought about how stressful that was but What what I have taken away from this is how much worse it is for for new contributors This was sort of before the the new modern wonderful Drupal mentoring program that kind of has Become the the canonical way to get people kind of involved in a very caring and loving way So this that didn't exist yet there was a particular issue I recall that was a Bounce some code that I wrote opened by another veteran contributor who he said, you know, this is completely terrible We got to fix it, you know like it's garbage and like the Drupal could never work this way And I you know immediately got my back up and was like well, you know what I will tell you this code is wonderful And then nothing, you know, it could ever be wrong with it Unfortunately in the middle was a brand new contributor who decided that he really thought that Drupal was really great and wanted to finally get involved and so he listened to the the person who opened the issue and started to work on this and was sort of you know caught in the crossfire between us veterans and And as anyone who has you know been in the core issue queues There's some like choice issues out there. You can go find where you know people resort to some pretty brutal Verbal tactics that like maybe taken out of context seem polite But are like pretty hurtful when when read in the moment by the people you're writing them to and so You know, I said some things that now if you read go back and read you're like I wasn't that bad But it got bad enough to the point that that new contributor. Oh, thanks. Yeah, that'd be great. I kind of need one of those That that new contributor ended up quitting Not just core, but Drupal all together And you know, I mean they're large like there's got to be other reasons. It's not all my fault. I swear But I do think about that often And it's like, you know, I ended up being right in that I got my way I was the stubbornest one and I took the most time and and just kind of through attrition got what I wanted more everyone down And it's it's a it's funny because it's like a admin UI facing feature And every time I'm building a Drupal site, I click on it. Oh god damn Like I'm glad it looks that way. It's wonderful. But like is that was that that little thing was that worth? Losing, you know a contributor and like how many How many contributors could that person have helped bring in and what changes could could they have? Brought to the project and was that one little thing, you know really worth it And it turns out, you know, I may have been right I may have been wrong. It doesn't really matter it You know it The technical excellence of the project isn't worth sacrificing people And like, you know, I'm still here still I'm working I stopped Contributing largely and in my free time because I'm grateful enough to be paid to do it during my as my day job But every once in a while, you know, it'll be like 5 30 or so and I should be done working And I I open an issue and I try to go find something that was worked on by someone new and really try to give them a first positive first impression to kind of atone for that Because I was I was thinking the The second best Pixar movie Ratatouille In that movie there's the phrase the motto of the one restaurant is anyone can cook and By the end of the movie that you know, the antagonist realizes that Really, it's not that and everyone can become a great cook. It's that a great cook can come from anywhere And I think about that a lot You know being the second best Pixar movie ever made And and so what largely like my initial thing was that you know, I mean, how do I how do I learn? to best kind of empower people who To do good in the in the triple community especially in Drupal core and so I sought out Angie Byron web chick who many people know And I said, you know, I want to work. I want to learn more from her She was kind of the reason I got into triple on the first player triple core in the first place So I applied to work on her team and that's how I got started aquia and I've been there next month will be four years and we still work together and So I would not only you know encourage you to to to better yourself through reflection and thinking about all the terrible things we've all done to other people But also to find someone who's a role model and find someone who you admire and lives Isn't it can be an example to you? And yeah, that's that's all you got. Thanks Hi, everyone. My name is Catherine Mulder I know I have one of those funny names that nobody can ever pronounce So I'm glad it wasn't printed anywhere because it turned into cat or Catherine or Valar David's excellent at that.  I know And they don't want to Drupal con And that was kind of the same thing Except one one minor detail I was staying at the hotel where the code sprint was at And web shake was hanging out in the lobby doing code sprint in the middle of the night They mentioned that my room was right behind the registration next to the elevator. I got no sleep I hated you all I hate you all because you were having fun and that was not my kind of fun and I knew That if this was it I was probably gonna leave Because it wasn't comfortable in any possible way So I stuck around I got my first Drupal job I think it was pretty good at it But I had no way of validating if I was because I would have to ask a white dude if I was any good Because there were no women besides web shake At the time at least that's what it seemed and then It was around the time of Drupal 5 to Drupal 6 And I had decided that our team was going to use domain access and it was going to be great But there was no domain access for 6 yet So I started committed patches one after another And Ken was really nice He didn't tell me that I was wrong or I didn't do it right or You know what I thought how it should work was Not the way to do it and at some point somehow I was go contributor and I was there and it was magical And nobody actually I didn't have to go and ask a white dude if I was allowed to do it He just let me be and by enforcing My behavior he made me feel I was welcome And then that happened again with another project And it was great and suddenly my mindset of I have to ask for an approval became I can do things and maybe somebody can learn from me and So the backtrack a little bit I grew up in Estonia in Estonia women teach men decide right so for most people growing up in America that's slightly backwards Especially for some European companies countries where that doesn't really happen right women are in charge So for me it was so so different So I figured why not I got the time I got the knowledge I think I know what I do So I started contributing More modules and more code and suddenly people actually wanted to participate and give me things back And that was that was great So it's like all right. I got this I got this maybe maybe I can help somebody else But this is where I went wrong I had to come the white dude Right in somehow in the process I started to choose women over men because it was like well women deserve a chance which is all fair But at the same time It's not right Now the women are getting preferential treatment over men just because they're women So I guess what I'm trying to say is You have to check your own biases you start from a point that seems comfortable to you You end somewhere else And you're doing exactly the same you hate That is being done to you So that was back in days of Drupal 6 so we have gotten so much better about being more open and transparent and welcoming But it hasn't been an easy road Like how often does a woman walk around in Drupal con and get asked so are you a themeer? Because a woman can't be a backend developer or a product manager Because you know For the longest time women couldn't code right? We didn't have role models. We had the web check It it's it's been a journey and Another thing I would like to add to this is it is okay to be wrong But also to realize that you are wrong and accept that you're wrong and learn from it It it's hard And you have to admit it And sometimes you cry about it That's it. Thank you So I'm heather radriguez and I currently work at digital services georgia um I am a solutions analyst and former front-end developer But I didn't always want a career in technology like Perhaps many of us in the room in fact where I went wrong was I let other people and my own insecurities dictate my future so When I was in high school um, I came down with chronic fatigue syndrome So I was about 13 years old and I uh I Started sleeping a lot. I was very sick. I couldn't go to school. I had home hospital teaching Um For for for actually a few years Sorry, it's kind of hard to talk about um but As a sort of a trade-off With the home and hospital teaching is that you know, it was really kind of a self-paced curriculum So I really didn't feel like I got the same Chemistry and math and you know the sciences such stuff that other people my age did So I was really insecure about it, but I was also, you know, a fairly you know smart Kid and when I went to college. I went to community college first Because my parents worked there.  I as soon as I got healthy I actually signed up as a foreign exchange student went over and lived in berlin germany But like that's another talk that we could have But yeah, so I was just really just you know, like eager to experience the world So I came back and I went to community college and I Took a lot of biology classes because I wanted to be a doctor because I was so sick You know, I wanted to heal other people and I wanted to maybe help people like me who were suffering So I You know, I had a teacher in my community college who really encouraged me and she was you know She was um, she was a doctor herself and she had just moved to the area And so she was kind of like, you know doing the community college teaching is just a you know side gig and she was like, you know You're really good at this stuff. You should really do it. And I was like, I'm gonna do it. All right. Let's do it so I applied to the university of maryland and I got in and as a biology major so I Went to the guidance counselor and I sat down and unbeknownst to me Apparently guidance counselors don't like to deal with community college transfers. They don't really like transfers at all They just want to put you in a little box like, okay. You went to maryland. You check these pre-rex, you know, etc So the guidance counselor looked at What I had, you know, here, you know, here was my like, you know 4.0 from community college and she just kind of looked at it and she just goes Yeah, we're gonna need you to take like calc one we're gonna need you to take um organic chemistry and physics And all of this this semester and then the next semester and she just rattled off the hardest classes possible in a very short amount of time and I learned later that You just don't do that to people. You don't actually tell a freshman, you know, or you know, whatever I was at that point Because I was transferring to take, you know, physics organic chem Calculus all of these things in the same semester necessarily like, you know, you kind of throw in some filler courses, you know So people don't just completely burn out But I was so insecure because I didn't have the same Science background and math background that I buckled and I said, this is this is not me. This I I can't do this I I would be a terrible doctor because you know, I'm just not smart enough and I don't I don't have the background and Yeah, I mean these people all, you know, they all look like they're they're probably going to be better doctors than me, you know, so I uh I cried and then I went over to the English department And I signed up as an English major because I was like, well, hey, I'm really good at reading. I like to read so you know that that was uh So I got my degree in English and you know, I don't I don't regret it and I don't regret the fact that you know, I got an internship at the end of my tenure at the university of Maryland and we Learned how to do html and css and then I started coding and then I had to Participate on this committee to evaluate cms's and that's when I found Drupal so You know, and I don't I'm not saying that I'm wrong about the career path that I'm chosen But I am wrong about letting other people tell me That I couldn't do it when I could because we're all winging it in some way You know, we're you know, you meet learned doctors and you know, it's not like they have all the answers In fact, they're just making it up as I go along too, right? I mean, you know, it's a myth You know that that You know with with hard work and perseverance. We really we can do this right and and I really um I just feel You know so ashamed to admit that That's something that minor completely derailed my career, but Yeah, that's That's what I got listening to all of these I like I'm gonna I'm gonna wing it a little bit of mine because I I'm gonna sort of Throw out some of what I thought I would talk about because I think you all took it to another level So, um My name is josh, uh, I'm a co-founder of pantheon. I've been involved in Drupal since uh 2003 So a lot longer than I would like to admit. I don't know it makes me feel old sometimes, but Um, uh, and I've been so lucky in my life Um, I mean I work really hard and I'm a pretty smart person and I I get along well with other people most of the time But I've been so lucky in my life and I have had so many advantages and privileges and just lucky breaks that have gone well Um, and so when I was thinking about, uh, David's topic originally I'm gonna do like the 60 second version of what I thought I wasn't gonna talk about and then I'm gonna try to Put together something and that's a little bigger picture So I wanted to Tell everybody how often I've like just made like mistakes like like literally Flat out boneheaded mistakes like deleted the database in production mistakes Uh, I've done that And uh, and I think that uh One of the things that I've learned as I've matured in my career I'd like to take my walk back worst mistakes I've made Then dropping a database in production or deploying something that like, you know takes down like hundreds of websites for a few minutes Uh, because I've done that too um worse than that I've been Really uncharitable towards other people when they make those kinds of mistakes Um, like I have you know high standards and I think it's great everyone should have high standards but sometimes I'm not Uh forgiving person and I can be very brusque in my reaction to something that disappoints me And um, I had it has been a long road for me to realize how destructive and toxic that can be In a team environment and how corrosive it can be to building trust Uh between people because if you don't have the room to make a mistake You are gonna slowly Shrivel up and freeze yourself into a box where nothing interesting ever happens because human error is inevitable It will occur and we need to think of ourselves our organizations and our technical systems as Being a resilient system means you embrace the reality of human error and figure out ways to roll forward when it occurs Rather than having to like pull the big red cord and have the screeching alarm go off And everybody run around with chickens with their heads cut off and then somebody gets chewed out in a closed office room And uh, it's been you know, I look back on on my career and I've done a lot of really awesome shit um And the stuff that I've done that's not often awesome has been Being too critical or being critical in a non constructive way Uh, and so um, so that was like kind of my prepared career oriented like hey people make mistakes. It's all good Uh, and I think that's a good thing, but I think everybody here I'm gonna try to tell a short other story about mistakes. Um, that I think will also end on a high note Um after some dramatic tension So one outcome of making mistakes is that you might get your heart broken um And this is sort of the origin story of how I actually found my way into droopal and it kind of comes up to the present day So when I was 23 years old and I was living in um an apartment way out in like the Like right on that gentrifying edge of brooklyn in a neighborhood called green point, which was still mostly full of polish people um living in a Row house that I filled up with all of my friends from college that was originally had like a backyard That was literally a hoarder pile of trash that we cleaned it out and we turned it into a cool backyard And we had barbecues and I went to a performing arts school I have a bachelor of the fine arts, which means my version of imposter syndrome was just fake it till you make it So I got no problem with that um And we were like I was doing web development to Bailey scraped by and pay the rent whatever I could get And I was doing performance art on the side and like Living this like we really kind of cool, but incredibly like stereotypically hipster lifestyle um I met a girl And she was amazing and she was like a little bit older than me like worldly and wise and she was in a band And uh, and we like went dancing and then we like started seeing each other like every You know every other day and it was like this kind of whirlwind romance Like I hadn't really felt since since I was a teenager Right, you know like you kind of have fallen love when you're young like maybe the first time or whatever it is Puppy love and it's this kind of overwhelming all-encompassing thing and that happened to me again And I don't know how or why or what actually triggered that But it kind of you know, you get this weird tunnel vision When you're in that moment, and I was just like this is it. This is so awesome. This person is amazing. It's everything She was she taught chemistry at like the best public school in like Manhattan and it was just like We had amazing chemistry And I was like I had my life that I was working on and I was you know getting involved and doing things with web development I was starting to get involved in politics at the time And I had this plan to move to california for the summer to work on this political project that I was doing And I was she was like cool. That sounds great And I was like, yeah, you want you want to come to cal you have this summer off You want to come to california with me and she was like, I'll think about it And I heard like that sounds like we're moving to california together And like that's so you know, I have this like dream in my head of how that's going to go and you know You can kind of probably tell where the story is going You know Well, wonderful woman is like a few years older than me Has actually a life that she's built up over several years Uh is kind of thinking longer term than maybe I am I'm like thinking maybe like three months out Is the my my the of my event horizon and it came down to like their like uh You know about end of end of may and she was just like, okay I Have been holding on to this and I really hate to tell you this but I'm not coming to california And I was like what and she was like and Probably you should just go and then we shouldn't date anymore And I was like what? And uh, and like you know, I like laid on the floor and cried for an hour And uh, and I was like very broken as a person as a result of that And so uh coming out of that so what did I do? I like threw myself into this project because that's what you do when you've got a broken heart as you find something else To work on and I had been involved in this like anti-war organizing stuff And I'd gotten involved in this political campaign There was primary candidacy of this guy Howard Dean and it was like the internet power candidate And it was like speaking pushing all of my intellectual buttons and like I was a big believer in this and moved to california and like Found some like rich people in california They wanted to fund this thing and started a nonprofit that was going to like stealthily help his campaign on the side um, and like You know really did like got very involved in this it was a life-changing event like it was um, you know I met my my business partners act through that process.  He lost Uh in a spectacular fashion.  Anyway, we were we were all out But it was Yeah, we figured it might as well like if we could we'll try to run it our way And if they shoot us down then we'll we'll go but it was burdensome bridges. That was not a that was a mistake So, um Drupal had continued to grow and take off And like, you know, we I had this early experience of you know getting involved first just using this technology for this campaign Which was not I wouldn't care about the community at all because we're just like go go go Let's make websites got to connect people and so forth But eventually figured out that the community was a huge asset and and was involved that Later on and kind of checked back in with the Drupal universe and it turns out you could actually pay your rent with Drupal now Which is awesome. And so I called around to all the people who see me running these Drupal shops And I said, you know, I'm this guy you can check my user number 3313. I've got some commits. I've done some modules I'm legit hire me And Mike from Trellon hired me And uh, that was an interesting experience, but it got me professionally engaged in in Drupal Which got me, you know to where I could move out of my mom's house, which was awesome Uh, and I moved back to Brooklyn and uh, and as I started to work more with this community And started to think like even higher level about what we were all doing here Like my heart started to get full again And I started thinking about all the things that like The internet really would mean for humanity And I had had like it's kind of some early experience with this I like had a a blog back in the day where I would just like tell on myself and like be way Share way over sharing way too much personal information because it was like but it felt like, you know I'm in a position of privilege where I can afford to do that And it feels like kind of living the open source life And as I started to you know see through the group the rise of Drupal how that you know Not that everybody should overshare about their personal information Absolutely not but that there was a way of of being connected as a result of being able to exchange stories and make connections and so forth and I got really really Fell in love with this idea of how this would really change the world and we'd make everything better because we could all connect with each other And I think you might see where this is going I didn't account for the fact that just being able to connect doesn't make people benevolent and there's like in a world where Connections are possible But sometimes the most like people with time on their hands and the biggest access to grind are the ones that can actually get things done You know all the jerks of the world can also get connected and and do bad things like I did not see that coming And I and for me it was actually like watching what happened around Gamergate I don't know how many of you followed that on social media, but that like that broke my heart Because I was like what the internet isn't supposed to be like this But it it can be and so The positive notes that's the dramatic tension the positive note for me is you know Even though that watching that happen in some ways broke my heart I'm still like my heart is filling back up again because now I think we're reaching a level of self-awareness about the risks And about the challenges of toxic online culture and the challenges of you know too much information being centralized in like a Orwellian box and people are actually talking about this and and not just with the kind of starry eyed idealism that I had When I was 23 years old but talking about it in a way that's mature and real and self-aware And my heart is getting full again, and I'm sure it'll get broken again, but my my point is that If you're not willing to risk being wrong You're never going to deploy cool stuff because we too afraid if you drop the database and drop in the database Isn't a big deal. There's always a backup But be be will hopefully Uh Be willing to be wrong At the level that your heart might get broken It's really hard to do. It's really hard to do and getting your heart broken sucks but Go there because that's how really great things happen and then and you're you know, you can't if It's worth it to be in love to it's worth risking getting your heart broken to fall in love with something And and you can't know that you're right in advance So be you know be brave and be willing to make mistakes Be human thanks in absence of a david. I think that's it. Thank you all for listening Um so It's kind of I don't think I necessarily did I just kind of got a little better for a little while and then I got sick again And I got a little better for a little while like certain drugs were more helpful to me and certain drugs were not I have every single Experimentative treatment that was possibly known to human beings at the time including giving myself shots every day um I would say for me like It was just a certain amount of like Building up my tolerance for exercise and for like walking around and stuff and then also Supported with some drugs Like do you want specific games like or because our okay Right right um At that time because we're talking like 97 Yeah, yeah, like I mean there's yeah, I definitely You know, we weren't we weren't making smoothies, right? We were definitely if you're just like, I don't know I don't know this kid throws up all the time. What do you do with it?  Like is that the thing? Yeah, absolutely Oh, okay. Yeah, all right Yeah Yeah, right, right. Yeah. All right, exactly Yeah, good for her. That's awesome. That's so great Right Yeah Well, thanks for sharing your story with me Right, right. Yeah, well, we might need to be moving You're so clever with my puns All right, there's Shannon. Let's do the thing. Hello there You're doing well yourself I'm all set. Oh, yeah It's a pleasure to start Right on. Thank you So I know it's a little early but For folks that want to pay attention to some of the commands you might see You might want to come closer to the front because I noticed this is a little small Just a pro tip. Oh, to follow along? Maybe? Yeah. Yeah, there's nothing wrong with following along I'll also be providing the Link to the slides after the presentation is done. So you have those as notes So you don't need to take copious notes Oh, very good. Yeah. All right. All right. Cool It is. Yeah, no problem Yeah All right, cool This is gonna be great and then I'll have to help you fix it after the talk's over So I'll I'll make myself available for that as well. I'm sure No, there's no undoing infrastructure. Maybe there should be Maybe there should be Yeah, yeah, maybe that that that should be like the next tool like command z Oh, yeah, let's get that teed up and make sure that works and then Oh No, well actually, no, yes, I do. I have a little video clip Um, so is there like a little oh, this is it right here. Thank you so much All right, let's turn the volume down before I blow everyone out of the sky Well, you never you never know.  I know it's linux. Oh, thank goodness It works. Okay, and then I'll play a quick Yeah


Okay, let me start sharing my screen. Hello to everybody. We meet again today and today I'm going to talk to you about another technique from unsupervised machine learning that is also closely related with many, many physical problems. The technique is clustering, mostly make groups for natural groups. We can see some examples for instance. The first question that one can make is what is a cluster? I think that all of you will agree with me that if I have this distribution of points in two dimensions, for me it's kind of clear that I have two clusters, right? Two groups of points. I think for everybody it should be like that, but there are many, many clusters, possible clusters that we can imagine just in two dimensions. This one is strange, but it's anyway a group of three clusters. So the idea is that what we are going to show you today and the next day, that it's Wednesday I think, it's just an overview of the techniques that we have for allowing our computers to do this in an automatic way. Clustering, it has many, many utilities. I mean, it can be used for instance for the site set of that from a library or whenever you google the algorithm performs a cluster for you before providing you the results. In image recognition, for instance, these are images from a cancer and when performing image recognition many times preliminary steps you need to use a clustering algorithm and everything that needs some kind of classification can be addressed with clustering techniques. There are many types of clustering. I'm going to provide you some kind of classification in order to have in mind the several types that we can have when we use a clustering algorithm. Imagine that you have something like that. If you have something like that, you can imagine that the most natural way of dividing these points is like that, but you can think also about something like that. Why not something like that or even something like that or that. All these kind of clusters, I mean, all these clusters, partitions are equally valid. So, one thing is that the result of your clustering, it's going to depend on what you define that it's a cluster. That's kind of a topology, but it's always like that. There is not a mathematical definition of what it's a clustering. It's really problem dependent. So, each problem will have different optimal clustering algorithm. It also depends on how do you compare the points that you want to cluster. That's the metric. The metric that you use, for instance, for comparing two different configurations will determine the results of your clustering. And also depends on the features that you have chosen. Imagine that you have, I don't know, a simulation of a protein. You can try to cluster the configurations that you sample in your simulation, depending on, let's say, the similarity to a given structure or also according with the, let's say, the angles explored during the simulation. I mean, the choice of these features, the choice of this metric, it's not trivial, and it depends on the problem. In some cases, it's kind of trivial, but in many cases, it's not so trivial. So, it's something that one must have in mind when applying clustering algorithm. It's not that you can use a black box method for clustering. You have to take all these variables into account. I'm going to provide you, as I told you, a classification of the different clustering algorithms. And I would provide a classification according to the output of the cluster. The first, let's say, the easier clustering is the flat clustering. In flat clustering, you perform just a hard partition of your data in groups, into groups. Okay. Then in flat clustering, you perform also a partition of your data into groups, but instead of assigning each point to a cluster, you assign a degree of membership. I will show you later what's that precisely. Finally, on hierarchical clustering, instead of having a single partition, you generate a tree. And this tree of partitions allows you to see many, many, many partitions. It's a kind of dendrogram. It's a kind of classification tree. I don't know if you think about, for instance, when you were in the school and you were studying species of animals, there was the vertebrates. Inside the vertebrates, there were the mammoths, the reptiles, so on and so forth. These were two species and individuals. Here, we do something similar. Let's see later what's going on. I will go into the detail for each of these points. In flat clustering, as I told you, each element is assigned to a single cluster. Assigned to point one belongs to cluster two. Point two to cluster two also. Point three to cluster one, let's say, so on and so forth. In traditional methods, what you have is that you need to define the number of clusters that you have, and it's provided as an external parameter to the algorithm. The question is that usually when one performs clustering, one looks for a hard partition. One wants to say that the elements belongs to a given group. Each element belongs to a group. That's what's clustering. By definition, for instance, if your structure, if your data structure is multi-level, you cannot deal with that. This is a case of flat clustering in which I divide my points in five groups. Each set of points, color with the same color, belongs to the same group. Okay. Flat clustering is a bit more sophisticated. As I told you, you give a degree of membership to each cluster, to each point in the, to each cluster. Of course, since a point cannot be, cannot count more than one point, this membership vector is normalized. It belongs to in this way. Okay. And again, the number of clusters should be provided, usually. And it's not always easy to transform flat clustering into a hard partition. In this case, for instance, if I perform a flat clustering on this set of points, I will obtain something like that. For this point, I would say that the 90 percent is assigned to cluster one, and nine percent is assigned to cluster two, and marginally, it's assigned to cluster five. This other point that it's in the middle between cluster one and two belongs 45 percent to cluster one, 50 percent to cluster two, and a bit to cluster three. This point do not belongs any to cluster one, not a bit to cluster one, nothing to cluster two, kind of a lot to cluster three, more to cluster four, and a bit to cluster five, and so on so far. Okay. Please, if you have questions, interrupt me, because I cannot hear the chat. Excuse me. Yes. In the flat clustering, the number of clusters was arbitrary, or how you choose five clusters in the previous classes? Let's say, in this case, I chose them because I have seen the points mostly, and I decide, but in general, we will see the techniques for choosing the number of clusters. It's not trivial, but now it's just a kind of introduction to the different methods. When I explain the methods in detail, we will go to that point with a bit more detail. Okay. Okay. Finally, hierarchical clustering. Sorry. As I told you, it produced a set of nested clusters. It's kind of hierarchical tree. Okay. It's the output. It's visualized as a tree. Okay. Just, we will see that later. But by doing, like, as a tree, you don't need any assumption about the number of clusters. Okay. If you are lucky, hierarchical clustering may correspond to meaningful taxonomy. It means that, if there is a multilevel structure in your data, what you want is that your hierarchical clustering reproduce this multilevel structure. And just by cutting the tree, it can be transforming many hard partitions. For instance, what I would obtain if I have something like that it's this partition where you see that all the points are kind of in the tree until I, I'm kind of merging trees until I have the structure. This is a good multilevel structure in the sense that it's, I see that plaster red and yellow are more connected. Let's see, let's say that green, blue and purple, right? And also I can see that green and blue are more connected and then to this third one and so on. Okay. This is what hierarchical clustering provides you. Some kind, a part of some kind of partition, it also provides you some kind of view of the structure of your data. Okay. However, it's not easy to flat. For instance, in this case, I obtain the two clustered partitions easily by dividing with a straight line. But it's, in this case, for obtaining the five clustered partition, I have to do something like that. It's kind of at all. So it's not so easy to do it in real world applications. Okay. I did it here just as example, but I would not know how to do it if I cannot see the data. Okay. So let me check if there are questions in the chat and before going ahead. Okay. There are many questions. Let me start replaying them. What are the mathematical differences between these methods? Okay. The question is that what I'm not talking is about actual methods. I'm talking about general classes of methods. Flat, faxian hierarchical clustering and classes of methods, each of them contain many different kinds of methods. So for replaying that, you should see each of the different methods. In general, in the, let's say, generally speaking, the differences between these three classes is the output. In one case, you have hard partition. It means seeing a signature that corresponds one to, from each one to a different cluster. In the faxian one, you have a degree of membership and in this case, you don't have a single partition, but you have a degree of partitions. Can we use the number of components from PCA as a guide for the number of clusters? Not exactly because it's different, let's say, the dimension of in which your data lives, it's not necessarily the number of groups that you have. I mean, for instance, the number of components of PCA in this case would be two, but the number of clusters would be five, right? Regarding the hierarchical clustering, do you have any references on this non-stake cut of the dendrograms? There are, I should look for that, it's long since I'm not looking for non-stake cut. There are many methods trying to optimally divide a cluster. As far as I know, none of them is generally applicable, so I decided not to explain them, but I can check, I mean, it's something that is still a work in progress for the community, trying to decide a general method for non-stake cut of dendrograms. Another question is, what about the position of the dots? On what basis are they placed? Okay, these are examples. I put them by hand, but in general speaking, what they represent is the position of your data. In the case of physical many-body systems, the ones that we are interested, they are usually all the coordinates of your space. If you are talking about, let's say, the XY model of the spin or the 2D icing, the positions of its configuration would be all the coordinates of each of the spins in your system. What is the point in using clustering techniques if the result depends on the technical number of clusters, etc.? Well, the point is that you need it. So usually what happens is that you need to perform some kind of division of your data, and the idea is that, of course, since you need it, you need to know all the clustering techniques. So let's say, the best clustering techniques, the better you can decide the technique to apply to your data. So the point is that it's mostly a matter of needing. In many cases, you need to blindly, because it's not said that you need to concede your data, divide your data in groups. It's useful for many, many things. And since it's useful and you need it, you need to apply these techniques. There is another question of Richmond. This is a kind of technical question about the silhouette score. In assessing clustering techniques, depending on data context, how reliable is the silhouette score coefficient? I would tell you that it's a coefficient that I don't like, especially because it has the problem that it tends to overscore, let's say, spherical clusters, spherical-like clusters. It's a coefficient that, of course, let me show you, I'm sorry for the other people, but I think it deserves a replay. If you have something, let me go back. Like that, the score coefficient of this partition would be really, really low because the silhouette coefficient somehow relies on the fact that your data is more or less compressed. It's more or less spherical. But if your data has a weird way of being clustered, it's not going to give you the correct answer. In many cases, however, it's a good option. In cases when you have some hints about the way your clusters are and you think that are something like this, in these cases, the silhouette coefficient will work perfectly. I don't know if I'll replay your answer. Okay, how can we say that a clustering which is applied to data is reliable or not? Mostly, what you do is to rely in the experience, in the sense that you have cases in which you test your methods, and if your method works in really similar cases to the one that is under study, you somehow trust. The other method is just to try to apply external coefficients like the one mentioned by your colleague, the silhouette coefficient, that try to measure, give you some kind of measure of how good, how compact, for instance, are your clusters. But this is kind of really dependent on the actual shape of your cluster. So it's not so... Personally speaking, I don't like it so much. According to me, the best way is to perform an external validation in some data set in which you know the groups and try to see that if this data set is really similar to the ones in which you are applying the method, then you can rely on the method. Okay, let me go to the first method that I want to explain to you. And the first method that I want to explain to you is the K-means clustering. This one is the, let's say, the father of all the clustering algorithms, and it's still widely used. I put here a reference, but there are several references that are used as the reference for K-means, and they still have thousands of citations by year. I mean, it's something that it's increasing and increasing and increasing is still really, really useful. Okay, so what is K-means? K-means, what does? It attempts to minimize the intra cluster distance, while it means the distance between points belonging to the same cluster, while maximizing the inter cluster distance, the distance between clusters. It's based on the concept of cluster centroid. A cluster centroid is the average position of the cluster elements. As I told you, it's still widely used, and it can be easily parallelized and almost linearized. It means that it's really, really fast. But as I told you, the user must provide K the number of clusters. So what one measures is this object function or loss function, and the method tries to minimize that. Theta, it's the array of the, that reflects the designation in clusters. And CL, it's the vector of the coordinates of the cluster centroid. So for the loss function, it's the sample of the clusters of this quantity, where this delta theta i, it's the difference. It's zero. If i, it's assigned to a cluster, but it's not l. And it's one if i, it's assigned to the cluster l. Okay. So what you compute here is just the average of the, of the coordinates. And here you compute the sum of the square of the distances from each element assigned to the cluster to the center of the cluster. This is what we try to minimize. And the way for minimizing that, it's just with a really easy algorithm. The first thing that we do is to initialize the cluster centroid. And the cluster centroid are points randomly chosen from the data. Okay. Then we enter in a loop in which we first decide the membership of all the data points by assigning them to the nearest centroid. Okay. And then we recompute the centroid by using this formula. This way of, of minimizing allows you to, in this step, minimize the intra distance, intra cluster distance. It, because they are just saying, okay, I'm assigning all the points, all my data points to the center that it's near, the nearest center. Okay. And then when you update your centroid, what you do is to maximize the inter distance, because you are saying, okay, if my two centers are nearby, I can recompute the centers. They will recompute the centers just as the average of the, these of the positions of my data in the clusters. Lucio asked a question. I will reply later. Okay. It's in the lecture, it's in the program of the lecture. So, for instance, imagine that you have your data, this data. Well, the first thing that you do is to randomly pick case centers. In this case, I pick 15 centers. Then I assign the computer assigns each point to its nearest center. Now you can see that they are of the same color. And then I recompute the centers. Okay. And it means I move the centers towards the center of my cluster. And then I recompute, I continue iterating. Okay. This procedure is known to convert, it must convert, and it converges when there is no change in the assignation of points. So you have a center and the assignation of points. But it's not said that you must arrive to the global minima.  But it's not necessarily the global minimum of the loss. Okay. And you can see that, for instance, in this case, in which I know the solution is 15 clusters. I assign K to 15. But due to the minimization procedure, I have, for instance, these two clusters divided by two or these two clusters merged. Okay. This is a problem due to the fact that my initialization is random. Okay. So I arrive to a given minimum of the loss function, but not necessarily to the global one. So K means that it's the father of all the methods, but it's already pretty old, has some weakness. And we are going to comment them. The first one is the one that I already commented, which sensitive to initialization. Yes, to share. They are totally random. Let me finish this point because now we are going to see that. I mean, if we pick this, I will have one solution. If I pick another sentence, I will have another solution that in this case is optimal. But I can have other solutions that are far from optimal. So each different initialization will give me a different result. What people suggest to do is to perform a better initialization, that it's not totally random, but still random. One would be, and this better initialization, the most used method, it's K means plus plus, in which you, the first center to choose it as random, then to compute the distance from all the data points to the center and take the, to the already assigned centers and take the minimum. Okay. And then you choose a new cluster with a probability that it's proportional to the square of this quantity. The only idea, we are not going to into the details because we don't have a lot of time, but the idea is, okay, if I pick one center in one place, the next center that I pick, it's better if it's far away from the one that I choose. So that's the final idea. You are choosing centers with more probability when they are far away from the existing centers.  So imagine that you have this case and I pick Q's K equal to three. The first step, I will pick randomly with uniform probability one point. Let's say I pick the six. Now I compute the distances from all the points to this center. I pick the minimum that in this case it's the, by chance the distance to the center. And then I pick the next center with a probability that it's proportional to this minimum distance to a given center square. So what would happen is the probabilities of these points that are far away from center six would be bigger than these probabilities. So I would pick for instance, center one. So if I pick this point and this point, what happened is that now I have to repeat compute the distances from sorry, from a center at the minimum. These minimums would be for the 9Ds, for the 8Ds one, for the two would be this one, for three would be this one, four, five, seven. So now what would happen in the, I would pick a new center with a probability that it's proportional to the square of this minimum. So the probabilities of points 8 and 9 would be much higher than four, five, seven, two, three. Okay. Therefore, I would probably pick one of the, sorry, for instance, a nine. And that's all. Now I have these three points, three centers that are not any more randomly picked, but picked in a wise way. And in this way, I will probably obtain the global minimum for this loss function in which I have three clusters here. Okay. So this is one of the weakness and it has been addressed in this way. The other, another weakness that you all asked me for is which K employing, which number of clusters. In K means it's usually, this problem is addressed by what it's called the screw test. And this test, what happens is that what I plot, I compute my K means four K equal to one, K equal to two, K equal to three, K equal to four, five, six, seven, so on, so far. I do the K means with all these different number of case. And I plot my loss function. I can call it the similarity objective function, whatever. It's the loss function, the sum of the distances from all the data points to the center of the clusters. If I plot that, I obtain what it's called the screw test. And I've looked at this plot for an elbow. If I have an elbow, I can say kind of confident that the correct number of K is three in this case. This quantity should be, if we arrive to the optimal, the similarity is the, sorry, Alejandro, it's the loss function. It's exactly, sorry, let me go back, that. Okay. This is, it's a different way of calling this objective function or loss function. The similarity, but whatever it's that. Okay. So, you plot the values of the loss function for each different partition that you've looked for an elbow. Of course, science, you, your K means algorithm. It's sensitive to initialization. What easily it's done, it's to take, let's say, 10 runs for each number of clusters and take the minimum value. Then it's sensitive to add layers. Why it's sensitive to add layers? Imagine that you have something like that. You would agree with me that the optimal partition would be here, right? But now I'm adding a point. Okay. And these are the cluster centers. Now I'm adding a point that is this one. That is far away. It's what it's called an outlier. What I would like is to have the same position. Of course, this point is far away. It's just one point. Why should it modify my partition? However, what happens is that it moves a lot my center because it's really far away. So if you remember the formula for centers, it has a lot of weight in my centers. So it moves my centers. And by moving my centers, what may happen is that my partition, it's not anymore the optimal one. That's the reason why it's really sensitive to layers. So people provide, try an option, a different way of doing K-means. It's what it's called K-medoids. And K-medoids, it's the K-means method, mostly the K-means method. But instead of working with centroids, you work what it's called medoids. And by medoids, that is, let's say, it should remember median instead of mean. The medoids are an element of the data that is the most central element of the cluster. So you are optimizing, let's say, your centers, but restricting yourself to have centers belonging to the data set. You can see that this will somehow mitigate the effect of outliers, right? Because if you have something like that, your center will never be here. It would be here. Okay? Because you are not allowed to move your center far from the data. And having the center here, you will recover the correct partition. Lucio Garcia asked me if it's like selecting the most center point in the simplex of the data. It's the more center point in the cluster, not in the simplex. So it's a bit different. But the idea is the same. I mean, you choose the most center point by just the one that minimizes the sum of the distances from all the rest of data belonging to the cluster. Okay? So this K-medoids has an additional advantage. And the additional advantage is that it can be used with whatever distance that you have within your points. Okay? Because while in the case of K-means, we are using the properties of Euclidean distances for computing the centroids. In K-medoids, you just need distances between all your data points. So you don't need these distances to be the Euclidean distances between data points. It can be whatever kind of distance that you want to employ. Okay? And finally, yes, I want to say the last problem for spherical clusters. And the last problem is that it only allows you to find what it's called spherical clusters. It's not that they are spherical, but let me explain it to you a bit better with one example. Imagine that you have something like that. If you have something like that, and you apply K-means, K-medoids, whatever, you are going to have, in the best case, with K equal to 2, something like that, with K equal 3, something like that, with K equal 4, something like that. You are not going to be able never to reproduce these two clusters with K-means. No K-medoids. And that comes for, because the way that you define the centers do not allow you, I mean, to obtain something like that. Because a point that is near in the center of this cluster would be assigned by distance to the center. In this sense, you can talk about spherical clusters, because the points are assigned to the nearest center. So this problem is addressed by other methods, like K-means, like kernel K-means. But today I'm not going to arrive to these methods. I think for today we can leave it here. Okay, not for today, but I want to replace your questions before continuing. So I was, there is one, is it possible that there be more than one minimum elbow in the cost function? The answer is yes. Mostly imagine that you have a multi-level structure. In this case, you would probably obtain more than one elbow. So more questions. If there are no more questions, I can go to the next point, that it's the fact she means. This is a method that it's quite all newer than K-means. It's something like 10 years newer. And old, of course, because it's from 84, and it's still also widely used. As I told you, it's a version, it can be considered as a version of K-means, where designation is fact sheet, in the sense that you have a degree of membership from each point to each cluster. And once you consider that, you just adapt your loss function and the optimization algorithm to this to fulfill this. The idea is that your new loss function came from this formula, where you, it's the assignation that now it's a matrix, right? Because you have a degree of member for each element, you have a vector of assignation. So the total assignation of your cluster is a matrix. And what you compute is the distances from all the points, the square distances from all the points to the centers, in which you consider the weight of the membership. This M, it's a parameter of the method. You can say that in general M, it's equal to 2. It's widely used. And now the center, it's also compute as the average, but the average weighted by the memberships of each element. Once you have this loss function and this way to compute the centers, what you do, it's, in this case, the algorithm is a bit different. Instead of picking centers to random initialize your memberships and then compute the centers and from the centers, you update the memberships. This formula for updating the memberships, it's not important, but it's exactly that. And it's just a way that saying that the membership of a data point to a cluster would be bigger if the center is near. And that's kind of logical. And it's normalized by using this formula, you have normalized memberships. And since now the memberships are not integral numbers, but real numbers, you have to put a threshold in the exchange of the membership metrics in order to finish the iterative procedure. It has the same problems like it means. It's sensitive to initialization, the number of clusters, you have to decide it. And you can decide it also with the script plot. It's also sensitive to the lines. And now there is not a Cayme-Deutsch way of solving that. And it generates clusters that are near the center. However, this is somehow mitigated by the fact that you have a fancy asignation. Questions? Maybe I was too fast on that, but now we have time for questions. So if there are no questions, I think we are going to finish here. So, okay, there are no questions. Let me stop there. They're serving. And nothing, I would share the slides on, not now, I would share the slides with the notes or also in the metrics. That's all. Mateo, I think we can stop the recording.


This review examined the literature on the use of immersive virtual reality, IVR, for physical activity. Eight studies were identified, which showed evidence of positive physiological, perceptual, and psychological outcomes related to physical activity through IVR. These results suggest that IVR could be a promising tool for developing and maintaining healthy lifestyles. This article was authored by Freda Giconier-Mirez, Andres Gadoi-Cumilaf, Sebastian Esposlazo, and others.


Hello everybody, I'm EvilRabbit. We're here on a set of Corsa DealsGap aka tailings of dragon to do a stay in your lane drift challenge with this S13 So make sure you guys follow me on all social media all found in the description box below So we do have a new wheel cam going on. We have a razor here 60 fps wheel cam So hopefully we're gonna get some crispier You know wheel cam footage for you guys, so we're gonna go full set if you guys don't know What? Stay in your lane challenges It is drifting in between the mayo and the mustard Where you would if you were actually on the road, so I would get Probably gonna go over the line a bunch. This is a very narrow road never tried drifting such a narrow road in one of these challenges so Like right there. We kind of just already went off the road so This is going to take some funness to be able to stay Oh fully on my side of the road So definitely a challenging thing I challenge. I've done this poor on a couple different tracks, but never One with such a tight Yep, we're way over the line there. Mm-hmm. Well, that's one Never one with such narrow like road So this is definitely a Fun challenge to stay on this side of the road And drift all the fun corners Got the pedal cam and everything back for you guys as well This is gonna be quite the challenge Because there's not much room for error putting this Yes, our rs v2 wheel through its paces There's a lot of corners that we can't a lot of straights that we're not going to be able to drift on Well, don't go to dirt. No Already in the dirt I mean, that's one issue there But we're gonna see what we can do fully This is an extremely Tough road to do this on As you can see, there's not much room for this car to fit to keep it in between the male and the mustard That's the tire drop there Gonna be using it lising a lot of left foot brake Stalled the car out sort of clutch kicks And a lot of handbrake to keep the car kind of an angle through this Oh dirt We did crossover on that because we had to come out of the dirt So the inner corners are a little easier Because we can kind of drop our tire In the the front tire in the dirt Not so much back there like that That could get super sketchy I mean my back bumper is over the line, but you know But if there was an oncoming car, we would have Definitely collide in Oh, we drop in dirt. Oh, we got it. We dropped the front tire there Oh, we're way over the line there Yep Front tire is definitely over that line This I don't think this road is even wide enough for One car to be going sideways I mean sideways is not much angle, but So let's talk about a challenge We need like a small little Like B out of 4th rear wheel drive or Something super narrow To stay fully On the side of the road Nope Cut over to I've lost count I definitely way over the line that one. This is This is hard Yep, that one too To be guys have this track. I challenge you to try and do this I feel like I want to bring a bunch of different cars and try this Some other street cars maybe some pro cars Staying here laying challenges something I've done a few times before Like I said But never on such a small narrow road Yep, we're over there I don't think it's Honestly, it may not be totally possible to do this We like said, we probably need a really short wheelbase car. We're not doing too too bad Given We are just going full sen too We're not trying to be very cautious That dirt job screwed us up and I got my hands all twisted Oh, we're way over the line there I mean full blown out drifting this course is super easy and super nice We're trying to stay on this side of the road Not so easy Oh, geez That part has a bit of a An offshoot that we couldn't utilize Just belching why here that was pretty pretty good, but we were definitely over the line with a bumper I feel like this car's got such a big bumper on the back end It's almost impossible not to Oh Oh boy I don't know how we saved that They were definitely over the line there. There's not enough room Man didn't try to make the best out of it Probably less angle we could probably do this but what fun is that? See if we do it with less angle like that we could definitely Stay in but That doesn't look as cool. Geez We just met hard break So we did not fall off the mountain that would have totally just ended everything off the rip our gear So I do challenge you guys to try and do this. This is a extremely puff course to do A stay in your lane and if you guys do do what I would love for you guys to show me the replay Either tag me in it on like instagram or What not because I'd be very curious to see some people do the entire deals gap In the stay in your lane challenge Oh And not cross the line Like I said We need a small car because this car is really big When it comes to the size of the bumper and everything Love s-13 is probably one of my favorite S chassis of all The road's getting narrower. Is it getting narrower? Is it just me? No, it's definitely getting narrower So I We managed to make it all the way up and uh We managed to fail the stay in your lane challenge tremendously So I challenge you guys To take on this challenge as well We're just gonna we're just ripping it downhill because why not? We're not trying to stay in the lane We may do that on another episode try and do it the opposite way in the opposite lane So if you guys enjoy this you guys want to keep seeing here more honest set of courses like this Let me know down in the comment section down below and as always I thank you guys for all coming back To another episode here on the channel. I appreciate all the support If you guys are not subscribed to the channel, I would appreciate it if you did Tap that subscribe button and uh hit the like button It helps me out tremendously in of course youtube algorithms So as always, I thank you guys for coming back and watching. I'm evil rabbit So yeah, we spun out. I'll see you guys on the track


during the last topic, she was arranged tod ke inst Father J hotel. the person entour very Männer Omitave barriers in the POS business, she said if POS business I would do show me at she swung the bottle filled with little water upward for the empty time you can see how frustration as she has the bottle landed on the table standing erect yet again d d d d Jenny d decorated onnaise  kla ი Mansion అతోక్పత్త మతుగాపెం. న İj క౉నా్లి� viendo�ా. న మ renovation మాిావాదkor మహై ం౗న్హెపిఆం కుచద్థఠి è centiro Fabio గా describe సనిన、ఆరికౕ addiction పక్రకనకరామ kunt�ిథ KENN�ిని Kö Turkey o ku ungettheagrimjoubs. Hayndz différents de méme and comedian's kits on sosial media  glare ____ to traduce biznes and deserved to involve the Ne...... ____銀 sen nít for the records. Financial inclusion is a deliberate policy of the federal government to alleviate poverty ____ n vars and reduce inequality gap in the country by formulating strategies ____ in tandem with the world bank goals to financial include ____ 80% ofate Nigerian population. Mobile money are bank agents who coincidentally are at the last rung of the ladder. Had the most important players in the drive to financially include the excluded population of the country. Many who have caught the dream since its inception in 2011 have carried the badge with dignity and honor. The progress achieved so far in this drive haven't been without sweat and blood of mobile money and bank agents. It is therefore saddening seeing how many who now enjoy the ease of access to financial services and pretend as priority themselves as agents make mockery of the business. These recent realities have the propensity of draining the goals of financial inclusion. And all players in the industry have roles to play in ensuring that the sanctity of the business is upheld through intense public awareness, agent training and retraining, and increasing innovative product offerings. Actually, the business is not for those who seek daily bread. This business is for those who are ready to go all the way to providing critical financial services to the last mile and also making a decent living while at it. Well, the way I see this issue, I believe perhaps maybe there should be what I call a cooperative approach. When I say a cooperative approach, I mean maybe there should be a coming together of groups of POs, organisations which will now enhance their training to develop and deepen this market more. I see that otherwise you will continue to see, as he mentioned, these gaps in their knowledge, this inability to know what to do. I don't know why you say it. Thank you. There is actually an analysis of mobile money and back-agent in Nigeria, which even in the six national conferences coming up next month. Beyond that, the problem we are seeing right now in today's sector, just like you are talking about climate change issues, which are not issue-based. It's a problem. I will narrow it down. Let me form an understanding. Financial inclusion from statistics shows that we have over 100 million bankable add-outs. Add-outs who are banked, of which over 50% of them are not banked. Right? Now, where the problem is this, the category error, people who sell catru, people who sell tomato, people who say yeah in the north, in the far north and stuff like that, they deal with cash. We talk about privatisation of business the other time, and you talked about probably access to finance. But cash is an enemy of progress because with that exchange of cash, you lost data. So if I want to finance your business, how do I want to know how your business move? Is it an ads option? And that's why you say I default rate in the notes that we are seeing right because there is no policy that is sweet to the market because the data is missing. People are actually transacting with cash, exchange of cash by hand, no data to support it. So what this financial inclusion tells is, number one, it's promoting identity just like the enforcement of NIN because if you want to open an account, a standard full-fledged account to be able to transact in millions because it will amaze you that all this base pyramid last month are the people who are actually transacting huge amount of money. See that over 40 million Nigerians that are banked that are already banked at the moment, how much salary? How much salary that is calculated? A category where I can do 5-10 million business in a day but beven version 1, beven version 2 do not allow them because you have basic identity. If you want to open a bank account, you have to have a national ID. You don't have to understand. So there are a lot of factors, program of development. What this periods business entails is a lot just like you have said. There are a lot of knowledge gap because people don't really understand what service they are actually rendering. Right? Now, you are meant to bank to create service for the unbank and the underbank. Who are the unbanked? These are the categories I just explained earlier. We don't even have a bank account at all. But what the current situation is over 50 million Nigerians. The current situation that we have in mobile money business today is the 40 million plus Nigerians that are banked already that we are fighting because it is somebody who has a bank account and has an ATM card. If you are not banked, you cannot have an ATM card to transfer to it.  So meaning that it is these 40 million that are not even doing much transactions like that until maybe a surge of when they pay salary but then you do the third week of the month or the month transactions are going down because you know people that already have those things very few that are actually people who are doing no business.  So people should see themselves as a problem solver. That is what is missing. They are not seeing themselves as solving problems. They are seeing themselves and it is an ideology as a general that I just want to make money. And that is why you see a period that was a year like that probably around 2006-2007-2008 when period that business started. You just see one person start period that business and say there is money here. All of Nigerians are rushing into period that business. You see, even those who are dummy because they have money they are just I want to start fintech business. How much do you like your license? A lot of license is wasted there. They have money. They are using their capitalists you know veto power to load on people or whatever but they are messing things up because they don't really understand the problem they want to solve. They are just seeing it in the aspect of I want to make money. The same thing goes to the issue of POS. Just like he said, people feel if I don't get my dream job let me go and start a BOS business. I say so that I'll be able to do my daily project. It shouldn't be that way. What problem are you solving? Is it like you have to have 10 kilometers to walk to the bank then provide a one stop shop where you have an agent that can actually provide that service instead of you walking 10 kilometers. Let's say for every one kilometer let us all one one or two two agents solve that problem. Or you have an area where a bank is situated and you have a bank to attend to 2-3,000 people in a day. If you have like 10 20 POS agents who are not far from there to decentralize that because all this transaction are still passing through the banks. So another problem that is seen is banks seeing those agents as competition. So wait a country that we will live in. Things will happen follow due process for charge back and stuff like that. You see them coming back to go and your money is with the POS. Are we not informing you not to use POS agent again. It doesn't speak well of a development that is creating jobs that is solving a problem that you are also making money from it and it paying your bills paying your salary that is a pure knowledge gap because those people are saying that who are staff and employee of those banks do not know what they are saying. It shouldn't come out. So you can see that beyond the pureness business even when you go into other set of Nigeria everything like that happens. If you see somebody sending flower like that to know the purpose. So I think what I will speak to is the propensity of Nigerians to double into any business without really understanding what it entails. What we are saying so far in the mobile money and agency banking is that you will ask the so called agents about financial inclusion they don't have information about it. So they don't know the role they are playing in the sector because and like we said we are supposed to include many excluded Nigerians into the financial space and why? Because you need to reduce poverty in the station where people don't have access to finance there is no way you can have access to finance when you cannot build credit and how do you be credited to have a bank account? That is what a financial institution will look at to see I mean it is easier for Salahiyanans to get credit because they have transactional history that the banks can look at but for the tokenizer for the carpenter who do not have account for your mechanics I mean after the finish fixing your car you ask them you want to pay they say me I don't use account how much do I have but the hand money in a week you know you can put figures to what they have and at the end of the day when they need some other things to expand their business and to do some other things they don't have access to this finance because they have not built a financial history that the banks can use so in this case as a mobile money or bank agent you are able to number one give identity to Nigerians by way of NIM do be be in enrollment these are services we are supposed to be offering you are supposed to be able to open bank accounts and issue ATM cards but what you see out there is because I see Mr. Hai doing well with a pure stamina then I joined the free I don't even understand why the business exists and that is why when they even have issues like he said and the bank staff so unfortunately many of them to I mean have this knowledge gap we still need to train them some of them even I mean think more of themselves because they in low fairness because they are in suit I mean they feel they understand the business more than you do but sometimes you will see that pure as mobile money bank accounts out there have more knowledge about the business than even some of the bankers that is the truth so you need to begin to see why and you mentioned something that there should be and as I said there has been as I said I mean since 2015 during a lot I mean I can tell you that the awareness about the business sector today I mean this old you can I mean say that Amban has done a lot about I mean creating awareness I mean giving finance support to financial support to agents and and then helping also to build some products because of the the feed knowledge that many of the members have so that's a bit of joining anything this copycat approach we just want to join we just want to do it and then you begin to mess things up and then that's where you hear I mean people say I just want to earn my daily bread the business is beyond and your daily bread the business is more than that the business is such that I mean if you look at some people who have started this business 2011 2012 and they tell you what they have been able to achieve why solving problems why servicing people going to the hinterlands the creeks to service people will normally will not be able to come to town to get financial access nowadays you have people walk few steps from their house to access their accounts to get funds to send money to people it has made life easier for people it has put food on the table of people people have been able to build a house and all of this but when you now see people who do not have this knowledge go on the internet to do skits to disparage the business you begin to wonder do they even understand what this sector entails what problems we are solving you see my approach to it is to look at it this way in a non-developed or developing society such as ours like I was telling you you always look towards government to build the structures it's not easy there's a reason for government I see a rule for CBN in the issue of financial inclusion you must take the policy from where you start to the end where you want to reach the problem I see is that an informal sector has been allowed to take over the thinking for government that is why you will find that is why you will find a situation where people are not aware of what they are doing you see I think personally that CBN should have a section if they can't do themselves they should create a body to link up with this cooperative that we have mentioned so not to continue right I think that is in place already we have what we called shared agent but people are not doing what they are supposed to do so these problems are things that you need to think through from the level of government that's why I say don't just say if I don't have work to do I will go there if I have no a belief of thought about what this business is about I will be like that but there needs to be more work when you have a society the education level is low let's not lie about it we are not educating our people many of our people are educated across the country we talk of the Fulani Kathuman you want him to come into the banking system to use POS to use this to use that when he is a nomad he has no education so he will say cash since you need a holistic program from the government level not stopping at some point as a private sector come and take over particularly when you know this private sector doesn't have the seniors they don't have the mausoleum they don't have the capacity what you are dealing with is a problem of lack of capacity you can't just leave it to them the bans are there for profit it is only the government that can think beyond profit this policy we want to use it we think beyond profit of individuals or banks or whatever we want to implement a policy of financial inclusion take society from this point and take it to the next point that's what I see here of course that doesn't stop you must develop education you must so there is a whole myriad of things government must still do it I know what you say in my place I understand the thing is this we cannot take the sector out of the main I mean the whole spectrum the sector or I do I put it is still a small segment in Nigeria and if you put that into perspective if you put that into perspective if how we run things in Nigeria you understand why we are at this level because of course we have laws our problem is this country has nothing to do with laws and policies we have the laws how do we implement this laws who are the ones to ensure that the laws are implemented that is where we have the problem until we get that the hand always seem to come too soon on the advocate however the advocacy continues on our social media platforms on facebook plus tv africa hashtag the advocate ng or on twitter and instagram at plus tv africa hashtag the advocate ng to catch up with the previous broadcast go to plus tv africa.com slash the advocate dot ng to subscribe to our youtube channel plus tv africa till next week same time on this station let's keep advocating for a better society bye bye


Rudy Giuliani has filed for bankruptcy. Of course, he lost the lawsuit and has been ordered to pay $148 million to the victims of his defamation. He also has very large legal fees. He also has unpaid taxes. And he's also, you know, in the midst of just finished his third divorce, which have all worked to basically bankrupt Rudy Giuliani. This is the Rudy Giuliani who used state power, yeah, to clean up New York, but he was pretty fascist in doing it.