The administration block. The administration block is a fixed block you'll see in many places in Moodle. It might be on the right as here, or on the left according to your theme. What you see in the administration block depends on your privileges on the site and also within a course. As a regular course teacher within a course, you'll see a course administration link expanding to give you options to help you manage your course. For example, editing the settings, enrolments and grades. We look at these in separate videos. You also have a link to switch your role to a different role, primarily a student or learner as we've called it. Clicking here would then re-display a course page or activity from the point of view of that role. This is useful as a teacher if you want to check how things work for your students. A student in a course would have a different view of the administration block as we can see if we go to the teaching with Moodle course where our user Sam is a student. There she sees a link to her grades and the option to unenroll herself from the course.


Why narcissists leave and never look back? Sometimes narcissists leave and never look back because they believe that they can continue to be successful without you, they believe that they can progress without interruption or impediment without something to hold them back from doing what they want to do or being who they want to be and they may lead you to believe that you weren't good enough for them or as though they found something better but you need to look at the behaviors that you witnessed before they left because that's typically what they're going to be doing after they leave, they never look back because they felt uncomfortable around you, you may have questioned and confronted them, you may have had all of these standards and expectations, things that would deal breakers for you and they don't want to deal with that, they want someone who will accept them as they are, someone who won't demand to expect for them to change will be better where they can drink alcohol every night and smoke weed and they can treat the other person like a fool, a doormat, an emotional dumping ground, they can go back and forth with them and relish in their chaos and drama because that's what they really want, they thrive in dysfunctional environments with people who they feel more comfortable around, people who know exactly who they are but don't mind because they knew they could never have that with you, you weren't willing to accept them and maybe you didn't openly reveal that to them but they constantly reading their victims body language facial expressions and tone of voice to see where they stand with them, to get a gauge on how they should act around you, to test the water before they decide to take further action and your boundaries were just too strong, they couldn't have their way with you, they couldn't get supply or it was just too much work, while narcissists don't like to work hard for anything, they'd rather have it easy, they'd rather run off and find an unsuspecting victim who doesn't know what they're about, rather than trying to rekindle things with you again, so in the end they follow the path of least resistance, they move away from pain and towards pleasure, whatever brings them amusement and enjoyment because that's all they're really looking for, someone who isn't going to judge them, someone who isn't going to resist them, someone who is just going to let them be who they choose to be, that is what they are seeking, someone who will make them feel how they want to feel, someone who will make them feel powerful and important, desirable and attractive, quick-witted and intelligent even though they may have never done the work and they may never have tried to develop themselves or achieve anything, they have this sense of arrogance and entitlement and they see it as though if they're not going to get it from you, they're going to get it from someone else but it is always the victim who initiates the discard, you saw something wrong with them and now they want to punish you, they want to teach you a lesson by leaving you and never looking back and finding a new source of supply so that they can show you where you went wrong or how you should have treated them because that's all it's really about, they're just trying to prove a point, they're trying to show you that you were wrong and they were right which is why they're just going to continue on their path for as long as it is benefiting them but as soon as things start to go wrong or they feel like they had a better situation with you then they may contemplate hoovering you unless they can find a more efficient option because if you made it clear to them that you're not going to accept that type of treatment they're going to know that they can't have their way with you anymore and just by you setting the boundary that can be enough to cause a narcissistic injury because they don't like to hear the word no they're very insecure so to compensate for that they're arrogant and entitled they believe they're better than you and they should be able to treat you however they choose to and as long as you're willing to support their delusion they will stick around or they will entertain coming back to you but that's all it's ever going to be it's never going to be anything real you're going to be doing all of the work to sustain the illusion while they're just sitting back feeling like the king or the queen but if you were constantly pressing them and trying to make them be better they're not going to want to go back to that it's too much work for them to manipulate you all over again it's much easier for them to find an unsuspecting target or someone who is more agreeable and on the same page someone who doesn't mind them going out on the weekends where they're cheating and sleeping around someone who can tolerate that excessive drinking smoking or doing drugs someone who accepts their delusions instead of trying to make them change because that's what they really want they don't want to build anything for real they already know they're not about life they just wanted to trick you so that they can use you for supply and when you started to catch on they knew that it was time for them to take off because they're never going to try to be better for you they're never going to be who you wanted them to be who they led you to believe that they were in the beginning they're just going to keep doing what they've always done what worked for them in the past what got them a result that they were looking for and while they may recognize that they were in a better situation with you a lot of them really don't care because they know they're not going to be able to sustain something like that they know they're just going to be the cause to its demise and then they will have to start again so they go where they feel more comfortable where they know that people will tolerate and accept them and they know they're not going to be given a hard time thank you for watching if you found this video helpful please give it a thumbs up share your thoughts in the comment section hit the subscribe button to receive the notifications if you would like to support the channel you can donate up here with the Amisrothnarch survivor you can book a one-on-one with me on my website it's NARXA5 at the Cuddle UK thank you for watching and I'll talk to you soon


Then we have startups who want to enable commerce via doing chats, right? And then the idea is that they want to automate all the things that you do in different apps in one app and do it using chats. Then we have a personal assistants who want to solve one problem end-to-end, problem like automating the way you schedule your appointments, right? And then we have developer platforms where people are building really cool high-tech stuff which they want to sell to different businesses to solve problems like automating customer care systems. So we sometimes wonder whether the chatbots that we see, whether these are really AI-powered or human-powered or human-assisted. So why is there so much interest in chatbots now? So if we wind the clock 10 years back, we had Google search bar, which was all the rage among web users, where you can just type a simple text-space search query and then you can get a bunch of results and then you're happy, right? And SMS was pretty much the mode with which we used to do messaging. Now 10 years from then, we have tens of messaging applications on our phones. Billions of users use these applications every day. And VChat, for example, has done a great job in terms of connecting consumers to businesses to do commerce, right? And if you ever use Amazon customer care, you might have been surprised by the fact that your query can be resolved in no time if you just do chats, right? So it is this notion of interactive search that is beginning to take over the notion of just typing a simple search query and seeking response. So in what all cases should we replace search bar by interactive search? So we pretty much see this search bar everywhere. If you go to a mobile app, you still have a search bar to do searching. If you go to web apps, you also have search bar. So on one side, I have shown a few applications which involve a few simple steps like booking a cab or paying your bills. And on the other side, I have applications like booking a holiday or you want to shop a fashion item, which are more complex, which require multiple steps, right? So let's say you want to book a cab, right? On the right-hand side, we have a popular taxi booking application which shows nice visuals. You have real-time information being shown there. You can pretty much do everything by swipe or by touch. And on the left-hand side, I have a chatbot from App Store. So let's say I ask chatbot to book a cab. And it tells me that your location is this. And what are you looking for? Are you looking for a hatchback or sedan? So if I select sedan, then it tells me, sorry, sedans are not available. What is your preference? Then I give some preference, but it seems it has completely ignored it. It is still stuck asking me, what do you want to book? Whereas I'm sure all of you have used taxi booking applications, so you know the kind of experience that you get when you have applications where you can do things by swipe, touch, and done, right? So that is what happens with these apps today. But we have chatbots where we have to type things. These don't really understand what you say. And these sort of hide information for you and give you a delayed response. But developers have also built chatbots on Facebook Messenger applications, right? So I managed to try one such chatbot which can do fashion shopping. So I asked, what can you show me? And it said I could not understand you, but here are a few tennis shoes. Then I said, I do not want shoes. And it said, sorry, I could not understand you, but here are some more shoes. And somehow I managed to type tops because I want to buy tops for my wife. And when I typed that, give me something. And I said, give me something between 1500 and 2000. It again, I didn't understand what I wanted to say. But you folks can understand that I was trying to budget my shopping, right? So again, we have chatbots which lack intelligence, which lack a personization, and which can't understand the context. So in my opinion, all these are attempts to morph the existing apps into chatbots. And people are somehow making simpler intuitive interfaces more complex and less efficient. So what kind of use cases for which we should really build chatbots? And what does it take to build such chatbots? So we at U, we are building a fashion commerce application. We are building a fashion shopping assistant. And we actually sat down with more than 50 shoppers to understand the way they shop, and the kind of experiences that they get when they have to go to a famous fashion commerce platform. So fashion is one domain where there is no single spec as compared to consumer electronics, right? There are lots of styles, styles keep on changing. And hence, people open multiple tabs when they have to search for something. And in search bar, many times people type, I want to shop something for Officeware. And that search bar doesn't really understand what to show for Officeware, right? And many times you see results. So even if you type Officeware, you see some results, but you see really surprising results. And I'll show you a few going down. So the interfaces that we have there, those don't really take any kind of feedback from users. So if you just want to say that, hey, I like this, I don't like this, there is no such mechanism to take feedback. And the dilemma of shopping still remains because there is these online search interfaces that don't really help you in making decisions. So I feel that to go from this kind of experience to actually have experience of a chatbot, we need four building blocks. A, we should be able to extract intent from the text. B, we should be able to provide results that are relevant for your intent. C, have some kind of contextual interaction. And D, make the experience personalized and help people to finish a task, right? So in this case, if I type, I want to shop evening party shirt in blue, so those spelling mistakes are deliberate because that is how you type, right? It should understand that I'm not just searching for any kind of shirt, but I want to go for a party. And then the kind of results that I see, those don't have checked shirt or lining because the bot understands that these are reserved for office wear. And then it somehow figures out that maybe I should ask the user what kind of color you're looking for because you're going to go for a party. And then it basically asks you if I can personalize the budget, makes sense? So I actually wanted to go step back and then tell you why block number two is important. So if I type a few search queries, so here I have type evening party blue dress. I'm one of the famous porters in India. And I don't see any dress here. And it has somehow picked up that evening and blue from some product and it has, so these are the top three results, right? That you get. And this is not a problem just with one commerce portal. So if I type something like office wear blue shirt for men, I get all sorts of results. So here the products are not well tagged because I'm getting both men as well as women items. The products are not normalized because, for example, a color, right? I'm searching for blue, but there's only one item there. And again, the products don't have tags like office. So as I mentioned, we can build chatbots for such experiences with four building blocks. And these building blocks can also apply to build chatbots for some other domain. So here for example, if you want to build a chatbot to book a holiday, the bot would understand a number of days for which you want to go. And the place where you want to go for a holiday. And if you want to go to Kerala, then it basically tries to ask you which particular location you want to go to. And based on that, I think you got the idea, right? So for the rest of my talk, I'm going to focus on how we can apply deep learning to build these two building blocks, extract intent, and provide results which are relevant to your intent. So here, for example, if I type shop evening party shirt, the intent extraction means that I've identified that there is apparel present, there is occasion, there is time, and there is color. And based on that, I have done search over a catalog, which is very well tagged. And I'm providing results that are relevant to occasion and time. So I'm going to go into some more details now. So I can break down these two blocks into three technical problems. A, we first should be able to understand the text. And I'm going to take instance of semantic spell correction, because that's the most common problem that we have seen when we have to build a bot ourselves. Secondly, I'm going to talk about extracting entities from the text. And this problem also applies to catalogs, because if you see e-commerce catalogs, you have picture and you have description. And that many times, the search engines don't really pick up all the keywords that you have in the description. So you also want to extract different entities from that description so that you have well tagged catalog. And then I'm going to also make use of images that you see in the products to extract the categories and attributes. So the first technical problem is from noisy unstructured text, how should we generate a structured intent? And I feel to solve this problem, any text processing block should have three properties. A, it should be able to understand context. B, it should be able to understand a semantic similarity. And C, it should be able to understand sequencing. So here, for example, I have this example of a shirt dress. So here, SHIT is not spelled well. And if I have to correct for it, I have two choices, SHOIT or SHIRT. So if I take simple edit distance, I don't know which one to correct for. But because I know that there is office as well present, I know that I can perhaps correct it to SHIRT, because office shirt dress makes more sense. Similarly, in a second example, a user has type. I want to shop for a sober shirt. And if I have a formal as an attribute in my catalog, then I should be able to figure out that I should better map sober as a formal and then give the user results which match a formal shirt. And a third example, which is more complex, where a user is saying that I want to shop for official dress that goes well with white jean, preferably in red color. Now, with whom should we associate red jean or dress? So if you just take word-based distance, you might associate that with jean. But if you actually think about encoding context within sequencing, you know that this red belongs to dress and not to jean. So we have seen several speakers from the morning who have talked about deep learning being applied to images and to text. So CNNs, for instance, have been shown to be very effective when you have to model context, because they understand morphological information that is present in the words. And they can also manage context well. So here, for example, if I give a lot of data to CNNs, they would be able to understand that office and shirt appear together a lot of times. And hence, you'd be able to solve the earlier problem of correcting SHRT to SSIRT. Word embeddings, again, have been shown to be effective to model a semantic similarity. However, these have some limitations. So in case of word embedding, most of you might know that you have to have all the data that you hope to get at test time to be given to a word embedding block so that you have a feature for it. So this is a word to wake works. And a word to wake, in some cases, has not been shown to be that effective when you have to model different dialects of languages. So recently, there have been some research work which talks about how we can replace word embedding by a character embedding. So here, you have a fixed dimensional vector for each character, and when you get a word at runtime, you form a feature vector. So that way, you can handle new words. You can also handle different dialects. And to model a sequencing, LSTMs and biodeaction LSTMs have been shown to be effective. And I'll talk about them some more. So we can combine these things and build a generic text processing network. So here, in this example, I have a paragraph at the bottom which says, show something for adventure trip. So now I'm going to parse words of this sentence one by one. So here, I have this word, adventure, for which I have constructed a D dimensional into a length of the word dimensional matrix. So this is something similar to what you get when you have to parse images. So this is now a two-dimensional matrix. Now, on this matrix, I'm going to apply W number of filters. And I'm going to form a deeper feature vectors. And then I'm going to apply the usual max pooling to form a feature vector. So now I have a feature vector for the word adventure. Then I'm going to give this feature vector to something called as highway network. I can talk about the offline, but highway networks have been shown to be more effective when you have to carry forward some of the context that you have in feature vectors to output vectors. So they essentially model morphology and context better when they are trained with CNNs. So now after highway network, I have a modified feature vector, which I'm going to give to LSTM. And LSTM is going to take these feature vectors one by one, and it's going to predict a new word. So it's going to predict to which word I should correct this spelling. And the output of LSTM is going to be the size of output is going to be the length of vocabulary that you have. So you want to predict a confidence score for each of the words that you have in your vocabulary. So now to this network, I can now give a bunch of pairs where I have misplay sentences, and I have misplay sentences which are correct. And that is how I can train this network. So we used TensorFlow to build this network and to train this network. We use AWS GPU instances. And to get raw data, we actually scraped more than 50K fashion blocks and social media streams, because you want a mix of data where you have correct spellings and incorrect spellings. And we also induced some transformations, some generic transformations. There have been studies which talk about how people type on phones. So using that, you can induce misspellings. And so we also took data from lots of product portals. And we had about 30,000 pairs of misspell and correctly spelled sentences. And some of these, we actually went and corrected manually just to ensure that the automation of data processing is working fine. So for the earlier network that I showed, we had a character embedding of length 20. We applied 1,200 filters for the CNN. We had two layers of hybrid network. We had three layers of LSTM. And the feature vector length of hidden units for LSTM was about 4,000. We had a total of 62 unique characters and 6.5,000 unique words in our data set. And the total tokens that were generated, this is all the words that we had in our training set, those were more than 5 million. And we used two metrics to evaluate the previous network. First, by complexity, which is e raised to negative likelihood by a number of tokens, it's essentially normalizing the loss that you have over tokens. This is a number which can go between 0 to let's say 200. And lower the number, better is your network. And we also used F1 score. We experimented with, nonetheless, a word CNN plus LSTM, and we removed the hybrid network just to see what kind of performance you get. And so as you can see, for the character-based embedding plus hybrid network plus LSTM, we are getting the best performance. So the complexity is, in fact, more than 35% lower, whereas the F1 score has improved by 10%.  So we kept D, which is the length of character vector, to 10. And the length of hidden unit that you have in LSTM 200. And the performance was not good. So after doing a lot of experimentation, we felt that D equal to 20 and M equal to 400 works well. So we also used learning from these networks to evaluate if user types, something that we don't know, whether we are able to extract semantically closer words or not. So we gave invocatory word, which is complement as input. And then we asked, using a cosine similarity, give me the top five closest words. So for the words CNN plus LSTM, we received complementary and matching. So network has learned some semantics. So this is what we received. And for the character-based embedding CNN plus hybrid network plus LSTM package, we received suitable matches and T. So this shows the power of modeling text by starting from characters. And we also gave a word which was not in our vocabulary. So sky blue polka. This is a pattern that you have in fashion sector. So because word to vague cannot have vector for the words that it hasn't seen, we can't get any word that is semantically closer to this word. But our network gave lots of interesting words, which are actually semantically very close. So I'm not going to talk about the second technical problem, where given you understand the intent, you want to have a very well-tagged catalog. And the problem here is that you have lots of product, image, and text data from different portals. And you want to normalize it. So you want to have a single schema so that you can do a good search over it. So this actually means that we have to extract attributes from the images and attributes from the text. So if you look at the image, a crop shape is something that is not present in the text, but it is there in the image. Similarly, a pleated. So this is a type of skirt. So the word pleated is not there in the text, but it is there in the image. Similarly, in case of text, we have brand. That's there. So if somebody searches for a particular brand, now we should be able to give out results. So the technical problem here is that, how do you extract categories and attributes from the images? And how do you extract entities, their types, and the relationships from the text? So I'm now going to extend the network that I explained earlier to solve this problem of extracting entities and their types from the text. So we have a similar architecture of having CNN and IA network, but now I have a bioreaction LSTM, where the LSTM now not just looks at the history, but it also looks at the future. And now I take outputs, the output feature vectors from these two LSTMs, and I have a CRF layer. So the output that I get is a type of entity. So I have here a sentence, red, zara, shirt, dress. And what I'm getting is color, brand, shape, and apparel. And again, you can form pairs of text where you have a paragraph on one side and you have the entities on the other side. And then you can train this network. So after training this network, we applied it on some complex text descriptions. And if you see, so this is a real description that you have on the product portals. So if you look at this sentence, this midi with sleeves as full. So here it has identified that a midi actually corresponds to length. And full is not a full neck, but it's a full sleeve. So if you have to write a text parser to parse these kinds of sentences, of course you learn out of rules. Let me also touch upon the way we extract different categories and attributes from the images. Some of you might be familiar with segmentation-based fully convolutional networks. So these were proposed last year. And these have also been used in self-driving cars. So what we do here is we take image from product portals and we segment each of the labels. So essentially assigning label for each a pixel of the image. And that's now your input. So that's the input to be a fully convolutional network. And in the end, your goal is to reproduce these labels. So in the process, network is going to learn some low-level and high-level features. So this is an example that I'm giving out of our network if you give this image as input. That is the output that you get at test time. So using this output, you have a subtracted background from foreground. And now you can also identify different attributes and categories from the image. So to summarize, I talked about four building blocks that I feel anybody has to build if you have to have a great chatbot-based experience. Actually, I like to refer to it as interactive search instead of calling it a chatbot. And I feel that if we focus on solving some complex search aspects and focus on building interactive search for a specific use case, I will be able to build a great consumer experience tools. And equally important is the role of deep learning where you have to parse, text, speech, or images at the input layer. And parse, text, images of the information that you have to collect at the back end to provide results to the kind of search queries that you would get at runtime. So the speakers from the beginning talked about the experience with which real researchers have figured out lots of these complex issues. So this is just a token of appreciation to people who work hard to do research. And we, startups, we make use of that research to build something useful. And I'm also thankful to IBM and AWS who have been very helpful to startups in terms of providing their compute so that we can experiment and survive and then build some experience for consumers. Of course, NVD. So that's it from my side. If you have any questions, I can


Community health workers, CHWs, are essential members of the healthcare team providing vital services to communities during times of crisis. During the COVID-19 pandemic, CHWs played a crucial role in surveillance, education, and support for those with the virus. Despite this, they often lacked adequate resources, support, and motivation which put them at risk of infection and stress. This article was authored by Solomon Salve, Joanna Raven, Priya Das, and others.


highlights a multi-scale structural carbon-fiber-based composite was synthesized through the assembly of one-dimensional materials. The construction of multiple conductive networks makes the composite have a strong EMI shielding performance of 73.9 dB. The reasonable design endows the composite with excellent positive and passive thermal management properties. This article was authored by Ming Zhou, Xu Wantan, Jingguan Wang, and others.


In Genesis 45, we see Joseph finally reveal himself to his brothers. And there's people in this room who you've had situations arise, maybe in the past year, maybe it's been even longer than that where your dreams haven't come to pass. There's been people who have hurt you along the way, people who haven't been there, who said they would, people who should have helped but didn't, people who talked bad about you, just like what happened to Joseph. And now he's finally at a point where he has to determine in his heart, Joseph has to say, all these things happened to me.  But how am I going to interpret what happened to me? And you see something so beautiful in the life of Joseph. It says Joseph in verse 40, chapter 45, he cannot control himself. So he stood by him and he cried out, make everyone go out for me so no one stayed with him. And Joseph made himself known to his brothers and he wept so much emotion so that the Egyptians heard it. The house of Pharaoh heard just Joseph releasing 13 years of pain and hurt. And Joseph said to his brothers, I'm Joseph. Is my father still alive? They didn't recognize him. And they were dismayed at his presence. They couldn't even answer him. Joseph said, no, no, come here, look at me. And they came near and he said, I'm your brother Joseph whom you sold into Egypt. Look at verse five. And now this is his declaration over what happened in his life.  It's a contradiction. He says to his brothers, you sold me. And then the very next verse he says, but God sent me.  You were pushed in to a pit. People abandoned you. They weren't there for you. They hurt you. And Joseph isn't denying that. He says to them, look, I can't take it back. It hurt me. You shouldn't have done that. You said you'd be there. You were my brothers. You pushed me and you sold me. But at the same time God sent me and they're not two different events. It's Joseph's perception. It's Joseph's interpretation of what happened. Instead of wallowing and what they did. Instead of wallowing and pain and unforgiveness and bitterness. He decided to see it through the lens of no, you didn't just sell me. God also sent me. There was a purpose behind my pain. There was a reason that this happened. And that's what I choose to focus on. One of the greatest gifts God will give you is the ability to see your situation through the lens of the goodness of God. Instead of seeing God's goodness through the lens of your situation. That's the temptation. God's not there. God forgot about me. They pushed me. They sold me. No, no, no. God sent me. And this might not have been the way that I planned but I'm not gonna step into 2020 and literally the rest of my future and my life holding on to the past, holding on to pains, reminding myself they sold me, they sold me.


All right, the first question is from Lucy Zl3 from listening to mine pump I've learned that compound lifts are essential for building strength and muscle Would you consider the hip thrust to be in the same category or is it more of an accessory exercise for those seeking to develop their glutes? That's a great. It is a great question. That is a really good question. And it's crazy.  Well, I didn't know I didn't know you were going to go this direction Yeah, the hip thrust, but we didn't talk about the intro the master of the hip thrust our our buddy over there Brett Contreras is getting some heat right now. Yeah, boy.  I mean and same thing with like luis I don't know she's going after him Well, you know, I listened to her talk. She's not throwing him under the bus.  I mean she did put a newsletter out like she's so she and she's got Like 300,000 followers. So she's got a massive following herself. So basically he was cheat on her Yeah, yeah, she don't know where there's a system for like a year or a year and a half for some shit Is what what she said, of course, and I'm only repeating what I've heard from her Yeah, we don't know that which I mean she's the victim I would think that she's probably the most credible source to like share the information. So it's not like I'm I'm sharing but we don't know for sure a hundred percent just based off what she says Yeah, yeah, yeah based off of what she said. Yeah, and then would you say about luis at luis same thing, dude? Yeah, yeah with uh, what's her face gen doc doc fit or whatever I forget her I forget what her her handle is or whatever same thing I you know, I was just talking to jordan at lunch, too Like man, I was really surprised That that didn't destroy his image I thought that somebody who's like that, you know, the oh it's super positive or everything like that and then I'm a good guy. Yeah. Yeah, kind of presents himself in that light would get really crushed by that and just didn't But I wasn't the one thing that I think both of them are doing and I've I've seen brett's page, too And I know there's already all this crazy hate just not acknowledge it. Yeah, just totally ignore it And the storm kind of roll by you know, this is so I actually respect lane norton a lot Exactly for this he oh, he addressed it. He yeah, he got divorced because He had an affair and he addressed it head on publicly which takes a lot of balls, you know And so I appreciate that. Oh, it's one of the things that we we've connected I mean we consider lane a friend and you know, he's a very polarizing personality But the end of the day I think that he means well We all felt that way and we felt he's authentic when we're talking about people that are authentic and really I like him or not.   That's who he is.   But okay For sure, so I know that I just took a left on that but that just reminded me that people are flawed dude People are flawed. We all make mistakes So it's just you know, and I think sometimes when you put someone in a pedestal or they put themselves on a pedestal Maybe it's a long fall, you know when when when shit well That's where I think it's crazy is that the ones that that put themselves on the pedestal And I think probably it's more surprising to me about lewis than it is Brett because I don't feel like Brett really talked about that stuff like he was really he kept all his personal life Pretty quiet. He stayed on to the the glute building. Yeah. Yeah All right, so let's get back to the to the hip thrust now I you know, I've recently been doing more and more hip thrust and I see a lot of value in them Yeah, your glutes look great. They look amazing. You should feel them, but I I'll have to give you a good game slap. No, I'm just kidding. Don't do that. I But you know to place them in the same category Because there's a lot of compound lifts Any lift that that uses more than one joint would be considered compound That doesn't mean that all compound lifts though are in what I would consider the the best, you know The top category of lifts which include barbell squat Deadlift overhead press. Those are the three kind of top lifts that I would say then you can throw in like a barbell row And a bench press. So there's your your top top five Would I consider a hip thrust? No in that and no, I the answer. Yeah, I wouldn't I wouldn't do that Like I can think so barbell squat. I would say one of the best exercises you could do for your lower body I think any split stance free would exercise like a lunge or bulgarian split stand squat still superior To a a a glute, you know a hip thrust in terms of just Functional performance and overall development any squat variation. I would also put above it front squats Back squats goblet squats Step-ups on a step Weighted step-ups. I might even rank higher.  Yeah, no too far exactly or it's the one of the best compound movements We can do no no no, it's not, you know, it's not the most functional It is not is it an awesome exercise. Fuck. Yes. Is it incredible for building the glutes? Yes Like it's definitely I definitely believe it belongs in a lot of people's repertoire for sure I don't think it's like just some good french there Did I mess it up?  I had that pure combo. Oh, yeah, look at it. Organify coming through there Wait 20 minutes 30 minutes. No, it's see it takes me longer. I think it takes a sal 30 I think we're almost like 45 50 years It's a little delayed in my brain a little bit But anyways, I just I I got into this debate with somebody that it is not And here's here's the case that somebody can make a first of all the uh, you have to write away anybody who's presenting it as as amazing as it is more than likely is profiting off of off of a product that's related to it So be careful of that. So if you're gonna if you're gonna read the science and the literature on it Read the science and literature of somebody that's not attached also to to the product itself So that's important that you do that. Yeah, and when you read all the literature that's around that movement Yeah, it's an incredible glute development movement and and are a lot of people suffering from anterior pelvic tilt Yeah, and I think that would be a great exercise to do to help counter that So it's a great strengthening exercise so long as you do it right, right exactly So long as you do it right that can help address that is it one of the best things for building the glutes? Absolutely So you can make a lot of cases for why it's amazing But no no no no does it belong up there with overhead press deadlift Now I want to add one thing to this is that and that is if an exercise Specifically corrects an issue or an imbalance for you that exercise becomes the most functional Excellent point. So to that argument a seated row could be the most important thing that you do right, right? I'm saying like so So if you have an issue with hip extension if your glutes aren't firing The way you want but syndrome right if it's underdeveloped if that's something that if this if the hip thrust Is the perfect exercise for your body and your movement patterns Then it does belong in the absolute.  Yeah, that's right No, that's a hundred percent right and all the ones that you listed before Step-ups, split stance, you know lunges Squats if you're if your glutes aren't firing properly and you don't have good hip extension Then barbell hip thrust could absolutely Supercede those movements totally because of that reason. So that is a very good point And we're speaking generally so generally speaking You know after training hundreds of people or thousands through the gym people have come through my gyms Um hip thrust generally speaking just aren't as valuable For most people like a deadlift or like a barbell squat or a split stance squat But there are definitely people um where a barbell hip thrust is the most Beneficial valuable exercise. So at the end of the day, yes, we're giving you general advice But you have to apply it to yourself as an individual and if you're somebody that lacks that hip extension Lacks that connectivity to your glutes or let's just say you're into body sculpting and body building You really don't care too much about function. You just really want to develop Just the glutes and you have trouble connecting to them with barbell squat. Now it becomes an extremely valuable exercise So I wanted to put that out there because for sure, you know, we have a lot of listeners and for sure There's at least five people listening who are like hip thrust change my life. Yeah, and they that very well may be true