So next is William Arias and he's gonna talk about deploying the machine learning bots like a boss using CICD Will William Arias you work for GitLab is that correct? Hello. Yes. I work at GitLab. Yeah, perfect. So you're the expert No, so right. Where are you joining from by the way? I am I am from Colombia, but I live in Prague in Czech Republic. Oh, right So it's a good time zone for you now, huh? Yeah. Yeah, okay. Excellent. Okay, so please start sharing your screen and then you can take it away Okay. Hello everyone. So my name is William and today I want to share with you some of the learnings I had since I started like back in 2016 working with developing bots and I am a big fan of NLP and while they use cases of a chatbot and in this in this talk I want to introduce you to how you can step up your game using principles of continuous integration and continuous delivery using RASA the framework for chatbots and GitLab CICD So why why why I decided that I wanted to share these these learnings with you because When you start working on this as a hobbyist or as professional I have done both Usually what you do is that you start behaving like a one-person band so I was reviewing the agenda of the talks today and If you have been following as well, you can see that there are presentations that they are teaching you how to Create a Docker file how to deploy a model using docker how to serve it so you have to create an API Besides you have to use other tools for to create a model itself And at the end we start behaving more or less like this like like I don't know if you like the symptoms When I was doing that, I remember this guy because we are a one-person band.  There is a learning curve that might be frustrated. I was the other day Teaching assistant Yeah teaching assistant in some online course where the students They were able to create the model for a chatbot But then when they were asked to please deploy to AWS and show us give us an endpoint where we can connect a channel and use the bot Many of them they start struggling because that's not what you are supposed to necessarily be aware of You know the models, you know, how to try how to use different libraries to create the to classify intense to classify entities But not necessarily all the tooling that you are expected to more of less Don't have some some some some knowledge to be able to surf a model. So example Let's say you use tensorflow for something for To create some some sort of some classification problem to solve some classification problem So your prototype in Jupyter notebook and once you prototype in Jupyter notebook You you if you want to store and probably you will need a database So you need to know which ones should I use should I use something like a Sandra? For example possible my sequel and then as as as I have to say before Then if you start digging into this you will For sure you will find okay So I should deploy it as a container and then cure and it is and how do I deploy it? Should I create a virtual machine or should I go directly to the platform as a service or should I just use an API so for the service whatever and Next to serve to the other world. So all of these things They are more of what they call today the fully stock machine learning engineer or data scientist. I don't know and I Want to share with you What was the approach that I follow and how today if your purpose or if the challenge that you are facing is I Want to create? I don't know my own startup in which I will build chatbots for whatever business and You want to be fast and you want to deploy in a very very like close to a standard professional way, but also With iteration in mind and being fast. So I want to show you how I did it How am I doing it? And this is not like written in stone This can change and all these workflows you if you know the principles then you can adapt it to your own workflow So how is the how I started to to divide this this problem when I say? It's taking me too much to deploy a chatbot to production It works in my machine the typical one it works in a machine is very easy to run it in local host But I want to deploy it and and if you are doing this for yourself as a one-person band or for a company You will find these these challenges. So first I started thinking a bit like what they are calling these days Machine learning operations that this could be there a workflow of that This this talk is known as Israeli about ML ops, but it borrows some concepts from there So first you are aware that the model that you are creating Has that some some life cycle in which you have to go through all these steps that? These are the ones that we are we are expected to be knowledgeable in how can I ingest the data? How can I version it or label it and run the validation test training model fine-tuned high-pay parameters Analyzes reading all these learning curves and then deploy and then get feedback So this is the only the model But one of the things that I learned that is very important when you want to scale these solutions And when you are not only developing for yourself, but this even helps if it's for yourself Because when you move to the process view of what you are attempting to do the first person that will be grateful Three weeks later of a month later. It's yourself. You say oh, that's so good that I put it in this in this view Because now you understand all the steps and more or less how you can Split the responsibilities And I put it here that one of them is a dialogue contributor because one of the things I have found while you're working developing chatbots with Russell library or others is that you Might be the let's say expert. I don't like that word But you might be the most knowledgeable person in how to build it The both but you are not necessarily the subject matter expert of the topic that the boat is supposed to provide a service And in many cases the subject matter expert is a person that they are no developers or they are no They don't have any Computer science on foreign generating background, but they are the ones that they know what should be the training data that you feed to the boat They know what type of questions there the end users will will ask So in this way, you are so it can start enabling other type of profiles in how can I incorporate their Contributions to my process to create a better boat. So this is a process view that it contains many of the steps from the model life cycle view and What are the benefits of this when you when you do this first is a favor that you do to yourself But also you have a common understanding of this process for everyone So if next time there is an iteration that something should change now It's very easy for let's say some some new employee or for you one month later to Retake and say, okay, this is this is what I was doing here Is where I am and and when you use this process modeling as well You can identify bottlenecks or where the things that you are doing might be failing And also this enables you with some standard that will enable iteration So you can improve with the pass of time the performance of the chat and now like how does this looks so the components view Here This is the high level diagram of what I have architected that it works to a very decent level in which this this could be the Pilot or prototype, but very decent not not POC hackathon level very decent pilot that I will go Step by step and I will show you starting from from this part. So what it's in the in this part in the left The dialogues or Python code. This is your development environment This is where you have your by charm or this was to your sublime text. Whatever here is where you have the your code Someone in dialogues in the certain format for your boat So the only thing you do once you invest time learning principles of CI CD is that you work in your machine Once you are happy with your changes or with whatever you did in your local environment You do a git commit and get pushed to remote So what I am doing in my workflow is that I create Mega change or in this case for this example I am adding more dialogues to the boat so the boat knows knows more combinations and is able to have better conversations This push will automatically and from here everything is automatic Back in the day, let's say four years ago when I started before using this You have to use the command command line and know each one of the commands that for example The raza framework provides to do raza train raza cross validate or raza Test data all of these things. So here what it's what is happening is that once I commit the code Automatically using it love CI it will start. It will start some runners or Containers or that was called runner that each one of these Will run the steps that you usually will run manually So this is not nothing new for someone who is who has been working in traditional development for years But this is more tailored for people that maybe they come With a math background or they are breaking into machine learning and they would like to build boats This is not necessarily knowledge that they have at least for example I didn't have it four years ago when I started these these good practices of software delivery. So Now that I discovered that's why I said, oh, this is this makes my life easier. I want to share with you So these these these steps that are usually Executed manually they start running in different machines. So one one one runner is going to validate that the data that you push To to the repository. It's okay. The format is is there with the one that the boat requires Then that the the data is complete And it will train the model and it will test the model and by test the model here I'm is the concept of testing in machine learning this with you can you can either create a testing Test this data set that you will run against your model or you can do for example in this case of my demo I do cross validation With the data that I have available So assuming that each one Of these steps It's successful then the model gets created. So you have an artifact now And the the artifact is your model And if you are happy with the performance because when you test the model You will get some metrics of the performance of your model And if you are happy with that you say, okay So now I want to do a merge request and and I want to put my boat into the main branch And this will deploy and this will deploy to production or staging and preproduct And here this part of the paper tray. This is this is one of the the key key key steps In machine learning operations that I am borrowing and bringing into this into this pipeline of of serving tablets is that Whatever you do, whatever you you change you make In your dialogues or in your code this by running these pipelines. This will create a paper tray What does it mean? You will have a record of For example, this is snapshot of today the model that was created today What type of the training data it used? What was the code at that moment? So in other words, this is version control that is getting into a record That I post in a wiki and if someday you work in a company that they will get some audit And they have to show show me why your model Was executing these predictions so you can easily go to the history of commits and say look This model had this training data and these were the parameters and here is the code and here is the data that we used to trade So this is the paper tray that this is required in in in the enterprise And also if you are just playing this paper tray helps you to keep track of your experiments and have some sort of report in which you can Compare if you if whatever changes you were making was improving or deteriorating the performance of your model So once the model is ready, and I'm happy with everything and all the steps and the testing From the software engineering point of view and machine learning is successful and I'm happy with everyone everything What I do here is that using this uh raza framework. It provides api rest that you can deploy A model server the model server in Whatever you want in my case. I'm using it in world cloud and then you can use this api api rest api to put And make it active and once the model is is Is there Then it's it could be available To be tested by real users or or other people that they can serve as testers of your both of your dialects And but it doesn't finish there because until this point I could be Quite happy that the only thing I had to do was Let's update the knowledge base of my bot Let's just do git add git commit git push. It goes automatically through all of these steps I don't have to worry about putting manually Executing commands and checking performance metrics because I can build a logic that if it's above certain threshold It's okay But once you are there and the model is served In this model server and it's ready to take conversations It's very important to close the loop with some feedback and the way that I've been using this and I will show later is that I am using the same rest api that provides the raza framework to extract Record of dialogues or conversations that the bot has been having with real users So what what but you can do here is that when you expose it to the outer world and the bot is interacting with real people using different Ways to say hi or to express an intent you can bring this back to to to To your environment and some sort of data playground and here you can do what you like the most that is okay. Let's use pandas python libraries to analyze To to to the nlp in other words and from there you can extract insights to later Feed it back into the bot and retrain it and it's our continuities. What I say before This loop that enables interage iteration to improve the bot performance so more of less what I'm telling you is that You you could be a one person Band but you can also bring a conductor to your orchestra Someone or something in this case technology that will help you orchestrate all of these manual steps And at the end of the day by using these principles of continuous integration and delivery We'll step up your game creating bots. I'm very important Really, it will make your life easier. I am a testimony of that I used to to Before as I was saying with the the other With the other talks I I had sometimes when I wanted to make some change and the change was minimal like adding just one more sentence or changing it happened to us building a bot for this topic that Have it here Have us here online. That is When we were building a bot like two months ago for frequent ask questions about coronavirus One day we were the bot was supposed to answer No, don't use mask because mask should be used only by health professionals one day later. No, no The bot should reply. Yes. Yes use use create make your own mask and please use it So it was only one single change in one sentence of the bot and it will imply that you have to maybe jump into the Dokey rematch makes a change of many things here. The only thing you have to do is Just put it in your in your pie chart in your local environment update it give commit give push and this will take care of that so This is how in this case i'm in powerpoint keynote so everything works in keynote So I want to show you a video of how it could look like so This I will share with you also a link. This is public on youtube So here typical developer workflow. I'm just creating a branch in which I want to work on my changes So once I create the branch i'm using the I'm this is the raza format to To add intense or knowledge to the bot. I'm just adding two words Okay, I am I'm just adding two words here Get add get commit and and here after I I commit the changes and I will push I will push them here is where the where the magic starts because I'm pushing to the remote and in the remote which is good lap is where I have configured all this orchestration with my new newly hired conductor for my orchestra So typical typical let's say developer workflow This is great in a merge request that when I come here And I these started automatically once I did the push Automatically this is started to run this pipeline One of the steps are ensuring that when the bot is ready is because it's really ready to be deployed to the production And each one of these steps what they are doing is what I described in the diagram before Is testing that the format of the template that we need to feed the the training data to the bot is is correct It's testing It's creating the model And once that it's creating a model is testing the model So typical developer workflow with the good practices So here what I'm showing is that I'm going one runner by runner And these are the the different machines that are executing Automatically the steps that I that if I don't have this I will have to do manually in command line. So by using these runners I am orchestrating automatically all these stages Following good practices of development and here. This is how my my my workflow or pipeline Looks like this is what the the bot The what I did what I provoke with this good commit is that is as I mentioned before these are the stages That it for this branch, they will end up writing a report that the report is this is a state Is this what we show me that The different artifacts that were created like these ones Different artifacts that get created when I train the model such as I don't know a histogram showing the prediction confidence distribution Or a json file that is showing me also some some sort of report of how the bot Perform based on that but this json is pretty helpful. But it's not Nice, let's say for a business person that they just want to show me show me how it looks like in a nicer way So when I this is step that is called write reports, what it's doing is in same good lab is writing in the wiki The report of the experiment where you can out to generate this thing that you can later revisit Or or or keeping some track of the changes of your experiments of the or of the model that is in production So once I'm happy with everything I can merge The the changes to my bot and here when I start merging. This is a view of the raza raza model server in which as you can see that moment when I when I took this video The model that was active was a model of last sunday But here this was Wednesday. I'm running a pipeline that is merging the changes into the main Main branch that once this this pipeline will will will finish What it will show show show us here. It's about to to finish the deploy stage There right there. What is going on is that my my pipeline is Talking to the model server to raza server and it's saying I am ready the model went through all of the steps Please deploy Once this is successful as we can see there I will refresh this page and you can see that now the model is ready was automatically deployed and made active And from there I can use tools like the ones that raza offer to create a link to share this newly created bot With external people so they can test it and I can also leverage an approach of conversation Driven development because from here before Deploying before following these steps that I just followed and deploying to production You can have more feedback of how the bot is performing So as if you appreciate the the beauty of this you were working in python You made two or three changes your git commit git push and all of these things started automatically and to finish the to close the loop I want to show you the last part is that in this case. I am I am using the api from raza and I am bringing Okay, we have five minutes and I'm using the the api from from raza to bring some of the Dialogs of conversations that they both had so this bot was newly created only for this event So it doesn't have too much too many Too much data, but this can give you an idea that here the sky is a limit you can say, okay I want to filter by number of intents, but the the Confident highest confidence of the best intent or what is the type of token that people are using the most? Are they saying hello the way I thought or are they saying hello? I want these are they using to move the intent in one sentence And for example in this one I was just extracting the last word and this for example Could give me a glimpse that look if the people are saying i'm a bit mad or i'm quite furious It's probably the bot is not it's not Working in the way that I expect so to finish that I show you how it looks like and if you adopt these continuous integration and delivery Practices it will allow you to have an orchestra for yourself with some conductor That will help you to make your life easier if you scale these after a company this will increase communication and collaboration You can have a more reliable solution and at the end of the day is setting you up to grow more from there You can grow from the manual development to the pipelines that I just show you to another point where you can Think of fully automated processes like instead of using this what I was showing you an api To call the rasa api to bring the conversations. I could automate this job every day apm and run some preliminary scripts And yeah, so this is like the the next step if you want to know more I have some links here and I will make available this is started project that you can fork and from there you can see how I Orchestrated all of this use it using git lab and rasa from this project You can just copy change to your point it to your own server and it will be ready to To replicate what I just did or I just show you in this demo video So thank you. I think this is I have three minutes of questions Thank you very much, William. That was a very nice talk very interesting indeed. So we have one question The question is that what are the cons and pros of git lab? Cicd versus having a Jenkins server okay, well If you already know Jenkins, so what are the pros and cons cons the learning curve if like me you came to this Cicd without knowing Jenkins. So good lab is very easy to learn So that's one thing learning curve and one one one pro is that in git lab you have everything under the There's in a single app. You don't have to switch environment. For example here It is I have in one single view. I have the pipelines here I can define everything and what I define in my project that will be my pipeline Is automatically triggered and read by git lab here, for example so pros and cons pro If you don't if you if you are comfortable with learning this tool because it's very easy and everything is Pre integrator, uh, pre integrator and as I said will make your life easier So you don't have to know to think about okay, so I need to learn a new tool I need to learn Jenkins plus raza plus my development here The reason I like this a lot is because here is everything Everything is here under this single application and whatever I push to my to my to this repository It will trigger a pipeline in my In my git lab ci So that's what that's something I can tell you from a point of view of Git lab fun But also personal point of view if you already know Jenkins learning curve Okay, go for the things you already know because at the other day you just want to make your life easier and deliver faster Yeah Okay, thank you for that answer Um, there's there's a second question. I don't know whether we have time, but uh, is there a difference between git lab ci cd and github actions Well, yes, there are different products Uh, yes, there are there are differences that We can take it offline because I'm this is moving me into the conversation of competition that Uh I can I can I can in the in the room. Sorry in the room because all of this is is public for for for git lab We have a competition page that if you google Git lab versus github actions in google, this is public and you will find it there It's not like it's no Possible for me to talk. No, you can do it and it's so transparent that you can have it only if you search for yourself But it's a quite long topic So, okay, so let's take that maybe offline into the into the talk chat We posted the link on the on the talk chat in discord and and so you can then find the talk room for this So thank you very much areas for the very nice talk. Let me give you your applause. Thank you. Thank you


I should put my sunglasses on. All right. Hello, everyone. Thanks for coming out. We're going to talk about digital transformation and a blueprint for survival. So we'll offer some insight into how you can leverage DevOps and some of the processes around people, processes, tools, and technology to make that transformation over to digital transformation, a much easier process. We'll go and introduce each other, and then we'll get right into the content. Hi, everybody. Thanks for coming. I'm Scott Bills with EMC Global Services, and I lead up our application transformation practice. Hi, I'm Bart Driscoll. I lead up our DevOps practice within global services. And I'm Jeff Olson. I'm an offer development lead in our global services cloud portfolio group. So when we think of digital transformation, we heard a lot about digital transformation and how it applies really in day one of this OpenStack Summit. And it's really important that we understand fundamentally what is driving digital transformation. What is some of these new paradigm shifts that are causing organizations to really adopt these new methodologies, new agile processes, and these new agile technologies to really help transform them. And when you think of it, it really boils down to four main pillars, which is mobile, cloud, big data, and social. And by the way that we're always being connected today is really that iterative process, that instant feedback, and having that information at our tips that really helps drive a successful transformation. But really what we'll get into further on is that technology isn't just necessarily end-all, be-all to really transform yourself. Things like DevOps and transforming your existing application portfolio are really important to that process. So really when organizations think about, well, what do I need to do to be successful? And how can I go down this path to really digitally transform? Really their main focus is they want to spot new opportunities, and not only spot new opportunities, but be able to help predict them as much as possible. And it's all about delivering that personal experience. So we all sit here on our phones throughout the day, and we're getting instant feedback, whatever we're interacting with. But really, in order to get those results back, a successful organization really has to be able to innovate in that agile way. You think about the long processes, and I think they talked about 44 days or 42 days, and the key one note wouldn't be possible in this new age where we're pulling this data instantaneously, analyzing that data, and giving it back to the customer, which really drives that I want to operate in real time. And at the same time, it's really being able to demonstrate that transparency and be able to trust that your data is secure as you're interacting with it and getting it back in real time. So like I mentioned before, it's broken down really applications where they're at your fingertips. Companies like Tesla, I think they're the first organization or first company where you could pretty much pre-order a car online. It's pretty amazing. I think we all probably in here might have a nest in our homes. And it all starts really with that application. But when you write these applications and when you're interacting with these applications, it's the data that you're collecting. And the data is help driving what you're going to do with that information, how you're going to analyze that information, and how you're exactly going to pass it back to improve on whatever information you're getting back to your end users. And really, by creating this type of cycle or this type of flow of bringing in data from your end users and analyzing and creating new insights, you're really focusing on creating speed. And it's all about that iterative process and speed to help you do that. But of course, there's definitely a challenge with digital transformation. I don't know if Bart, you wanted to go ahead and jump on this one. Yeah, sure, no problem. So one of the things that we find when we're working with customers around digital transformation is really this lack of a holistic vision. There are typically three key parts to digital transformation. One is around the data, a second being around customers, and then a third being around those internal processes that ultimately help enable you to actualize wins in that customer and data side. So without having this vision, it's actually really difficult to start building the right solutions on the back end in order to be able to support digital transformation. That kind of walks into the identifying the use cases. If you don't really understand your customer, whether it's an internal or external customer, it makes it really difficult to provide the correct services and the correct level of interaction with those services to those end users. We find one of the other common problems is a burden of technical debt. Most large enterprises have been around for 20, 30 years. They've got applications that are equally that old. And as a result, there have been a lot of decisions made, great ones at the time, that are slowing down or impeding how quickly you can add change. Part of its inflexible architecture is part of its very complex dependencies. And some of it is just old platforms that just aren't designed for this kind of new digital world. One of the other things that we see with digital transformation is that it's a very pervasive change in the organization. This isn't something that's just IT or just marketing or the business. It really touches all aspects of the enterprise. And as a result, it makes it really difficult to coordinate, particularly when you're looking at 17 or 23 different stakeholders that are all required to help make decisions in this process. And that leads to the last one here around organizational inertia. Change is hard. And for some people, it's downright scary. So introducing these new concepts and these new ideas takes time. You need to create that space and allow people to build trust in these new operating models and these new tools as you're starting to move towards digital transformation. So really getting to the meat and potatoes. Really, the blueprint we've laid out is you can think of it broken down into four main categories, starting from bottom left to right. And it really starts with having an agile infrastructure. Having something like OpenStack as your underlying infrastructure resources that can scale is really going to be that beginning point that you want to make sure that when you're developing these new applications or using a platform like Cloud Foundry or Pivotal Cloud Foundry that you can really start leveraging that developer ecosystem. So we'll start with agile infrastructure and we'll get into that developer ecosystem and then get into, OK, well, once you have these tools and have these technologies up and running, it really comes down to, well, then what? Just because you have these technologies installed and running doesn't necessarily mean you actually know how to use them. And it's really where that people in process comes into play around changing your culture by leveraging things like DevOps. But I think in the reality of it is is that a lot of organizations have these applications or existing applications that they need to leverage. So some of these, I think they call it mode one and mode two applications, that they want to leverage. Not every organization can start net new or start in a green field environment. So we'll get into how we help customers transform existing applications and integrate into existing tool chain and processes and so on and so forth. So agile infrastructure. So like I mentioned before, you can think of it as that baseline or that fundamental environment that you need to have up and running in order to allow everything above the stack or the abstraction layer to take advantage of. And when you think of things like agile infrastructure, you really want to have it programmable, which is you want to treat that infrastructure as code. You want to limit the amount of manual processes that you can bring into it. And you want to templatize as much as you can so that it can scale out automatically. Definitely want to have it as multi-tenant and multi-services. So what I mean by multi-services is that you can think of things like Amazon Web Services, right? When you just log in, you're not getting just compute. You're getting compute networking and storage resources.  You're getting things like object storage. You're getting things like content distribution networks and so on and so forth. And these are all the different services that you want to leverage in an elastic-type way in order for you to take advantage of that underlying resource. And of course, it has to be economical, right? So commodity hardware, software-defined services, as well as leveraging open-source technologies is really going to help you understand where you're getting that value from. It doesn't make the most sense if you're spending a lot of money on some of these underlying infrastructures and you're kind of getting caught up in the procurement of resources as it moves through that purchase chain within that organization. And developer ecosystem. Sure. So sitting on top of that agile infrastructure is what we like to refer to as that developer ecosystem. And as you remember, I mentioned a little earlier, it's really all about knowing your customer. So developers really don't want to muck around in the storage and network layers of your data center. They would much prefer to be writing code, building new features, and getting those features out into production. So one of the things to consider as part of your digital transformation and as part of building out this set of services is understanding what it is developers need access to. Using a platform like Pivotal Cloud Foundry, you get a lot of really robust features out of the box around health monitors and container provisioning, as well as access to a bunch of frameworks that will actually enable developers to start writing code quicker. In the end, that's really what that developer ecosystem is all about. How can I provide my development and testing resources with the right tools and the right access to services like a database or a messaging layer without having to have them go and configure it? Basically it allows them to focus their attention on what they're truly interested in providing value. So kind of moving into the next phase, which is really talking about that cultural change through DevOps, I know it's already come up twice in this session, but during the keynote earlier, when they were talking about the company that made the big investment to improve their deployment cycle time and it went from 44 days down to 42 days. Everything that we've talked about so far is about implementing that tools, implementing those tools. If we're not thinking about how those tools are mapped to the process, the sets of processes that we use to develop and deploy code into production, then we're gonna have a lot of trouble with adoption and we're not gonna start to see the acceleration and throughput that we're really hoping to get through this transformation. So when we're talking about the cultural changes through DevOps, one of the key underlying tendencies automate everything.  Really anywhere where there's a repeatable task that's happening as part of your software development lifecycle or your release management process, automate it. But it's not just writing scripts, right? We want these scripts to be managed by policy. Most large enterprises have strong enterprise architecture in governance program in place. We wanna make sure that some of the important assets in IP from those systems are embedded into the tool chains that we're building as part of DevOps. It's not about just going fast, it's about going fast but having confidence that what we're deploying is gonna service the needs of our customer. The extensible platform, so I talked a little bit about this on the slide before. This is really all about that ecosystem, understanding that complex portfolios are gonna require multiple tools to do the same thing. I'll probably use Jenkins Maven for a Java build and I would use MSBuild for .NET. Both tools do the same thing, but if I were to use MSBuild on a Java application, not so good, right? So we wanna be able to have that flexibility to support multiple tools, recognizing that we're gonna have these complex portfolios. I think another key cultural change with respect to DevOps is this concept of transparency. For most large enterprises, the software development lifecycle and your release management process is a black box. Requirements kind of go in six months later, something comes out, you hope it works, it gets deployed to production, breaks a few things, everybody spends a long weekend fixing it and then you get it into production and people start using it, right? DevOps wants to kind of take the cover off that and really give you some transparency into how changes move through the process, how long each step takes, what's the success rate of each of these different steps so that you can start collecting data around where to best make investments moving forward with respect to implementing new tools and optimizing your processes. DevOps is really focused on value, so it's based on Lean, it's based on Agile, which have both been around in IT for a while, but the whole goal is, is how can we create value faster? It's not how can I write code faster? It's not how can I create an environment faster? It's how can I bring all of these disparate pieces together and create a working application in production that will create value for the enterprise as whole? And it does this by using highly collaborative and cross-functional teams. The goal isn't to make generalists across your entire enterprise, the goal really is how can I bring that expertise and that experience together to build a solution that's really gonna address the needs of the organization? So we do talk a lot about tooling with respect to DevOps and it is a really important piece because really without it, it's really difficult to accelerate. But one of the things that we wanna make sure that we're careful of is that when we're building and selecting tools is that we're creating tools that are gonna be able to work and integrate with each other. It's all about that API library. So I do wanna create a common workflow or pipeline that will manage change, whether it's an infrastructure change or an application change, and then I wanna be able to integrate tools into that pipeline to be able to accelerate that end-to-end flow. All right, so when we think about digital transformation, there's the pieces around tooling, culture, DevOps that we talked about, but one of the biggest challenges, a lot of our larger enterprise clients in particular face is what to do with the existing portfolio. And how do you leverage DevOps, microservices, continuous delivery release models to unlock value from the existing portfolio? So if you think about your typical enterprise, they'll have a whole set of legacy monolithic applications built on really high-cost, old platforms, which is a problem, but at the same time, there's a lot of IP that's been developed over the years that are in those applications that you want to unlock as well. So a big part of the challenge for digital transformation is taking a look at your portfolio and figuring out what do you wanna put into a transformed DevOps-type model. It seems relatively straightforward, but take a financial services, global financial services institution, for example, they're gonna have consumer apps, they're gonna have commercial apps, they're gonna have trading apps, they're gonna have core financial systems. Not all of those are applicable or appropriate for a DevOps-type model or will have the same value derived from continuous innovation and leveraging those types of tools and processes. So a critical first step is taking a look at the existing portfolio and figuring out where DevOps can really help you unlock value. And when you're talking about application portfolios and the thousands across both COTS and bespoke applications, that's typically a non-trivial task. And one of the first steps that we see organizations that are really aggressive about digital transformation doing is taking a look at that portfolio and figuring out where the value really exists from digital transformation. So if you take a look at new app development, of course you're gonna want to leverage DevOps and PAS and microservices to develop your applications in a new way, that's really a no-brainer, right? But the question on what you do with the existing portfolio tends to be a little bit more complex and involves a whole set of issues around the business importance, the business criticality of the app, how it's implemented, how it's deployed, the cost of the platform, strategic importance of the app going forward, the usage demographics, a whole set of factors that will lead you to take an application and say, you know what, it might make sense to actually modernize and rewrite this using a DevOps kind of transformed process. Others that may make more sense just to migrate, kind of lift and shift as is to cloud platform or infrastructure as a service environment. Others you want to retire, and some you may just want to keep as is, but maybe expose a little bit differently to other applications or leverage a data fabric to transform those applications in a little bit different way. But in any case, the key is to understand really what the sources of value are for transforming, understand where the value might be in your portfolio and then really think about what an appropriate attractive strategy is for transforming the existing portfolio as part of your broader digital transformation effort. So I guess really before kind of closing, we just wanted to share a case study that we've been working with a customer on. This is one of the, actually this is the largest global bank, they currently have got over 30,000 IT professionals working, seven different divisions supporting over 6,000 application development projects. And this customer has a problem. Despite their size and their success, they're realizing that their ability to generate revenue costs more than it does their competitors.  So the company has made a very significant investment in developing some new products and new customer channels in order to drive some new revenue, but at the same time, they're really taking a laser focus internally around operational efficiency. How can they start to drive down that net operating cost? So we started working with the bank in early 2015. And what we've been doing with them is first aligning a lot of their key stakeholders around what their development and delivery practices are. And taking a closer look at what some of the tools do with respect to infrastructure automation, continuous integration and continuous delivery. And where we've started is by building out a pilot, a pilot continuous delivery pipeline. And we're starting to build out a framework that's gonna integrate some of the infrastructure automation services that they're building as part of infrastructure provisioning and management work stream. And the whole goal here is to really embed the tools from both of these work streams together in an active development project. And part of the reason that we're trying to embed it in part of an active development project is so as this development project progress, we can start capturing some proof points around where these technologies are working, how we're embedding them with the teams, what some of the new practices, processes and methods are that we're developing. And we can begin to embed them in the global software delivery management program, which is a much larger top-down initiative to simplify operations and reduce risk at the bank. What we've been doing with them to date is providing coaching services, technical experts and some implementation services to really help build out that initial pilot and start training local internal champions that are gonna help radiate this solution as we move forward. Interestingly enough, the bank, like a lot of the customers that we work with, kind of had an early realization when we started doing our advisory service with them and that was that they really weren't good at doing software development. They wanna be more like a modern software development company, even though they're huge. And so what we've been able to do is kind of systematically work through some of those problems and create a framework for addressing them by both introducing infrastructure automation tools and practices and integrating those with some software development tools and practices. So pretty much wraps it up for today before you go. If you wanna learn more about what we're doing around the digital transformation space, definitely come visit us at the booth. Also, these two guys, not including myself, have some great blog posts on our EMC Global Services in Focus webpage. Highly suggest you take a look at it when you have time. They've write some great things around many of the topics that we've covered today, both around DevOps, around agile technologies, as well as transforming application portfolios. So what we'll do is we'll close it out here, we'll open up to questions, and I know we do have a raffle for an Echo, correct? Yeah, Amazon Echo. Amazon Echo. So we're going to- And we just have one. And we just have one. So does anyone have any questions for you? Do you have like some sort of upfront assessment process that you use, like kind of going in, like if the clients don't already know exactly what they wanna do, which is probably most of the cases, where you determine like which aspects of these transformation elements, how and where they apply, like some sort of a regular structure kind of assessment approach. So are you talking about from an infrastructure or from a DevOps perspective or kind of the whole big picture? Cause we do. Like is any of it, yeah, like where you start to determine the opportunities and the applications, how to come in and what to recommend and stuff. Sure, yeah. So really that type of service that those capabilities that you just mentioned is really how we try and help our customers. So the reality is our customers are learning this just as much as some of the vendors are. So we wanna help our customers through that entire journey, not just about selling them technology, it's not just about standing up that technology, but it's really helping advise them, what is the right strategy they need to be looking at to make that informed decision. So really we have a set of advisory services that range from on the infrastructure level, you know, things like OpenStack and PCF or CF all the way to kind of the DevOps side of things. So we'll work with the customer and really kind of gauge where they're at from a maturity perspective. And once we can gauge where they're at from a maturity perspective, whether we need to address it more at the infrastructure layer or certain technology at the infrastructure layer or further up the stack, we're gonna help that out or help the customer kind of see that journey through. And then we can take that all the way through, deploying that specific solution or product to even helping manage it if they don't have the skills or the cycles that do it themselves. Yeah, I think one thing I'd add to that is we do have some really kind of lightweight, early workshops up front that are fairly broad in scope that are really designed to help map out your current maturity as it relates to modern application development and digital transformation. We also have another one around IT, general IT transformation. And so both of those can kind of provide that baseline to make that determination on what's the best next step. Do we wanna focus more on DevOps? Do we wanna focus more on infrastructure automation, et cetera? Any other questions? Shook, floor is all yours. Oh, mine. All right. Who wants to pick? You wanna pick, I'll pick. Last three numbers, five, four, four. Five, four, four. Come on down. Oh, I read that backwards. Cool, there you go. Enjoy. All right, thanks a lot, everyone. Take care and enjoy the rest of your time here in Austin.


A Minnesota police officer has appeared in court on charges stemming from the shooting death of a black man during a traffic stop in a St. Paul suburb this summer. St. Anthony police officer Geronimo Yanez was released on his own recognizance after a brief hearing Friday. Yanez was charged this week with second-degree manslaughter in the July death of 32-year-old Philando Castile. Yanez is expected to enter a plea later. If you've enjoyed this segment of Lakeland News, please consider making a tax-deductible contribution to Lakeland Public Television.


The California Adult Education Digital Learning Guidance supports adult education programs in effective technology integration and provides strategies to build educator and system capacity focused on digital learning. Guidance Overview. This video provides an overview of the guidance and addresses the impact of digital learning and technology on adult education. Hello, I'm Dr. Carolyn Zachary and I am the Education Administrator and State Director for the California Department of Education overseeing the Adult Education Office. The guide goes into focusing on how to ensure accessibility using universal design for students in online instruction. It talks about edtech tools that can be used and it gives teachers a real primer in what they need for ensuring students have success in their online instruction. And it also gives administrators sort of a guideline for what they need to do to ensure that they have options for different types of instruction within their adult school. Adult educators are looking for a roadmap that will help them to continue what they have put into place over the last two years. This guide will help reinforce areas of strength that they have seen and they've been able to adapt. But the guide will also give them additional tools to ensure that they're meeting students' accessibility needs, that they are looking at other ways of instruction. Perhaps they're used to doing synchronous only and they're going to dive into that idea of doing something asynchronously. That's where I really think this guide will help those educators throughout the state of California to move beyond what they've been doing and to make it part of their normal practice of using technology and online instruction. Development of the guidance was made possible by the California Department of Education Adult Education Office through Workforce Innovation and Opportunity Act Title II funds. The videos were produced by the Outreach and Technical Assistance Network at Sacramento County Office of Education in partnership with the International Society for Technology and Education. To find more resources for implementing digital learning in adult education, please visit the Outreach and Technical Assistance Network website at otan.us.


Come back, savvy traders. My name is Faso and we are back rated to trade on this lovely Thursday. We're about two minutes after nine. So a couple of things are moving. Really nice little pop right here, M-I-N-M. I know some of you guys have been kind of enjoying it this morning.   At 745, stock started right around here. Look how beautiful this thing is. Gorgeous. Started around 380, stock already to 560. This is why you trade in pre-market.  I know some of you here in social media are still trying to figure out like, how do I get into these stocks?  And you got to get access to the right execution and you got to join the cyber group room. So if you're watching live on social media, just make sure on the top left hand corner, you got your phone, you could just scan it. I'm going to be doing a live event today. Make sure you ring the bell, give us a thumbs up and also subscribe to the channel. All right, so let's go through a couple of things that are moving because yesterday was actually a really nice day, shockingly compared to, you know, I thought the other day was good, but there was a lot of good stocks that are moving and want to kind of talk about them, what made a big move. So we had this LBPH, want to bring this up right here. So this stock got destroyed. Okay, it was a nice little mover. It was gapped up, but look at this stock. A little came back down, really nice short on that stock right there. That one, Coin, all of them had some, Coin had a nice little bounce. There we go. So Coin took a very, very big hit, got a little crush over here, went from like 185 down to 40, but we got a nice little bounce with that. With that, a lot of other stocks that were in the mining and also in the Bitcoin industry, Mara, something a little bit more, probably a little bit more reasonable price where some of you can go out there and trade, that stock had a good bounce from 20 to 24. I'm putting Mara back on the watch. Well, it's already here on my watch list on the right-hand side. That one did pretty well, Mara. Okay, Eli Lilly, I was talking about that stock too yesterday. Very expensive stock though. I know you can do an option play on it, but big fan of it just broke a 50, actually an all-time high. I was actually listening to some analysts on TV how much they love this stock right here. But you know what? You don't have to trade that many. You know, listen, you could buy 100 shares of 62,000, half that's like 32,000. You know, 10 shares is like 6,000, but nice little move that stock, 5.75 only to 6.20. Yeah, we do trade expensive stocks, but once again, I like the cheaper ones, but I'm gonna throw that out there anyway, because it was one on the watch list. Any XI, that one, once again, a lot, a lot cheaper. This one had a good move yesterday, $4 to $10. Beautiful move on that one. We had that one, a bunch of other stocks too that we had, a good short on RX, XRX, that thing got crushed, that one from 18 down to 15, and then Boyle, actually this one's doing pretty well. I'm almost at the point I might average up. I might average up on this trade and buy more, you know, I've been talking about it for about a couple, about a week already and moving out of the coin, because the coin stock right there, we had a great run on that one on the swing trade, but Boyle looked like it's coming back down right there. Pretty much does it. Nouveau's also moving up pretty well. I gotta add Nouveau, I'm probably screwed that up. It was a high there, 506. I got out there a little early. I was getting a little nervous because I was a little bit more fan of Lily, Lily, so that's the reason why. But that's what happened yesterday, okay? That's what happened yesterday. That's what happened on the swing trades. Let's focus on today. So what do we got going on today? Most importantly, you know, we have the event going on. We have our 12 o'clock event that's going on today. If you haven't registered, I'm just gonna put that on social media really quick. There you go right there. You got the link that is posted up there. We got a lot of events going on. Listen, let me tell everyone, I know your students here are getting ready. You're in classes, Josh has classes today. He's gonna be focusing on discussing, on preparing behind trading and the market close. We're gonna talk a little bit about that.  If you knew, you gotta learn, you gotta learn. This is what, we're traders.  I don't care, we're traders. Do I care that this company's got a drug that maybe hurt somebody? We're traders. We're gonna trade it. That's what we're doing here. There's a lot of stocks out there that are doing well. You gotta learn and it starts with today. So if you haven't registered already, damn, you better do it because I don't know what you're waiting for. Now let's go through this watch list and see what's going on because there are a lot of stocks that are making some nice moves. So let me open up my default to get my level three up and we have that here set up right here and let me just squeeze this up for you so you guys can see a little bit better. There we go. Here we go. All right, so we got our buyers, got our sellers to see what's going on out there in the market. I got level level four of you on the right. If you're watching on the other channel, you can probably see it on my social media.  But let's go through to watch to see what's going on. So you got this stock, the MINM. Let me just fix the filters out here. Issues with this right here right now is that it's got a lot of 100, it's got a lot of 10s. Not a lot of big iceberg orders yet. So I wanna be a little careful on that stock right there but it's cheap, it's inexpensive, it's got a good move. It's up about 183%, what a coincidence. Not like we never seen that before here in the morning, right?   Let me tell you, there's nothing more that would tick me off is that you did good in pre-market, you give it back when the market opens. Forget it, just take the day off. Don't worry about it, tomorrow's another day. We always find these 100% movers. Here's another one that's going up right now. OMGIA, and let me see if I got going over here. There was a big iceberg order out there for 114,000 shares. All right, let me bring it up over here. But he canceled his order, okay? He canceled his order, OMGA. I'm looking at level four and I hop over here at level three. So he was out there at 490 and I'm gonna probably fix the filters here because I wanna see nothing less than 500 shares. So he pulled his order, he's not there anymore. There's a seller out there for 10,000. You can see it at 540, I see him out there too. But it's got a nice little push. You know what? 12 million shares already trading pre-market. I'm almost not even open. This one's not bad and I love the price. Got nice price levels, got good movement, second biggest percentage gainer. It's actually the biggest volume leader in the market too. So we'll keep that one on the list. So we got Jeff here too. This one moved up a little bit nicely here. There was a big order. There was a big order, he just pulled it, JFBR and I'll bring it over here for some of you could see it here. So here's level four, you could see it right there. He just pulled his order right there. How big was that order? About 12,000. So we're watching live data on the left. We're watching previous data that was out there on the right. So for some of you watching social media, that's what we got going on right there. But that one was a pretty good stock right there. We'll keep that on the watch list right there. Like the volume, like the movement, two million shares. Probably put it on the B list, but it looks like it's doing pretty well here. I like it. And it's Thursday, Thursday's hump day. So I always rather put a lot more stocks on the A list than the B list when it comes down to it. All right, we're at number four. All right, we're down to 25%. Really, I don't like the trend over here on the pre-market. We're gonna scratch that. SMFL, two million shares, pretty cheap here, up 23%. SMFL, let's see what we got going on there. We got about 15,000 shares. So right now at 218 kind of makes sense. You could see that was the higher around 8 a.m. You can see where the order's good. Nice iceberg orders, nice support resistance levels. I see it by tape reading. So that one I like. All right, so we're focusing on, remember we're looking for big iceberg orders, big, big block orders because that makes support resistance levels fellow traders. Remember that's why we hear, we hear the follow of the money, right? That's why we do this. This one's a little bit cheaper. It doesn't look like it's going anywhere, 14%. All right, we'll pass 10. This stock is getting crushed. Okay, I saw this earlier this morning. I put it in the chat room. I don't know if it's on your short list. M-B-L-Y, but let me tell you, they are getting destroyed. Not even getting destroyed from yesterday because it was down from the highs from yesterday, took a big hit. I'll even show it to you from here. You can see it, it started trending down a little bit but really took a crash today. And it looks like it's still going lower. I don't know what the news is. We'll post it in the room, but it is not looking good for M-B-L-Y. Actually, I got a trivia question to share everybody. Okay, the stock is down 31%. It's down $12. It's at $27. It's down a lot. How much lower can this stock go? How much lower could it go? Oh, they updated their fourth quarter earnings, guidance for 223, thanks a lot, Rich. That's right, congratulations. And you know what? People on social media didn't say that, okay? I don't know why I don't want to. You two didn't know that answer or whatever it is, but the right answer is zero. Don't ever forget that. And that could happen. Remember, we see stocks here. We're like, my God, it was like $300 last, the beginning of this year. It's at a dollar, okay? Carl, you got it, Gary. Thank you very much. We got somebody in the room on YouTube that had the right answer. All right, anyway, can we get a dead cap bounce? Earnings really, sometimes you do. Pharmaceutical stocks, we don't. We'll put it on the watch list, M-B-L-Y. All right, so we got that one. We're gonna see how that opens up. Here's just down 17%, too cheap, tap-oh. All right, hop over here in New York. What we got going on over here, 18%, 700,000 shares. I don't really like the trend of the stock right here. Not really a good pre-market. I did see this, though, QS. I did see this one. And okay, all right, there's a problem with QS. QS got a ladder effect. And it was a lot of people talking about it and seeing that to say, hey, it stocks up nice, cheap stock and expensive, good spread. I'm seeing a ladder effect on level four. And we know, we cover that in phase three. We're gonna talk about that next week. The ladder effect. And I'll show you what I'm seeing over here. See you guys, fellow traders. See what I'm talking about? Ladder effect. Started about eight o'clock this morning. Someone's pushing it down. There is a little bit of buyer over here at 9.60, but a little tight, okay? So, but we'll, listen, we'll put on the B list. Cause sometimes somebody might remember, program trading kicks in right at the open. And then obviously Boyle, okay, that was in a morning watch list. For some of you logged in early this morning. And if you're at an alert service, so Boyle's looking pretty good on a swing trade. You can see it's already up there. If Boyle is up, that means KOLD is down. Remember it's the opposite, okay? KLD, this stock in November was a $45 stock. It ran all the way up to almost 120. Hell of a good move. Hell of a good move. That was a good, good run up. But very, very volatile. One's a short, one's a long on gas, okay? You know I'm a fan of gas.  Do I really care? Oh, actually I do care cause I love my gas stove, okay? But you hear about it and they're trying to do everything they can to regulate it. And as a trader, all we do is we just trade it, okay? So if you hear they win, you hear they lose, whatever it may be, at the end of the day, those stocks are going to affect it. And we're traders. That's all that matters. I want to trade that stock. So remember, don't tip of the day. You don't take anything personal, all right? Don't take anything personal. Save that after the side of the group room, all right? Remember, no politics here. I haven't said that in a while, right, Josh? No politics. All right, let's get ready for the market open.  So once again, don't forget, market's opening up. We got about 15 minutes. We're gonna get ready for the room. If you're watching on social media, like I said, take your phone. If you're watching the recording, just scan the QR code. You can get in the room.  Ring that bell and subscribe to us. And once again, I got a bunch of new videos that came out also out there. I posted yesterday. Go out there and watch them. Make sure you like them. Make sure you leave a comment and please go out there and share them. And let's get ready. If you're new here to cyber trading, remember, just look, listen, and learn. And traders, like we always say, you see something, you say something, right? So that's the reason why we're here. We here to trade together and make money together. Good luck, everyone. Happy trading. I'll see you in about 15 minutes with the market open.


I feel very proud to be an Indian and I'm sure lot of people feel, but corruption bothers me and I'm sure you also spoke about it. How… do you think spirituality can help get rid of corruption to some extent? So let's understand this corruption because it's a… it's a very important thing that everybody understands this properly in its right perspective rather than reacting against a bunch of people who are in an advantageous position. Okay? Why I want you to understand this is because for the first time in the history of independent India, the sixty-four years, that means two generations of people, they have at least fifty to sixty percent of them have had such a bad deal. Today you and me will talk all this and go home and eat well. There's a whole bunch of people, almost four hundred million people who cannot do that. So if we handle the next five to ten years' right, we can change that. It's a tremendous possibility which is on our threshold. There's an economic possibility sitting on the threshold. If we conduct this right, we can change their lives. Those people who have not eaten properly, those children who are malnourished, which have the highest level of malnourishment, those who are not educated, those who don't have opportunities, those who are in that horrible social and economic pit, their lives can change in the next five to ten years if we conduct our act right. Every Indian should understand this. It is not just about economy means stock market. It is about hungry people who will have food on their plate. Economy does not mean stock market, economy does not mean foreign cars coming into India, economy does not mean you wear better clothes or this and that. Improving economy means there will be no hungry children in the country, which is something all of us should do something about. And that possibility, that possibility is being jeopardized. So this possibility is being jeopardized by a handful of people or it is wrong to say it's a handful of people, it's a nation full of corruption. Because how many people in Mumbai streets, if there is no policemen will start at the red… stop at the red light, I think only ten percent will stop. So these ninety percent are corrupt people. If they make… if you make them the chief ministers and prime ministers, you know what they will do. So instead of just calling it by one bad word called corruption, we need to understand we as a society are trying to move from a feudalistic way of managing our lives to a democratic way. The democratic way has still not sunk into us. Democracy will not happen with an active sense of education as to what is democracy, what is the power of democracy, what it means, what is the responsibility of living in a democratic society. This has not been done. We just took democracy from the British and we think if they just put their vote and get their fingers dirty once in five years, everything is settled. No, we have not educated people. We are still a feudalistic society acting to be democratic.


It comes with a microphone, which tracks for your science and frequency, and there's a sensor on the pillow that tracks where your head is, mostly on the pillow. And right now I'm using the app because it's a test run, and I'll show you right now. So, I just inflated it, you can put your head back right out, yeah? So, as you're, you know how, when you're slipping straight up, your airway's, right, elevating the neck, right? So, what our device does is it's slowly tilts your head, and it does not, it does it very slowly, so it does not disturb your sleep. Yeah. It tilts your head to the side, and you will not put it on the refiner, but on a flat bed. It's going to make your body want to fall to your head. Okay, so it'll make you roll over? It'll make you roll over, and you know how, when you're on the side, your breathing is good. Yeah. So, it goes to your head. Okay. Yeah. Okay. And then, what's great about our device is there's no, like, there's no electronic inside the pillow, like other devices. Yeah. You can put a big machine on your face, and you know how many people, they're concerned about the EMF? EMF, right. So, it's low EMF? Yeah, there's no EMF. There's no EMF. Okay. Yeah, there's no electronic at all. It's just air bubbles inside. Okay. It's connected to the pump, it's just connected to the machine here. Okay. So, now it's at 100%. You should start feeling, you should start feeling that your head is tilted to the side. Yeah? Yeah, it's wanting to roll. Yeah, it's making me want to roll, yeah. And the great thing about this is we also have an app that comes with it, tracks your sleep daily, monthly, and weekly. Okay. And it will record up to 250 of your sleeping patterns. Oh, wow. And then, after it analyzes 250 of your sleeping patterns, it will adjust the settings to your sleep. Because you know how some people, they have like more sensitive sleep, or a little movement will make them want to turn. Yeah. Some people, there are more heavy sleepers, or they need more movement in order to turn their robot on. Right. You can set that all in settings, or have the machine do it itself. After checking your analyzing sleep, for now it should be degrading. Yep, I'm starting to, yep, I can feel like I can roll more. Roll my head more this way. Yeah. And so, now this is the motion pillow one. The great thing about the motion pillow two is most people are concerned about having this big box by the bedside. Yeah. You need to have this plugged in. So the motion pillow two changes top side into a charger, a wireless charger. Oh, wow. Yeah, so many people have chargers on their other bedside table anyway. Right. Yeah. So motion pillow two, you just put your phone on top and it's going to charge it from full. Very cool. Yeah. Yeah. So you're using it on Amazon right now? It's on Amazon for $370. Okay. And if you are interested in our motion pillow two, you want to complete the wireless charger. Right now we have a promotion from Indiegogo that's 50% off. Okay. The original price is around $400. So you pay about $200. Oh, okay. For the first generation. Oh, wow, okay. It's only for the first hundred million.


The researchers found that a subset of neurons in a spiking network could be trained to mimic the activity of neurons in the motor cortex during a decision-making task. This was achieved by creating strong synaptic connections between these neurons, regardless of whether they were part of a trained or untrained group. These strong synapses allowed for the spread of task-related activity throughout the network, even in untrained neurons. The researchers also used optogenetics to observe how this spread of activity affected the network's dynamics. They found that the motor cortex was strongly coupled, suggesting that this mechanism may apply to other cortical networks as well. This article was authored by Christopher M. Kim, Arsene Finkelstein, Carson Seachow, and others.


Bill Cosby was all smiles but offered no words after he was freed from prison and returned home.  The court ruled that he never should have faced charges after striking a non-proscussion deal with a previous district attorney more than 15 years ago. The Pennsylvania Supreme Court issued its split decision after Cosby has served more than two years of a three to ten year sentence following his 2018 conviction. How could a man who was being watched by the FBI every day be raping and drugging women in the sixties or seventies especially a black man who from all walks of life as I said earlier James Brown made a song it's a man's world that would be nothing without a woman and Mrs. Cosby was that woman 57 years the queen the matriarch of the Cosby family who fought for his vindication who said he would be vindicated and today on this hot day this is a hot verdict for us that we will forever cherish because we got one of the greatest or the greatest entertainer alive today Mr. Bill Cosby this great American citizen this American treasured icon. Hello hope you enjoyed the news please do subscribe to our YouTube channel and don't forget to hit the notification button so you get notified about fresh news updates.


Have you ever wondered why some people seem to attract success like a magnet, while others can't catch a break? It's a puzzling question, isn't it? Some believe the answer lies in the law of attraction, a concept suggesting that our thoughts and feelings magnetize certain experiences into our lives. It's as if our minds are powerful magnets, drawing in what we focus on, be it success, happiness, or even failure. Today we delve into the law of attraction, its origins and how it is understood in our modern world. The law of attraction isn't a new age concept, it has roots that trace back thousands of years. Let's take a journey through time to discover how this powerful principle came to be. In the ancient civilizations of Egypt and Greece the concept of like attracts like was a part of daily life. The Egyptians believed in Hecca, a magical force that could be manipulated by thought and emotion. The Greeks on the other hand had a word for it, Eros, the compelling force of attraction that they believed was at the heart of creation. Fast forward to the Renaissance, a period of intellectual and artistic rebirth. The law of attraction found a home in the philosophy of Hermeticism, a spiritual, philosophical, and magical tradition that grew out of writings attributed to Hermes Trismegistus. These works known as the Hermetic Corpus introduced the idea of as above so below, implying that our thoughts can influence the physical world. Next we turn to the 19th century, a time of great change and expansion of ideas. Here the law of attraction was nurtured by the transcendentalist movement. Thinkers like Ralph Waldo Emerson and Henry David Thoreau championed the power of the individual mind and the interconnectedness of all things. They believed that our thoughts could shape our reality and influence the course of our lives. In the same century, the new thought movement emerged. Further developing and formalizing the law of attraction. Figures like Phineas Quimby and Emma Curtis Hopkins expanded on the idea that positive or negative thoughts bring positive or negative experiences into a person's life. Their teachings form the foundation of many contemporary self-help and personal development philosophies. So you see, the law of attraction isn't a fleeting trend or a modern invention. It's a time-tested principle that's been woven into the fabric of human thought for millennia. Though it may seem like a modern idea, the law of attraction has been influencing thinkers and philosophers for centuries. The law of attraction found its footing during the new thought movement in the 19th century. This was a time when spiritual exploration was at its peak and people were keen to understand the power of the mind over the body. The new thought movement was an influential spiritual movement that focused on the power of positive thinking and the idea that our thoughts shape our reality. It took the philosophical musings of the law of attraction and turned them into a widely accepted spiritual practice. This movement was responsible for popularizing the law of attraction, making it more than just a philosophical concept, but a guiding principle for many. A key figure in the new thought movement was Phineas Quimby. A clockmaker by trade, Quimby suffered from tuberculosis and sought various treatments. His journey led him to discover the power of the mind in healing the body, which he referred to as the science of health. He believed that negative thoughts manifest as physical ailments, while positive thoughts can heal. His teachings greatly influenced the new thought movement and the understanding of the law of attraction. During this time several books were published that propagated these ideas. One such book, The Science of Getting Rich by Wallace D. Waddles, played a significant role in spreading the message of the law of attraction. Waddles proposed that by focusing on positive or prosperous thoughts, one could attract wealth. This book is considered a classic in the new thought canon, and continues to inspire countless people today. The new thought movement also saw the birth of several organizations dedicated to the study and practice of these ideas. Churches and societies were formed, providing a platform for the exchange of thoughts and philosophies related to the law of attraction and other new thought principles. The new thought movement was instrumental in shaping the way we understand the law of attraction today. It introduced these concepts to the general public, and made them accessible to everyone. The new thought movement brought the law of attraction to the forefront of socio-spiritual thought. Fast forward to today, and the law of attraction is a household term thanks to figures like Rhonda Byrne and her book, The Secret. The law of attraction, in its most modern understanding, is often presented as a method for manifesting one's desires. It's about focusing your thoughts and emotions on what you want to bring into your life, with the belief that like attracts like. If you focus on positivity, you'll attract positive experiences. Conversely, if you dwell on negativity, you'll attract negative outcomes. This principle has permeated pop culture and self-help literature, spawning countless books, seminars, and online courses. It's been discussed on talk shows, featured in movies, and analyzed in news articles. Celebrities from Oprah Winfrey to Jim Carrey have openly shared their experiences with using the law of attraction to achieve success. Yet, it's not just about material wealth or professional achievements. Many use the law of attraction to improve their health, relationships, and overall well-being. It's about creating a life that aligns with one's deepest desires and highest values, not just achieving external markers of success. However, the law of attraction today is not without its critics. Some argue that it oversimplifies the complexities of life, reducing everything to a matter of thought. Others worry that it can lead to victim blaming, with the implication that if something bad happens to you, it's because you attracted it. Despite these criticisms, the law of attraction continues to resonate with many. It offers a sense of empowerment, a belief that we are not helpless victims of circumstance, but creators of our own reality. It encourages us to be mindful of our thoughts and emotions, to strive for positivity, and to visualize our best life. In essence, it's a tool for personal growth and transformation, a way to consciously direct our focus and energy towards what we want, rather than what we don't want. It's about cultivating an attitude of gratitude, optimism, and resilience, qualities that are universally beneficial, regardless of whether one believes in the law of attraction or not. In our modern world, the law of attraction continues to inspire and guide millions in their quest for success and happiness. So, what have we learned about the law of attraction? We've journeyed together through the fascinating origins of this concept, traveling as far back as the early days of human thought. We've seen how the ancient Greeks and philosophers like Plato and Aristotle pondered on the power of the mind and its potential to influence the world around us. This idea, this seed, grew and evolved across centuries, reaching a pivotal moment in the 19th century with the New Thought Movement. The New Thought Movement, as we've explored, was where the law of attraction as we know it today really took root. Figures like Phineas Quimby and William Walker Atkinson played critical roles in shaping and propagating the idea that our thoughts have the power to manifest our realities. They believed in the magnetic power of thoughts that like attracts like, and that by focusing on positive or negative thoughts, we can bring about positive or negative results. Fast forward to today, the law of attraction has taken on a whole new level of relevance and popularity. It's not just a philosophical idea anymore, it's a practical tool used by millions to shape their lives. From books like The Secret, to countless self-help gurus, the modern interpretation of the law of attraction, emphasizes the power of positive thinking and visualization. It proposes that by visualizing our goals and maintaining a positive mindset, we can attract the things we desire into our lives. But it's not just about wishing things into existence, it's about aligning our thoughts with our actions, about setting clear intentions, and about believing in our ability to achieve what we desire. It's a powerful reminder that we, as individuals, have more control over our lives than we often realize. Understanding the law of attraction and its history gives us a greater appreciation for this powerful concept and its potential to shape our lives. But is the law of attraction the be all and end all? It's a question that invites us to delve deeper beyond the surface, beyond the attractive promise of a life molded by mere thoughts. Because, as intriguing as it is, the law of attraction isn't a magic wand, it's an ideology that encourages positive thinking, but it's crucial to remember that it shouldn't replace action and personal responsibility. Think of it like a garden, the law of attraction provides the seeds of possibility, your thoughts, these seeds hold potential, they could grow into anything, a rose, a sunflower, a towering oak, but seeds alone can't create a garden. They need sunlight, water, care, they need the gardener's touch. That's where action and personal responsibility come in, your thoughts are the seeds but you are the gardener, this isn't to say the law of attraction isn't powerful, it is, it can shift your mindset, guide your focus, and help you visualize the life you want. But it's only one tool in your toolbox, just like a gardener needs more than seeds to cultivate a garden, you need more than thoughts to cultivate your life. So let's not view the law of attraction as the ultimate solution but rather as a guide, a compass pointing towards positivity and possibility. The law of attraction is a powerful tool but remember, it works best when combined with action and genuine effort.


Hi and welcome to the session. I am Asha and I am going to help you with the following questions.  Now the standard form of a complex number is of the A plus iota B. So we will try to reduce this in the form of A plus iota B.   It is further equal to 1 plus iota minus 2 plus 8 iota upon in the denominator we have minus 3 iota plus 4 into 3 minus 4 iota upon 5 plus iota and let us solve first 1 minus 4 iota into 1 plus iota to show that the denominator is equal to 1 minus 3 iota plus 4.  So we have 1 minus 3 iota plus 4 which is further equal to the numerator we have minus 1 plus 9i upon in the denominator we will have 5 minus 3 iota into 3 minus 4 iota upon 5 plus iota as a test which can further be written as minus 1 plus 9 iota into 3 minus 4 iota upon 5 minus 3 iota into 5 plus iota. Now on simplifying the numerator and denominator we have minus 3 plus 4 iota plus 27 iota minus 36 iota square and in the denominator we have 25 plus 5 iota minus 15 iota minus 3 iota square which is further equal to minus 3 27 iota plus 4 iota is 31 iota minus 36 iota square is minus 1 upon in the denominator we have 25 on simplifying 5 iota minus 15 iota we have minus 10 iota minus 3 into iota square is again minus 1 which can further be written as minus 3 plus 31 iota plus 36 on in the denominator we have 25 minus 10 iota plus 3 which can further be written as 33 plus 31 iota the denominator 28 minus 10 iota and now let us rationalize it so we have 33 plus 31 iota upon 28 minus 10 iota into 28 plus 10 iota upon 28 plus 10 iota. Now in the denominator we have 28 square minus 10 iota square since A minus B into A plus B is equal to A square minus B square and every place of A we have 28 and in place of B we have 10 i and in the numerator we have 33 plus 31 iota into 28 plus 10 iota now let us simplify the numerator first we have to multiply 33 by 28 plus 33 into 10 iota plus 31 iota into 28 plus 31 iota into 10 iota and in the denominator 28 square is 784 minus 10 iota square is 100 iota square which is further equal to 924 plus 330 iota plus on multiplying 31 iota with 28 we get 868 iota plus multiplying 31 iota with 10 iota we have 310 iota square and in the denominator we have 784 minus 100 iota square is minus 1 so it is further equal to 924 on adding 330 iota with 868 iota we get 1198 iota plus 310 and iota square is minus 1 and in the denominator we have 784 plus 100 which is further equal to now 924 minus 310 is 614 plus 1198 iota the denominator we have 884 now taking two common from the numerator we have 307 plus 599 iota on the denominator we have 884 now I am cancelling the common factors of numerator and denominator we have 307 plus 599 iota upon 442 so on reducing the given problem we get our answer as 307 plus 599 iota upon 442 so this completes the solution hope you enjoyed it take care and have a good day.


lkthrough of the secretary of state's office um how opr received the federal department of labor grant um specific to reducing barriers of entry to professions um one of the four focus groups of that grant so there's four focus groups let me back up there's four focus groups for that grant one being immigrants the other being the chronically poor and underprivileged third is people with criminal backgrounds and fourth is military families so um opr responded to a grant again with brilliant writing from gave um and we were awarded a grant a three-year grant 150 thousand dollars every year for three years we have started working with that and we're part of a consortium of states we're one of ten um and so there are conversations happening at the national level on licensing with the national council of state governments is the that sort of liaison in head of this occupational licensing work through the federal department of labor so there are conversations happening about how to reduce barriers for immigrants the other thing is that members of our boards and Gabe and i for our advisor professions do go to national regulatory associations so these are the people who normally administer the tests so for in social work we go to the ASWB meetings and they promulgate and offer the test and um one thing that is imperative as a small state of Vermont is that we can go to those meetings and say hey what are we doing about accessibility to my to the migrant professional and you know we're just Vermont but Vermont is very mighty and as we know and we can affect some change on the national level or at least prompt some conversations those questions at those meetings so what were the four groups again low-income immigrant um people with criminal backgrounds and military families and we have six of our regulatory programs selected barber and cosmetology funeral pion security pharmacy real estate and nursing and it was it was a grant like a barriers for licensing barriers to all licensing of barriers so specific to um professional licenses that did not require a baccalaureate degree so it was of the goal of the grant was to reduce barriers of entry to professions that did not require a baccalaureate degree with those four populations in mind it is interesting that that ratcheting up with the educational requirements because and it seems to me that it's probably kind of cyclical the more the fewer people you have going to school the more emphasis the college has put on having a degree and put pressure on their accrediting people to get more people to come to school so then it just keeps i was part of that rat race this is something to look out for when we are seeing in the professions is devious a little bit from immigrant specific matters but i mean yeah we that's lauren i had been working this session and the opr bill will reflect um an effort to modernize the athletic trainer scope of practice and speaking with our advisors though and this is not an isolated case but a good illustration of it just as we have third party intermediaries imposing requirements about criminal background or language proficiency we didn't know about we it is possible for an accreditor to wag the dog in a way oh and say you know in a few years you're you know used to be a bachelor's profession and i'm now it's going to be a master's profession used to be a master's profession now it's going to be a doctor um and the academy is not going to tell you that's unnecessary they're going to tell you the high schoolers come to us knowing less every year and you know and um you know so now the bachelor's degrees the new high school department measures the new associates whatever um but look out for it because the the net effect can be really pernicious for young people where athletic training used to be a baccalaureate training program and then you were ready to enter the marketplace and provide those services with you know four years of debt isn't good but it's fewer than seven and we're watching that go up and even the professionals in the field we talk to say it doesn't make sense you know you said what's the new curricular content you know what's the what's done what's what's being added in this you know about $50,000 yeah and we've got a world where we have young people entering their first serious jobs half a million dollars in debt and that is a major problem and licensing is a tool that can contribute to that it's it there's not an easy solution of a lot of this stuff but it's certainly something to look out for and it's very hard to argue against ever more education you know well but in some cases the plus of our workforce development work in this state uh is that we are going back to exactly what you're talking about here which is looking at re-looking at apprenticeships and really underscoring the value of I like the way you describe underappreciated apprenticeships are underappreciated and that we should be looking at what was your nice word you use disuse that had fallen into disuse and that that should be revived and and I think they are being slowly revived they are being the CTE program is the better the CTE program the better that very true in the in the I should say they're I kind of make the colleges the bad guy not always you know in in funeral service for example uh CCV has been a critical component of we had a funeral service model that was our board in addition to saying it wanted to switch to an advisory model said we want to get out of the national model for funeral service because the nearest school I think was Boston and then you had to go to like Minnesota or New York that's great the school that graduated most new funeral directors in New York had a big testing scandal that threatened the licenses of half the funeral directors in New York caused a huge mass the whole system fell apart but had kind of an opportune time because it made everybody step back and we said wait a second you know why don't we have a system where a Vermont who wants to get into the field can do that without leaving the state of Vermont for two years and without going 50 or 70 thousand dollars into death and it turned out we can do that we we the funeral directors association worked with CCV and their and their curriculum director we got heads together they came up with I think it's a eight or twelve course sequence right where they said you know here's the core things you know bereavement and and counseling and the business uh business law etc and the mob and then some period of apprenticeship and if you paired with apprenticeship and so the net cost of going from identifying funeral directorship as something you want to do to being licensed it will fall dramatically and the optician 60 percent was the analysis should be amazing and the optician re field is also an excellent example it used to be that an associates degree it was kind of a mostly disused somewhat used apprenticeship but generally speaking you have to leave the state because what I don't even think we had an optician program anymore get an associates degree we were just talking with a witness upstairs about the optician re amendment he said well you need you know about five thousand dollars a semester for four semesters is about twenty thousand dollars the the career progression program that is recognized in this year's OPR bill costs nine hundred dollars and you can do it online if you get the digital books if you want hard copy the charge of eleven hundred and they'll finance it so that me and so we will can take that field from one where you had to leave the state of Vermont to get the formal training and be five figures in debt to one where a vermoner who may not have any available cash can initiate that training and do it from home which which is great and supports our state college system all at the same time exactly i think i think there are opportunities to talk about the ccb one which ccb offers that the funeral they're offering it through a lot of it through distance learning and many of what they'll many of the core courses i mean when i met with them i met at the wanooski campus but um it will be available i think the most of the courses in that sequence do require some physical attendance but it's limited and so most of the course instruction can be had online so if you think it's opening fall of 19 that's right there was fall that's for this fall so and some of these good ideas have come from the regulated community itself funeral and optician certainly have some of them require the state to say don't be so protective and of your marketplace and so that can be sometimes a and a harder conversation funeral it was a fairly easy conversation because and dentistry was a fairly easy conversation just anecdotally because those two communities were struggling to find people to buy their practices there was there was i had one correspondent when i was general counsel for dentistry um i had like a pen pal a woman in retland who was wanting to sell her practice and couldn't find anybody um a dentist and just she just was like please do this i have a buyer but she just needs to get a license and you can do it and please do it um and it had the support of the association so that was a very successful story but that really came from the community having a desperate need other times um it this it's a really a place where there needs to be active state supervision to say no this is an unnecessary barrier you're putting up um we don't need to do that um you haven't thought about x y z and b um and all implications that can have so we see it in two um ways coming from the profession and also from us saying to the profession don't do this right thank you i'm i'm going to read this before next week what day are they on deck first friday friday at one fifteen i think oh we're going to say the best for life right did i give it back to you all right all right good thank you thank you thank you i understand this it's a neat issue well and we will make sure that our other committees are aware of the i think this is going to be one of the things that we kind of as a whole senate are going to in different committees are going to look at that um now if we could just get you to solve getting um is it h one five h one b visas for our undocumented dairy workers could we please do that federal immigration policy is its own is its own monster and unfortunately it's lurking behind this whole thing yeah i know it is it is anyway okay so thank you thank you