Hi, welcome to nursing school explained today. I'm coming to you as a yoga instructor emphasizing the need for relaxation and stress management. There is one pose that is really easy to do and has a really great calming effect on the body and the mind. So this is something that I want to share with you today and it's called legs up the wall. So really all you need is a wall and maybe a blanket that you fold up that you can support your hips on. The easiest way to get into this is come really close to the wall with both buttocks and then walk on buttocks up the wall and then simply roll on your side and bring the legs up the wall. Now you can scoot yourself in a little bit and straighten the legs. Depending on how your hamstrings and your glutes are doing you might want to put this blanket underneath your bottom for a little bit of extra support and to elevate the hips plus it takes the stress out of the hamstrings and deltides. So this is one option or you can just simply scoot yourself back a little bit which will decrease the angle of the legs as well. So you just find whatever works for you and then you bring the arms out by your side with the plums facing up so the chest can be nice and open which allows for the nice expansion of the breath.  While you imagine that there's a balloon at the belly button that you inflate with the inhale and then pass the inflate at a deep later with the exhale and as you start to settle into this pose just notice where your thoughts are when they drift away to anything else that's on your mind besides this pose and the breathing right now just simply draw the attention back onto that breath those nice deep inhales and exhales and the sensation that the inflow and outflow of the air creates on your body and your mind. I recommend staying here for at least three to five minutes you can even stay in this pose a little bit longer it also helps to relieve any aching the legs you might have after a long hospital shift or clinical shift or just being on your feet if that's what you're doing for a living when you're running around all day long it really helps to reverse the direction of the blood flow and has this nice effect on the nervous system you know so it works well to do this before you go to bed in case you don't sleep well it kind of has a nice common effect on the entire physical and after you've been here for about three to five minutes the easiest way is to just bend the legs here at the knees and then just slightly roll in and roll back out rest here for a moment on your side to let the blood settle back in that this horizontal plane with gravity just press yourself up to a seated position maybe take a moment to notice how you feel maybe close your eyes take a deep slow breath in and out thank you for joining me in this very simple relaxation technique stay tuned for more of those to come up on YouTube as well as on Instagram here at nursing school thanks for watching


Good morning! Oh my gosh. I feel like I slept so hard the last night. Anyway, it's morning time. Our room is a mess because go wild and it's morning time! Oh my gosh. Ah, see? It's really morning time, y'all. Um, Ryan's in the shower getting ready and I'm gonna get in the shower in just a moment here. But it is day two of go wild and I'm looking forward to today's speakers and all of that good stuff. So I'm just, I'm just excited. I'm excited for the day.  Once ever, that's how it's supposed to look. It's supposed to look extra crazy today. So, um, we've got day two of go wild and then we've got, um, at the end of the day, our plan, er, planjama? Oh my god, I'm like really second-guessing what it's called now. You know, yeah. Planjama. Oh my gosh. I'm really losing it. Okay. All right. Well, I'm gonna get in the shower in just a couple of minutes and I will see you when I am dressed for the day. Now we're together. Hello. We'll do a little outfit of the day. Would you like to talk about your outfit and how we can't see you? A gender-neutral desert camo crew next watcher from Old Navy and jeans from D crew and then just comers. Nice. I'm wearing a Levi's of a denim jacket, a shirt from Amazon because, you know, and then this is my ode to Jen Cabrera. It's very dark from this way. Okay. There you go. Oh, there we go. This is the ode to Jen because she cannot be here today. So decided to go with some rainbow stripage just for her. Hi. Good morning.   Downtown Disney. Ryan's here. Got an Uber. It is coming in four minutes and I'll show you the whole when I get back, but we just had some lunch. We just needed to get out of the hotel and just venture out, you know. It was kind of nice earlier, but now it's pretty windy and a little chilly for even us Minnesotans. So. Gale force winds are in the forecast. Yeah. So we are not having, we're supposed to have our plan jam outdoors tonight, but it's been moved indoors because there's some wind issues. So, but we'll get ready for that as well and I'll show you our little outfits and yeah, I'll show you all the swag and all the stuff I got from Disney in just a few minutes. So sorry I didn't vlog in there, but we literally just went shopping and went to lunch. That's all we did. We didn't do anything exciting, so. It was delicious and expensive. It was, but I feel like everything here is expensive, not just because it's Disney, but like just Anaheim. Also we're on vacation, so like whatever. This person looks like it's just pulling up, so we'll see on the flip side. Well, hello. I am ready. Well, not ready, but I just put my pajamas on. I got this from a little number from Amazon. It's like the Amazon special. I'll put it down below. I'm just got stuff here. I'm gonna flip here. I'm showing my bed quick because I got stuff. This is the stuff I got at Downtown Disney. This California sweatshirt is from Audrey, Aubrey, Audrey. Yeah. Anyway, it's really nice. It's not like a Disney brand, but it was, there was a Disney store. It's a really nice little sweatshirt. And then I got this t-shirt that just says Disneyland and all of the like characters. And then I got some Star Wars pins because of course we had to go into the Star Wars store, which is exciting. And then I got these because nostalgia. Do you guys remember the Muppets? The Muppet Show? So cute. Anyway, but these are the things I got. And I am going to partake in figuring this situation out, which is like all of our swag. So it's like these, the purple bag, the kind of bluish purple tan, and then this huge bag is full of stuff. So that's my plan before we go to Planjama here in about an hour or so. So yeah. But yeah, that is the plan. And I will kind of show you the process when I finally get done with it. Okay. So we have decided what we're going to destash, what we're going to keep, all that good stuff. So Ryan had the genius idea to actually bring a bunch of his de-stashed stuff from Minnesota to Anaheim here. And it's all in this orange bag. So yeah. And so there's a ton of stuff that was his. And then there's a bunch of other stuff that we ended up de-stashing from the stuff that we got. So obviously nothing's wrong with any of these items whatsoever. They're lovely shops and lovely shop owners and very generous. However, the nice thing about de-stashing it here is it's actually going to go to planner people. So we're going to go do that on our way to Planjama. And yeah. And I actually noticed that down in the lobby, there was like two or three tables, like full of de-stashed items. So that is where we're going to leave our little area here. So I'm sure if someone is going to use and love all of these things. And yeah. So let me show you what I am keeping from my, or at least an overview of what I'm keeping. And yeah. So I sat at the mild liner zebra table. I think it was just called the zebra table. So the first thing is this huge box set. I'm keeping that. And then I have a bag. This is like a cute little gift bag from Aaron Tondren. There's actually another cute little gift bag that we had as well. So I'm going to keep those, taking those home with me. I have my t-shirt from registration. This was from the table.  And then some of this stuff was from my table, but other stuff was from like other little giveaways. And then these, I have a whole bunch of these, like just more random pens. I have a couple bags I am keeping. And then this, I will go through at some point and show you. But it's like all of my extra stickers. And there's some washi and there's a planner and some notebooks and such. And I don't think I have anything else. My plan jam outfit didn't go as planned, so we're wearing my wild U-shirt because that's pajamas that I got pajama pants on. So nothing crazy. But so I sat at the Christian Designs table because I'm a caddict and that's pretty obvious from my whole life on the internet. So we got these adorable mini little sticker binders and it says don't touch my stickers. Super cute. And then in here we got a really fun, it was like a Christian Designs.  Like I'm a smart lady. But yeah, so you can see we got a cute little pen here and then you know, Kristen, when she picks the color scheme she like goes all in. So you got this fun little one here and then obviously these say like don't forget evening routine, some stuff like that. And then there's a kind of a coordinating mini kit that goes along with each of them, which again, gorgeous. There's some other sticker sheets that I put away. I use the sticker bind this little thing I got actually from the flask a wild and I just kind of tucked a lot of what I had in here. I'll do a full haul on my channel, but we also got these adorable notebooks that say the answer is stickers. I don't care what the question is. There's a whole bunch of other stuff here. I think I'm going to be doing a giveaway because Emily, some of the time Emily didn't want. I'm going to kind of collate and do like a wild at home giveaway for those folks who weren't able to make it. So that will be fun. I'll put that together and you'll be able to enter that. So it'll be like you get some of this swag from hanging out at home, which is fun. But yeah, I think we're about to head down, right? About that time. So yeah, where you're going to run down to the situation downstairs, the planning of the jammas. And then I'll take you along with me and we'll see you in a few. Jammas. So convenient. Anyway, the conference is now officially over. So bye-bye. Go wild. But we're here for a little while longer. So yeah, tomorrow we are going to take you along on the journey and keep vlogging until we stop vacationing. So we're going to go to Disney tomorrow. I'm excited. I've never been. I want to see Mickey Mouse. It's Ryan's turn to vlog tomorrow. Ryan is very excited for the Star of the Wars. Oh my god. Freaking out. Okay, did I talk about this yet? That I was lost money. Okay, I don't know if I even talked about this yet. But we went, okay, so we went to Disney, downtown Disney, right? So there is like just a bunch of shopping and also all of like the food because we just wanted to go out and get some food, right? We walk in and directly to the left is like this gift shop that's all Star Wars stuff, right?  So okay, to be fair, this is my shirt for tomorrow. Yes. And on the back, it says a long time ago in Galaxy Far Far Away. Now, I'm going to just say Star Wars is one of my favorite movies of all time. Like I remember, like it's a core memory thing. Like I saw them with my dad when they re-released them in the 90s. Like it was a thing. So when you walk, when you walked into downtown Disney, there's like, it looks like a rebel base. And I like, I was like, are you serious? I thought it was something under construction. Okay, keep going. You did. I forgot. I totally did. I've never like, yeah. Anyway, because I was like, why are we going into something that like, you know, looks like like the military is like setting up camp. I don't understand. And so I was like, no, no, no, no, no, no, I'm like, this is a rebel base. It's very similar to Gavin 4, which is from one of the movies.  Yeah. I like, I dope deep. And then you'd be like, what's that? I'd be like, did you know? Yes, I was getting a lot of factoids. Yeah. Yeah. So I just, I love those movies. Yeah. As I know that Galaxy's Edge and Star Wars is going to be just nuts. So I really want to do Rise of the Resistance. And then I hear what it's called the Millennium Falcon 1, where you can like be a pilot or an engineer. It's all gone way over my head. All the things you've been saying. So. But we're going to do the classics. We're going to go see the castle. We're going to get some Mickey for Emily. Yes, Mickey Mouse.  We're going to get her dole whip. Yeah. I don't know what that is, but I've heard good things. Yeah. So I've never been to Disneyland, but this is random, but I, I love Disney YouTubers. So like Michael Kay and Jen LaForge. And then Bippity Boppity Brooke has her shop here. I like dove really deep like two years ago in the pandemic and watched all these old videos. So like I'm knowledgeable, like booksmart about Disney, but I've never actually applied it. So I'm excited to be like, yes, we go here. We're here and here. Yeah. So I'm pretty stoked. Um, this one is going to cry tomorrow. I guarantee it because. If I make a lightsaber. Okay. I'm going to cry. Here's the thing. We got to this like underground temple area, whatever today. Rebel base. Whatever. It was a gift shop.  And I'm like, dude, it's a gift shop. Are you okay? And I mean, he's been telling me this whole time, like I am going to cry when we get into the Star Wars world land, whatever. And I'm like, so I mean, if he was like on the verge of tears, if you were on the verge of tears today at a gift shop that was just themed, what tomorrow it, you're going to, it's going to happen. Two things. One, let me put it to this way. I have one tattoo on my body and I have considered multiple times getting the rebel alliance symbol somewhere else as my- I mean, why don't we do that tomorrow? You know what? I don't think that Disney specializes in tattoos. Don't they? Secondly, I made the joke earlier this evening that I said, Emily, now you understand other people's reaction outside of the planer community when we freak out about new pens, new colors of mild liners, this amazing new thing at the target dollar spot, like the joy and the like absolute emotion on this of like the gratitude of like, I found planer peace.  Right. You witnessed that for something else? I did. Which is just pretty funny. Yeah, I did. And like, I recently in the last like decade watched the first couple of the, you know, Star Wars movies or whatever, like the first original three, and then I haven't really seen the other ones, like the new-ish ones, like episode one, two and three, right? Those are the new ones. New-ish. Yeah, those ones. Okay, so I saw all of those. The old ones are the best ones. The new-ish ones, like the episode one, two and three. I didn't get it. There are some good ones. The timelines a little weird, do you have to follow along? That's the problem. I was like, this escalated quickly. Oh yeah, no, there are moments. Yeah, I was like, I don't, huh? Like, anyway, but yeah. So it's not like totally for me, which is fine, but it's definitely for this kid over here. So he is going to be freaking out tomorrow. So this is the long-winded way of saying, you need to watch the next vlog because, oh my gosh. Yeah, I just, I overall like the go wild weekend part of this. Like, I just want to thank everybody on Team Wild. Team Wild! Jeanette, Lauren, Jasmine, Lisa, everybody that volunteered, like Julie, Jen, Lauren, you all just stepped up and like made this weekend possible for a lot of us. Like, I was like, I didn't believe this was happening still, even up until like our point. Right, exactly. Like I kept waiting for it to be pulled out from under us and so it was a wonderful weekend. It was so nice to see everybody again and be in the same place and just soak up that energy. I'm gonna need to process. I have to put off the processing, I think, until we get home. Yes. Because we're going to Disney tomorrow, as you heard. But yeah, just a wonderful weekend. Chef's kiss, if you will. Yes. Yes. So anyway, we're gonna go, we're gonna say goodbye. Here, we'll do it this way. This is like, that angle is like. Hey, you know what? I'm a professional, okay. Okay, but we're gonna go and we'll see you in the next vlog. We're gonna go watch every Star Wars movie before tomorrow. No, we're not gonna do that. Then I would not go. Yes. I would be like, no, thank you. I bought your ticket, you're going. Well, I know, but like, I don't know. Is this gonna be like Lord of the Rings? What? What's wrong with Lord of the Rings? Okay, I gotta go. All right, I'll talk to you guys later. Well, folks, it's time to kick it off school.


Free and open science means everyone should have the freedom to share, study, and modify scientific material. And in free and open source software, everyone should have the freedom to share, study, and modify software. Seems to me almost identical. And this includes all research related activities, tools, and output, not only source code.


Hi, I'm Iaku Parota and I'm a Senior Software Engineer at RELAT. Today I'm going to talk about the trustworthy decision management and how you can increase the trustiness of your decision models using trusty AI capabilities. I'm going to talk about trusty AI in few minutes, but first of all, let me quickly introduce business automation, for those who are not familiar with it. Trust automation was born because some businesses simply needed to automatize processes. And the goal was to increase the efficiency and control the costs over the organization. Think about it, if you have a decision or a process that follow a standard workflow and that you can automatize, you would like to focus only on the problem itself and not on the technology. The business value is your decision and not the run time or the development of such decision and the maintenance of such decision model. For that reason over the years, some standards have been developed so that you can just focus on the model definition and not on the technology that runs it. In the industry we have some standards, for example for processes we have BPMN, for decisions we have DMN and for rules we have DRL and rules in general. In this talk I'm going to focus on DMN only. For that, strongly believes in open source and open standards. And business automation products have been built on top of such standards. And the idea behind these products is to provide a generic run time for business automation resources, so BPMN, DMN and DRL. Those products are perfectly integrated and they enable really a lot of new scenarios with this combination. And in particular I'm going to focus on BPMN and PMNL. PMNL is a standard for the serialization of machine learning models. You can start with your data, train your machine learning model with the language with the tool that you prefer and simply export it into a PMNL file. You don't have to be an expert of PMNL so it's just how you're going to store the model. It doesn't impact the training of the model at all. Once you have exported your machine learning model you can then import it again with the same tool but also with other tools written in other languages. Also your model has become portable and the training is now completely decoupled from the run time because you can train your model with Python, with R, with whatever language and execute it in production with another language, for example, because the service will simply import the PMNL file and execute it. Once you have exported your PMNL model it can be simply be called by a DMN decision. And this integration between PMNL and PMNL enables a lot of scenarios because it combines the capability of both standards. It also supports this soft connection between departments between the same company. So the communication channel are now the standards and both parts do not need to be technology dependent because the business analyst that gets, for example, a PMNL model doesn't really need to know how that model was trained and what was the language, what was the data, because it is a portable model at the end of the day. Red Hat started 20 years ago with business automation, so it has a lot of experience. And a few years ago Red Hat started a new brand project called Kojito to build business automation microservices. Kojito is the next generation cloud native business automation solution provided by Red Hat and it's built on top of corpus and springbook if you want to use it with both. Roughly speaking Kojito is the runtime for your business models, BPMN, DNN and DRF. It's super easy to use and also to consume because you just create a new Kojito project, which is a Java project at the end of the day. You take your business models and you put them inside the project. You just compile the project and Kojito will generate the microservice for you. And it's ready to be consumed. It is already integrated with all the top notch technologies for microservices, so Knative, Kubernetes, OpenShift, Kafka, Grafana and Prometheus for monitoring and many, many others. But now we get to the point. Can you trust your decision? Because the standards are not enough anymore. In the last years many companies faced reputational damages due to machine learning usage. And in this example it's just an example. An Amazon store was biased against women, but there are plenty of examples like these that impacted all the big companies, but also small companies. And not only, there are also some regulations like GDPR that make some constraints and are making things even more complicated for production environments. Since we are dealing with decision models and in particular machine learning for business automation, it is necessary now that decision services are monitorable, outbeatable and explainable. Usually there are different personas involved in business automation. So, for example, we might have data scientists that have a very good knowledge from a technical perspective, but they might have limited knowledge on the business domain. On the other side, we have the business analyst who has a very good knowledge of the use case, but maybe it doesn't have that good knowledge of the machine learning model that has been used or, anyway, technical knowledge. Of course, this is not always true, but in general it is, so take it as it is. And as a matter of facts, it's easier to explain simple models rather than complex ones. Usually complex models can solve complex problems with very high performances, but there are black boxes and they are hard to explain. So, we have a trade-off between the explanation of a complex model and its performances. I've been working for some years for an insurance company and we were trying to find some new variables to improve the risk score calculation. And we used machine learning, very complex machine learning models, but when we talked to our colleagues that were doing the traditional risk score, they said that they already tried some complex machine learning models, but the main problem was the regulator. So, the regulator is a person from the government agency whose job is to check that insurance companies are not discriminating anybody, that they are following some strict rules and, for example, that the margin of your risk model is not biased and it's not against the interests of the policyholders, for example. And they used GLM for 30 years, a machine learning model, because it was really simple to explain and it was not possible to use a complex one because it was not possible to explain it. If we improve the explanation of such models, it will be likely to be used to be more adopted in the industries. Thrust AI is an initiative from Red Hat started two years ago and its goal was to add capabilities to business automation services. Thrust AI is in the ecosystem of Kojito and to get a bit some other services. The features that Thrust AI has to add to decision services are monitoring, tracing and accountability and explanation. And let's quickly go through them. So, the first one is the business monitoring. Based on your model, we provide some metrics that are dependent to your decisions. So, for example, if you think about the risk score calculation, a possible metric would be the average price for the request. And another one might be the average age of the request, for example. So, those are metrics that are really dependent to your model. And they are automatically generated. This is the nice thing. So, we provide a generic runtime but also a generic analysis of your model. We have another kind of metrics, which are the operational metrics, and they are more DevOps oriented. So, they are used to check that the application is running fine and it's healthy, for example. So, that the response time of the request are within a particular range, or for example, the number of requests over a one minute average and so on. The second feature is the accountability and the tracing. So, we keep track of all the executions of your model. And for each execution, it is possible to drill down to each specific input and output. So, for each execution, we provide the input, the outputs, the intermediate decisions, the model that was used to evaluate that particular decision, and the explainability for that execution. We provide two kinds of explanations. The first one is line, which stands for local interpretable model agnostic explanation. And it can be applied to any model that, so it fits perfectly our purposes. It provides a feature important chart, and the explanation is calculated as following. So, a data set is built, starting from the original execution, perturbing some inputs, and keeping fix some others. All those executions are then stored, and the result is stored, and a linear classifier is trained by labels. So, to understand what were the most influencing features that impacted the original decision. So, for example, in this slide, we see that the children is a very important feature for the original execution. But for example, the age was not. The second type of explanation is the counterfactual. And this kind of explanation aims to provide explainability by examples. So, for example, let's take the mortgage approval use case. A customer requests a mortgage, and the mortgage is rejected. We might wonder, what do we have to change so to get the mortgage approved? So, we set the desired outcome, which is the mortgage is approved. And we also set some constraints on the inputs. So, for example, I cannot change my age, of course. So, that one must be fixed. But for example, I can change the total amount of money that I request. Because maybe I cannot request $100,000, but I can request, I don't know, $80,000. And with $80,000, it gets approved. So, I let the total amount of money to vary. And let's see if counterfactual is found. So, now we get to the deal. And our use case is the mortgage approval. So, the customer requests a mortgage, the mortgage is rejected. And we put the head of the case worker, and we do some analysis, and we try to understand what happened. So, we have to start with the DNN model, of course. So, we have some inputs here. So, the age, the monthly salary, the total asset, the total amount of money that are required, that are requested, and the number of installments. And those are the inputs of this risk score decision, which is basically calling the PMML file that we are using here, which is a random forest model. This random forest model should provide a number between zero to 100. Zero, if the risk score is very low, and 100, it's very high. And you see here that this risk score number is then the input of this mortgage approval decision. And it's basically a decision table. So, if the risk score is below 40, then the mortgage is approved. Otherwise, the mortgage is not approved. I've already exported this DNN model, and I've already created a new cogit application, and I also deployed within the trusty AI infrastructure. So, if you would like to know more about how to create this DNN model, how I created the PMML file, how I trained the model, and how I created the cogit application, and deployed the trusty infrastructure, I will provide all the resources in these slides. And very briefly, if you would like to know to reproduce this particular demonstration, just go to my GitHub account under the trusty AI or the SC West repository, and you will find all the steps. And if you would like to try to build the cogit application by yourself, there is another repository always under my GitHub account, which is called FromDataToCogitoDemo. And if you would like to do it step by step, I have another presentation at the key line, which is our community channel, and it's 45 minutes. So, if you would like to have a look and comment it if you need any help, just feel free to write in the comments or to reach out directly to us. We have an open chat on Sully. So, okay, now we can try to execute a decision using this DNN model. So, the cogit application is running under localhost 8080. And here we have this work UI that we can use to interact with the service. And here we see that cogito has created an endpoint called MyMorgage, because the DNN model was called MyMorgage. And we can check it out. So, for example, we can evaluate the DNN model using those inputs. So, the age is 20, the monthly salary is 2000, the total asset 50,000, and the total amount of money 100,000, and the number of installments is 150. So, we execute it. And let's have a look at the response. We see that the risk score is 43, and the mortgage was not approved, because the risk score was above 40. Now, we can go to the trusty UI. The trusty UI is running under localhost 1338. And let's reload the page, because of course, no executions were calculated before I executed it. And you see here that we have one execution of the MyMorgage DNN model at the date is one minute ago, and the execution start was completed, because it was evaluated successfully from an operational perspective. We can drill down to the execution, and let's see what was the outcomes, the inputs, and the models, and etc. And you remember we had two decisions. So, the risk score and the mortgage approval decision. And you see we have two outcomes, the risk score and the mortgage approval. And we can see both the results. Then we can drill down to the details of the outcomes. We can select it with this menu. So, let's have a look, first of all, at the risk score. And we see that those were the influencing inputs. So, all the inputs were relevant for this decision, and it makes sense, because, of course, I created the PMML model, so I know it. And all the features were relevant for the risk score calculation. And here we see also the inputs, of course, of this decision. And if we go to the mortgage approval, you see here that the mortgage approval was not approved. And the input for this particular decision was the risk score. So, we can see all the intermediate inputs for all the decisions. This is really interesting. And we can have a look again at the input data of the model. We can do the model look up. So, for example, you see here, we have the model that has been used to evaluate the decision. And now we go to the counter-function analysis. So, as I said, we can set up the desired outcome. For example, let's leave the risk score to be adjusted automatically, because, of course, if I keep this risk score fixed, I cannot get the mortgage approved. Because, you know, if I keep risk score equals to 33, this will never change. So, I leave it to be adjusted automatically with this check. And I would like to get to have my mortgage approved. So, I set it to true configure. And now I can set some constraints on the inputs. So, for example, you know, I cannot change my age. So, I leave it as it is, meaning that the counterfactual must have age equals to 20. Let's try to change the number of installments. I can set a constraint. And the minimum value is zero. And the maximum value is, oh, sorry, not the number of installments, but the total amount of money that I require. So, here constraints zero. And the maximum value is the same of the request, so 100,000. I apply it. And then I can simply run the counterfactual. This is, you see here, this is going to be run for one minute. And it will find the best results that it can find within one minute. We have just waited a little bit. And you see here, a new intermediate result was found, but it will keep trying to find better results if possible. So, but in this very moment, you know, if I request 96,000, more or less, my mortgage will be approved. So, let's see if there is a better result, but I don't think so. So, we just wait until the time out. And then that's it. So, you see, all right, the best counterfactual you see here, it was found 96,000. But of course, 97,000 was better, because it was closer to the original request. And it was found. So, this is the best result that it will find to get the mortgage approved. Let's try it. So, we go back to this Wookie UI. And let's try with 97,000. And you see here, now that the mortgage was approved. So, this was the counterfactual analysis. Here, you can find all the resources with some new videos, with all the trusty AI introductions, and all the rest. So, thank you very much for attending and waiting for your questions.


It is my sincere pleasure to be here with you this evening, and it's a great privilege and honor To receive this award. I am deeply touched by it When I was a boy, I was lucky enough to have the opportunity to meet quite a few world leaders while traveling with my dad Something that struck me then and still does today is the reassuring humanity of those encounters However great or powerful a leader may be they are still just people and The majority that I have met I have to say with some gratitude Want to do what is right for their citizens and for the world If that weren't the case it would be a far grimmer world And it actually is The challenge of leadership indeed the very essence of it is To fairly balance the competing interests of different groups of people who have at times quite different aims and needs But sometimes events coalesce There are times when our principal aims and needs Become universal And I believe we are living in such a time right now Some might look at this council's half-century old mission to promote cooperation across the Atlantic as the rarefied concern of elites or an idealistic throwback to another century Well, nothing Could be further from the truth We live in a time Where global peace and security free and fair trade Human rights and liberty have never been more Intertwined or in this post-war era at greater risk and in greater need of our active focused engagement Alliances that have underpinned global security and prosperity since 1945 Are being put to the test And the urgency of the challenges we share in common climate change and drought Income inequality violent extremism Civil war and the mass migrations that result Continues to grow allow me to repeat that last bit in French for the folks at home Certain pourrait croire que la mission confié à ce conseil il y a demi-siècle soit celle de promouvoir la coopération des deux côtés de l'attentique Thelitiste ou qu'elle rappelle un idéal de notre siècle c'est faux nous vivons à une époque où la paix la sécurité mondiale les échanges commerciaux libre et équitable les droits de la personne et la liberté sont plus interconnectés que jamais Autrement dit dans cette période d'après-guerre ils ont jamais été autant en danger ils n'ont jamais autant eu besoin de notre engagement active et profond les alliances qui favorisent la sécurité la prospérité dans le monde depuis 1945 sont mises à l'épreuve et les défis auxquels nous sommes confrontés les changements climatiques et les sécheresse Inégalité des revenus l'extrémisme violent les guerres civiles et les migrations de masse qui en résulte sont de plus en plus urgent Worldwide the long established international order is being tested With Russia's illegal annexation of Crimea and encroachment in Ukraine We have seen the first major territorial seizure in Europe since the second world war This is not the time for retrenchment It is a time for the Atlantic democracies to renew our commitment to universal standards of rights and Liberty enforced through a multilateral rules-based order that has promoted peace and stability and stood the test of time We have to work together on this Which means a renewed commitment to long-standing alliances such as NATO and NORAD Bodies such as the United Nations and the WTO Global security Requires the ability to project hard power when it is needed. That is one reason why earlier this year Canada announced a robust long-term Reinvestment in our military with significantly increased spending for the tools and training our women and men in uniform need To do their jobs the second major pillar of global peace and security is of course free and fair trade As you know As you may know as you hopefully know Canada is currently engaged with the United States and Mexico in Modernizing the North American free trade agreement We're working hard and we're looking forward to hosting our partners in Ottawa this weekend for round three And as you may have seen in the media, Canada has been very ambitious at these talks particularly in advancing a Progressive trade agenda that puts gender equality the rights of indigenous peoples environmental protection and labor standards squarely at the heart of the discussion now Some appear to have been confused by this It's as though they expect us to do trade exactly the same way it was done by our parents a quarter century ago And yet there is a precedent Sita Canada's groundbreaking trade agreement with Europe goes into provisional application in two days It is the most progressive trade agreement in the world today We made it that way for a reason trade as it has long been done though broadly positive for the majority Has not been perfect If it were there'd be no political current against globalization Yet there is such a current especially in places where traditional manufacturing has been disrupted by Automation automation and off-shoring So we need to do a better job of ensuring the benefits of trade Extend to the middle class and those working hard to join the middle class not just the wealthiest few We made a deal We told people that trade and the things that went with it would lift all boats would benefit everyone And people have been wondering when that benefit is going to hit the majority That's what we need to turn around We need to do more to help the people displaced by economic shifts So that they can get well-paying jobs and provide for their families a big part of that Is upholding labor rights not just in our own countries but worldwide And again that's an important bit so I'm going to repeat it for the folks at home The solution is to get well-paying jobs and to support the needs of their families The solution is to get a big part of that in the defense of labor rights Not just in our own country but worldwide In short, progressive trade is not a frill In addition to being the right thing to do It is a practical necessity Without which popular support for a growth agenda could not be maintained The third pillar of peace and security is the advancement of human rights Liberty and tolerance the very touchstones of our societies Although even the word tolerance is something that I like to think we can get past Because use the word tolerance in a sentence I tolerate that you exist Doesn't sound very warm I mean there's no religion in the world that says tolerate thy neighbor I mean there are places in the world where a little tolerance will go a long way But I think in countries like Canada and the United States and Atlantic democracies We need to move beyond putting up with each other Towards words like friendship, acceptance and yes love This is both morally necessary and practically vital Respect for others regardless of what they look like The language they speak, the God they worship or the person they love Makes it possible for the human family to get along And getting along makes it possible for humanity to survive In the 1980s when I was a teenager The fight against the apartheid system in South Africa dominated the global conversation Canada through its leadership at the Commonwealth Played an important role in helping coalesce world opinion in opposition to apartheid Now we need to be every bit as strong every bit as vigilant in opposing the scourges of racism Sexism, homophobia, transphobia, ethnic and religious bigotry, neo-fascism, neo-nazism And the violent extremism of Daesh that confront us in 2017 We cannot waver It would be unconscionable to take even one step back In upholding the standards of decency Of the sisterhood and brotherhood of the human family That won the day in the most painful struggles of the last century Many of you here in this room remember those struggles We must not relive them and this brings me back to where I began The thing we begin to realize when we appreciate that all leaders are human Is that nothing is guaranteed That the global order that our grandparents and parents built isn't cast in stone It can change for the worse or as I prefer to think for the better But in order for this to happen Our definition of what constitutes leadership or who gets to be a leader needs to broaden Every person here is a leader Every citizen in the choices they make The things they choose to say or to not say To do or not do To teach their kids or not teach is a leader It's not just every vote that counts It's every choice that counts So I'll leave you with this Let us be good leaders Let us be the best leaders we can possibly be Together let's roll up our sleeves And let's get on with the tough entirely achievable Vitally necessary work of leaving this world a better place than we found it Our children and grandchildren deserve nothing less


And that person is Mike Bloomberg.  And I watched a little bit of MSNBC, something that nobody should ever do. And even they were saying that Mike Bloomberg was the loser. So you can't possibly spin this. You can't suggest that he came out on top. This was a bad, bad, brutal debate for Mike Bloomberg, because not only did he have to defend himself when it comes to stop and frisk, he had to defend himself when it comes to redlining, sexual harassment, why he hasn't released his tax returns, why he has all of this wealth and whether or not it's earned and deserved. And it was so bad that after the debate, his Wikipedia page was updated. And it claims that he was murdered by Elizabeth Warren, Bernie Sanders, and Joe Biden. And guys, he lost so bad, his campaign put out a statement.  And it reads, Mike was just warming up tonight. We fully expect Mike will continue to build on tonight's performance when he appears on the stage in South Carolina next Tuesday. Yeah, you better hope so because if he has more performances like that, it doesn't matter how much money you spend. You can spend 10 billion of your own wealth, but that kind of a performance shows voters.  Like what he did to Hillary Clinton on that debate stage in bringing on Bill Clinton's sexual assault accusers and calling out Hillary Clinton's record on trade, you know, basically trying to attack her from the left. Imagine what he can do with Mike Bloomberg. There's no way he'd be able to maintain any lead that he has currently over Donald Trump on a national debate stage.  So we're going to go through a couple of clips here and I'm going to show you how one by one. Elizabeth Warren, Bernie Sanders, Joe Biden, even Amy Klobuchar took turns dunking on Mayor Bloomberg.  I mean, he threw in a couple of jabs here and there, but it's clear that this, you know, opportunist is jockeying for position in Bloomberg's administration. Possibly your VP position and you know, whatever. But the people who took shots at him, they got in some really good blows and they landed. And the first one is Bernie Sanders. He explained why Bloomberg is poised to lose to Donald Trump if he were to win the nomination. In order to beat Donald Trump, we're going to need the largest voter turnout in the history of the United States. Mr. Bloomberg had policies in New York City of stop and frisk, which went after African American and Latino people in an outrageous way. That is not a way you're going to grow voter turnout. What our movement is about is bringing working class people together, black and white and Latino, Native American, Asian American, around an agenda that works for all of us and not just the billionaire class. And that agenda says that maybe just maybe we should join the rest of the industrialized world, guarantee health care to all people as a human right, raise that minimum wage to a living wage of 15 bucks an hour and have the guts to take on the fossil fuel industry because their short-term profits are not more important than the future of this planet and the need to combat climate change. Those are some of the reasons we have the strongest campaign to defeat Donald Trump. And that is such a great point. If you want to win, you have to increase voter turnout. If you don't recognize that you can't beat Donald Trump because Democrats for too long have just been fixated on winning over moderate Republicans and these suburban white voters. But listen, it's not just this fixed portion of the electorate that will vote in every single election. See, when turnout is high, Democrats win. When it's low, they lose. Hillary Clinton lost because she couldn't excite younger people. Individuals stood home and a lot of people did flip from Democrats to Republicans to support Donald Trump. But I mean, if you want to win the best way, the safest bet is to turn out the base. And how are you going to turn out the base? How are you going to energize black and brown people if you were the mayor who had this explicitly racist policy where you threw black people against the wall and frisked them? Like there's a video from the New York Times with an individual named Taekwondo and he explained how he was stopped four to five times per month during the stop and frisk years. Four to five times per month. You can't win with that kind of a record. People of color will not come out and vote for you.  And when it comes to the issue of racial profiling, they actually stayed on this for a while. I'm shocked that MSNBC actually talked about the audio that Benjamin Dixon released or at least popularized where he explained how, look, we have to over-police black neighborhoods because that's where all the crime is. I'm genuinely surprised that the media did their job in that respect. But Joe Biden jumped in and explained how racial profiling that we saw from Mike Bloomberg, it really is disgusting. It's evil. The mayor makes an interesting point. The mayor says that he has a great record, that he's done these wonderful things. Well, the fact of the matter is he has not managed his city very, very well when he was there. He didn't get a whole lot done. He had to stop and frisk throwing close to 5 million young black men up against the wall. And when we came along in our administration, President Obama, and said we're going to send in a moderator to a mediator to stop it, he said that's unnecessary. So we're going to get a chance to talk about the mayor's record. But in terms of who is best prepared to beat Donald Trump, look at your poll and what it says. Now, what Bloomberg tried to do was feign ignorance here. He tried to make it seem as if, you know, he didn't really know about what stop and frisk was doing, how he had the NYPD basically terrorizing communities of color. But that's a lie. That is a complete lie. He knew what was happening and he refused to end stop and frisk until I believe a judge ordered him to. Now, Elizabeth Warren actually got him there on that lie and claim. No, you knew exactly what this was. Targeting black and brown people wasn't some type of unintended consequence. That was exactly what you wanted to do as the mayor of New York City. So he really tried to wiggle out of the corner that he was backed into and none of the Democrats were having it. Nobody would let him out. And there was a moment where moving on a little bit where Mike Bloomberg was asked whether or not he deserved or earned the money that he has. He's worth over $50 billion. And Bernie Sanders had just the perfect response to what he said because he answered, yes, I did earn that. But look what Bernie Sanders said in response. That was just brilliant. And it communicates to people that Bernie Sanders knows about the value of just normal workers. We take for granted the people who work at Walmart. We take for granted just the people who are working these nine to five jobs and they haven't seen a raise. They're struggling to get by. They can barely pay their rent. And Bernie Sanders is demonstrating that he's in touch with what Americans need.   So I love how each candidate took turns dunking on him, but I've got to hand it to Elizabeth Warren. It was really her who landed the knockout punch because what we saw here was just it was masterful. And I think that if you are ever going to be in a debate, you have to watch this performance. And watch what Elizabeth Warren did and pay close attention because this is how you expose someone who was a fraud. This is what she did when it comes to the sexual harassment allegations that came up to Mike Bloomberg. Several former employees have claimed that your company was a hostile workplace for women. When you were confronted about it, you admitted making sexually suggestive remarks saying, quote, That's the way I grew up in a lawsuit in the 1990s. According to the Washington Post, one former female employee alleged that you said, quote, I would do you in a second. Should Democrats expect better from their nominee? Let me let me say a couple of things and if I can have my full minute in the quarter. Thank you. I have no tolerance for the kind of behavior that the Me Too movement movement has exposed. And anybody that does anything wrong in our company, we investigate it. And if it's appropriate, they're gone that day. But let me tell you what I do in my company and my foundation and in city government when I was there. In my foundation, the person that runs it's a woman, 70% of the people there are women. In my company, lots and lots of women have big responsibilities. They get paid exactly the same as men. And in my in city hall, the person that's the top person, my deputy mayor was a woman and 40% of our commissioners were women. I am very proud of the fact that about two weeks ago, we were awarded. We were voted the most that the best place to work second best place in America. If that doesn't say something about our employees and how happy they are, I don't know what does. Senator Warren, you've been critical of Mayor Bloomberg on this issue. Yes, I have. And I hope you've heard what his defense was. I've been nice to some women, doesn't cut it. The mayor has to stand on his record. And what we need to know is exactly what's lurking out there. He has gotten some number of women, dozens who knows, to sign nondisclosure agreements, both for sexual harassment and for gender discrimination in the workplace. So, Mr. Mayor, are you willing to release all of those women from those nondisclosure agreements so we can hear their side of the story? I have a very few nondisclosure agreements. How many is there? Let me finish. How many is there? None of them accused me of doing anything other than maybe they didn't like the joke I told. And let me just put, and let me put, there's agreements between two parties that wanted to keep it quiet, and that's up to them. They signed those agreements and we'll live with it. So wait, when you say it is up to, I just want to be clear. Some is how many? And when you say they signed them and they wanted them, if they wish now to speak out and tell their side of the story about what it is they allege, that's now okay with you. You're releasing them on television tonight? Senator? No. Is that right? Senator? Tonight? Senator, the company and somebody else, in this case, a man or a woman, or it could be more than that, they decided when they made an agreement that they wanted to keep it quiet for everybody's interest, they signed the agreements and that's what we're going to live with. I'm sorry. No, the question is, are the women bound by being muzzled by you? And you could release them from that immediately. Let's understand, this is not just a question of the mayor's character. This is also a question about electability. We are not going to be Donald Trump with a man who has, who knows how many, nondisclosure agreements and the drip, drip, drip of stories of women saying they have been harassed and discriminated against. That's not what we do as Democrats. Now, you can see that he was visibly uncomfortable because there was no way that he could respond to not look like a horrible human being right there. She had him backed into a corner and as I'm watching this, you know, I'm loving it. I like that she's dunking on Mike Bloomberg. But the question is, where was this Elizabeth Warren at the last three or four debates? Like, if we saw this, there's no way that she would be in the position that she's in currently in this overall race where she has a one in 100 chance of getting a majority of Pledge delegates and winning the nomination. That's according to 538. So I mean, if she brought this heat at previous debates and they didn't kind of just like fade into the background, she would be excelling right now. But I mean, getting back to Mike Bloomberg, that was just embarrassing. And I mentioned this in my main debate breakdown video, but I don't know who it was. If it was a journalist or whatnot on Twitter who basically said that they were at an official Bloomberg campaign debate watching party and there were like visible groans and they really didn't like what was happening because Elizabeth Warren, you know, was kind of destroying him there. How do you respond? There's no way to respond, right? There's just no way to respond to that. Everything she said there was just perfection. And I think that she probably prepared so much that she even anticipated responses and knew exactly what to say to hit him and thought through different scenarios of how he might answer this. And I mean, how can the question is after seeing all of this, how can you still support Mike Bloomberg? If you were backing him because of name recognition based off of those ads, the answer is I don't think you can. And look, even Amy Klobuchar dunked on Mike Bloomberg when the issue of why he hasn't released his tax returns came up. And I thought that she handled this phenomenally. It just takes us a long time. I'm fortunately or fortunately I make a lot of money and we do business all around the world and we are preparing it. The number of pages will probably be thousands of pages. I can't go to TurboTax, but I put out my tax return every year for 12 years in City Hall. We will put out this one. It tells everybody everything they need to know about every investments that I make and where the money goes. And the biggest item is all the money I give away. And we list that every single donation I make and you can get that from our foundation anytime you want. I'm just looking at my husband in the front row that has to do our taxes all the time. We probably could go to TurboTax. And the point of this is I believe in transparency. I had a physical, by the way, it came out well. We might all be surprised if my blood pressure is lower than Mayor Pete's. That might really shock everyone out there. And I think you should release your records from your physical. Secondly, when it comes to tax returns, everyone up here has released their tax returns, Mayor. I think, and it is a major issue because the President of the United States has been hiding behind his tax returns, even when courts order him to come forward with those tax returns. And I think I don't care how much money anyone has. I think it's great you got a lot of money. But I think you've got to come forward with your tax returns. So I don't usually say this, but good job Amy Klobuchar. Now, in case you missed it, he basically said that he's too rich to use TurboTax. And on top of that, he says that the biggest item in his taxes is all the money he gives away. So he's trying to cultivate goodwill with viewers, except save it. You're not using that money for causes because you have this altruistic belief that your money can make the world a better place. You're buying influence. You're buying endorsements. You're buying television advertisements. So save it. I don't care about your philanthropic endeavors. I couldn't care less.  And look, I don't necessarily care that much about tax returns. I think that his support for redlining, his lack of support for the minimum wage, which Bernie called out, his stop and frisk, his sexual harassment, that's all more persuasive. But I think that this is important in tying him to Donald Trump because he's trying to position himself as the person who is poised to beat Donald Trump. But what this portion of the debate proved was that how he's going to beat Donald Trump when he's very Trumpian himself. He's a billionaire. They both haven't released their tax returns. I thought it was great. It's a good strategic move. And yeah, so I don't know what to say. If I'm like Bloomberg, I'm never showing up to a debate again. I'm bowing out of this race. That was too embarrassing. Just say face, drop out, leave your legacy intact. Although I don't know that that's possible after you've been exposed over the course of the last week. But I mean, within the first couple of minutes, he was already dead and they kept beating his dead carcass on that debate stage and it was just so glorious to watch. Like this is really what we needed. We needed all of the candidates to take turns dunking on this oligarch because shame on anyone who thinks that they can buy their way into the White House, that they can buy our democracy. It's just, it's grotesque. It's morally reprehensible. Like if you truly want to live in a democracy, then you can't allow billionaires to do what Mike Bloomberg is doing. He's buying endorsements. He's buying democracies, buying television ads. It's just, it's disgusting. Who can compete with that? What normal working class American who wants to be president can compete with a billionaire oligarch like that? And if he's able to prove that this is a successful strategy, then who's going to run next? Is it going to be Mark Zuckerberg or Jeff Bezos or someone from the Walton family, Leon Cooperman? We can't allow this to happen. And so that's why the candidates needed to dismantle his campaign. And I think that they did as good as they possibly could have tonight. And let me say this, my expectations for Mike Bloomberg were very low, but he even underperformed my expectations. Like he did worse than I thought he possibly could have done. And even with my low expectations, regardless, I was still shocked at how bad this debate was for him. Horrible. Zero charisma, no policy substance. He's only on that debate stage because he thinks he's entitled to the White House because he has lots and lots of money. And this debate showed that you can't necessarily buy an election so easily. Or at least if you're going to try to, there's going to be some heavy pushback. So kudos to all the candidates who took on this oligarch.


Why narcissists turn against you? Why they become unfriendly towards you? Why they don't have any sympathy for you? The love-bombing phase doesn't last long and then the narcissist becomes very disappointed with you They become sad and displeased because in their minds you have failed to fulfill their hopes and expectations When they idealized you They saw you as being perfect They had to see you in this way in order to function They projected this idealized view of themselves onto you, but of course No one is perfect We all make faults and mistakes We all have flaws and imperfections So it was inevitable that the narcissist was going to be disappointed They expected to receive this perfect relationship partner Who would do and be everything they want This person who is an extension of themselves This person who would reflect back to them how great they are and it isn't only their relationship partners that they do this with They also see their children as an extension of themselves Where the child is either all good or all bad The child is either a convenience or a problem and this all depends on what the child is able to reflect back to the narcissist When the narcissist turns against you, they will criticize you They will indicate your faults in a disapproving way. They will show disinterest in anything you have to say They will compare you to other people They won't talk to you as much When the narcissist turns against you You might feel very confused You may experience hopelessness Because you've just gone from this fantasy world Where everything seems to be perfect To this world where you have now lost everything you thought you had The narcissist made you believe that you were more than good enough for them They made you believe that you were perfect Until they then turned against you Which then leaves you questioning yourself and everything that you experienced It makes you feel like you are missing something It makes you feel like you're not good enough and you may then want to return to them for validation Because you want to know what you did wrong You want to know what happened to this fantasy world where everything was perfect You want to re-establish what you once had Because although the narcissist lured you in with a false character For you it was a real experience It was an event or occurrence that left an impression on you It gave you an idea feeling an opinion about them in some situations The narcissist isn't even interested in the person they're with and they are only with them to gain something materialistic In these situations the target may experience intermittent reinforcement Well, the narcissist has a conditioning schedule in which the target does not receive a reward each time they perform a design behavior They are awarded for their behavior at seemingly random intervals, but either way a Narcissist cannot experience love or intimacy The narcissist will invalidate you and make you feel like you're not good enough Which then makes you work harder It makes you want to prove yourself to them so that you can re-establish the idealization phase But the narcissist will continue to display their opposition and dislike for you They will experience temper tantrums Because you're not the idealized partner that they expect you to be They become this cruel and oppressive dictator Well, they infect harsh and authoritarian treatment on you Because you didn't meet their standards or expectations You didn't reflect back to them what they wanted to see in themselves But even though you're not this idealized partner that they wanted you to be They will still remain in the relationship. They will still choose to be around you So that they can take revenge on you So that they can harm you in return for the injury or wrong that they believe they have suffered at your hands They will be very angry and aggressive towards you For failing to be the perfect partner that they imagined you to be They will remain in the relationship to continue extracting supply from you To continue extracting your attention and admiration You continue to pursue them with fear and anxiety In an attempt to re-establish the idealization phase So narcissists will remain in the relationship Just to take advantage of your body or your money or anything else you have to offer While going back and forth between seemingly trying to pull you back in and then pushing you away again Which leaves you very confused It leaves you unable to think clearly Although the idealization phase didn't last long It made you feel attached to them You continue to remember this stage Even when they turn against you It makes you want things to go back to how it used to be It makes you put in more of your time and effort But the narcissist uses intermittent reinforcement They don't always validate you So even when you go out of your way to do something nice for them You still doubt yourself You still wonder if what you did was good enough Because you just went from being this person who was supposed to be perfect To someone who is now completely worthless Now the narcissist is doing everything they can to humiliate you They are trying to make you feel ashamed and foolish By injuring your dignity and pride And this is when they will discard you and move on to someone else Someone who they will triangulate with you Someone who they may display ostentatiously In order to provoke envy or admiration to show defiance To show bold disobedience, resistance and opposition While even a normal person may display opposition during a breakup and say some hurtful things With the narcissist it affects everyone and everything It makes its way into every aspect of your life And it's something that you have experienced throughout the entire relationship You have experienced their anger and their desire to hurt you They have a deep need to humiliate and destroy you And strip you of your dignity and pride So even when they discard you That doesn't mean they're just going to let you move on to your life They will start a smear campaign against you They will stalk and harass you They will threaten and intimidate you Because they're not just trying to hurt you They're trying to destroy you Thank you for watching I hope this video resonated with you Please like, comment, share and subscribe If you would like to donate My PayPal link is in the video description Coaching inquiries You can email me at coachingatnaqsurvivor.co.uk Thank you for watching and I'll talk to you soon


I want to say, first of all, thank you to Elizabeth Saikler and to the Brooklyn Museum for this opportunity. I'm happy to be in New York. I could only dream of showing my work in a context I am honored to be part of. As an exchange student for one semester at the Cooper Union in 1994, I was introduced to feminism, mainly in bad girls and very bad girls show, in the new museum that year. For me, feminism is a constant invigorating, sometimes subversive starting point, a well-lit ground, a starting point that was marked by the work of women who changed the world of art in the last 30 years. 30. I am going to talk today about the significance of place in how I conceptualize my work and in the way I think within my installation projects. I will try and describe to you the way I create a place where an encounter of the viewer and my experience is made possible. So the first work you've already can see. Do you hear me? This is called Resident Alien. It was shown in a 1997 document in Castle. And what you see here is a cargo container, standard six meters, where I change the floor, which is normally from either sheet metal or wood. I took a sheet of metal and hammered it with oxy-citalin with a lot of heat and deformed the floor into an imprint of another place. So this work is extraterritorial, is a non-place because it can move from place easily from one location to the next. And it is not dependent on a site inside a gallery or inside a museum. Wherever I exhibited it, it stayed outside. This is another angle where you can see it's quite laborious work with heat. In the smaller box there, there's a small container. There's sort of a lit space and a radio playing. And if one wanted to, I just want to show you when you are in the box, your head is coming out of the hole of a, we call it a Turkish, an eastern toilet, something that you really see more in the east, more in the army. This is just another work that has nothing to do with it. So there's really a head container inside a product container. And in order to deform the metal, I needed to heat a hammer and use another hammer, a cold hammer, to actually hit this red metal. And so part of the process came into the work because I just exhibited also my work tools in the other side of this hill. Loud enough, yeah, OK. This is the evening before I shot the video on the beach of Tel Aviv. And this work called Barbed Hula is shown here in Global Feminism. This sort of dress rehearsal in which I was dressed as well, not like on the beach the next morning. I performed it. I practiced on a roof in South Tel Aviv. I still live in the same neighborhood, by the way. And it's about a certain, also if the container is a non-place, this is a very small place. It's 90 centimeters diameter of sort of a border that with a centrifugal force, I am always in contact with this barbed wire.  So I'm not being wounded or shredded or whatever Robert Smith wrote in The New York Times this day. It's actually more dangerous to come near me and something that can't be sort of access this body. I think I was without clothes at 5 o'clock in the morning, the next morning, where I shot the video. And I think it's normal to take off your clothes. Otherwise, I started the issue of why do I wear this or why do I wrap myself in these bubble wraps? But you can decide. I'm not showing the video right here. This is another territory. Three meters diameter, I made a large hula hoop. And posing to the sort of being one woman inside the barbed hula, this is a group attempt at mastering this hula dance with a bigger territory. It's like a task of a group, of a collaboration, a cooperation, cooperation as well.  I inverted one of the sides of this scale and turned it into a small island of a small deformed mountain. The same technique of the container. And it's the same sort of, well, actually, this is a sort of absurd situation where the work, the inversion, the deformation, the heat, it changed nothing in the reality of the physics of this tool that, of course, stands for justice or tries to make justice shown, justice in place. Well, there's another music box around us now. This is a study for another project that followed the container. And it was a different sort of container, a concrete mixer. I was turning into a concrete mixer, turned into a music box, turned into an ice cream van. And this is one of the end results. I did this show in many, many locations in Europe, also in New York. I borrowed the logo of the European Union. I added forks underneath this truck. And it was a work I thought of, I mean, a proper place. It came when I was living in England and trying to sort of decode the system of how to reach audience without being part of the class system, the system of the galleries, the system of the museums, the heaviness of an art world. I proposed to make a project that, first, the public hears music. Then you see this sound object, this vehicle. And then I wanted to serve the audience with a story, a simple story that you don't, it's the fairy tale actually. So these are just to show you, this is a mold of an icicle, a popsicle. I don't know how you say it in American ice lollies. And it was an ice lolly in the form of a frozen girl. And this story was on the wrapper, which was sort of a body bag for this archaeological finding. In September 1998, the remains of a frozen vagrant were found at a building site on Orlandian Burgersstrasse in the city of Vermlin. Archaeological analysis of the small corpse provided scientific proof that the little matchstick girl from Hans Christian Andersen's tale truly did exist. The child who was nicknamed Orla, this means foreskin in Hebrew, aged about five must have been trying to keep herself warm by lighting the matches that she was supposed to sell. As the city celebrated Christmas Eve, she froze to death and was preserved under an urban avalanche originating. So it was referring to the time I lived in Berlin, and there's a moment in 1998 where they found a very ancient Homo sapiens frozen between Italy and Austria, and there was many details about his life. Anyway, ice preserved this girl who actually, I remembered from my childhood, this fairy tale where, for a change it was a girl who was a protagonist, but she didn't make use of what she had, and it was matches, she could have warmed herself instead of warming herself with the matches. She was supposed to sell them before coming. She had no mother. Her father said sell them or don't come back home, so she lit them and she imagined. She started fantasizing about house, about food, about things that are most important, and then she saw her grandmother in heaven and she froze and joined her grandmother and she was very beautiful found in the morning. So I did a performance just of giving this story, giving this ice lolly and I was sort of being the opposite of her. She was supposed to sell matches. My task was to distribute for free ice lollies, meaning she or her end was to freeze. My end would be to, oh, three minutes, would be to probably burn my destiny. I'm gonna go really fast, three minutes, that's the long. This is a project in New York City, Threadbacking Space, the last show exhibited there, curator Leah Ganjitano, and I did a big crater full of sugar, this is the idea behind it, that thatching sugar from clouds into thin walls and making a new topic sort of society that can translate this love or this empty energy into a real place. This is the Sahara Desert, this is me working, this is my lover who had, through his sweats, made this substance, transformed it, it's a very nervous, we call it, it's a material that transforms wonderfully this sugar, from light pink and airy, it dissolves into concentrated red, bloody, and this is a whole project which we're not gonna talk about that I made from newspapers, and I'm just ending this lecture. I meant you to talk to me as we go along, but maybe we have one minute left even for questions. Two pieces I made when I was in Cooper Union, both of them I think the most verbally I had to present them as feminists, because they were, this is influenced by Carol Gilligan's writings about entering of the wall in the traumatic way, there was a chapter about entering patriarchy and entering the wall, entering traumatically, I took a, I had to give in a work, I finished the semester one piece, I had money for one little package of Fimo, it's called, and I made this swimmer and entered the wall with her, and then I did, they said it was a performance, I showed Hans Hake, how I'm milking a bull, I bred, you don't see it in the photo, many, many catalogs of the names and the qualities of different kind of sperm, but the milking is just made out of, it's a milking machine for female cows, not for bulls. Okay, just to show you what salt can do, it's in the lowest place of the world where I started working the salt, and this is last year, so that's it for now. If you want to talk a little something, I know there's no questions usually. All is clear, like the same German. Sorry, that's so short. Thank you.