Hey everyone, SheaBear1000 here today. We've got this ceiling fan. It's pretty cool. We're going to open this up We're going to take the old ceiling fan down out of mom's room And we're going to put this one up and we're going to check it out. It's remote control Should be pretty handy for her Okay, so let's get this opened up. Let's see what comes in the box This was sent to me from a company that sends me some things to try out And do quit videos on so but this one I'm going to do a video for them and a video for you guys So the color is white. It is a 19 inch fan. Okay, we have some hardware here and the instructions This looks like the remote control It's got a little Hoster that you can Hang on your wall We're on your nightstand beside you Let's open this up Let's get this out Look at that. That is nice Very nice. Awesome. Okay, so We're going to have to go take the other fan down So we can get this one hung up In its place Should be pretty self-explanatory But I'm going to show you how we're going to do this So let me get you set up in the bedroom take the other fan down And we'll get this one Starting on putting it up and hooking it up. Okay guys. So now I have The power turned off. I'm gonna take this off The globe monkey Had this fan installed before we got together and She says she never liked it so It is an LED fan. It's beautiful fan very expensive fan So we're gonna try the one that the company had sent me and Hopefully right this one was making some noise it stopped, but it would only do one speed And I'm thinking it just needed to Be oiled, but it started working again. So We're just going to go ahead and take it down because I'd have to take it down in any way to oil it So we're gonna put up a new one. I'm gonna feed I'm gonna speed you up through this process Well, I'll just go ahead and make a cut because you get the idea. I've got to take these fan blades off Take one off and then we'll get the idea Okay, there's one Now I'm gonna do that to the other four blades and now we're just taking off the light assembly here and There's the light assembly out now We have to take the top off and I've got to get a short screwdriver for that because the screws are hidden up on top and I'm gonna have to get see if I got one of the elbow Fill up screwdrivers because this is still too long to go up in there So it looks like there's there's three screws up there. So let me get see if I got an One that shape like an L. I don't have one, but I do have this bit And it's quarter inch wrench here that will work So again, this is gonna take a few minutes So I'm gonna kick you back on once I get the Last screw out turns out there was four of them up there. These I can tell you Or cross thread and well this there was three out of the four That were put in at an angle. I said I didn't put this fan up. So Now that screwed in Down through the top. So I'm not sure Never seen it set up quite like this before This is screwed on to this Down through here. All right, there we go. So let's go ahead Two just has to be loosened And two have to come clear out There's the two that have to come out. Now we're gonna loosen these two just a little bit. Yeah, that's a weird setup Now we're going to stop Okay There's usually they have a hook that you can hook these on and hang them While While you're working on these this one don't have that the new one does Okay, so we've got there's a ground got red Get white to white Black to black. So they did that right. There's that take the ground wire off All right Now we're on hook. We can set this down in a nice spot where I can trip over it and that's a straight This is a Phillips or straight. That Let me go get a Standard screwdriver and we're gonna take this off and then this will be already this will be down. So our new fan will be Mounted to the ceiling to the drywall itself. Okay, you get the idea. That's a That's a really long screw there There we go I'm gonna get a bag and put all these screws in so we're gonna start with hooking up our wires They're color-coded and Labeled this is your live wire. It's the black one. This is your neutral wire So it's got an N on it.  I'm gonna do that with the other two wires I'm gonna do that with the white wire and I'm gonna do that with the blue wire again Our blue wire is going to be the ground just like that Next I'm gonna utilize these two holes that already have from the other fan that I had removed and I'm gonna Before I tighten them up. This is just to hold this in place So I can mark my mount With my little pencil here Then I can run two anchors and two screws And that's going to be perfect for what we need to do now. I'm gonna make two holes Where my marks are here is one mark I'm just going to take a screwdriver and Push it right up through there. I'm gonna push my anchor up in there, and I'm just going to tap it in It's like that. I'm gonna do the same thing with this one over here on this side Just like I did that one Your application may be different. You may not have these two holes here They give you plenty they give you four anchors and four screws Which would be plenty to hold this light up now.  It's going to go to ground and we're going to do that Just by putting a couple wire nuts on and we'll do that with the other two and Then we're going to put this up into place now We have three screws to put in there's three holes here one goes there one goes there and one goes there They are supplied with the unit now put the other two in One over here one over here. We'll wipe it down and try it out. Oh done time to check it out Okay, now it's time to check this out first. Let's turn the light on it has a handy-dandy remote control So we're going to use the remote control. We're going to turn the light on There is three different light settings It's got white light yellow light and natural light. There's the white light There's the yellow light and There's the natural and you can also Brighten them We're dim them. There's dim all the way up to bright. This is very user-friendly remote control It also has a one hour and two hour Timer on this remote. So we're going to start with the fan. We're going to go to low very quiet No vibrations We're gonna go to medium now. We're going to go to high and there is a stop button on your remote control That'll stop it and then you can turn off the light Like that or you can use a switch This is perfect for a child's room or an elderly person's room, which that is what this Incidentally this fan is in It's in my mother-in-law's room seems to be of a good quality It was easy to set up. You don't have to pair the remote control.  Okay guys So there you go. That was um Really easy to set up and it actually covered the hole from the other fan Now if you noticed there was a red wire hooked up. That's because someone when they put all these fans in they put two switches one for light and One for the fan This one you don't need that. You only need the one switch.  That's only three wires. You have to worry about so Yeah, it's um Very nice. I'm I'm telling you what I'm impressed with that fan and the fan is also Reversible We'll let it stop here on the remote control. There's a red button up on top While that is running you hit the red button You'll hear that beep it will slow down automatically stop automatically and then Reverse itself in the other direction and there it goes Very neat Beautiful piece. So guys there you go. There will be a link in the description down below In case you're interested in one of these. I'm really impressed With how much error that is moving Opposed to that big giant fan that was up there and this thing looks really nice. It's gorgeous So though I'll put a link in the description below So if you have any questions, please comment and I'll answer them the best of my ability. There is an instruction here Instructions very simple guys if you've ever hung a ceiling fan up before any DDI wire can do this theirself so Yeah, I'm very impressed. I love all the functions And I like that it's remote control for her mom. So Now depending on whether should you have it blowing down in the summer and things like that To me what makes sense is in The summertime like the big fans. I usually have it sucking the hot air up keep the hot air up here We all know hot heat rises So that's what I do. I turn them on backwards. So that way the cold air stays down here the fan sucks the hot air up and In the winter I have it blowing down Because again the heat heat rises it blows the heat back down on you Again, it could be just a matter of preference whatever you want to do, but that's the way I usually do them A lot of people think you should have it blowing on you But I'm really hot days Let's say you don't have air conditioner in a room or something like that And if you have that blowing down on you you can actually feel it blowing hot air on you And if you turn it around to where it runs backwards, it sucks that hot air up It actually makes you cool down more because it's sucking hot air up past you That's just the way I've always done it it makes sense to me, but you can do it however you want to do it Especially with this thing. So thanks for watching guys appreciate it She better the myth the man alleged I'm gone for now. We'll see you guys in the next one. Bye. Bye and take care


Welcome guys, my name is Piyush Makhija, I am a NLP engineer at Wahan AI. Wahan AI is a Y combinator back start up, where we are building a jobs market place to help low scale to semi-skilled people find jobs and we are essentially solving the problem of high volume recruitment for last mile workforce for e-commerce and on demand logistics companies. To give you an idea of why we are even required, take a look at some of these articles that have come out in recent times and many more. The point is the on demand and logistics companies have put forward a new jobs market place for last mile delivery workers. Let me ask you guys a question, how many of you guys have ordered online or shopped for food in the last month, in the last week? So is there anybody who has never shopped online or used any of the e-commerce companies? The point that I am trying to make is that these services have integrated so well into our daily lifestyle that they have almost become a necessity. In some terms, we can say that the delivery person that brings your products to your place on your demand is as close as we can get to a modern day Santa Claus and the demand for these modern day Santa Claus far exceeds the supply. To give you some metrics, there is currently a demand of 500,000 delivery jobs in India and this is increasing at a 30% year on year rate. Most of the e-commerce and logistics companies are already heavily investing in scaling up their logistics operations. To give you an example, Danzo, a fairly new player, increased the size of its logistics operations by 10 times is just in the second half of 2018. So why is this particular problem hard to solve or what is different about this problem of hiring last mile workforce? The first point is that the per month higher requirement is extremely high. It can range between 500 to 10,000 depending upon the scale of your logistics operation and if you feel this number 10,000 is high. Swiggy Flipkart during the seasonal sales have a requirement of up to 50,000 delivery jobs in a month. The attrition rates in this particular industry is extremely high which is somewhere around 75% in 2 to 3 months. The hiring demand is seasonal and sporadic and the nature of the hiring process is highly manual and unorganized. So the job space is highly fragmented, inefficient and really hard to scale. So the problem to put it in simple words that we are trying to solve at Wahon is to build an efficient and scalable system for high volume recruitment of this last mile workforce. And once we had the problem in mind, these are the design considerations that we took into account while building our solution. The first is that we need to reduce manual labor by a lot. So we have to bring in automation in some sort to the processes that are involved. Second is that we need to build a one stop solution that is there needs to be a one solution that accounts for different scale and size of logistics operation and works for different verticals. We should be able to work at scale if we have a requirement to hire 500 delivery persons in a month and immediately next month we have a requirement for 10,000, we should be able to scale to that. We need to account for high churn rate and attrition which is a reality in this particular sector. And next there is no LinkedIn for blue collar workers. By this I mean there is no social or professional platform on which these people can connect with the recruiters or their peers or they can develop a career profile. And finally when we are developing solutions we think let's build an app for that. But in this particular segment an app brings a harder challenge of adoption. Will the user use my app or not? Will the user after using the app not discard my app? Because a particular recruitment app is not a daily use application. So it has no use being on your mobile applications once its purpose is fulfilled. Following these design considerations in mind, we at Vahan came forward with the following solution. We needed to automate job seeker engagement on existing messaging platforms. The idea is very simple that on the existing messaging platform such as WhatsApp or Facebook Messenger you can reach out to us on our account and get the conversation started. We recommend you jobs and help you guide to a job process. By the way this is a dummy number. This is not the actual number we have in production. This is just to illustrate my point. So how did we at Vahan address the design considerations? Let's go over those points. The first and most major challenge that we solved was to circumvent the adoption. So India runs on WhatsApp. 97% of the smartphone users in India are already using Facebook Messenger or WhatsApp in some form or another. They are very comfortable with these platforms and most of these platforms are being used on a daily basis. So our users are already existing on these platforms. So we adapt to the users. Our users don't adapt to us. Next we need to automate certain processes and we found that these are the processes that we can automate. That is we can pitch to the user a job, gauge the user's interest in that particular job, do some basic screening for the job requirements and get them to a walk-in. Next we thought that our solution needs to be a virtual assistant in order for us to be automated and a virtual assistant can be of different types. It can be an IVR based solution, a voice based solution or a text based solution. An IVR based solution is a very rigid and inflexible way to solve this problem. Our users won't be able to interact properly with our system. They won't be able to provide different kinds of inputs. They are restricted in the kind of inputs that they can provide and they cannot query to input. So we move further to the next. You can standardize in any language. The point is you can only collect limited amount of input. If the user provides any feedback, you won't be able to respond to it. You won't be able to adapt to the user at that point and hence it's not an efficient mode of conversation. Next we move on to a voice based platform. In a voice based platform the issues are that we have to provide real time responses and given the data bandwidth and quality issues that we have currently coupled with background noise and error amplification in speech to text and text to speech systems, we found that this might not be the way to go right now. And hence we decided that we will go forward with a text based virtual assistant or a chatbot. We decided for this because our users were already familiar with these texting platforms and they were using them on a daily basis. So it further helped with the adoption. Furthermore we needed to avoid hopping across different channels through various segments of the recruitment process to give you an idea of the current recruitment process in this domain. The first things that a recruiter does is that they generate leads via classifieds through knocky.com or quicker. Next they process these leads on excel sheets or in certain cases by manually on hand by paper. Next they engage these users via telecalling or in some cases on ground operations in person to person way. And they screen them on site, they call the user to their hiring centers, they screen them there and get them on boarded. So the complete hiring process is very manual and very segmented. There are different separate processes that are interacting. So we need to reduce the attrition over here and bring these processes together in some way. The next challenge is scalability. Most of the companies that are doing this task today have a very high scale logistics operation which are interacting in a very manual effort like it's telecalling or person to person interaction. But with a virtual assistant we can reach out to thousands of people at any instant. Next we needed to counter churn and we were able to do that by increasing the top of the funnel that is due to a high adoption rate by bringing in automation and scalability we can provide more leads. We can generate more leads or get more people into the system and counter for the churn that happens. And finally we are able to build rich user profiles which is ultimately going to lay the foundations of a professional platform for these blue collar workers. So essentially what I'm talking about the solution that we have built is a goal oriented dialogue system that is we are going to carry out conversations with the user to complete certain tasks and finally reach a goal. The goal being that we need to qualify a user for a job that he or she may be interested in and the task that we are going to perform over here are pitching the job to the user gauging their interest screening them on our platform itself and scheduling their walk-in. So to give you a bird's eye view of our solution of how a sample interaction happens on our platform take a look at this example. Consider the case that we recommend a job to a user something like we have a job we can see and so and so company and so and so location are you interested. Option one yes option to no the user may choose to directly respond to us that yes I'm interested no I'm not interested or they may ask for certain things by themselves they may have their query of their own. In this scenario the user is asking hi sir salary kithna melega which is hi how much is the salary that is associated with this job. And as you can see certain words in this utterance are misspelled because that is the way we type we do not care about spellings or grammar when we type on these texting applications. So the first thing that we do over here after preprocessing is apply a basic text normalization which is something something of a fancy spell correction we'll deal this deal with the detail in a few slides later but for now we are normalizing the data and standardized bring it to standardized words so correcting the spellings of some sort. Once we have corrected those spellings we have reduced the variability in data we first check that this input utterance match any of the option choices that we provided. The user might have said I am interested which is an indirect way of saying yes we could have matched that over here but in this scenario the user is saying the user is asking how much is the salary so we further go to a intent classification system. In the intent classification system we identified the user's intent as a request for salary information and once we have identified with certain confidence about user's intent we can do a response lookup and provide appropriate response to the user. This is a sample interaction with the user that happens on our platform and in this particular sample interaction we are using two machine learning models one for text normalization and one for intent classification but for any machine learning model as it's always the case your model is only as good as your data. The problem with our systems is that for any machine learning models we need to collect the data first and the kind of case that we are solving does not have any public domain data that we can use and this problem is further aggravated by this following things. The first thing is that our user uses mixed languages. Our user does not use any kind of proper languages and most of the users in India are polyglots that is they mix multiple languages together when they are typing or speaking. I myself being a native Hindi and English speaker converse while mixing Hindi and English words together in a statement and that is the way I type and while typing I further produce more interactions in the way that I will have typos I will have slangs I will have abbreviations or misspellings or mispronunciations that creep into my typing itself. Furthermore the vocabulary that I use while mixing my Hindi and English might be different from the vocabulary that you have while mixing your own Hindi and English. So my English is going to be different from your English which brings to me next point this high variability in the data that is to write a simple word such as yes for you and I to understand over a texting platform there are at least 50 ways in which I can say yes and you will understand I can say yeah yep yes all meaning a positive yes. I can also type these in roman script but in a different language like ha for Hindi how do for Kannada or in certain case for native karnataka speakers who have the some way of spelling out yes as s with a heavy intonation to the letter s they also type out s in this way as a response yes. So this all brings a lot of variation to the data and the problem that we are dealing with is again that we don't have these kinds of data sets available anywhere. There is poor availability of research level data on these data sets the proper term over here with the type of data that we are dealing is a code mixed data set and furthermore it is this problem is aggravated with regional and cultural influences to give one more example of regional and cultural influences. If I say to somebody in Bangalore call Madi which is a English word coupled with a Kannada word meaning call me somebody in Bangalore is most likely going to understand it because this kind of phrase is associated with this region but somebody in say Delhi won't be able to understand this. So all of these problems coupled together made us very hard for us to solve any of the text normalization or intent classification issues. So we had to invest heavily in data collection exercises the first that is we had to build bots to collect data for our bot. The first exercise that we entailed in is creating a jokes and daily codes bot.  So we decided to go that route but this approach did not help us because we received a lot of spammy messages. We were not finding any data that we could use to build a comprehensive data site. So we moved further and built a translation bot that is users will come to us and we'll provide input English translations to whatever input they provided. This seemed like a good approach but the problem was it had very sporadic usage. It was not something that the user would come to come back to very often. It was an upper need basis that the user would come to us. So this did not seem like a reliable way to collect data. We moved further and built a English learning bot that is we put together a script where we'll help the user interact with us and learn some basic English. The problem was with our script that the content that we were receiving was very narrow. We are receiving only very limited kind of interactions which did not help us build a comprehensive data set. Finally we struck gold with a friend finder bot. This is an idea that came into inspiration via chat roulette. The idea is simple that we are going to connect two people on an anonymous chat, let them talk about whatever they wanted to and with their permission collect their data. This bot got so popular that we were collecting two million messages per month. So finally we solved a cold start problem for the data set and have a reliable way to collect a comprehensive data for code mix languages pertaining to the population that we are going to build the product for. Next thing is that how do we handle all these nuances of code mix data? So the first problem that we have is the text normalization. Here is a very simple example of how our text normalization system works. Say you have two sample utterances from the user. Hi I have a bike with high misspelled as hii and mere pas bike hai which is a Hindi statement saying I have bike in which the last word hai is misspelled as hii. Both of these utterances have the same letter sequence but both of these letter sequence are misspelled in the wrong way. So a text normalization system needs to take into account the context of the statement or the context that is occurring with the question maybe and produce a correct normalization. In the first case the user is providing a greeting hai and in the second case the user is providing a Hindi word hai which means I have. So taking into account the context we need to provide a correct spelling check. So this is some sort of a fancy spelling character and the way we did it was via machine translation models. So we started with a statistical machine translation because it had lower data requirements and a statistical machine translation provided good performance with smaller data set. But as in long whenever data set grow statistical machine translation stopped providing incremental gains in performance and we moved towards neural machine translation model. A statistical machine translation works on a probabilistic way that it sees a certain interactions happening n number of times and maps it as a Markov chain. But if in case it has not seen a particular translation happen or a particular instance not happening it won't be able to account for that like in this case h followed by triple i which is misspelling of hai a statistical machine translation model was not able to correct form. But a neural machine translation model given enough input utterances can account for similar kind of misspellings which it is able to do here with the same training data set. This particular model we were able to train with over 5 million data points and it is still providing us incremental improvements in performance. To dive a bit deeper into the neural machine translation that we implemented it's a pretty standard character level model that we implemented that is available in the text. So we have input embeddings for all the roman characters and we pass them through a bi-directional LSTM layer which further go through a attention layer, a decoder which is a simple LSTM and finally a softmax layer. So the kind of performance we were able to get with these machine translation models provided significant improvement over baseline. Our baseline was a 52 percent word error rate that is 52 percent of the input words that we have did not match anything in a standard English dictionary. 52 percent of the words were out of vocabulary for us but after applying machine translation methods less than 3 percent of the input words were out of vocabulary which was a significant gain and helped us improve our intent classification furthermore. The average sentence level blue improved up to 0.97. This is a metric that is lying between 0 to 1 that is we computed blue score over every utterance and took average upon all the testing set which was held out of sample. So now that we have solved so now that we have solved the text normalization issue we've moved further to the next problem the intent classification how do we understand the intent of the user. So in this particular segment a user can ask different kind of questions something like Apcon who are you that and why you testing texting to me so we reply to them accordingly. The user can provide something input that is more colloquial in nature so if we ask to the user do you have a driving license as a screening question for a particular job the user responds with I have LL only. In this context LL means learner license our normalization system is able to take that into account and we understand that the user is saying I have learner license that means I don't have a driving license that means the user is saying no and we respond to the user accordingly. Similarly the user may ask different kinds of queries or different kinds of indications regarding the job or their interest in a particular type of job something like what is do I get part-time job do you what kind of salary or incentives do you provide and so on. But as I said this intent classification system is made particularly to solve this domain specific problem so it cannot solve out of domains problems like a bus reservation. If you ask it to book a bus for you it won't respond properly and keeping in mind the data that we trained with if there is a particular a trends that you did not train it to handle for example this thing happened so it won't be able to handle this thing has been since corrected with but then there are certain cases where your model over fits and it tries to respond to questions that it is not supposed to handle. Taking into for instance this kind of a trends I don't know where to find a Pikachu this is a fictional question and our bot having overfitted over certain words like where in this case this understands this that this might be a location query and provides the response according to that in this case it should not have but it still does. So a little bit more about the performance that we are getting and the systems that we used for the intent classification model. We have experimented with Rasa NLU and Fastix libraries. We chose these libraries because with these libraries we did not have to take on the burden of building a new embedding layer for our specific data set. We can't use a generic glove embedding or our two way model. So we had to build our own embeddings and this particular case or these particular libraries did this autonomously with the data that we provided. Provided we had to give it sufficient data and Rasa NLU worked well with limited number of instances but when we increased our data set size over time Fastix provided phenomenal performance gains. The fn score we are able to get was somewhere around 0.94 and we were able to get up to 0.92 coverage. Coverage here means that of all the input utterances that we are receiving from the user, which are not direct responses to our option choices. 92% of them we were able to respond to. The current ongoing efforts that we have at one to improve our machine learning models is that we are exploring with different methods or text normalization approaches, particularly in machine translation to improve our models like BERT. We are trying to improve our performance on the domain specific data itself so that we handle the user's responses very well. Apart from trying to improve the performance and intent classification systems by adding more data, we are looking into different architectures by which we can improve our performance. We are also looking into expanding our domain to different languages. Currently we are able to handle mixture of English, Hindi and Kannada very well. We are expanding to mixture of English, Hindi, Kannada, Tamil, Telugu and furthermore than Bengali and Marathi also. So this is some of the ongoing efforts that we have. We are also looking into creating a context-based dialogue system where we can understand the user's context and provide a much more humanly responses instead of just basic index lookup. A few key takeaways from the problems that I have illustrated is that there is a urgent need for a high volume recruitment solution in this particular domain. And this need is now. There is an urgent need for a social and professional platform to be provided to these users so that they can build their career profiles and exceed in this career. There is a the kind of solution that we build needs to adopt to the user rather than the user adopting to your application or whatever solution that you bring up. And this solution needs to have some kind of daily use for it to be relevant to the user. There is a immediate need for research and development on code mixed data sets or the way people interact with each other colloquially. And we can start by study forming strategies to collect large amounts of such data sets. And we need to also account for personalization of regional persona. We need to adapt ourselves to the particular region or the particular way a person interacts. The long term vision that we have at Wahan is that we not only solve the jobs problem for these kind of people, but we also help them hone their skills, become financially stable, develop a social and professional community we can where they can look towards the holistic development. In the short term, we are we think that in the near future, once your modern day Santa Claus comes to you bearing gifts, he or she would most likely be recruited via platform. Thank you. Questions? Correct. So, there was heavy focus on like labeling that data. But we also apply different approaches to make more use of that particular data. So, we use certain data augmentation approaches to increase our data set size that is synthetically generating data. So, half of that would be like manually annotated half of that would be labeled or synthetically generated. Correct. So, I mentioned over here that we are still working on building this for domain specific data. So, the data that we collected using friend finder bot is kind of like a generic start that we got and then we collected further more data from our platform that is the job finder application on WhatsApp. So, from that we connected very domain specific data or use cases where the user tells us about misspellings of self-salary, misspellings of timing, misspelling of say company names and so on. So, we also train on that data basically by guiding the user. So, considering direct and indirect responses of the option choice around 10 to 15% is text that is not matching the response choices. Anybody else? Yeah, we have obtained the WhatsApp API and we have like all the business contacts. But before building the tool, we had a cold start problem. We had no way to like collect data and even if we launched our tool without any NLP like we would be collecting not enough data on a daily basis with a small start. So, we solved the cold start of data collection problem over there. So, since then that particular bot has been discontinued because we are collecting a lot of data on this platform already.


From around the globe, it's theCUBE with digital coverage of Red Hat Summit 2020 brought to you by Red Hat. Welcome back, I'm Stu Miniman and this is theCUBE's coverage of Red Hat Summit 2020, of course, this year's event happening digitally. So we're talking to Red Hat executives, partners, customers, where they are around the globe bringing them remotely into this digital event. And really important topic of course has been automation for a long time. I think back to my career, automation, something we've been talking about for decades, but even more important in today's age. Happy to welcome back to the program, Tim Kramer with Red Hat, Vice President of Engineering is the title we're have listed to you here, but since we last talked to him at AnsibleFest there's been a little expansion in the scope of what you're working on. So first of all, welcome back and tell us what's new in your world. All right, well, thanks a lot. So, yeah, there's been a rather substantial change in roles. So I'm now in charge actually of all of the engineering within Red Hat, all the development engineering. So that includes the middleware teams, Red Hat Enterprise Linux, course management and automation and the newly, the new team that we just brought over from IBM doing advanced container management. So I'm basically running the whole thing now and OpenShift of course. Excellent. Well, just a few things to keep you busy, Tim. Congratulations on that and love your sport in the Boston Hello World Rella 8 shirt that of course we saw last year at Summit. I know one of the things being digital is people do miss some of the t-shirts. I know my family was quite fond of the May the 4th be with you shirts that Red Hat did one year at Summit. Of course, celebrating Star Wars Day, highly celebrated in the Minnowman household. But, Tim, let's talk about Ansible. So just bring your audience up to speed, what's happening, some of the latest pieces and of course it's been one of the great success stories. Ansible was a lot of adoption before the acquisition but really accelerated over the last few years. Yeah, so at Ansible Fest, we talked a lot about technology to come and showed a few demos of the possibilities. What we have done since then is actually bring all of that technology to life and to expand it. One thing that Red Hat has really done is continue to invest heavily in Ansible to make sure that we can bring new capabilities and new value to the subscription for everyone. So some of the things that have been happening since Summit, and since Ansible Fest since we last talked was that the community continues to scale at a really rapid rate. It's almost hard to keep up. And the number of modules that we have had has grown just tremendously. So we have well over 3,000 modules now that are available. And as customers and partners and also just casual users are looking through that, it's difficult to figure out what's really supported, what's really rock solid, what can I count on and what is maybe sort of that Wild West community I'm just trying out some stuff with Ansible and see how it goes. So what we've been focusing on a lot is a place that you can come to the Ansible Automation Platform and the Hub where you can now get this content and you can rely on the fact that it's going to be certified by partners, tested by partners, they're always keeping up with the latest updates. A great example of this is, let's just take NetApp or F5 or Cisco as good examples across the various spaces. We absolutely in the Ansible engineering team are not experts on all of the latest changes, the new hardware coming out, the new software upgrades that they're making and our ability to keep up with that is pretty difficult. We just can't do it, but they sure can and their customers and our customers are both demanding that we give them more content, better content and we need to be able to do it at the rate that our partners want to be able to provide that content. So as an example, normally we were kind of slowing Ansible down and trying to do one release every six months but if a new piece of software or a new switch or a new disk array or anything comes out in the meantime, all of our customers had to wait for that next six months release. That was not very convenient and having an expectation that our partners were going to line up on our schedule is, well, that didn't work out so well for them. So we've created this certified content and we now have the goals to have 50 certified partners back at Fest, I think we had three or four, we're now up to 30, our goals to hit 50. We had about a hundred modules that we showed at Fest that were certified. We now have over 1200 modules that are certified content and these are our partners creating this content and making it stable and secure for everyone to use. So that, I think, how far that was the coolest thing that we've done. Yeah, it's great to see that progress. Congratulations on the momentum since Ansible Fest. One of the other things I talked about back at that show, we talked about how analytics and automation, how those are going together. So, how's adoption been since last we met? Yeah, so adoption on the analytics side has been taking off. It was pretty nascent, so I mean, I could tell you that we've grown by about 5x there, but we started a little bit small. So we had a few customers that signed up early on to do it. I think probably the more impressive thing is that we have a couple of customers in markets that you would traditionally think we're not going to get their data, they're more concerned about what we're sharing, but we have a major bank, we have a major manufacturer that have well over 10,000 systems providing data back into Red Hat that allows us then to analyze and provide a bunch of analytics back on their running estate. And I think that that's amazing, right? Seeing the big customers that are coming in from markets that you might think, we're probably not going to get a lot of uptake has been really exciting to me. All right, so you talked a bit about how Ansible fits into the ecosystem. Of course, being at Summit, want to understand a bit more how Ansible, the latest of how it's fitting into the rest of the Red Hat portfolios. So, I've got interviews with Stephanie Shiris talking about you, Raell and Joe Fitzgerald talking about ACM, your group I know is heavily involved working on a lot of those pieces. So help us understand how this is kind of a seamless portfolio. Yeah, I think that's one of the most important things that we do within the Red Hat team is that we have to share this efficiency across all of the product groups, make them better and provide an additional enhanced value there. We've done a lot on the Raell side. Probably one of the maybe lesser known thing is that we've been working really closely on OpenShift and actually we have a lot of customers now that really want the Ansible Automation Hub available on OpenShift as a first class application. So we're doing things, we're writing operators for those so that we can automate the updates and upgrades and backup and all of that important functionality so that it's really easy than to manage your Ansible Automation Hub running on OpenShift. So that's one big thing. And then we're going to integrate that really well into the advanced container management that the team from IBM that came over is working towards. So a really close partnership with ACM team to make sure that we can start to not only gather lists of affected systems but then take that list and do a bunch of automations against it. So that's one. On the Raell side, we've done a lot. So we introduced at the last summit Raell-8 and we talked about having insights as part of that. Since then, we've been adding more and more capabilities into insights to enhance that value of the subscription of Raell. So we're looking at, we looked at adding in, well, Advisor is now what we used to call Insights. It's just something that advises you about problems or issues that may be occurring in your Raell instances that are running on Chrome. We've also added in a drift service. So you can tell if your configurations are sort of drifting apart. We've added in a compliance checker. So you can define some kind of a policy or compliance that you want to enforce on all of your running instances and we make sure that you're still compliant. We also have a vulnerability detector which you'd kind of expect. So any nasty security issues that come along, we can pop those up and show you right away. And probably some of the, one of the newer things is we allow you to do patching and you can do that patching right from cloud.redhat.com. We also have another new, very exciting feature which is subscription watch also on cloud.redhat.com. And what this allows you to do is to see and manage all of your subscriptions across your entire hybrid estate. So from what you're running on-prem to what you're running in any of the public clouds, we can actually track that for you. You can see what kind of usage you have and then make better economic decisions for yourself and then be able to easily expand that usage if you want to. It used to be a little bit more difficult to do that. So we're trying to make the subscriptions just as much in the background as possible to make it easier for our customers to make. Yeah, so Tim, one of the big changes customers have to go through is moving from their environment and their data centers to the leverage of SaaS and managing things that are outside of their control in the public cloud. You've got an engineering development team and you've got software that went from mostly going in customers data centers to you've got SaaS offerings, you're living in the public cloud. So you want to understand what's changing in your world? What advice would you give to other people as to the learnings that Red Hat has had going through those pieces? It's actually kind of a neat story because after we changed to start making a lot of our services that we had just only shipping products on-prem into cloud-based services, we had to develop this platform to be able to host all of these services. We started with the Insights platform because we already had that running out in the public cloud. So that was the obvious first thing to base everything on. But we had to build out that platform so that it could support all these services. The ones I just talked about that are with RHEL are really good examples. So between a policy, compliance, drift, all of these different kinds of services that we're offering, we had to build out that set of capabilities and services in what we're calling sort of the cloud.redhat.com platform. What I'm seeing is that a lot of customers are going through some of these same kinds of thoughts. Like they have a myriad, let's say, of applications that are running that they're trying to provide back into their own company. So different divisions of a company, they have things that are running in the cloud, some things that are running on-prem, and they want to start to be able to offer a more cohesive set of services, consolidate some of this, share some of the engineering effort that they have across their various teams. This is exactly the journey that we went through to get to cloud.redhat.com. I'm finding a surprising number of customers that are actually really interested just in that story about how we did that. One of the things that we've found is we've been working with the folks at the Open Innovation Lamps within Redhat. And this is one of the transformation stories that they see constantly as well. So we've worked with them and shared this. They're a great resource to help customers kind of think through that problem and get them into a new kind of a platform. But it's been quite a journey, right? I mean, we've been really focused on the infrastructure and on-prem. So moving to the cloud was a big deal, but I'll tell you, engineering can move so much faster in a SaaS service than it can with on-prem software delivery. It's been remarkable how quickly we could get there. Yeah, Tim, one other thing, if I look at Redhat, your global company, most development organizations are highly distributed to begin with. So many companies today are now having to rapidly figure out, how do I manage people that are working from home? How do I live in these environments? From an automation tooling, I would love to hear any advice you have there, as well as just anything else from your engineering experience and your teams that other people might be able to learn from as they're dealing with today's landscape. Well, I mean, to be honest, right? This is a, we've never seen anything like this in our history with this kind of pandemic that's happening worldwide. So it's shifting everything about business. And it has been challenging just within Redhat engineering for how we can manage the engineers and their expectations and how difficult it can be to work from home. I have amazing stories from my own engineers. I had an engineer who's in Spain and his wife as a nurse. She's on like 18-hour shifts. The hospital comes back, they have to separate. He's got the kids because they don't want them to get infected. It's a really, really difficult working situation for a lot of families out there to try to make it through this.  It's kind of too much. So we've been really, we're trying to be very compassionate with our folks letting them know that we have their back and it's gonna be okay as we try to get ourselves through this ridiculously different time. I mean, we've never seen anything like this, like I said. From an engineering perspective, I think work from home has been, it's okay for some people. If you have a larger home, I think it's a little easier maybe to find a room that you can go into and do your work.  And it can be really challenging to figure out how to work for eight hours a day with sort of a lot of distractions or just feeling confined. And it just being really difficult for anybody that wants to try to get out.  So the good thing, I guess, is that engineering naturally lends itself to being able to be remote and work from home. So we have an advantage that way than other industries which is great, but it's definitely been really challenging for our teams to be able to cope with this. And all we can do is just be really understanding. All right, well, Tim, appreciate the stories there. Definitely everyone's working through some challenging times. I want to give you the final word as to really takeaways as to what should people be watching? What things should people be going back and looking at from an automation standpoint as they leave Red Hat Summit 2020? Well, we're just going to continue to work with the community, work with our partners, get more certified content and continue to scale the best way that we can for all of our users and our customers. That is the key focus. We want to continue automating and providing all of that flexibility. If you want all 4,000 modules and a big download, we certainly are going to continue to give you that option. But if you want to be able to start customizing what you download, maybe only relying on certified content instead of community content, we're going to give you that option now as well so that you know what you're running. And with the analytics, we're just scratching the surface here. We're getting some great data. It's helping us to develop new ways of insights into how your systems are running and that'll get very exciting as we go forward. I know that we've seen like a 4x increase already in the amount of insights attached to REL, which is really great. And we're now at least in the hundreds of customers that are using the AI, I think as we show more value there, we'll get a lot more customers to provide some of their data, which will allow us then collectively to come up with some really great analytics to help people become more efficient with their automating. Well, Tim Kramer, thank you so much for the updates and thank you to everything your team's doing. And just a reminder to the audience, of course, these communities not only are important technical resources, but many of them you've made friends with over the years. So if you need help, reach out to the community, there are so many good stories that can be found amongst these communities, helping each other through these challenging times. So, lots more coverage from Red Hat Summit 2020. I'm Stu Miniman and thank you as always for watching theCUBE.


Hey everyone, I'm Bianca Renee and you're watching Bianca Renee Today and today I'm going to introduce to you a new product I'm going to be adding to my long hair journey routine.  If you're new to my channel, welcome. This is a new haircut for me, and I'm growing it out. So now that we're all cut up to speed, let me introduce to you my new best friend, which is this scalp massager. It's an actual massager for your scalp, and it does what your fingers cannot do.   So when you first get it, it doesn't have batteries, you know, it's just like Christmas morning when you want to play with your toys, but you got to put batteries first.  Then you just slide it back on in there, lock it into place, it says lock and open, so you know what's going on, and then it's good to go. But I do like that it actually detaches because now if you get too much shampoo or any much whatever product on here, you could just take it off and rinse it really easy and not affect any molding or water damage to the battery area. Now luckily you can use this when you're not in the shower on your dry hair, or you could use it in the shower with your shampoo or with your conditioner. Today, I'm going to show you how I used it during my co-wash, meaning I did not use shampoo, I just use conditioner, so I'm going to apply my conditioner and use it then. If you do use shampoo, I'd probably recommend using it with your shampoo to really cleanse the scalp, then you can rinse it all off and then do the conditioner. You don't have to do it again with the conditioner, but it feels so good, you just might want to. Now this scalp massager came from VanityPlanet.com. It's part of the VitaGoods line, I believe, and what it's supposed to do is promote a healthier scalp, helps control dandruff, lifts away any dead skin cells, massages and invigorates your scalp, and it's waterproof. Better be waterproof because we're taking it in the shower with us. Now I have been dealing with some dandruff lately and it is not cute to have a whole little sandbox resting on your shoulder. So this is going to help with the dandruff and make my hair grow longer at the same time. So without further ado, let's get to the shower and get to massaging.   Just try not to fall asleep. You're going to continue to massage in a circular motion on the top, on the back, and on the sides of your head. Now when massaging your scalp, you're not supposed to use your nail, you're supposed to use your actual fingertips, but if you have long nails, that's kind of hard to do. So now you're preserving your nails by using this brush instead. Now if you just did the big chop or you have a TWA and you're tired of waiting for your hair to grow, this will definitely create some blood stimulation, which will then create hair growth faster. After a couple of minutes, all you do is push the button to turn it off to save that battery, and then you can just keep in the shower for next time. So there you go, that is how I use my new little scalp brush. I will be adding this to my everyday washing routine, especially because I'm really excited to see how much my hair will grow from using the scalp massager because as you can see, if you do follow my channel, my hair has grown since my initial haircut. I'm going to be posting some length check videos for you guys, but I really want to see what's going to happen now that I'm massaging and getting all my scalp stimulated on the daily or whenever my wash day is. But before you go, let me tell you how you can get one of these scalp massagers. If you are dealing with dandruff or you want longer hair, you might want to give this baby a try. So you can go to vanityplanet.com. When you go there, you're going to see that it's $40. I know it's a little much, but don't worry. I got you. I'm going to give you guys a 50% coupon code. Yes. So instead of it being $40, it's only going to be $20, which is much better. If you like this video, please give it a thumbs up and please remember to subscribe. I post new videos every Sunday and speaking of dandruff, I'm going to do an apple cider vinegar rinse, which is something that really helps clean that scalp and mix with this guy. I'm going to have the cleanest scalp in the world. So if you want to see that video, please remember to subscribe because that video will be coming soon. Well, I will see you guys next time. Thank you for watching Bianca Renee today and happy scalp massaging.


Now let us see the disclosure requirement of IES-7, meaning what we are supposed to disclose in these statements. Sometimes we have to give the details in the statement itself and sometimes we give in the notes to the effect. The separate disclosure of cash flow statement present represent the increase in operating capacity and cash flow that is required to maintain operating capacity is useful enabling the user to determine whether the enterprise is investing adequately in the maintenance of its operating capacity. As I said that is a very important statement, it shows a lot clear cut whether the company is progressing or not. As I said in the beginning that operating cash flow from operation it must be positive, at least you should generate enough cash to pay off your current assets, current liabilities and your expenses too. Similarly, you look into the investing activity, you should not just keep selling your assets, it means you are closing down your business, you must see that there is some improvement in your capacity by adding more non-current assets as well. Certain additional information is relevant to the user of financial statement in gaining an insight into the liquidity or solvency of the entity. Now liquidity in the sense that the operating cash flow from operating activity should be enough, it means that you are capable of paying off your current liabilities, current expenses and solvency means that you can continue business, you are not going to close down your business because if you adding your non-current assets and you are also adding some more money into the business, so that means you are a solvent when you are not going to be bankrupt soon, so it looks that the company is solvent, they want to see through the statement that the company is solvent. Another important thing is un-drawn borrowing facilities, you know sometime we arrange with the bank credit line, credit line means simply that bank allow us to draw so much money during a particular period, let us say there is given you 100,000 credit line, you have used let us say about 50% of it, so the 50% is still available, so if there is something like that, so we must mention it so that people know that currently they still have money in the bank which they can draw, though they have not drawn yet, but they can draw because this is un-drawn and it is allowed by the bank that you can draw, they may be available to future operating activities and to settle capital commitments. Financial success is dependent not only a company ability to generate revenue and earnings, but also cash flow. As I said earlier, we are making profits and when we are making profits we are doing some adjustment here and there, in fact many companies do manipulation in earning of profits, let us say talk valuation, depreciation change and so on, capital expenditure, revenue expenditure change, so they can change profits, but so far cash flow is concerned, it is highly impossible that you can play with it, there you have to be very clear that how much cash is available and how much cash you paid and how much cash you received, but also cash flow, quality of earnings supported by the cash flow from operation, in fact we used to call quality earning, what is quality earning are profits which are supported by the cash flow from operation and that is the most important thing nowadays, mostly companies are having problem to pay off their suppliers to their employees because their operation is not generating any further cash flow or enough cash flow to pay off their current liabilities, which are very very very very important, if you want to survive make sure that you have available funds to pay off your current liabilities. The current commitments you have to and that is the important thing and that's what basically in disclosure people want to see whether the company is really really having funds to pay off your liability. Thank you very much.


I'm Zeke and welcome to the dream green show in this episode I'm bringing you guys the top for Monthly dividend stocks that you should probably add to your portfolio today, especially in the month of October guys But these four dividend stocks can make you Passive income every single month because they pay out their dividends every single month So you guys can be able to pay off your bills pay off your car note with your passive income by doing Absolutely nothing in the form of dividends and these four companies down bringing you guys today and this video has a very high Dividend you and they pay out every single month You could take the compound interest effect and reinvest it back into these companies to make even more year after year Like I'm gonna show you in this video or you can start to pay off a couple of your bills with your passive Income in the form of dividends guys, but before we go on to these four dividends Make sure that you guys go down hit the subscribe button hit the thumbs up button and most importantly hit that notification bill by hitting that Notification bill that helps out this channel more than you can even imagine if you want to support this channel Hit that notification bill, but before we dive into this video This video is bought to you by Moomoo sign up now by clicking the link down in the description Deposit $100 and you will see a free stock of lucid that is an electric vehicle company You're guaranteed that stop if you click that link down in the description Also, there's a link in the description to weeble sign them down with weeble deposit $100 and you receive two free stocks valued up to $1,750 with those two free stocks You could keep them inside the platform and use it or you can sell those two free stocks and withdraw all of your money It's really free money guys do not pass up on free money, but enough talking Let's go ahead and dive straight into this video Here we are on my Robin Hood account. I'm sending at $72,193 and 51 cents The four dividends that we're gonna go over in this video is EPR properties. That's a real estate read Realty income that is known as the monthly dividend stock Stag whoo, let me tell you guys about stag. You're gonna see in this video and then Pba pipeline. Alright, so let's go over the first one, which is EPR All right EPR properties so EPR properties they have a dividend yield of point 144% Robin Hood is not so accurate, but they are a 3.9 billion dollar company and over the last year They're up 104% after taking a big dip from the pandemic They still have not fully recovered up to their $77 price point and one thing about EPR is that their real estate read real estate reads are required to pay back their investors 90% of their taxable income in the form of dividends, which is right. They usually have pretty sweet dividends So EPR they specialize in only experimental real estate such as on movie theaters like AMC theaters ski resorts and other gaming facilities But as you guys know AMC Ski resorts and other gaming places all got shut down from the pandemic But as the pandemic started to recover you guys could see EPR price start to recover and during the pandemic They did halt their dividends that cut off their dividends Because they was not bringing in any source of income from the movie theaters the ski resorts are the gaming facilities But as the world started to open back up, um, they started to recover and that did bring back their dividends on july 2021 so they brought back their dividends, which is it yields now over six percent So now they're back to a six percent dividend yield company and it looked like we could still be getting them on sale And this and this is um EPR properties So this is one to definitely have on your radar Right now they're 52 dollars You could get them all the way back up to 80 dollar ish if they do fully recover As the economy starts to open back up as people start to go back to the movie theaters You could see um EPR start to recover back to their original state Um, the next one is ticker symbol realty income. This is known as The monthly paying dividend stock over the last year. They're up four percent Um, they have a dividend yield of four point one nine percent and they are a 26.17 billion dollar company now Now realty income is compelling investment. Uh, it is a portfolio of strong Up clientele including wallmark dollar general and as these tenants, um should continue to do well as long as wallmark dollar general Is doing pretty good Then you're going to consistently get your dividend payments from the monthly paying dividend stock So ticker symbol realty income is also a real estate read and this is one that I actually have inside of my portfolio I've been getting dividend payments from them for quite a time now And this is one that you guys should probably also have on your watch list to add to your portfolio And that is ticker symbol realty income. Now the third one is stag. Let's go to stag right quick Now stag man. Listen when I when I do the analysis at the end of this video keep an eye out on stag Now stag over the last year is up 22 percent. They have a dividend yield of 3.57 percent And there's 6.7 two billion dollar company now stag What's notable about them is that 40 percent of stag industrial portfolio handles e-commerce activities with amazon So yes, they work with amazon, um as a e retailer Which drives the man for the end for the industrial space. It has rented out as uh at healthy rates So stag owns the buildings that amazon is there all of their facilities that drop off facilities and They own that real estate land That amazon is using that um off of and it's 40 percent of stag portfolio So as long as amazon is doing good as long as amazon is still expanding stag is going to span And they have been killing it guys you will you could have made so much money from stag um over the last five years up 82 percent And you would have made even more in the form of dividends passive income by doing absolutely nothing So you want to invest into these real estate reeds that have great companies inside of their portfolio that they're leasing out their land to Like stag fourth one is pba. So let's pull that up right quick p a Um, this is a pipe non company that have a dividend yield of 6.07 percent A 18 billion dollar company and over the last year that up 44 percent and over the last five years They still have not recovered from the un-pandemic, but they still are up 8 percent over the last five years Pre-pandemic that was up 40 to 40 dollars and now they're 32 dollars and 90 cents All right now unlike the other ones. Uh, this is not a real estate reed. This is a pipeline company It is a canadian company specialized in transportation and storage infrastructures for the oil and gas sector majority of its income is from fee based contracts Which explains why the company can not only pay but also increase dividends every year for the past Two decades now that's very important to find a monthly paying dividend stock that is also increasing their dividend payments every single year and they have been increasing their um Dividends every single year for the last 20 years guys So let's go ahead and dive and and compare these four dividend stocks to each other To see which one if you had to narrow it down to one or you had to narrow it down to Which two are you looking at to add to your portfolio? So we're going to look at previous Um growth to try to analyze future growth to see which companies should we divide? Our percentage of investments into all right here. We are on the portfolio visualizer Let's say that we started to invest into each of these companies back in 2012 Um, I think that's when the last company the first year that they have with public was 2012 So we have to do it from then and let's say we started off with a thousand dollars and we reinvested um Let's say a thousand dollars Every single month. So 250 dollars a week we invest into the stock market Um and just for inflation and we invest a thousand dollars every single month. Um, no rebalancing Um reinvest dividends. Yes display income Yes And here we go tick assemble the first one's going to be Realty income the next one is going to be EPR and the last one is going to be stag stag And there we go. Let's rename these portfolio one is tick symbol for your tools e p e pr and portfolio three is stag stag in portfolio one a hundred percent one hundred percent and and 100% now when we're here analyze, this is us investing a thousand dollars back in 2012 And then a thousand dollars every single month to each of these companies here analyze portfolio And we're also reinvesting our dividends. Let's scroll down. Um on tick assemble. Oh, we'll have 200 thousand dollars after what 10 years EPR we'll have 152 thousand dollars in stag. We will have almost 300 thousand dollars in stag Now, let's go look at the dividend income. We will have now like I told you guys. Um, epr did cut their dividends in 2020 And they are just bringing it back. But let's take a look at stag right here We'll be bringing in an extra 9,300 every single year in just the form of dividends When we just was starting we was only bringing in 600 dollars a year from dividends and Tickets in but all you will be bringing in 7,000 and epr will be bringing in 3,581 dollars But before epr cut their dividends back in 2019 that was making that was making way more than stag um, in fact in 2019 that was making 9,598 dollars in the form of dividends Before they had to cut their dividends due to the pandemic. So let's replace, uh, epr with pba So let's scroll back up and change this to pba There we go and change it to pba Scroll down here analyze portfolio And there we go guys pba will have 173 thousand dollars. So it's around the same as um EPR and if we scroll all the way down here goes pba We're in 2020 seven thousand dollars from ticket summer o eight thousand dollars from pba And nine thousand dollars from stag. So overall stag is looking like the way to go. We'll have close to um 300 thousand dollars in the bank Just from 2012 to 2021 That's just nine years guys Um that we grew account with a thousand dollars every single week to 300 thousand dollars bringing in an extra 10 grand per year Increasing our salary by 10 grand by doing absolutely nothing in the form of dividends And there we go. You too. Let me know down below In the comments section, which company which dividend companies do you have in your portfolio that has been performing pretty well? um Which one of these four companies are you looking to add to your portfolio? If any at all or if there's another one that i missed that's even better than all of these Drop that down in the comment section down below if you guys would like to have um Access to every time I buy and sell stocks I'm going to leave a link in the comment section to my patreon You signed up for that and I'll um I post over there in my discord every time I buy and sell stocks So if you want access to that that would be down in the comment section Um before we go don't forget to pick up your two free stocks on webu And your one free stock of lucid by depositing 100 dollars. Um those links are down in the description But enough talking. I'm zeke bring you to dream green show and i'm out. Peace


Are you applying to NYU's medical school or have a laundry list of secondaries are coming in way too fast and you want to know kind of what that formula is do research and especially for the why us like why do you want to attend this medical school or that medical school um so stick around and I will share kind of what you should kind of look out for and then hopefully you can start recycling these as a template. Thank you for joining me on my channel for the best personal statement and secondaries coaching definitely hit subscribe and you won't miss a video. So with free tuition NYU's medical program the competition is stiff right and so we're going to get into what you can start kind of really learning about really to find out if they're a good fit for you if you're a good fit for them all that good stuff. Hi I'm Dr. Josie with write your acceptance I have over 10 years of experience working with students on their personal statements secondaries all the writing all that good stuff and here is kind of wanting to share some brief tidbits on how to research certain kind of pointers of a school to their specific info very quickly so let's get started. Step one learn how to research what they're asking for so one of last year's secondaries asked the admissions committee uses a holistic approach to evaluate a wide range of student qualities and life experiences that are complementary to demonstrated academic excellence strong interpersonal skills and leadership potential what unique qualities or experiences do you possess that would contribute specifically to the NYU School of Medicine community. This is your typical kind of why you plus NYU equals perfect match essay for me this is a nice balance of the diversity secondary and the why us secondary. So you want to show them kind of how you are a good fit but you also want to show them that you've done your homework basically beyond their brand name beyond their brand power to know that you would be a successful candidate there. So like I mentioned with full scholarship NYU Grossman is incredibly popular as you can imagine before the full scholarship they were incredibly popular it's about 9000 applicants in any given cycle about a thousand MMI's are conducted and about a hundred students are accepted into the program so so it's really really competitive. First up is really find out exactly what the mission statement is and start to it's not just enough to learn the mission statement find little phrases key phrases in the mission statement that you can kind of attach an experience or kind of work ethic an anecdote a basic story that you can kind of show them that you can demonstrate that quality. So their mission statement is we strive to enroll a diverse group of academically talented students with their personal attributes endeavors and accomplishments to succeed as future leaders and scholars of medicine. Our ultimate goal is to enroll a student body with a collective desire to improve the health of all segments of our society through outstanding patient care research and education. So those three right you want to kind of see where you fit in from your kind of extensive academic and social experiences already whether it's character traits personal kind of attributes endeavors what you've overcome accomplishments what you can boast and maybe it's a combination of two of those are all three you want to kind of show your commitment to the trifecta of the patient care research and education. So step two is to find what your strongest and capitalize on that so if it's patient care you have ideally an emblematic story that is not represented in your personal statement already or memorable experiences in the activity section and you can kind of use that to anchor then kind of how important patient care or how important your philosophy that patient care is capitalize on diversity inclusion right be kind of authentic about it but you kind of want to you want to capitalize on that research some of the phrases that I loved from their website from the bench to the bedside to the community they have this kind of community-minded guiding compass for their research and that's very important so if you've done research that has short-term or immediate positive impact to the community that is something that you can connect with as well there are vast opportunities for research just especially if you are between year one and year two there are summer research opportunities there are concentrations that you can focus on so I'll link that below and you can pick one of those and really talk about that in the secondary how you've started working on that introduce yourself to that and how you would want to kind of deepen your contribution as an NYU medical student another interesting innovative department is a translational program from drug development to population health to health care delivery they're thinking about kind of public policy how medical care how access to care affects swaths of community and public health right and so that's interesting and a few medical school students and some of them kind of will say I've talked to them about this specific program and some of them will say kind of that they had one path academically or professionally that they thought that they were going to kind of you know become a doctor become family practice or something and then this kind of program opens up the opportunity to kind of think through different avenues of contribution professionally and intellectually and the program is sounds just incredible so some details treating patients in acute settings redesigning how parents learn to best give their kids medicine how to replicate in real world and disseminate information and findings so there are a few different kind of aspects of the program that's great there are selective courses available and even individual study from autism spectrum breast surgery to care of the child with chronic illnesses they're really kind of thinking about all different dimensions of care patient care education research and just you know an incredible program as you can imagine so you really want to hit very targeted research kind of questions for you for when you are writing that why us secondary this goes for most of your why us secondaries your kind of information will depend also on length how long the essay is that trifecta right patient care education research and really specifics on kind of name a course really specifics on kind of a research initiative or professor but then also think about reaching out through linkedin let's say to an alumni and kind of learn about their experience and you can write that in with permission but you can write that in and really show that you've kind of done your homework and due diligence to really see yourself successfully there beyond the brand power i hope you found this helpful please give us a like if you are writing your secondaries are going to start very very very soon definitely check out my guide in the description below and i will make a couple of these links as well on the in the description so you have that too um good luck and i'll see you soon


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