This talk is, as the title says, about crowdsourcing, and when I received the invitation to give the talk, first I thought, oh my god, I have 45 minutes or 30 minutes to speak, and there are so many things to talk about, and I'm very passionate about this area as well, so I would never be able to cut it down to 30 minutes. Then I started doing some research to see how this community, how libraries, how research libraries in particular, do already apply crowdsourcing, and I found so many exciting and interesting projects, so then I had my second moment of panicking, and I thought, oh actually they know everything about the topic, so there isn't much I can tell them that they don't know about, so this talk is basically the result of the struggle, and my hope is to convince you that crowdsourcing is not just a very hyped word, but it can actually help in many of the content management tasks that you are dealing with on a daily basis. However, crowdsourcing is also a very complex field, so in this talk I'm trying to give you an overview of the different types of crowdsourcing, of all the approaches, the richness of the space, which you could take into account when you set up your own crowdsourcing project. I would also want to give you a feeling about the types of tasks you should use crowdsourcing for, and the ones in which you should rather maybe invest in technology, or train your in-house experts to carry them out, because as much as it is a solution to almost everything online, crowdsourcing might not be the best solution for your particular problem, especially if we take into account very mundane things people might not want to talk about like time and accuracy and budgets and so on and so forth, and then in the end towards the end of the talk I want to introduce you to this vision that we have in one of our research projects at the University of South Hampton, which is related to what we call social machines, which are online large-scale assemblies of human and computational intelligence, which come together in some sort of a utopic scenario to make sure that we solve all our problems in our daily and private life, and that we advance economy and society. So that's basically the executive summary. Let me get back to crowdsourcing as it is. How many of you did hear about this term before? So, yeah, as I was expecting, basically everyone. So in a nutshell, the topic has been around for more than eight years now, but it stands for a general framework by which you have a problem and you solve it via an open call. And when I say open call, I mean you don't use typical outsourcing mechanisms in which you approach another organization to carry out a task and execute a project, but you use an open call to a large network of potential contributors. And you can take this concept and apply it from the enterprise setting in which it was originally defined to online worlds, to social networks, to public sector information, to consultancy, marketing, and so on and so forth. But the basic thing to remember about it is that the call for contributions, the type of people that will help you to run your project, are previously unknown. You want to have lots of them or as many of them as you need to carry out the project, but you don't know them in advance. And since you don't know them in advance, you have to, there are different ways in which you could interact with them or influence their behavior as compared to when you have an enterprise, when you have a group of students in the university and you let them execute the same project. There is a different type of social or organizational structure. There are different types of things you know about their performance. There are other means you have to set up in order to encourage them to behave in a certain way. There are many and many forms of crowdsourcing. So on the, this umbrella on the left hand side is a rough attempt to classify some of the approaches you might have heard of in the literature. So the red and the green bits distinguish between the granularity of the tasks. You have something called macro task which stands for any type of project which you just give out, publish, without giving specific instructions about how the actual project will be executed. The classical example is you want to design a logo for your website. You want to outsource the design of your website itself. You want to find the name for a new product. So you're looking for creative ideas from people you don't know of in advance and you're asking the crowd to come up with solutions. The other type of crowd sourcing, if we talk about it in these terms, is what we call micro tasks. And as the name says, this stands for those types of tasks that are very small, atomic. An example is for instance, tagging. You want people to tag the papers that you have in your repositories so that you can take advantage of all the beautiful search features you have heard about in the previous talk. A micro task in that particular example would be the task of tagging this particular paper. Then you can specify it further. So we're talking about finer granular tasks and the point there is you would want to have many people engaging with these tasks in the same time in parallel. So there, the reason why people do that is because this type of work can be broken down into many, many smaller bits that can be executed independently. And if things work the way people tell you in the literature, then you would end up tagging hundreds of thousands of papers in something like this, which is something for various reasons you wouldn't be able to do in your organizations because you have other things to do because it's too expensive to do and so on and so forth. The other parts of the umbrella, there are contests and crowdfunding. I will leave crowdfunding aside. Contests are complementary to micro and macro tasks because they just speak for a form of engaging with the crowd, which assumes a certain type of reward. So there, basically, you will reward only the top three or something of the contributors and everyone else will go home and will be happy that they participated. Contests can be, so this contest model can be combined both with micro tasks and micro tasks and as I will explain later on, there are other reward models you could apply as well. So already from this picture, I hope you understand that when you talk about crowdsourcing, let's crowdsource a project, you already have a series of specific methods and approaches you could rely on based on the task, on the type of project that you have and on the rewards that you are willing to give out. What are the challenges and opportunities for research libraries from my point of view? I have gone out there and tried to see what type of projects could be useful and interesting for this audience. I have started with something which maybe some of you know, which is an older project called Distributed Proofreaders, in which the idea was to improve the results of OCR processes. So you have digitized text and then there are mistakes, errors that can happen in the automatic process and then you ask experts or volunteers to help correct those mistakes. A similar type of project is a project in the Zooniverse citizen science platform. I don't know how many of you have heard about it, so Zooniverse is a platform for what we call citizen science or crowdsourced science that runs at the University of Oxford. They have 20 or so projects in various scientific disciplines. One of them is called Operation Word Diary. So similar to Distributed Proofreaders, they have digitized context pictures of old war diaries that they would want to be organized and tagged and enriched in a particular fashion. What else is out there? So something I found very interesting is called metadata games. This is a slightly different approach to the usual. I put the content out there. This is a task that will advance the humanity, come volunteers and help me do it.  And what it does is the approach is called games with a purpose, whereas the purpose is understood from the point of view of the designer of the game. You can imagine, you can understand them like quizzes, casual games, very simple games, played at a very fast pace where you are asked to answer questions like, I don't know, what is the capital of Latvia? Is it this city or this city? When was it founded? And so on and so forth. So you play this game, but actually the replies, the answers that you provide are used as metadata for some digital artifacts in the back end. And this metadata games is an initiative to develop technology to create such games easily. And it's been used by a number of libraries, for instance, to build image tagging games. So in terms of opportunities, by engaging with the crowd, be that volunteers or paid contributors, or participants in a contest, you have an affordable and most of the time is quite accurate way to enhance your information management services. This means you could outsource tasks such as image annotation, labeling, or even search to some extent, if you apply social search features. You could also capitalize on a scholarly practice that is getting more and more important in different disciplines, which is citizen science, which outsources, applies crowdsourcing ideas to engage with citizens as part of established scientific workflows. You could also, but I will not talk about this in this talk, have a better customer experience. So visitors of online websites expect certain things from any website. Like in the previous talk, so if Google does it, then of course your search feature will also have to support you to some extent, because they're used for if Amazon allows you to interact and give reviews and so on and so forth. This is something that you will, you will need to do as well. So crowdsourcing is one way to engage with your customers and give them the feeling that they are part of the process, they can, their wishes and thoughts and needs are listened to. The challenges, however, are to understand what would actually drive participation, especially in cases in which you want volunteers, people to volunteer their time to do it. Many projects in crowdsourcing apply similar principles to the ones that I will introduce, but do not reach critical mass. And one of the things I will go into in more detail is what this critical mass actually is. So you have this, this power law distribution that you also see in Wikipedia, the 10% of the actual, of the customers, of the visitors of the website, other ones who contribute 90% of the time. This is not something that should be discouraging. This is something you should be aware of and you should think about what kind of contributions you could realistically expect from the long tail, from the 90% who visit the website maybe once and edit and, and I don't know, correct one spelling mistake in the Wikipedia article and the 10% who actually put lots of effort into editing the articles. These types of contributors are likely to be driven by other types of rewards and motivation. And it will, one of the main challenges when you set up a crowdsourcing project would be to understand that. In this talk, I will understand crowdsourcing as what is called human computation. Human computation means that we resort to human intelligence, to human contributions, to enhance the results of automatic algorithms. If I go back to, well, let's say extracting keywords from a research publication. This is something, this is a task that could be executed totally manually.  And then probably you ask more than one person and aggregate the results and select top five keywords that you want. That's one way to do it. Alternatively, you could say, I apply some sort of machinery and information extraction algorithm who will tell me, oh, I think these are the top 20 topics I would extract from, from this document using models like the TFIDF one that was mentioned earlier. And then you ask, you apply human intelligence just to enhance the results of that algorithm. And this is the classical human computation scenario. This is opposed to something like creative processes. Where, for instance, an organization would reach out to their customers to come up with a new combination for the McDonald's burger. This is actually done. And it's one of the most successful examples. So they reach out to people and say, create your own burger.  And then whoever wins has their burger in some area, at least in Germany it was done. And it's actually sold in shops. So I will not talk about this. I will also now from this point on, I will introduce you to the main dimensions of a crowdsourcing project. So the types of things you have to think about when you set it up. And I will use one example, which is the crowdsourced collection of data citation information. So this was an experiment we ran completely by coincidence two months ago at the Semantic Web Conference. And the task was to collect, we wanted to know. So we are obsessed with publishing linked data. We have many of our data sets published as linked data. And we want to know who else is using these data sets in their research papers. So we wanted to collect information about these data sets and about the versions of the data sets that are useful. For instance, I don't know if you have heard about DBpedia, which is a more fancier version of the Wikipedia info boxes, basically. So if you search for DBpedia papers, Google's caller would give you something, 9000 something publications. There are also 40 or so versions of Wikipedia already available. So we would want to know as a community, in order to understand the research to reproduce the results and so on, which version of DBpedia is used in each paper. So we set up this website, which you can find at that URL, just to see what type of crowdsourcing methods and mechanism we could apply in order to get this information. And this is the example I will use in the following. So you want to set up a human computation project. What are the things you should think about? Well, first of all, you have to consider what types of tasks, what type of work you want to outsource in the first place. Because in theory, you could, every task could be amenable to crowdsourcing, but some tasks are more, well, benefit more from it than others. And these are typically those tasks which do not require lots of expertise, but rely on human skills that all of us have. So visual recognition of objects, language understanding, communication and so on. Then you also have to think about who do you actually reach out to. Is it everyone? Is it a casual visitor of your website? In theory, this is not everyone. So based on whom you are going to disseminate, you're going to promote this project so you will not reach everyone. So you'll have a bias, actually, in the types of people that will go back to the website and engage maybe with the project. How are you actually going to outsource the task? So there are a number of things that need to be taken into account here. So I mentioned this micro task. In this scenario, which is typical for human computation, you break down the actual work into smaller units and you have people working on them in parallel. So you have, I mentioned Zooniverse. One of their projects classifies millions of images of galaxies that have been collected by the Oxford Observatory. And they want to know what type of galaxies are there. So they ask people, look at this image. You see some sort of white sphere in the middle of the image. What is this? Does it look more like a star? Does it look more like a plate? Does it look more like a UFO? So they capitalize on our basic object recognition skills, collect that information. Well, that's not science in itself, but it helps them train some image recognition, image analysis algorithms that then lead to scientific discoveries in astrophysics. This type of task can be broken down into smaller units because you have one million images and every user of their system can classify how many images, whatever number of images they want. When you have something more complex than that, you will need to coordinate between the individual, between the individual contributors. And this will require more effort from your side. And it will also slow down the process. What kind of complex work flows do I mean here? Well, it doesn't have to be complex in the sense of something that cannot be written down as an algorithm. It is as, take for example, the task of translation from one language to another. You could, you have a paper and you want to have, you have it in English, you want to have a German version. What would you do? Would you give the paper to one person and say translate it? Would you give it to the crowd and say, everyone, why don't you translate this paper and then I'm going to collect the results and see how I merge them and what do I do with them? What if the document is 500 pages long? Then you're actually one to break this down and to give people, I don't know, maybe one page to translate? Then again, you'll have to think about, do they have the right context to make the right translation? You might also want to go for a setting in which you would ask someone to do the translation but you will not do the correction and the editing. You will ask yet the crowd again in a second step of the workflow to go through the translations and pick the best one. So this is an example of what they call complex work flow in crowdsourcing, which is everything that cannot be, bluntly broken down into smaller units like the million of images of Galaxy example that I brought up earlier. Right. I think I mentioned this already. Zooniverse has something like 27 projects at the moment, some of which probably also interesting for this audience, most of them in astrophysics, and they have a million users. So one million people go to their site and spend hours and hours of their day classifying galaxies, labeling specific objects and videos, transcribing word diaries, transcribing weather logs and so on and so forth. Now let's get back to the example I had before. So remember what the task was? The task was these are the papers, these are the data sets, the data sets, let's establish the links, which paper uses which data set. That's one way to define the task but it's not the only way. You always have to think is this the most appropriate representation of the domain? What am I going to show to the user? Is this enough? Or is it maybe overwhelming? So in our experiment we had just the bibliographic item, the title, the author and the publication venue and some information about the data set. This might be enough for someone who is an expert who comes from that area. For someone else you might want to show them an abstract. You might want to show them the first page. You might want to show them the full paper. What if the full paper is not available? What if it's very long and then the whole process is slowed down? So you have one of the things you have to be careful about is how are you going to represent and specify the task to the contributors? What happens if we don't know the list of potential answers? So in our example it was quite clear because we were thinking about one particular data set. What if you don't know these data sets? What if you ask them what data sets do these people? Look at this paper and tell me the data sets that are used. You will have no means whatsoever to know whether the results are correct or not. You may want to merge them. You will have to deal with different spellings. You will have to deal with different ways of writing down versioning numbers and so on and so forth. Who would be the crowd in this case? Well the people who know the papers and the data sets or even the authors of the papers they require almost no context information whatsoever. You can also think about anyone else in the field. Anyone knowledgeable of English for instance. Anyone with a computer. Anyone with a cell phone. Again if you want people to execute the task on their cell phone you'll have to think of various other representations of the task. You don't show them the full abstract on the mobile phone. So you'll have to think about what crowd would be the most appropriate? What task am I actually trying to solve? And pick the ones that are right for you. And no one says you should just go for one option. How is going to in this experiment so what types of task models can we imagine? One option would be let some algorithm identify the data set names and then offer these candidates to the to the volunteers to select. You could also use something like paid micro tasks. Have you heard of Mechanical Turk? Yeah. So these are platforms where you pay people four to five cents a dollar to solve tasks like that. You could use them to do a first screening and then you could have experts or even the authors of the papers to sort out the challenging cases. You could organize a competition via Twitter. You could have I don't know the question of the day which which version of this data set does this paper use. You could involve the author saying oh we found out that this than this and this data sets are used in your paper. Is this correct? Yes or no? Let's move forward. Two more dimensions of crowdsourcing.  You are me the way to validate the results because whatever will come in from the from the volunteers might not be is not per default accurate for various reasons. Maybe you didn't specify the task well enough. They didn't understand it. You have lots of spam on some of these platforms.  So it is a big problem and it is up to you to actually collect the results from the crowd and decide which ones are correct or not. Of course some cases are easier than others and I mean by that those cases in which the set of potentially correct answers is no. So if I know all 292 open data sets published as linked data that's all there is to it for me and I will look for different spellings of those data sets and that's it. If the answers are open, if you have free text as contributions then of course you'll have to think of other things.  In our case the validation was quite straightforward. It is quite straightforward as I was saying as the set of potential answers is fixed. What you want to do there as well is to have more than one person giving the answer to the same task because you want to have redundancy and because you want to apply something like some sort of majority voting to identify those answers that are that are likely to be correct. Now something that is less straightforward is related to incentives and of course everyone would want to have volunteers engaging with the site, executing the task, giving ideas for new services. But the problem with volunteering is that it's highly context specific. There is one successful Wikipedia and there were 200 other projects at the same time, similar scope, similar technology, they failed and we actually don't know why. It's not applicable to arbitrary tasks as well. So people are very fond about galaxies but maybe not so fond about research papers and data sets. So this is why you actually go to things like contests or mechanical Turk. Just to worry about this, so if you decide to pay your contributors, it is in general it is affordable because you pay something like four to five cents for each correct answer. However if you want to do this as part of your internal processes, you'll have to think about optimizations because you don't want to spend, so for the 9,000 papers I mentioned earlier, we would have to spend something like five thousand US dollars with all the redundancy embedded with all the validation afterwards. Well for five thousand dollars, you actually hire someone who has knowledge in the field and you can expect other types, other level of accuracy from them. Analytics can help. I don't have much time to go into details for that but this is some work we've been doing for for citizen scientists from Zooniverse where we give them basically a dashboard of what their users are doing. So they can see when users leave or predict when users leave. Think about the performance or study the performance of the individual contributors and then decide how to act accordingly. In the experiment that I mentioned earlier, the important thing to think about is who will benefit from the results and who will own them. So assuming I will actually create all these links between datesets and papers. Is it something for the public good? Is it something that me as a researcher just crowdsourced to the community and then the results will be free? Wouldn't it be a better model maybe to work together with a publisher who has maybe all the papers? Who has already a community? Who has a website in place that is highly visible? But then the question will be will people come back to the site and engage with the experiment if the ownership of the result is with the designer? And so on and so forth. You could use different crowds for different tasks as well. I mentioned this a bit earlier as well. This is some work we have done for the International semantic web conference in which we have successfully combined experts in a contest and then paid micro-turkers to curate dbpdm. But what you want to have in the end, as I was saying at the beginning, is to use humans. Humans are a very valuable resource and they can be quite unreliable as well. You cannot really predict how they will behave. What you want to have is to use them only for those cases which are really engaging and interesting for them, but are also beneficial for your project. So what you want to have is to have the symbiotical relationship system that uses computers and humans to solve specific tasks. And this is this is already very very very technical but just to give you an idea of what for instance the database people are doing. They are extending SQL and so they're query engines with crowd operators. So for particular things, like when you want to merge those two tables over there, they will use half of it will be classical SQL query execution, but in five of the cases they will ask the crowd. And I would like to conclude the talk by revisiting what I said earlier. So I hope I gave you an overview of or at least the feeling of the diversity of this field and the types of questions that you want to consider when you set up a crowdsourcing project. I haven't had time to talk about sustaining engagement and this is this is more an art than a science and I'm a scientist and not a marketer. But I would want to reinforce the last point that I made that computers are still very good at many things. They might be imperfect at others but the ultimate aim should not be to have crowdsourcing applied over and over again for the same types of tasks. The aim should be to collect, to use, to capitalize on these contributions to improve information technology, which is what we call and the social project the age of social machines. Social machines is a term that has been introduced by Tim Berners-Lee early on in which he lays out this this this vision in which you have social machines enabled by the web and which people do the creative work and the machine does the administration. Thank you very much for the invitation again and if you have any questions I'd be happy to take them. Thank you. Can I have any questions for Elina? Thanks a lot for your talk. Irina Kuchma Eiffel I have a question what do you think about the term crowd sourcing because there was a comment some time ago from Francois Grays that it has this allusion to cheap labor menial tasks so maybe it's better to call it crowd crafting because then it would be real innovations by volunteers. Thanks. I look at it from from a systems engineer perspective so I don't care so much how it is called as I care about the principle and the original principle did not involve necessarily these aspects. I think this comment which is which is valid refers to platforms micro task platforms like Mechanical Turk but even then you have to imagine so when Amazon introduced this in 2004 this was quite a revolutionary concept because it brought the computing back to the humans I mean the first the first computers were humans they were actually females and they were hairdressers. The first computers were human computers were during the French Revolution were used to build logarithmic tables. So there was a very simple process apparently hairdressers in that time in those turbulent times didn't have much to do so they were all they all came together were paid to to do these very simple computations this was the first the first example back then and now Amazon in 2004 hundreds of years later introduced it again on the web no one actually knew what this is going to turn into and then you have seen this development some an economist says say or at least the discussions I had this development wasn't quite unexpected it was a particular type of labor market that they're very fond studying in which you see developments such as you know supply and demand you have a very adaptive way of defining the prices the prices per tasks and mechanical turks turk are now on an average of five cent per task from one cent five years back you have the turk the workers as well organize themselves you have a union for instance of turks mechanical turk so the platform provider is now much more careful in terms of ethical considerations legal and taxation issues and so on and so forth so in short yes there are some of these cases but from my personal point of view it's still a very rapidly changing field and which we will see some some directions which are typical to labor market that will try to deal with the situation how many of you have a crowd sourcing project can you please raise your hand ten percent yeah and how many of you like might to start a crowdfunding project crowd fun oh a crowdfunding yeah a crowd sourced project oh and there's also some people do some people do yeah well i hope that you can take some of the some of these insights to into account when you set it up we have another question there uh yes thank you uh adam sofronovich university library of belgrade you mentioned that creativity is an important part in distinguishing between machine work and human work and can you elaborate further on how we define creativity nowadays in the future because we have machines driving cars winning jeopardy contests everything that five or six years ago was considered to be a creative job um and if you could elaborate further on which jobs would be creative in academic library in this sense right thank you okay well let's walk a lot during the presentation so i was stuck here um right creativity for me and from a from a crowd sourcing design point of view creative is everything that you cannot that you don't know how to do so you actually don't have a cookbook saying first you do this then you do this then you do this then you do this and you pretty much can can um estimate the range of outcomes for each step so this would be creative is something that you cannot pin down write down as some sort of algorithm that can be engineered but that's my very limited view of the world and and and the point of view i taken this talk and now the second part of the question was creative jobs in the um in the in academic libraries right um well i think there will be still lots of of creativity and and and room for for humans to contribute when it comes to the design of new services i don't think data processing data processing should be outsourced to to to machines for most of the times it is not done today because the our algorithms are just for our tools are just so frustrating then in the end you just decided to do everything in excel um but um this shouldn't be the case and the hope is that through crowd sourcing projects we will manage to solve at least some of the some of these project uh and some of these challenges but the create the creative bit will still remain in how what type of services do i offer to the visitors um how do i design them how do i interact with them um it will also human communication is something that that is very difficult to be to be to be replaced as well so i think in in that in that um uh regard we shouldn't be so worried yeah we actually should be very hopeful that we will have the time to uh think about new and exciting services and things we could do as opposed to doing content management thank you again so now we have a second round of poster presentations could i invite please the visitors of posters to form a lineup because we're going to have uh lots of posters in only 10 minutes um and while we're forming the lineup may i invite you uh because after these 15 minutes we have a coffee break um you can afford the queue if you go to the reception desk and cast your vote for the best poster you've seen and you're always free to go downstairs and have a look at them again um so please do cast your vote um and now we'll be ready for our posters mechanism is very simple one minute of poster so i would like to first speaker please hello everyone my name is Tanya Stoyanova from New Bulgaria University in Sofia you can see our iceberg actually this is a Bulgaria but it's a metaphor because Bulgaria is a very warm country and our repository was launched in 2005 and is the first repository launched in Bulgaria it has two unique features depositing is voluntary and entirely made by authors and the second one uh the original content is deposited on its uh unique language uh our team performs uh monitoring of the metadata that is uploaded into the repository all the time so that to improve the depositing and self-archiving literacy and trainings also a six month uh survey has been conducted to find out what are most common mistakes made by authors during the depositing and if you want to see the results and to learn more about our open access policy you are welcome to visit us a deposter area thank you very much and congratulations for the conference in the city of Riga good afternoon colleagues my name is Thomas Baldwin i'm from the m25 consortium of academic libraries we're a consortium of higher education and research libraries in the southeast of the united kingdom we recently ran a JISC funded project to examine the consortial purchase of ebooks that project was ebass 25 we identified four possible patron-driven acquisition business models within the project purchase rental usage and evidence based the evidence-based pda model was selected as being the most desirable for our consortium because it combines user choice with the possibility for alignment with libraries collection development policies the poster briefly notes pros and cons of three of the models and then gives more detailed implications of the chosen evidence based model as m25 transforms this project into a service thank you good afternoon everybody the Slovak center of scientific and technical information is a national information center and specialized scientific library this key position in information support the science and research in Slovakia we are a project solver of several national project co-finance from EU resources they are also known as a so-called structural funds our first and main project is name is the national information system to promote research and development in Slovakia with subtitle access to electronic information resources known to academic sphere and in all country under the acronym NISPES project has four specific goals our posters introduce three of them first is centralized provision of access to electronic information resources second national search portal for science and research and third one central data bank of Slovak information resources for research and development please welcome us we are ready to answer your questions thank you my name is that's a Rosenbarber and I work at the Royal Holloway University of London as you may know in the UK we have strong focus on open access largely driven forward by the open access policies from different funding bodies and our poster looks at how one such policy research Council's UK policy on open access has been implemented at Royal Holloway what internal processes we have in place to support academics to meet the requirements what advocacy we do and how we distribute and monitor the funding for article processing charges if you would like to know more or would like to share your experiences please come and talk to me thank you with afternoon my name is Mireia Pérez Cervera and I come from the open University of Catalonia in Barcelona in the UC virtual library we have our website as a unique point of interaction with our users in this poster we try to present how we've passed from an old-fashioned website and usable and not intuitive to a new library site organized using a user-centered design method to do so we've conducted benchmarking benchmarking analysis interviews focus groups and user tests then we've been able to identify problems and develop new actions like including better explanations of processes and services organizing the the access to the content in terms of user needs rather in of in terms rather than in terms of library tools introducing one simple point of access to resources and structuring the content and information to each profile so that each of them could now know the specific conditions of their profile come to visit poster number 16 i'll we i will i will be downstairs on the coffee break thank you my name is Yolanda Ivanova i'm from Riga technical university scientific library the poster theme is creation of common territorial complex for Riga technical university the Riga technical university scientific library which is still combination of the past and the present must be viewed with a new perspective and understanding if it is to fulfill its potential in adding value to the advancement of the university academic mission and in moving with university into the future the poster's main goal is to reflect the new and combine services along with their added values in the united are to use scientific library complex so if you have any questions find me during this conference and we will discuss about it thank you hello my name is Luna Liga i'm coming from the university of Maribor library our library producer decided to support the strategic goal of our university this is to increase the usage of e-learning environment at our university approximately 50 percent to the students this is nine thousand students are users actively users of e-learning environment model so we have to decide to meet their needs for library services also inside of the e-learning environment we started with a pilot this year with the we finished a showcase with one subject at the medical medical faculty so we do this have done this in two levels first level and the enter page of the model with external links as offer for the students and the second level is the my courses page where we use the functionalities of epsco discovery service and lip guides to create a recommended list there did these do the professors and to establish tighter connection between students and our subject librarians so thank you very much for your attention i'll be downstairs number 18 thank you hello my name is Tatiana Timotyevich from the national library of Serbia the title of our poster is how we made it is more visible well in Serbia we have a lot of institutional repositories but the last year we implemented national repository of it is which is called the doi Serbia phd why we did it first to promote our institutional repositories and second to make our thesis more visible how we did it well that is a question now we did it by assigning a doi to all our thesis and also equipping all records for thesis with a lot of useful useful links also we implement and deposit metadata to our various open access repositories such as the european library dark open door etc so thank you for your attention and if you have any questions feel free to ask thank you very much so we have an actual poster it's in the room so my name is Matilde Panest I work for the library of medicine of the university of Lausanne and in Switzerland and my colleagues and I worked on on the ownership roles in the biomedical field we created a new model that defines 10 roles in the publication process this role reflect reality of the division of labor during the publication process and is different from the model that is currently used at the faculty of medicine in the second phase of our research we conducted interviews with researchers to confront our model to the reality their reality and the model we created as well as the results of our interviews are available on our poster please come and see it because it's not here obviously and thank you a lot hi i'm Mariko Willems from the labor office and i wanted to explain your poster number 15 from european newspapers by giving you the premiere of the european newspapers animation the united kingdom is newspapers i find something unexpected every time i look at one it's the newspapers i find something it's time to make some practical announcements oh really? yeah that's the best solution yeah newspapers i find something unexpected every time i look at one it's the diversity there's a whole world inside their pages the news of course but also cartoons letters shipping reports they're endlessly useful to researchers like myself through them i can track the spread of ideas the evolution of language the aspirations and achievements of nations the technology is dramatically changing their value not long ago i'd have to go through fragile paper copies one issue at a time now millions of newspapers are freely available online like the collection created by european newspapers it's 10 million historic newspaper pages from across europe all searchable on a single website the possibilities make my head spin so much content and so valuable i'm very excited about the trends i might now be able to see uncovering how new words spread from one country to another or comparing regional opinions to elections or wars advertising could tell me about the evolution of consumerism or graphic design the real digital revolution is that in two million pages the structure and content is being tagged i'll be able to distinguish headlines from articles search for paris the city instead of paris from greek mythology biella the river instead of the famous comet i see it as a liberation of the newspaper okay i think you have two small announcements to make but before i do i'd like to have another reprise for round of applause for all of our poster presentations


We look at how policies get changed in context outside of the Global North. We want to understand what factors change policy and that can inform advocates for policy change, but it can also inform researchers who want to make sure their research has impact. We're doing a number of case studies in different contexts around the world to understand how policy makers make the decisions they make. The case studies include studies from Bangladesh, Singapore and South Africa. We find there are a number of factors that influence whether or not a policy change occurs. These include things like who the policy is being made for, the political environment in which the policy is being made, the kinds of knowledge that are available and how they're being used, as well as who the actors are, which kinds of coalitions form, which kinds of advocacy groups form. This is useful for example for researchers like myself. We often imagine that if we present research to policy makers that they will use it immediately and the uptake will be linear. Often that's not the case and we're quite frustrated by that. For example, migration policy at the moment is highly politicized. It's also increasingly global, so weaker states in the global south are often being put under enormous pressure by other countries, perhaps more economically powerful countries to implement certain kinds of policy. That may mean that even if the research suggests otherwise, a state might be under huge pressure from a range of international actors to implement policy that looks a particular way. Very often research oriented towards human rights policies tends to focus on the abuse as people suffer. When in reality as much as we may need to know that, often we already know that and what policy makers need to know is what kinds of policy options are there out there and what could they do differently. And that kind of research was largely absent in the three contexts we've researched. We need to think about the political context into which our research is placed. We need to understand that if we're going to have an impact. We need to think about packaging our research in creative ways and in particular we need to think about whether we've done the right kind of research for policy makers to use.


Welcome to the crew, Josh Marr, the new Brew Crew radio guy. It's gonna be lots of fun on away games with him. Go Brewers, go. Welcome Josh.


Frankie finance is back and I guess finance isn't really the best word because all I really do is explain to you guys that the 1% want to steal your money and people really need to get in their heads that That's their primary goal control the money control the resources and they control the people a few months back I was the only person to call the crypto crash Coincidentally one week before it happened literally one week before Bitcoin tanked from 60,000 to 35,000 and not only Bitcoin all of those other crypto currencies also took a dump Did that crash steer so many people away from crypto that they need a new gimmick or is it the constant mention of cyber attacks and power grid shutdowns 69 million dollars. So what's behind this latest craze? That is the question to ask Okay, so there's some super strange stuff happening online right now, and I need to tell you about it First look at this tweet the first tweet ever tweeted in the history of Twitter the tweet was by Jack Dorsey I'm one of the co-founders of Twitter and this tweet was somehow just purchased for 2,915,835 Dollars and 47 cents Are you serious? And it's not just a tweet Just last month a single JPEG sold for $69 million. Oh my god. The NBA is selling little moments of basketball games Percenters of thousands of dollars. This is all sorts of digital things that people are purchasing a Version of them for lots of money all of these digital currencies Crypto every single coin NFTs have completely fabricated made-up stories behind them BS No accountability and keep in mind the 1% elite aren't just you know a few hundred billionaires they have millions and millions and millions of pawns Pions working together to deceive you especially on social media Any cryptocurrency video on YouTube will have these fake comments on it bots Shilling for crypto trying to convince you to invest and then as soon as enough average dummies put their money into that investment They cash out and tank it and and one over looming thing is is that even a word over looming? The new world order government coin What's going to happen are these crypto currencies going to be void and crash when the government announces their legitimate coin is the government going to adapt Bitcoin or one of the main crypto currencies as We don't know but all of these conspiracy theories come true So that's going to happen. What is an NFT the stands for a non fungible token But what exactly does that mean fungible means the ability of a good or an asset to be interchangeable with another Individual good or asset of the same type so an asset that is fungible is the best kind of asset to use in commerce The prime example of a fungible asset is cash if someone gave you a $100 bill and you gave them back 520s no one loses no one gains anything Because cash is fungible the same thing would be true if you gave me an ounce of gold and I gave you back a Different ounce of gold. They're both worth the same. They are interchangeable for one another now a non fungible asset is one that cannot be Substituted identically for another asset. So if me and you were to trade cars Even if the car was the same model in year It would not be fungible because one of us could have a manufacturer defect or maybe yours rides a little bit better But the gas in your car that would be fungible because it's interchangeable other more traditional Non fungible assets include real estate artwork and now encrypted digital tokens aka NFTs now the word token in the case of non fungible tokens refers to a digital certificate Stored on a blockchain in the exact same way that your favorite cryptocurrency is stored on a public ledger So an NFT is a digital asset that can't be substituted for any other digital asset and it's publicly Verifiable now you might be thinking why would I pay $100 or one million dollars for something that I could literally just screenshot and how for free in my phone and That's a great question. I'm not saying you can't make money trading crypto or stocks But for someone to make money on these currency exchanges Someone else has to lose money so many average people normally sheeple whatever you want to call them Lost so much money on that previous crash that the elite Secret society degenerates can no longer steal money as easily using that tactic They created the game. They make the rules and you can't beat them But if you don't play their game, they can't win I think there's an analogy for this like like if you're getting bullied in a sandbox go build your own sandbox Again, you can make money trading, but the odds are against you. It's not something for the average person You will never have the insider trading tip of when the big dump is Because you're playing in a rigged system the average person trying to trade is like a kid going to his first little league game and You know Justin Verlander is on the mount against him These pricks in control of social media have done an excellent job at gaslighting people into losing their life savings Or at least portions of their life savings And this is really one of the biggest lies there is if they are unable to convince you to invest in Systems they own they can't steal your money and continue to be parasites So thank you guys for joining me today. Some of you might be wondering well Frank. What do you do with your money? I am a quote business man Unquote as in I guess not a traditional business man that invests in businesses and flips them and that stuff I have my own creative ideas that I am fortunate enough to be able to Turn money into more money and in unconventional way, which is a unique opportunity, but I'm losing my mind doing it and I don't know how much longer or less so Hopefully this helped you guys out You can go to Frank cash to follow calm to support me through all of my businesses if you can leave a comment down below if you Have any insight any questions Like the video subscribe so that YouTube can unsubscribe you next week and be sure to check that notification bell So they don't notify you of my videos Thanks again guys, and I'll see you for tomorrow


Some pretty nasty vampires. Hey guys, this is my review for episode 11 of Supernatural season 13 I apologize for being a little late. I honestly did not know that yesterday was Thursday I'm back on set and the whole week is just everything just melds together The only reason why I'm reviewing it today is because I actually got today off for some reason and so I Get to review for this this episode for you guys today this episode had Donna from Minnesota in it and it immediately tried very lazily to explain why even just after the whole idea of kinship and family between the wayward sisters was very very well established in the last episode She immediately is doing this with the boys. They say something about oh, she's Jody's got her hands full of the girls I don't know I just I wouldn't have used this episode This early on or if anything, I wouldn't have used it in this series if wayward sisters is gonna get picked up. I Just I don't know. I thought it was a bit weak, but otherwise the episode itself is actually pretty good It's very dramatic. It's got some really cool dark tension It combines the monsters of humans as well as monsters Pretty well into this dark net sort of auction buying off of organs and whatnot a little bit cheesy A little bit over embellished the ending has a few too many twists to handle it kind of goes from a Serious very dramatic setting to just kind of off the wall cheesy with the amount of twists that happen as well as Um, how many things become problematic and are solved in like record time Donna's husband becomes a vampire Boom, he's cured Sam is kidnapped by the FBI agent who actually turned out to be the guy That everyone was looking for in the first place boom Dean saves him I know this is a regular thing But the fact that there were so many plot elements put into this episode and they're solved so quickly This could have been a two-parter almost, but it's a filler episode so that's why it wasn't every time they bring humans back into The fray I always compare it to the benders episode because that is the best episode that's ever had humans as a villain in it And this one comes close better than the episodes prior throughout the seasons There's been some episodes about humans that just have sucked this one did not it was an enjoyable episode There were some cool moments. There was some funny humor, especially Between Donna and her husband just the whole oh, yeah Yeah, I became a vampire it's this I thought it was hilarious and the fact that I just finished the first two seasons of Fargo made the experience a little bit more funny and a little bit more enjoyable aside from the amount of predictable Outcomes as well as ridiculous amount of outcomes that happen in this episode. This was a pretty good time I like the idea of monsters actually bidding for people like that was kind of cool Just showing them all on computers and just being like all hungry and whatnot The one thing I was kind of thinking though the whole time is how do the auctions work?  Oh look that box is leaking blood I'm saying the idea is actually a pretty cool idea just when you think about it There's a few issues that would possibly happen in the postal system. Anyways, I'm gonna give this episode a five out of seven I thought it was a good time. I thought it had some good humor. I had some cool elements It was a filler episode but Admittedly I like the ending with Sam for once being the negative one kind of having the rules reversed This has happened several times before the brothers have switched their emotions and their outlooks on life and blah blah blah but I Have a hope or a thought an inkling that this is leading up to the Supposite possible end of this show kind of some foreshadowing it might just be nothing it's been that before but One could wonder anyways guys I hope you enjoyed this review if you liked the video leave a like down below And if you're interested in watching more of my supernatural reviews hit the subscribe button anyways guys, that's all for me See you guys next time


From the Bellagio Hotel in Las Vegas, it's theCUBE covering UiPath. Forward 4, brought to you by UiPath. Welcome back to the Bellagio in Las Vegas. theCUBE is live. I love saying that, I'm going to say it again and again. theCUBE is live. We are at UiPath Forward 4 at an in-person conference. Lisa Martin with Dave Vellante. We're going to be talking about the vision of the UiPath platform. We're very excited to welcome to the program Ted Cumbert, Executive Vice President of Products and Engineering at UiPath. Ted, welcome to the program. Thank you. It's great to be here with you and it is great to be live. It's been so fun over the last couple of days to spend time with our customers. It's just been so great for the team and everyone. I can imagine what it was like for you yesterday on main stage, looking out to a standing room only crowd for the first time in probably 20 months. Yeah, and that was actually quite fun as you know, speaking to a camera. You just don't get the same energy. You got to muster all of the energy yourself.  Exactly. Well, from a customer perspective, I know that the number is now over 9,000. You guys have an incredibly high retention rate. We're talking 96 plus percent. A significant portion of revenue comes from those existing customers. We talked to a whole bunch of them yesterday. We've got more of them on today. We're hearing that validation from the voice of the customer on what UiPath has been doing. Talk to us about the vision that you unveiled yesterday, strategically, what some of the feedback has been from some of those folks that are here in person. Great. Well, so let's start the story by looking back first and talking about the phases of the market because I really see us entering phase three of the automation market. Phase one, I'd describe as the core RPA platform. And that was, you know, the elements of that are the runtime, the robot, the thing that knows how to execute these workflows. It knows how to do UI automation. It knows how to do API integration. It knows how to do long running workflows and interact with humans, developer experiences, low code visual developer experiences, plus the orchestration. And that gives the enterprises the manageability and the governance. I'd say that was phase one. Okay. Daniel and the team then at forward three, the last this community got together right here in the Bellagio, at the end of 2019, rolled out an expanded vision, which we talk about as the platform for the full automation lifecycle. And that added elements of, let's help end users engage more easily with their automations. They engage with them on their desktop. So they need to think of it like a start menu, like experience with the UI path assistant. They need rich user interfaces. So we introduced a low code application platform, UI path apps. They want to interact with natural language. So we integrate with chatbots. And then we find a lot of customers, when we initially start their journey, they have a lot of knowledge right away of opportunities. They see things in the call center, front office, back office, finance department. They see things to do. But then they say, help us find more opportunities to automate. So we have this old discovery area to help them find more opportunities to automate. So this vision is this end to end lifecycle that covers the core platform plus engagement and discovery. That's the journey we've been on over the last two years. And I think part of what we talked about yesterday was just how we're continuing to fulfill that vision. And then that set the stage for us to talk about a few innovation themes as we look forward to phase three. That I would emphasize we're still building out this end to end automation platform covering the full lifecycle. But we do see some pretty important themes going forward. Such as? Well, we'll start with four, kind of four key themes. One is enterprise grade platform. The second is platform expansion. You know, healthy platforms grow and expand what you're able to do with them, what developers are able to build for. The notion that discovery becomes more continuous. I liken it to a nervous system for the processes and the work of the enterprise. It's always there watching, helping you find opportunities. And then we talked about this last concept which is semantic automation. Which is, I'd say, the real big idea in the forward-looking vision. I wonder if we could, in your keynote yesterday, you talked about the fragmentation of the enterprise, software business, and of course, perpetuated by the SAS. Easy button, great. I got all these different SAS products. And you're sort of creating a layer across them. Sort of a couple questions there. Maybe you could just sort of describe that dynamic and how you guys think about it. And then I got a follow-up. Yeah, I think, if you're a historian, you look back and say, in the past, a lot of business process centered around the deployment of a few monolithic applications. Your ERP, your CRM system. And then if somebody in another department wanted something different, another part of the process, you might customize or deploy an add-on. Now, what's great about the SAS era is we have a lot more solutions that are now purpose-built toward a lot more functions, a lot more processes are being automated, and that's fantastic. But what's that done is it's expanded the landscape of applications now that enterprises hold typically. And that's where you get to the issue of fragmentation. And the reality is, is that the real work in the enterprise, the real work people do every day, and the process, it spans all of that stuff. And I think as an end-user, you resonate with this, because you will work with desktop apps, you'll work with these SAS apps, you'll work with these line-of-business apps, you'll have to navigate to this one, cut some data, copy it, paste it over here, you'll work in Excel, you'll send an email. And that type of work, nobody really wants to do that. And especially if it's something you have to do all the time. So automation, we are in fact not the first platform to walk in the enterprise's door and say, hey, we can help you integrate your systems, we can help you automate business process. This is, this goes back to the early 2000s and the arrival of the first-generation integration products. So what's so different about RPA and these automation platforms in our automation platform? The difference is really being centered on UI automation. It's got three key attributes that I think are super important to understanding why this is such a different phenomenon. The first is because it automates via the UI, it can capture the actual work people are doing so we can emulate the actual work people are doing. That's number one and that's critically important. The second thing is it can reach anything. If you've got an integration problem, you don't want connectivity to 82% of your systems, you actually want to cover everything you need to cover. And UI automation can reach anything that has a user interface. And then the third thing is because it's emulating the work people do, it's very intuitive to develop for. And as such, the developer experiences are very easy to use. Don't require traditional coding skills. Customers tell us that unleashes more capacity and they get really fast time to value. And that's kind of a win-win-win. And the interesting thing then is if you think about it, the business wants to move forward at a certain rate, but that application's estate is only going to move forward. It's going to move forward kind of at its own pace as well. And this automation layer can really deal with the sheer between that. It can help you move forward quickly up here while you're waiting for this layer to evolve as well. I wonder if you've mentioned kind of history if you look back. And you're somebody who spent two decades plus at one of the great software companies. If you think about the great software companies, Microsoft, we know how they got there with the PC ascendancy and then took it to new levels. Oracle, SAP, Salesforce is vying to become a next great software company. Bill McDermott wants to take service now in that realm. And I have a sense that with your vision of a fully automated enterprise, you guys could aspire to be a next great software company. I think you're humble, but you're bold. So with somebody who has a historical perspective on great software companies, what does it take architecturally specifically to be that next great software company? Well, it's a great question. You know, I said yesterday to the audience that the reason I came to UiPath is because I do believe this is one of the most significant platforms of this time. And I do believe, as we just talked about, it's UI automation is the central element that's really making it different. Now, all these other technologies and capabilities are super important. We announced yesterday a new service in our platform called the UiPath Integration Service. We acquired a company named Cloud Elements six months ago, an API integration company, and that is now landing in the UiPath Integration Service. We've always had API integration as a part of our platform, but now we've got this richer catalog, we've got new services for developers, and that only expands what they're able to do. And as we talked about the future themes of innovation, we talked about this platform expansion, and I assert as a historian, healthy, vital platforms grow and they grow on their own, just naturally, because there's always some adjacency where if I bring that in, I can enable my community to do something different. They can build something different. And so that was why, for instance, let's embrace more API integration surface area. Why did we enter low code application space? It's because we thought there was a lot of power for our community to now be able to build rich user experiences. Why did we bring AI and ML in as a first class citizen with an MLOps platform? We're not trying to be a general hosting of models, but we want to make it easy for those skills to be used. So there is a thing just about just continuing to expand what you're able to do, but there's an important thing you got to do as well is you got to stay true to your personas and your user community. So anytime we do this, we think, yes, we're bringing in API integration, but we're not trying to be an I-Pass. We're trying to serve our RPA developer community, and we have to be true to that developer experience and the thing that's made us special. So we really focus on landing it in an integrated way that really helps our community do more and more with the platform. Do you feel like you're seeding a new breed of developer or maybe your ascendancy is coinciding with a new breed of developer? Let's say there's a general trend and we label the general trend now low code, no code, which I frankly think as a historian is just a new way we're talking about the idea that you want to continue to simplify developer experiences. And if you do that, everybody likes it and it does enable you to grow the pool of developers that you have. And in our case, there is a new, this is a large and growing discipline if you looked on LinkedIn, community of RPA developers. There are new personas, new jobs being built around this platform today. We're blessed with a very, very large community of developers. This is a new discipline. Over a million, I believe? Yeah, I think those are the range we're talking about. Yes. And it's amazing asset for us as well as we do new things. We've got community ways they can engage with community builds and previews. It gives us a lot of expertise to tap into as we're deciding to do new things. I was going to ask how influential that large community is and the product direction roadmap, the vision execution. How influential is that community? They're immensely influential and that goes from when we're early on and we're ideating and we're talking to our customer advisory boards or customers one-to-one or as features are starting to come out in community previews, customers are an instrumental part of that journey. I think this is one of the things if you spend any time with Daniel at all, you'll understand how important customer centricity and true customer centricity is to him. And I think that's a, I only joined the company 18 months ago, but I walked into a company that I really understood, knew what that meant. The words are easy to say, but really being that and having customers shape who you became, I think that's something that the company has done actually quite well. The CrowdStrike announcement was notable. I'm interested in how you're integrating that. I know that's endpoint security. I know you've done a lot of work historically in identity access with Auth0 and doing some deep integration there. How should we be thinking about the CrowdStrike? It's more than just a press release. It's engineering going on there. What can you tell us? Yeah, that's a very important thing for us. I talked about another one of the key innovation themes is enterprise grade platform. And that one might seem like, well, of course he's going to say that, but we do want our customers to understand we know this is a mission critical platform. And it's now integral to the work people do. It's integral to the process. If it ever fails them, that's a mission critical failure. And so we're making deep investments like this. This partnership at CrowdStrike is about delivering a solution that, an endpoint protection solution that understands robots. And they are not unique in that, unfortunately, they are subject to a lot of the same forms of attacks that humans can be subject to. And, but they're also unique and then need unique protection. And so as we came together with CrowdStrike, one of the important elements for us was let's enable there, in this case, Falcon platform to understand robots. And let's do it as a seamless part of that experience. And so there's a few elements we deliver together. They have a lightweight agent that gets deployed with a robot. And then most importantly, we provide metadata. We provide data back to log information back to CrowdStrike. So now a security analyst sitting in the Falcon console knows when there's an activity that's related to a robot versus related to a human. And then there's also specific mitigation actions that are relative to a robot. You may want to just block that instance of that automation from running again or you might want to block all instances from running again. And so there's specific mitigation, there's specific visibility we're providing to the security analyst. But then it's all done in a seamless way. The customer, when they have 2110, they have the latest Falcon release, there's no extra licensing. They just have those two products and it just works. How much was that accelerated? The last year, 18 months, we've seen the tremendous change in the security landscape. Ransomware has become a household word. Everybody knows about Colonial Pipeline. We're seeing so much activity there that it's a matter of when customers get hit, not if. How much of the events of the last year have accelerated that partnership with CrowdStory? And how you're enabling RPA to be that protected asset that the organization needs to ensure is protected? It'd be fantastic if we ever got to a point where we felt like security was a solved problem and it won't ever be. And this is why we felt like we needed a world-class company to partner with who's an expert in this landscape and they do their part and we do our part. That was why we took this approach because we know we're not going to have and build that expertise. We know about robots. We know about that side of thing. They understand security. And by working together, we can connect the dots and we can hear everything they understand that we're never able to replicate. How unique is that sort of robot optimized so the security? It's as far as I know, it's the industry's first solution. It's important to know that endpoint protection does provide protection for robots today. And all of them do, but it doesn't know about them. It can't tell the security analyst that was an action a robot took versus a human. And it doesn't know how to take specific mitigation steps. And that's the exciting thing we've done here. So to my knowledge, it's the first endpoint security offering built for, as we say, the robot workforce. And so you bring engineering resources to create that value and collaborate with CrowdStrike? Yeah, yeah, we both did work on both sides. It's been a really fantastic partnership and it was great. We had a video from their Chief Product Officer as a part of our discussion yesterday. It's been a fantastic relationship and partnership. So it's one of those tricky things. That's IP that you're developing with CrowdStrike. At the same time, you nailed it, right? It's never going to be solved, but one of the ways in which we can counteract the adversaries who are extremely capable is sharing. So is that IP that gets shared, or is that IP that you keep for yourself? We're both doing what we do. They're IPs, they're IP, our IPs are IP. And so it's all good there. Focusing on your core competencies. Yep, exactly. Well, Ted, thank you for joining Dave and me today talking about the vision, where things are going, the excitement, the partnership expansion. A lot of activity since the IPO. We appreciate your time today. Very exciting times. And as I said at the open, it's great to be here with you. Great to be live. Isn't it great to be live? It's great to be live. Really is. For my guests, I'm Lisa Martin. We're live in Las Vegas with UI Path Forward 4 at the Bellagio. Dave and I will be right back with our next guest.


Good afternoon, folks. This is Larry Pesavento giving you the mid-morning update here for the stock market and all the other markets. It's an OTMMB, boys, folks, over the map. Everything is all over the map today. We're having some pretty wild swings, and the most wildest of them all is coming in Treasury bonds, folks. We've made a 50% retracement. I'm going to be covering that very shortly on my show, but pay attention to that. The rest of the markets, we're still up on the day in the Dow Jones industrial average. Yes and P is lower. The NASDAQ is lower. The NASDAQ is so weak, folks. If you took a look at it, you'd even begin to think that it's still in a major bear market here. Gold is up about $13, and we've got silver is up about $0.53, and crude oil is heading to the subbasement again, looking like it's heading toward $64, is what it looks like here from charts that we're looking at right here as we see these things unfolding here today. So those are the things that we're paying really close attention to, and I think it's important to remember, folks, we're in the Christmas season now, and believe it or not, this is when volatility will increase because there are less people around trading, and that means there's pockets of illiquity. So try to remember when you're putting these orders in that you must put your stop in. You might get a bad fill, but at least you'll be out of the market if you're wrong because if you don't put a stop in, you're telling Mrs. Market that, hey, I know where you're going, so I don't need to put a stop in, and Mrs. Market does not like to hear things like that. So be sure to remember that it's not how much money you make, it's how much money you don't lose. That's the key to what you're looking at here today, folks, because we've got some really big markets coming for 2023, and we want you to be around. By the way, Basil Chapman, December the 15th, don't miss it, folks.  He's got some great stuff, all so much material that you'd be hard to absorb at all, but he's going to do a great show. December 15th, Basil Chapman, don't miss it. The best $295 you can spend, that's a cost of a good meal in New York, a half a meal in Austria, and a quarter of a meal in Bangladesh. Where is the place at Monte Carlo? It's where it's the most expensive. So anyway, that's what we're looking at here this morning, so I want you, folks, to stay tuned for my show 24-7, and we'll try to cover this stuff. My guest is Jeff Hughes of Alpha Insights. We'll be right back.


So Appreciate everybody for coming along maybe sneaking out of the keynote a bit early the CERN presentation was fascinating I thought that was a really cool stuff. So it's it's good to be here. This is my sixth open stack summit myself I've been with new lodging networks for about a year and a half You're in three quarters, but uh with viata before that and juniper before that And so I've been around these things for a little while and it's just it's amazing to see how it's grown and and How it's gone global and and how it's gone beyond the what three or four hundred people we had in San Francisco at the first event I went to so anyway I'm a networking guy and and and I've been passionate about networking and data center networks and and worked on some Networking fabric things and have kind of evolved that technology and what I've been working on into some network virtualization and SDN things But the really interesting part of that conversation isn't necessarily IP routing and transport and things like that It's about how we start to abstract the network into a really consumable model for DevOps and IT people So that's really what SDN is all about. There's lots of arguments over Open flow and various protocols and what's valid and what's not and is my controller open source or not But really what it comes down to is how I represent that network as a service to users And so this is what newage networks is all about and what we're focused on We do some really cool things at the networking layer that I'll talk about a little bit about how we can kind of enable a higher performance Neutron environment so that Neutron networks become production ready become enterprise ready as we all know as if we've if we've Worked with OpenStack at all the base level neutron things even in Juno is still pretty lacking Has some serious scale issues and and some limitations what I can and can't do when I get into a cloud environment That's very very multi-tenant as we've learned working with a lot of large cloud service providers around the world Those limitations with multiple bridges and namespaces and things like that really starts to affect performance So we're doing some pretty cool things. We think to fix that leveraging a lot of routing technology from our parent company Alcatel Lucent and then Wrapping all that in this nice framework. That's really well aligned with the the Policy framework that the network policy for neutron framework that we're also contributing to so I'm gonna do a quick overview of the solution And then a demo of our our application framework our application policy framework that we're shipping today Even in advance of the neutron work being complete. So Really the driver for all this and why SDN exists is that data center network is fundamentally flawed It's it's a bit broken. I've got a virtualized compute and management system that lets me deploy resources quickly I still go through a lot of manual process with trouble tickets and teams and groups of people to have to configure things and Request V lands and have somebody touch the firewall and the router and the switching so This really slows down what I can do This really limits the footprint on where I can deploy my compute environment Dynamically because if I have to wait for a trouble ticket to get completed It's it takes too long. We've done a lot of things with SDN or neutron or other elements where now Maybe my network is represented as an API. I've accelerated things a lot I have a programmatic interface that maybe I can start to incorporate into my DevOps tools But it also could introduce some new complexities Maybe I'm forcing my DevOps guys to worry about networking Like this network is a service environment which neutrons is Amazon Web Services in the VPC context is very similar in that now I'm forcing my DevOps people to learn how to Provision networks. I'm presenting an interface to them like in neutron that says Hey DevOps guy who's really good at deploying applications and servers go create a network Go assign IP addresses go configure a router and assign ports to that router. These are a lot of steps that require Network topology awareness and network configuration awareness that may be a DevOps team is not expert in and so it's not really abstracted into a Consumable bottle and it puts a lot of burden on that DevOps group to learn new concepts and have to manage new things What the DevOps people are good at is understanding their applications and how they need to be grouped together And maybe how they need to talk to each other They don't care that I use a vlan or a subnet or a router a firewall They know my web servers and my app servers and my database servers need to be in different Segments or different groups and I need to have some connectivity model between them with potentially some security policy that defines that So the DevOps team really needs a simpler more abstracted view and the neutron group-based policy extension stuff is Intended to address this and there is a lot of good work happening around that And I believe it's an extension that will be available in a later release of Juno And then it should be much better a little bit later on The new guys have been contributing to this and working this and then delivering product that actually provides these Functionalities for about a year while we've been shipping this product for about a year and a half But what this gets us to is this policy approach to networking and by policy I really just mean templates, right? I can define my network service as a template Maybe my network administrator actually makes those templates Configures all that specific routing detail because the network administrator knows how to do that and knows what's required I can have my security audit team review the templates to make sure they're compliant And then I just give those templates to my DevOps guys to deploy over and over and over again through a really simple API call or simple API Interface and so this is what our what we think policy-based networking is all about So this gets us to this mode where my tenant or my application request request compute resources that happens instantly there is a call to a network API that New wage would deliver and That network API would just consume those templates that were predefined and all of the networking is done dynamically and automatically and rapidly The new wash solution is is a bunch of software and a couple of pieces of hardware that actually deliver on this to allow you to build infrastructure we start by leveraging open v-switch down here at the base where This is our we use the base kernel level open v-switch on KVM We've also got flavors for ESX and for Zen server and I can mix those together in the same environment But we use open v-switch We do some software on top of open v-switch where we actually replace that user agent with our own code and Turn that thing into a distributed virtual router So we're doing distributed routing and ACL capabilities as well as switching on every host That's all controlled by an SDN controller Which is actually an operating system for a very from a very mature advanced BGP MPLS router so all of my routing functionality is available there today And then that sits on top of that is our policy engine or this policy framework the GUI I'm going to show you in the demo is the user interface to that But there is a full set of REST APIs underneath that GUI that you can use to program There's a neutron plug-in that talks to the VSD the policy engine. There's also some v-center and v-cloud director Integration and we've got a cloud stack plug-in now as well and the thing about the new wash solution is I can blend and mix those things together So we think what the requirements are for a production open stack network Something that I can do in production today with rock solid available stable networking are kind of three things I start with performance and deployability and by performance I mean I need to be able to do security grouping and multi tenancy at scale I need to be able to support lots and lots of high-speed flows I need to be able to saturate that 10 gig length that I bought on that server I don't want to have to choke that thing back to four or five gig if I'm limited by some Multi-level kind of switching layer I need a rapid convergence performance if I'm going to build a large-scale cloud environment And I have a dr scenario I have to be able to stand up tens of thousands of new VMs quickly and not wait hours to do that And I also need a way where I can integrate into existing environments because in the real world in an enterprise Not everything's virtualized. Not everything's open stack. I still have some VM. We're over there I still have a bunch of mainframes over there I have to be able to tile those things together and so to do that I need to be able to leverage some gateways and we deliver on all of these things One of the problems with with open stack is this network node where I can do some simple L2 switching between two common VMs on a common subnet But if I have to route between them, I've got to go back to that network node This creates a lot of congestion issues when I have to go for north-south traffic out to the WAN and also with east-west traffic between VMs the distributed virtual router in Neutron in Juno starts to address this east-west use case It's not all that mature. There's still a lot of work to do there But it is a step in the right direction But the north-south use case of getting in and out of the environment is still not totally addressed Also the multi-tenancy aspects of needing multiple bridges to use IP tables to carve up tenants on a host is not completely addressed by DVR So the new wash solution actually turns that open V switch into a full-blown L2 through L4 router So we do IP routing. We do ACL enforcement. We do VRF So I've got isolation of IP space and routing on the hypervisor itself Controlled by a very very scalable control plane that can manage hundreds of thousands of servers in a single cohesive environment So I eliminate this problem of needing to go out of the server to get between subnets I can do low I can do local routing IP routing and transitioning between subnets Without leaving the host because I have routing on the host itself. I Can go directly and choose the best path for east-west traffic between hosts Just using a VX LAN tunnel in between these two servers and my north-south traffic is directly integrated with the LAN router This control plane that we're using is an OS from a very mature router the Alcatel Lucent 7750 Which is deployed in just about every carrier around the world if you're pinging an LTE network right now You're probably using a 7750 router So this OS is very mature very proven. We're using Multi-protocol BGP and some MPLS EVPN context to advertise these virtual overlay networks to a MPLS PE router at the data center edge So if my data center is behind a router I can advertise my virtual networks directly to that router and tunnel directly to that router with an automated Advertise kind of control plane interaction So I don't have to manually configure everything on that router to support these services I don't have to go to a VLAN gateway and then out to some trunked interface to get to that router I'm directly integrating with that router. So very powerful in how we handle east-west and north-south traffic When I get to control plane of performance. So in this model I'm tackling that flow and that IP routing we can saturate a pair of 10 gig interfaces pretty easily on this And we're pushing towards 40 gig and then using some of these VX LAN off-load nicks that we see out there 40 gig and potentially 100 gig is well within reach using open v-switch and then of course We're across DPDK and some of these other technologies to look ahead of that on the control plane performance There have been some published studies and reports that say just the raw neutron networking that was in Havana I Would get about if I wanted to start say 75 kvm's in about eight hours I'm seeing about two or I can start about 75 kvm's in eight hours, which is about two and a half vm's per second We ran into a customer on Wall Street in New York City that wanted to test a larger scale than that or wanted to test Some scale where they have 65,000 vm's running and then they restart the network stack And they wanted to measure how long it would take to bring things back up again on the base neutron They saw around two and a half vm's per second They tested one of our competitor solution and that brought that down to about 18 vm's per second But then they tested the new wash solution and we were able to bring up All of those 65 kvm's in eight minutes, which was about 135 vm's per second So in order of magnitude faster, we do that by using Multi-protocol BGP and some some techniques within BGP to advertise security groups across the network Using this federated control plane using the same scaling techniques we use in the internet itself So, you know very very powerful highly available very proven and can support just about any large-scale environment that we've seen so far On the openness front, which is the other thing we one of the other things We think we need for a production ready environment is I need to be able to choose I need to be able to run open stack, but also blend in some vm where I need to maybe use some cloud stack here And there where I need to but I need to have in a cohesive networking system across those I need to be able to choose gateways to connect to vlan based infrastructure that might not be Virtualized and I want to be able to do that with multi vendor hardware So we have our own top of rack device I can also use a Rista and cumulus and a couple of others to enable that kind of environment and I need to be able to provide Security and other services through partners So we've got a very advanced service chaining feature set that lets me connect in third-party firewalls DPI devices building some IPAM integration with some External vendors as well and then the last sorry so more on the open thing on the last thing I need I'm kind of rushing because I do have a six minute video and I have six minutes left in my talk So on the policy abstraction front I need happy users and happy DevOps people using this system And so to do with that I need some sort of really IT focused interface to this environment Supporting the policy framework that that neutrons developing but delivering on that today So I'm actually going to jump real quick into the demo This is recorded because you never know how internet connectivity is going to work What you're seeing on the screen. Sorry. Let's try this again. What I'm seeing on the screen. Are you guys liking that? Let's find there we are Make that big So this is our GUI over here on the right and then I've just got a terminal that we're going to do some neutron commands in a minute This is the new watch VSD user interface. It's multi-tenant multi-user I have a care service provider view or a enterprise administrator view that will let me affect Security rules and network topologies for all my users and then I can allow my users to log in directly to the GUI or give Them direct API access or give them access through the neutron plug-in to go consume the things that the administrator would create So what we're doing here is we're just defining an ACL that says from anything to the enterprise domain I'm going to block tell that and this is an administrator creating this rule So it's going to be enforced on all of my tenants VMs and all of my tenants networks And they're not going to be able to modify that rule. It's it's sort of a master rule that's going to be looked at first so This will get created here and Applied and we'll see I've got this applied on a couple of other domains domains or what we call tenants or user is in the system So I see I've got a couple rules already built here now. I'm going to switch over to the our application designer interface now so Now I'm going to go create this application stack and this is really similar an interface to that policy framework stuff that I was talking about before where I've got a user down here Just created a new website template from that He's going to create an application tier and call it web We're going to create another application tier and call it Logic and then we're going to create another application tier And I think we called it DB But these are just groupings where I'm going to connect servers to and then I have some predefined security rules or contracts in the Neutron a policy framework definition that will allow certain traffic types between the web tier and the logic tier in the database tier And so I'm allowing my SQL. I'm going to allow some other things I have a macro that's defining my public internet or my floating IP space and I'm going to assign a rule to that as well I'm going to make a contract here. That's going to allow HTTPS to go in and out of that and Then I'm going to actually create another little network macro that says from my enterprise group I'm going to allow SSH and so these are predefined macros are pre-divine Network zones that the administrator created and then this would be a user of a system just creating these Templates based on their application needs. So I'm allowing SSH here So I've created these as I switch over and go back and look at one of those domains I used I see that I created a few ACLs here So those ACLs show up and I can go and look at those rules and I can reorder them as an administrator if I need to So those things are automatically applied based on what was defined in that previous app designer interface now I'm going to switch over here to the Neutron side to the open stack side. I don't have any VMs running. There aren't any networks Created yet, and I've got some images here We're going to start a we're actually going to use the new edge extension to our neutron plug-in This is some extensions We have where I'm going to bind essentially create a port and bind it to one of those tiers in that app designer thing that I did before so I'm creating a new app called website And I'm going to bind that to the tier of web over here in the app designer And then I'm going to create a you know that tiers called web server And now I'm going to go boot a VM and attach it to that port that just got created through that bind process So booting a web server. I'm actually doing it in a container because I can and We just used a small server to do this demo So it was easy to run that because we do support Docker and Linux containers in our environment as well But so I'm just booting that VM, and I'm attaching it to the web server I'm going to do a Now I see the neutron port list down here. I see I've got that port Created and it created a network and so what just happened is my devops guy didn't have to go create a Network in a subnet and a router and a port all that stuff got created automatically by binding Using the nuage network bind function to just consume one of those one of those Groupings in our app designer function and and so then by starting that VM the network is automatically created The subnet was created or the router was automatically created The devops user didn't have to go step by step by step and design all of those networking things the IP address is automatically assigned and Everything based on the templates that my administrator would have defined now. I can see that that VMs up and running I have an interface on the nuage system to monitor my VMs and see what's where I'm going to speed this up a bit. I've got all kinds of statistics I can monitor on those VMs and on the networks that created we can go collect stats We store them in a Hadoop based database as part of our policy engine so I can do monitoring and billing and threshold alarms on that as well I'm going to go create a couple of more VMs. Those all get started pretty quickly and then Hopefully I can run this through without going too much over my time But so now I've got a couple of other VMs up and running Attached a couple of other ports on the other tiers on this thing What we're going to do in a second here is switch back over to the VSD interface our nuage interface and See that we also have a logical topology view of this network that administrator can use to look at I've got these other VMs up and running. That's what we're showing here Now over on the domain side. I can look at my design I see the logical topology of all those subnets and all of those networks that I created I can look at the VMs I can see which access lists are applied if it Administrator wants to change an access list on a running environment The administrator has a master view of that and can implement that change and then as I go back and start deleting these subnets and deleting these VMs I See them get pulled out of the VSD and everything gets cleaned up automatically so Back to presentation mode here to kind of finish up for you guys So to kind of wrap things up we're actually delivering on this policy-based framework Today we've got abstractions for it users that make them happy. We've got a very high performance very scalable solution That's deployable. We've got a lot of customer references of things that are using it And then it's an open solution that lets me mix environments and choose best-to-breed hardware and also choose multiple cloud systems to work together and finally Directly upstairs from us at 1115. We've got three tracks in a row First numer G is one of our marquee customers here in Europe is going to talk about how they're using new agent open stack together Then Jonas one of the guys from my team here in Europe is going to talk about some use cases and private cloud things and some things We're seeing in the banking environment with SDN and and open stack and then finally Dimitri Stiliatus our CTO is going to talk about scale and kind of the future of networking and SDN for open stack So thanks very much for your time. Follow us and follow me on Twitter We have a booth down at the end of the hall and please attend our sessions this afternoon. Cheers


Hello, this is Nick from Laptop Media and today we will show you how to open the ASUS ZenBook 14 Flip OLED, UP3404. In order to open the device, you need to undo seven Torx head screws. There are two hidden Phillips head screws beneath the two rubber back feet. You have to unglue them and then you can undo the two screws. After that, you can pry the panel with a plastic tool. The easiest way to pop the plate is to start lifting it from the zones around the hinges. Please remember, it would be of great help to us if you just hit the like button and subscribe to our channel. That would motivate us to make even more and better videos for you. The battery is a 75 watt hour unit. To remove it, pull out the connector from the mainboard. The next step is to undo the six Phillips head screws that keep it fixed to the chassis. The capacity is enough for 14 hours and 35 minutes of web browsing or 11 hours and 7 minutes of video playback. The memory here is soldered and you get up to 16GB of LPDDR5, 4800 MHz RAM in dual channel mode. For storage, there is just one M.2 slot for Gen 4 SSDs. The NVMe is covered by a metal plate that has a thin thermal pad on the inside. The cooling system comprises one fan, a thick heat pipe, one decently sized heat sink and a heat spreader.


An epidemic is coming. It will consume humanity. Gotta move!  Chaos is inevitable! I've been expecting you.