Hello and welcome to the session. I'm so excited to be joined by Mia and Maha to share with us a session on building appreciative narratives of equity and care in the open. This is one of our first workshop sessions here at our conference today and I'm really looking forward to seeing you all participate. The session is going to run a little bit differently and I'm going to let Mia and Maha explain in their own time how things work. But for now, a warm welcome to you all. I'll post some helpful links in the chat in a minute for all those who've already joined and I'm going to hand over here to Maha and to Mia. So welcome to you both. Fantastic to have you with us and enjoy the session. Thank you, Maren. Thank you, Maren. Welcome everyone. Feel free to introduce yourselves in the chat because it kind of feels weird that we don't know who is here. We know Johanna Funk is here. Hello. Oh great. We can see you when you post in the chat so it's nice to see that. And feel free to tweet about the session. These are our Twitter handles. We're going to be talking about building appreciative narratives of equity and care in the open. And Maren will put in the link to the slides. Hi Martha, hi Wendy. Hi Wendy, hi Martha, hi Francis, hi Laura. Yeah, all the lovely people that we care about equitably. Hi Lorna, hi Gabby. Hi Sarah, Lorna, Gabby. Okay, we need to stop, right? Yeah. It's very difficult to stop, but yes, okay, cut off. Up early from Texas. Okay. This is a little tricky to navigate, but the first thing we want to ask you is, how are you feeling today? Tell us in the chat. Hi Katherine, hi Kate, hi Jonathan. It's really hard not to do that. I know. Tell us in the chat, how are you feeling today? Hi Joe, hi Johanna. Everybody's saying hello. Oh, hi Patricia. So happy you're part of this whole entire conference. Relief to be with all of you. Yeah, I feel that kind of relief in meetings with people who are kindred versus some of the work meetings that are stressful. Yeah, yeah. Feeling good because it's spring. Yeah. Physically exhausted and spiritually excited. I can relate to that. Grateful for small kinds of justice here in the US, yes. Yes. Waking up with a sense of relief. Waking up with a sense of relief that there's accountability. Oh, Debbie's breaking away from supporting duty. Sneaky. Up since 4.30 a.m. Oh my goodness. Some people need coffee. Yeah. Yeah. Good morning from this side. Good afternoon to many of you. And yeah, there's probably other time zones as well represented at some point. So hi everyone. So for today, we just did the checking in on how you guys are feeling. Keep that going as long as you like. Like keep using the chat as long as you like. Apparently we can't type for you in the chat, but Marin can type for us. So if we want to type to you something, we'll do it. But we can see your chat as you can see. And then we're going to talk to you about the equity care matrix that Mia and I started working on at the OpenEd conference, but we're developing it further because this is the OER conference. So we have to do it. And then we're going to head over to Zoom to do a breakout room activity that hopefully will be fun and interesting for all of you and then come back here in the main room. We're going to try to keep time. Hopefully, inshallah. If something needs to figure it out, that hopefully will be all right. So we wanted to start with a quote from Bell Hooks. Teachers who care, who serve their students, are usually at odds with the environment where and they teach. And so Mia and I, before our OpenEd keynote, tweeted this out. What is equity without care? What is care without equity? Some of you have actually participated in responding to this and we're going to show you some of the tweets that came from that and the model that we developed and where we're going with it and how we want to expand it. So the first question we want to ask you is, what is care without equity? And we'd like for you to type that in the chat after you have a think. What is care without equity? Even if you've answered it before, you may think something different today. Yeah, we know about that. It could be patriarchal. Johanna says it's performance. Pity, paternalistic, really important words there. Thank you so much, Marin, for highlighting those comments. That's so cool. Yeah, performative. Performative and performance is very funny because Mia and I, recently, we're talking about how Sarah Ahmed uses that term. But I think she uses it for equity without care. So it's interesting that people, colonial, I love that one. Lots of hard work, Tanya. Yep. Oh, Anna is AC Page. I just realized that's Anna Page. Tanya, lots of hard work. A mask, Autumn says. I like that. Something we see a lot of here in the States. Sarah is saying lots of care is not equitable, like family relationships. That's a very good angle to take on it as well. All right, I move on to the next one. Unacknowledged labor, Lorna says. Unacknowledged labor, for sure. And what is equity without care? So we want you to think the reverse. What is equity without the care? No recognition of structure, Catherine says. Laura Gibbs says scary. There's infantilization, which I think is care without equity, right, Lou? And Anna Page is saying exclusive, which I think is also care without equity. Gabby says an academic exercise when thinking about equity without the care. That's interesting and good. Lip service, Teri says. Yeah. And Lorna is saying both are performative, like things both are performative. Joe Murphy is saying algorithmic. Oh, Catherine was saying that was the first question, Mia. Sorry, too slow. There might be lag too, so. Matt's talking about Spivak and speaking for people rather than letting them speak for themselves. There's instrumental from Francis, flag waving from Laura Gibbs, soulless from Page. A spreadsheet from Johanna. That was so cool. That's a new one. I don't think I've heard that one, but I know what you mean, like checkboxes, right? Checking boxes. Yeah, it's all about ticking the box. Yep. I love it. Yeah, exactly. I think we're going to use that one. Can we use it, Johanna? Permission to use that one? Because we haven't heard anything like that one. Actually, is there a way to save this chat? If someone can save the chat for us, I'd be very, very happy. And then we'll ask permission to reuse some of these terms. Okay. So in the crowdsourcing, so many amazing responses came, just like this moment we're having now. We'd like to highlight Kate Denial's response because it sort of opens up both directions. So she says, care without equity is fundamentally unjust. It's a fundamentally unjust practice that tries to place a bandaid over a deep rupture and pretend the injury is taken care of. Meanwhile, when you're thinking about equity without care, she's acknowledging that it can be harmful. It privileges a goal over the humanity of those engaged in reaching that goal. And then Kate Bowles reminded us that both care and equity are design choices made by those with the power to choose how others will be treated. So neither of them fully challenge the power, the person who's powerful that gets to choose. Both are trapped in the nexus of power. So we often refer to Nancy Frazier's work about the concept of poverty of participation. So we love this quote from Desmond Tutu, I'm not interested in picking up crumbs of compassion thrown from the table of someone who considers himself my master. I want the full menu of rights. So it's about this coming to the table, who's invited to the table, who's listening at the table. That's the metaphor. But we would like to argue that, you know, what about the creation of the menu itself? You know, who's choosing the ingredients? And we also found that Mel Nottings has a concept of care with parity of participation herself, because she says do unto others as they would have done unto them. And so this is sort of trying to oppose this patriarchal. Is it patriarchal? Patriarchal? Anyway, patriarchal approach to care where the carer assumes they know what the other wants. But actually, this in this case, listens to them and gives them the opportunity to say how they would like to be cared for. So Kano Algi says, care is ameliorative and often the responsibility of or experienced by the individual, while equity is transformative and has systemic impacts. So often we think of equity in the realm of policy and institutions, care in the realm of individuals. And so me and I, when we were looking at all these quotes, we came up with this matrix that we're still developing. It's always a work in progress. And so this is the latest version of it. And so we're thinking equity without care is what Tanya Elias talks about in the sense that it could be structural, could be ingrained in our ways of thinking so that it cannot be undone by carelessness. So she's thinking of it as systemic in the same way that Tsukaina said. And Donna Lanko also talks about this. She's like, I don't need my institution to care for me. I need equity. I don't need empathy. I need justice. And I kind of feel this is a little bit of what just happened yesterday, right in the US. You need justice, empathy of individuals. You need justice in a system, right? But these are the positive ways of looking at it. But there are also ways of seeing it as tokenism, diversity, theater, performance and things like that that you all have also mentioned and window dressing, lip service. Go ahead, Mia. In the lower, like bottom right hand corner, you see that care is paired off with inequity. So, you know, think the idea of giving care in a context in which maybe that isn't covered in a systemic or policy orientation. So, Autumn says, care is a coping mechanism that arises in environments without equity. And Catherine has said, care without equity is care for a few, the few who are seen. This means less or no care for those who are less visible, already marginalized. Care without equity, writ large exacerbates inequality. So, it's selective and certainly sort of drains the individual who's dispensing care. And we kind of feel parity of participation is definitely, in our opinion, a way of doing justice in care and also intentionally equitable hospitality, which the co-directors of virtually connecting talk about, is ways of trying to address both systemic equity issues and also to embody care in the ways that we try to do that. Mm-hmm. And then finally, in the lower left hand corner, we have the nexus of no-care inequity in systems and we know that is ultimately systemic injustice. So, just putting it all together in a cleaner form over here and we will move on to this. So, equity work is a marathon, not a sprint. It's a lifelong commitment. And we have some quotes here, one from my graduate student, Sonanda, who says, if you care about equity, you do more than just say it. You share the importance of it and you take steps to begin integrating and enacting acts of it in your daily life. You demonstrate that it's not a sprint, but it's a marathon. It's the long game. Equity is a long game and it's a marathon of goodness and learning. Jasmine Roberts says, if you care about equity, you realize there's no shortcuts to this labor. It's a lifelong commitment to socially just student experience. And we didn't know Jasmine was going to be keynoting the conference. We also found this quote from White in Toronto about justice needing care, because justice requires the empathy of care in order to generate its principles. So, Mia and I have been thinking about where people were thinking that equity without care would be okay at least. We're thinking that doesn't actually work. So, here are some broad conclusions. Mia and I wrote an article and Mia is going to start us off with one of them. Sure. So, equity is multidimensional. This is acknowledged by Nancy Frazier. And oppression is multidimensional. So, essentially, injustice lives in varying spaces, economic, cultural, political. Oppression, as we know, is intersectional. So, we have to think about that complexity when we're thinking about the convergence of both care and equity. And then oppression also occurs at those multiple levels. If you're aware of those four eyes of oppression, you're internalized, interpersonal, institutionalized, and ideological. And so, therefore, work on equity also needs to occur on multiple levels, systemic levels, and interpersonal levels as well. And that's the work of Borski's equity literacy. So, this one's important. Care is not monolithic. Care can be harmful. So, when we get into this, we start to think about the carer's goals, right? There's ideas like virtuous care. Oh, do I look like I'm a caring person? Or instrumental care, which is, you know, I feel the responsibility, but my dispositional leaning is not to nurture. Care can be distant and professional. So, sort of like what you see in geriatric care, or care can be focusing on things that are visible. We see that in the medical or healthcare profession quite a bit. Body is the focus, but not the soul. And care can be weaponized in the ways that Autumn Keynes and Cindy Richard talk about by, you know, a lot of ed tech companies who claim to be doing something to help students learn, but actually really harming. And carers can be exploited and require care themselves. This one came out for some of you, like a sort of effective labor, right? Like the people who care take on more of a burden of care. They get exploited for it, and everyone else doesn't do anything. There's no equity. Um, finally, or not finally, there is power in relationships involving care. That's an important acknowledgement. Care can be patronizing, patriarchal. Francis brought that up early on. You know, care can carry that. I fix that. I'm going to fix this mentality. And a Korean care worker incomplete if the recipients of the effort are not themselves empowered to participate fully. So examples of equity in care, inequalities in access to educational development support worldwide. Also urgent need for community building online with care and equity. And we've been working hard at that in our own realm. So if you didn't know about this project, Mia, Autumn and I, and a lot of other people participated in this, created these community building resources with demos to help people figure out what to do, you know, if they were teaching online for the first time, and I didn't know how to do community building online because not everyone has enough factory development support to do that. So this is one example of us trying to tackle a systemic issue with care, um, by using open, right? Openness as a solution to systemic inequality. All right, so we are about to head over to Zoom. I want to take a look at the chat. We're doing good on time. So I'd like to head over to, I'm just going to look at the chat as I, or actually, Mia, you look at the chat while I set up Zoom. Sure. And we're going to get you guys to go three minutes in trios just to say hello, so that the next time you go to the breakout rooms, you can focus on the task. And so, and I had it. Marin will share the, maybe I can stop sharing my screen. Marin can share the links to the Zoom. Absolutely. I'll put it in the chat. So we're going into this other space, but we're continuing on, so just click the link. I'll send that to everybody in the chat now, and I'll also stay in here for any later finals. Okay, I am in Zoom now. Can you hear me in the stream yard? Yes, but I'll, um, I can remove you from the screen now. So people are welcome to start coming in. Great. I hope that link is easy to, all right, I'm starting to admit. See you in 20 minutes, Mara. Mia, are you leaving as well? Yes, I'm, I'm entering the other space. Great. I'll see you all there. So there's the session chat now. I've put the link to the Zoom room in, and I'll put a notice up here. The session will stay live, and we'll see you back here in 20 minutes. Hi, Mara. Did you need anything? Thanks. We're good. I think we're good. Ma has probably, like, uh, getting those slides up so that we can tell everyone what we're going to do in breakout room. In essence, we're going to be telling stories. Let's send them, let's send them to breakout rooms to say, uh, hello first, and then I'll set up everything else while they're in three minutes. So three minutes, that's just like one minute for each person to say hi. Okay. Everyone gets to say hello, and that's it. And then we'll come back and start working together. Mia, you're going to end up in one of the rooms, okay? That's confusing, because I don't want to be, like, using power, but I do want to guide in a way that's thoughtful and good for everyone in our community, because some of that stress has been seeping into our experiences as a community in just interactions and classes, and it's complicated, right? Everyone's coming back. Great. I think we did something wrong with the time, but we'll be okay. Welcome back, everyone. I'm sorry, the slides were not editable. I just realized that, like, I'm so sorry. So initially, welcome back. I'm sorry about the slides. It's always happens.  Thank you, Kathy. Oh, Kathy, thank you so much. So we were going to send you back for five minutes to try to bring out common themes among your different stories, but your stories may have been quite different from each other. Lou was actually starting to do that in our main breakout room, but because we're sort of running out of time, I'm going to send you for three minutes to do, and then we'll go back to the main room and everyone will share in the chat. Is that okay? Yeah. Yeah? All right. Okay. Can you hear me? Okay. It's working. Hi, everyone. Are you back? All right. So we have about, yeah, about 15 minutes, which is not bad, to hear from you about some of the themes that came out. I'm so sorry about the slide deck. If you have a minute to go back and write some stuff, I saw some of you already did that. So if you want to share something, go ahead and share it in the chat. I feel so agile popping through platforms. So what were some of the things that came out in your sessions? Like in our main room, Gihad Bumicroft, and there were some interesting new terms that came out. Gihad, you want to talk about some of the other people types? Lou told a wonderful story of a colleague who was in a supervisory position who she felt was genuine and very wonderful to work with. And there was a kind of public forum in which she hadn't seen this person for a long time. It might have been, you know, like something that might have been forgotten, the connection, et cetera. This person was very public and gracious about their connection, and they came together in a way that was very fulfilling to her in this public space. And it would have been something that was quite easily kind of, you know, she's the center of attention in this space and could have easily just sort of moved beyond her. So we were talking about the issue of power, but what she said was that that's a moment of solidarity and coalition. Because in a sense, it's sort of, you know, speaking to that sense of connection publicly is speaking to the way we're all in this together and working together. So that was an interesting navigation of power structures and the public private aspect of it. You know, how would it be different if it was in a private space that welcome hello versus in a place very public? We were thinking about that. It's just a small anecdote around these issues. A lot of the comments before Frances's comments were about, like, the jumping between Zoom and here. But this one is about the topic. The issue of anonymity came up in our breakout, and that's something that Frances brings up in general a lot and has made me think about a lot. And she's saying that has care equity implications. Sharing was easy in small group, but tricky to share in public side. Okay, that's fine. And that's totally okay if you didn't want to, yeah, to share particular stories in that way. That's a good point, and we should keep that in mind. Like, we don't always have to use every story. Sometimes it's just useful to listen and enrich us. It doesn't have to go out of the room. So you're kind of lucky that the slides weren't editable. What you were saying behind your back. Gabby, the word that came up in our group from Autumn, with a double M, by the way, was recognition. Public greetings sound like an example of that. Yeah, going into a university setting with equity is important to build on the growth of education as a whole. Yeah, so Patricia's acknowledging that institutional policies are kind of the foundation work for any caring work that comes there after. It's, if caring is the glue, but there has to be that sort of structure, the bones of those intentions. Frances is asking that she could share them anonymously. Yeah, sure, if you're okay with that, you won't get recognition for sharing the story. But yes, please, if you're willing to share the story anonymously, that would be great. Lou is also reminding us of the book she's reading. And Anna Page, also recognition was something that featured in the stories she and Patricia told. Okay, that's interesting. I don't think we've talked about recognition at all in our page. Yeah, yeah, as a matter of fact, this is an exciting kind of pathway for us to start to think about. This is what does recognition mean in the act of care and in the realm of institutional ambitions towards equity? Absolutely. And yes, Catherine is making that connection to Nancy Fraser, because the cultural misrecognition, right? That's what it is when you misappropriate a culture or you don't recognize a culture altogether. So I think I'm actually going to meet with these people again and talk about it a little bit more. Tania talked about the importance of building relationships. And that's also like, I think what Mel Nodding talks about in terms of relational care versus virtuous care. Let's see here. Johanna was saying, witnessing how students with different experiences receive equity in care. Yes. So that's actually the whole, you know, carers have their own intentions, motivations, etc. They're at play. What are their goals? And then this kind of, when we come together in community, how is that received by those who are on the receiving end of care? Is it distributed equitably or is the intention to do that? But then the perception of how it's received, misunderstood, these things become very complicated. So an example that I'll give from my own personal experience is just a quick one is, as a mentor, as someone who directs many people in their MA or their graduate thesis, I work very hard to pay attention to each project as much as I can and there's a lot on my plate. And yet there might be a case wherein you offer some kind of advice but that advice is not taken. And then that advice then is sort of seen as, there's a misperception in the way that you dole out your feedback, etc. And this is very difficult. So I'm conscious of the fact that there are many other stories coming in but that mentorship role is a very complex minefield for this issue of equity policy and care. I'm going to read these upside down so that's going to be easier for Mara to highlight them. So Kathy was saying about the importance for people to have agency to not accept care. And that's a really important point. Again, do unto others as they would have done unto them. I think our children probably often feel like we're not be showing unto them that they want to be done, especially as they grow older and we still cuddle them or whatever. And then I like Verena talking about a theme of reciprocal care that came out in hers. And again, Nell Nottings talks about this so much, even when there are power relationships, even with a mother and child or a teacher and student, there is room for reciprocity. It's not equal reciprocity but there is room to recognize and show the caregiver that the care is working for you or you're appreciating your other side of that. And Ana Pei just talking about recognition that breaks down through hierarchies. Frances, you are right. You are always right about these things. We should have maybe said at the beginning, if you want to share, give us your notes. You don't have to share. Someone can decide to keep it public. And then it's up to you whether you want to be acknowledged or to keep it anonymous. And if I ever do an activity like this again, I will take that into account. And of course, one of the other things, and Kate Bowles is not here but she would have told me, that maybe sometimes someone shares a story that others could be triggered by. So maybe also let people know you don't share the most tragic experience you've ever had. I don't know you that might actually trigger them. So thank you, Frances, for always. We're shining people who does that to me. Yeah. Well, but we're finding process and practice. Yeah. All right, Tanya, like that. Yeah, that's really interesting, Tanya. Maybe we need to create places and spaces where care goes in all directions. Not so much caregivers, caretakers, like emanating from one source. This is the complexity of power involved. Care is not exempt from power, and that's the problem. Yeah. And there are relationships that are naturally supposed to be like that? Supposed to be like marriage or whatever. Or like teachers in a department together. But in reality, there's underlying power, whether it's power in terms of hierarchy or power in terms of identity, male-female, there's that already, the gender issue. With teachers in an apartment, like the one who's more experienced or the one who's from the Ivy League College, or you know what I mean? All of those other things come into play. Actually, I think the open spaces have more space for that kind of non-hierarchical relationships, but they're still create their own hierarchies, right? And it's Bonnie Stewart's work, and a lot of our work over here, we recognize that even though they're supposed to be more equitable, because we don't report to each other, but there's still other kinds of power playing here. And those two are always in the floor, yes. Sometimes care can be just bearing witness, giving attention, exactly, Louise. Especially if we aren't in a position of changing things, we can care even if powerless, and that can be powerful. I often, in the chat we had with Lou and Maha, we were, I talked about the fact that care is exhausting because so much of it is bearing witness and paying attention, listening, which is, it exacts a lot from your humaneness. It requires all of you all the time, and that I'm hyper aware of as I move through my own life. Autumn is talking about recognizing the third space. Yes, so the cultures, yeah. That's so important. And then Joe Murphy is saying, so just one important thing is that power can be exercised in a caring way, but we need to, yes. So I found this article by Nicholas Burbules called Theories of Power and Education that talks about all the different ways philosophers have tackled this issue of power because it's not always that power is something someone has and someone doesn't, but there are some ways in which we're all exercising power in different ways. And I need to reread that article, but it talks a little bit about what you're also saying, but then power exercised in a caring way can also be in a patronizing way. And that's a little bit, again, this weaponization of care that I think is exercised in families, exercised in societies, like exercised with education and educational technology sometimes as well. But of course, a lot of us exercise power all the time, right? Or we believe we are and hope we are, but the leaves and what's a beautiful observation? I think the observation is the power of attention. The importance of attention. Should we look up that hashtag? Thinking environment? Recognition, obviously. All right, we have two minutes left. We do have references at the end of the presentation. We can't see your screen just now, but I'm very happy to, all the link is already in the chat, and I'll just post it again, so everybody has to link to the slides. So, yeah, you guys, that was an amazing session. Yeah, Jill came late, but she said something really important here. Yeah, those last questions I love. She said, labor often falls to people with precarious contracts, women, POC, or many other responsibilities, especially things like diversity, equity, inclusion. Yes, for sure. And she asked this important question, how can we make this shift systemic considering equity for educators too? And it's a hard question. It's a parody of participation because you want the most marginalized to make the decisions, but at the same time, you don't want them to carry all the labor. And I think what happens in institutions is that they give these people of color the responsibility, but they don't give them resources and they don't give them funding or other people, and they don't try to change the entire culture, and they ask this one or two people to fix it. It's like star-making trapped. There can be stars that are trapped in a box, right? Oh, wow. That's a place I know well. Okay, it's one minute, and I want to give hugs and kisses and I'm part of everyone. Thank you all for being so thoughtful with us and just really enriches our work as we continue thinking about this and trying to figure out this complex nexus. Thank you, Maren, for this wonderful opportunity, and thank you. I know Louie's drum is also one of the organizers that we all organize this conference for letting us play around with platforms. Yes, it's been an absolute pleasure to have you with us and on behalf of everybody and all together here in the room, thank you so much for joining Maha and Miha for what's been a very thoughtful poking workshop. We hope you enjoyed the rest of the conference and we'll see you all soon. Bye. Nom, nom, nom.


What is going on guys welcome back to the channel and I appreciate you being here today I am back with another fortnight video and today I believe I have for you another sign that the end is coming but before we get into that guys I am giving away 2800 vbox to win make sure you are sub to the channel and have that Balboa and ticked drop a like on this Video only they comment down below winners are picked at the end of the week and contacted via direct message So good luck everybody so it's happening people I believe is actually going to happen and that is that meteor over in the sky is going to hit the map and wipe it out Now where did this start? Well, let's recap well with a recent update over a month back I believe we saw the addition of a meteor over in the sky a meteor which is more than just something pretty to look at This meteor was in the game files and it's been proven that it has a second phase This thing is coming closer and closer the meteor was added with the inclusion also of telescopes all over the map Pointing towards it. It's also being linked with turret towers being a place of impact on the map, too We also had some clues within the battle pass that the map will be newt the newt logo being one of them And also we had that dinosaur emblem, too We also see many space themed items in the battle pass to leave the minute to believe it has something to do with Out of space so what links it to turret towers? Well something interesting is the fact that battle rails map is almost identical to Poland's map Interestingly, turret towers is located in the exact place Poznan is located in Poland Poznan is a place which was hit by a meteor roughly 10 years ago So that's very interesting indeed We also had random controller vibrations found in game on consoles which turned out to be hidden Morse code when put together They translated to SOS D5 418 SOS means save our souls D5 is the exact place within the map Turret towers is located and 418 means we believe April 2018 We then also had the datamined information about a new playlist found within the game files called Impact I mean it's all starting to add up We also recently started seeing smaller meteors fall from the sky which were only visible within the replay mode When you slowed the footage down as much as possible They have now started getting bigger and much much more apparent and smaller meteors flying through the atmosphere Normally suggests a bigger one follows But the most recent evidence of this meteor playing a major part in the future of the game is now the weird sound you get when aiming at it You can do this yourself. It's a little hard to hear but with your volume full It's quite clear. I will pause myself for a second so you can hear you on full volume. Take a listen Things just keep on coming guys All which I believe to be some kind of warning as to what's going to happen Now it was first believed that only turret towers are going to be destroyed But going by the size of this meteor if it did hit turret towers Which is most probably going by the game's clues will be the place it will hit It will surely destroy the entire map and that is what's now believed the entire map might be wiped out And we will basically either get a new map to play on or play within the left of a ruins of this map Either one sounds absolutely epic to me This though in my opinion is a big step if it is going to happen, but epic do take risks I think it's one though if done right will surely pay off Now if this is going to happen if this meteor is going to strike the map I don't believe it will happen until season 4 or maybe the start of and this makes sense because there are many challenges to do Within the season 3 battle pass which take part in certain areas of this map I mean the areas will still be there, but if it's been struck by a meteor how would that affect said areas? So if it's going to happen, I don't believe it will happen until season 4 And that's what the 418 means within a translated most code. It means the end of April, but we will see guys We will see I honestly just don't believe all these clues in game or the evidence which point towards this thing can be a prank Right epic some things got to come from it, and I believe it will but guys only time will tell and that note I am out. What do you think about all of this? Do you think the map will be wiped out? Would that be something? You'd welcome let me know down below, but guys Frank says always for stopping by I hope you enjoyed the video leave your thoughts below and hopefully guys. I will see you on that next one


And for those of you who are still here, really, really thank you, you know, really thank you for staying for my talk. I'm going to talk about knowledge extraction in retail or the Internet of Things applied to the retail store. It's a talk about shopping. Some sociologists claim that we people only care about two things. One is shopping. The other, I won't say because we are being recorded. But since shopping is what's really relevant to the talk, let me emphasize. Shopping is procuring objects and objects define us. The objects we buy nourish our body, keep us from nudity, define, project the image of who we want. Objects we buy change, turn our houses into homes. Objects we buy as presents establish bonds with our families and relatives. So shopping from a personal point of view is really important. But from an economic point of view is extremely important. Shopping in macroeconomic terms is called consumer spending, which together with public spending and industrial investment and the housing market are the main drivers of the economy. If consumer spending goes down, everybody panics. So it's important to take a good look at shopping and our research is basically on two hypotheses. First, shopping is a very important industry which is very, very far from efficient. There's a great deal of productivity we can still squeeze out of the shopping process. And the second, there is a great deal of knowledge completely untapped in the shopping industry. At least in digital brick and mortar shopping, in online shopping, which is a model for us, there's a great industry dedicated to applying machine learning and artificial intelligence to analyze every click, what's called click stream analysis of what happens in online shopping. But all of that up to now, it's completely untapped, underutilized in traditional shopping. But first, why does all this have to do with the Internet of Things? Well, very quickly, the Internet was originally designed to put computers in communication with each other. Very quickly it became a phenomenal success at connecting people with each other and people with computers. And that's the Internet we know and love and use right now. Well, the Internet of Things is about a third player in this game, which are objects, things. Most of the IoT Internet of Things we know are smart cities, smart farms, which are basically sensorizing objects and capturing this data into information systems. Well, what we are interested here is in a different kind of relationship is the interaction between objects and people, which is a less studied relationship that emerges from the Internet of Things. And when we talk about Internet of Things, a lot of people think about smart refrigerators and cars and this. Well, we have chosen the most difficult problem, which is the problem of interaction with people and simple objects. Clothes, books, things we buy in the retail store. And we do have a few technologies, the most important being RFID, that allows us to detect a lot of these interactions and capture this data for further analysis. Well, the two hypotheses were that shopping is far from an efficient process. It's actually like a hurdle race. Well, we start by being called potential thieves as we enter the store. You know, there are some gates there that say, we're watching you, we're watching you. And then we see lines. Many times we don't even enter the store because of the lines. It's very complicated to find things in a store. It's very hard sometimes. And then when we find, finally the shelf or the product should be, very often, more often than we would like, the size of the color we wanted is not there. Which is extremely frustrating. If we need to try something on, it's also extremely frustrating. We go there, it's the wrong size. We have to undress, redress, hunt for the size we wanted, go back. It's really, you know, a miracle we end up shopping at all. And finally, lines. After all that, lines. And after all the design of the product, the marketing of the product, the having the store, having done everything, it turns out 30% of the people abandon the shop with the product already selected and ready to pay after five minutes' wait. No wonder online shopping is such a success. Because all these problems don't exist.  There are no stockouts. Everything is available. You have plenty of information. There are no lines. Of course it has some drawbacks. Of course it has some drawbacks. Because you cannot feel the object, the product. You have to wait a few days. Less and less anymore. But you have to wait to have your, there is no immediate satisfaction of your shopping needs. But still, you know, the fact that shopping online is so much more convenient is making online shopping go in double digits while traditional shopping, what's called brick and mortar shopping, is declining in fact. But first hypothesis I remind you was it's a very inefficient process shopping in a store, but also there's a lot of opportunities. And the technology behind online shopping is amazing. We don't know as users, but they are analyzing every single click we're taking there, you know. Machine learning algorithms have progressed tremendously. They had to be adapted because they were not satisfied with the statistical learning from shopper behavior. They want to take actions immediately. They are analyzing your clickstream and making decisions on exactly what your next screen is going to look like to maximize the probability of you actually buying something. What's called conversion ratios. Conversion ratios are the ratios of the different steps from landing in the landing page of the store until checking out in the shopping basket. Well, for instance, recommendations. We've heard a lot of talks here about recommendations. Well, in shopping recommendations, it's extremely, extremely important. 70% of Amazon's homepage is devoted to recommendations because 35% of their sales are originated in the recommendations. That means that the jump in sales is plus 50%. Amazon sells 50% more thanks to recommendations. Well, you go to a retail store and none of that is there. No recommendations, no convenience, why? Well, not because there are no technologies that could do that. This is pretty much a green field, a blue ocean of opportunity for us to, if we can, generate something equivalent to the clickstream in the retail store to take all that wealth of knowledge and analysis into the physical retail store and save a lot of businesses and save a lot of jobs in the process. Well, one way to analyze that is not to antagonize online and offline retail models, but to start thinking about a single model. Well, brick and mortar model retail is about putting shoppers and products in contact through a physical space. Online commerce is basically doing the same thing, but in a virtual space. For several years, they've lived completely separate lives. But more and more, through something that's known by the buzzword of Omni Channel, more and more these two things are convergent. And the vision of our research group is there will be a platform that will get inputs of all kinds and produce outputs of all kinds to create a mixed media or a mixed platform shopping experience. We'll be able to shop online, get the stuff in the store or the opposite, shop in the store, do part of our shopping there and get an online order from the store that shipped to our home, start shopping in our phones and end in the store, all possibilities. But in order for these two worlds to merge, the customers we should find in the real store something similar to what we find in the online commerce platform. And this is basically a lot of interactivity. Online shopping is really interactive while a traditional shopper is far from interactive. We should have a personalized shopping experience which online it's getting more and more personalized and in traditional shops it's completely anonymous and also contextualized. Everything that happens should be about what we're interested in. So these are the different technologies that create this interactivity personalization and contextualization of shopping. RFID is a technology, cheap technology that by adding a five cent antenna and chip to the label of the products or to the products themselves allows the product to make its presence known in any space. That's simple. A shirt, a book, a pair of shoes, anything can make its presence known in a space. And that announcement of the present triggers events that until now did not happen. So we don't need a very complicated technology. All we need is a certain item to make its presence known. RFID is a technology that identifies every item, not every reference, not every class of products, but every specific object. So we can track the life cycle of that product from manufacturing to stocking in the store, buying, maybe returns, the whole thing. So we're talking about life cycle. We're somehow giving the concept of life to objects. We're making objects active. The real goal, what we really wish we could do and we're only starting to accomplish the technology is we would like to click in the store. We go to the screen online, we click and we find information. We click, we find opinions. We click and we find recommendations. Well, we touch the shelf and no matter how much, nothing happens, right? Nothing happens. Well, we have not completely solved that problem yet. We're only starting, you know, some only half satisfactory solutions to it. But although we don't have a solution, we have a name for this. We have coined the Pormanto term Cric. Cric is a combination of brick and mortar clicks. So Cric is the abstract term of being able to point to an object and create events, interactive, contextualize, and personalize events about this object. Some of our early attempts have been using augmented reality, augmented reality and RFID. If we put RFID antennas and RFID labels on the objects, the shelves know what objects are more or less where with a precision of 25 centimeters. So if we point an augmented reality software to the shelf, we can map the screen coordinates to the shelf coordinates, ask the shelf what contents are in that particular position, and then find information about this product and create whatever interactive experience is called for in that particular instance. Well, that pretty much works. It has its limitations. But as always, you know, limitations are not so important if you really need it. Who really needs that? Well, people with physical mobility limitations. If you are in a wheelchair, you cannot browse a shelf. You can go to a store, you know? The chairs can do pretty much everything. They can drive, they can take the bus, they can access any building, but as shocking as it may be, they cannot shop independently because anything that's outside arms reach, they cannot browse, they cannot find information. So they need somebody to go with them with the consequent lack of privacy. And this is a product that after certain surveys of people with mobility limitations, you know, they have said, yeah, I would like to go by myself, not with somebody next to me. You know, that's watching over my shoulder what I am doing at every moment. So either with a handheld or even a lot of people with a bound to a wheelchair have also serious arm mobility problems. So with Google glasses, and we've been able to fix the gaze of these people in a certain position on the shelf and give them information. That doesn't completely solve the problem because at the end, if they are interested in something, they need help to get it. But at least the browsing part of shopping they can do by themselves. And the obvious question is why don't online, all they do, they do all the time, but if you talk to them, they say, yeah, but I want to go to the store like everybody else and they have the right and it's understandable. Well, now, after once we've learned and we keep working on this better and more efficient and more usable implementations of creaking, I'm going to show you a lot of different strategies we're following to capture extraction. We are in the phase, sorry, to capture information, to extract knowledge from the store. We are in the phase of solving the problem of capturing the data. Eventually when we have all the data available then we'll worry about what to do with it. But that'll be a simple problem in the sense that online commerce is already working on that problem. So our idea is to provide from physical shopping in the physical store the same or similar levels of information that we have from click stream analysis and then machine learning algorithms, recommendation algorithms, all these things can be run on this data. But extracting data from click stream from a mouse click is a completely different problem than extracting data from people shopping in the store. And there is a lot of hardware and a lot of software that needs to be developed in order to obtain that information. Well, there have to be a lot of solutions to coding. It's very important that the right number is given to every tag. But the first problem is knowing where things are. That may seem like something that's not necessary. Don't stores know what they have and where it is? Well, they don't. Or if they do, they know at best with 80% accuracy, which is far from what they need. If Decadlon wants to compete with Amazon, they are going to be sourcing online orders from the stores. So 80% is not sufficient. They need 99.9% accuracy in the information of what they have and they need to know where to get it. This is why, for instance, Decadlon, Inditex, Macy's, Marks & Spencer, Tesco, all the big retailers already RFID tags in all their objects. We have several solutions, but one solution that is actually relevant to the minds to context because it's a solution that will require cooperation with other groups in the department is the idea of a robot that will go around store capturing information about inventory and location. The question is what products are where? This is like the basic information we need for anything else to happen. And the fact is that this is far, far from solved right now. You can go around with a handheld either with a little antenna and electronics detecting the tags, but you're in a huge department store that's a task that goes beyond the capabilities of humans. They get lost, so you can send a robot. Right now we have certain limitations with the robot. We need to provide the robot with a map. Once we have a map, we need to tell the robot more or less what path to follow. Of course we would much prefer a robot to be left in an unknown space and the robot first to explore the space to create a map and second to plan its own path along the map. So we're talking about exploration, planning, all things that if you've been today in these talks you know, ring a bell. So making the state of the art in robotics for inventory there are only two or three companies in the world that can do that. One is here, we're collaborating with them. But the state of the art is that the robot cannot plan. So we are trying to push that state of the art beyond its current limits. Okay, then we have the smart shelves. We've already talked about that. The smart shelves of course provide inventory. We are also applying machine learning techniques to detect when a customer interacts with an object. The augmented reality creaking technique works but it requires a technology in between. The ideal would be we take a book from the shelf and immediately something happens. Well it turns out it's a difficult problem because RFID to read that the shelf continues to be identifying that book and there are changes, subtle changes in the power and phase parameters of the RFID detection that can be inferred as being an interaction with that. And we have applied the classics, support vector machines and regression and different techniques and have obtained good enough results. It's good enough to publish. Good enough to publish. So I think we are pushing in the state of the art of interaction detection using RFID. Shelfs also displays. I could get into the importance of displays. Displays are more for brands and they are business changing but let me continue. Then there are other interesting cases like for instance the fitting room. A place where the presence of a certain object can trigger an interactive contextualized experience is a fitting room. And there are systems already developed which when a customer enters a fitting room the products that she or he is wearing appear on the screen. The first reaction is what a coincidence. The marketing content is exactly what I have. Maybe the second time or the third time they will say maybe it's not a coincidence. It's not a coincidence. This is another way of quick-cricking. The mere presence of a garment inside a fitting room cricks an event to happen. And here we have an opportunity of showing opinions, showing recommendations, showing but the key here is not to expect a customer to do anything. A lot of people say why don't you have a barcode reader and you read the barcode. Then you require a very small intervention by the consumer which means that 99% of the time it won't happen. We are lazy. People are lazy. So it has to be completely automatic. An RFID allows that. Well we want to determine things like an object leaving the store or entering the store. Well it turns out these problems seem are easy and look easy but turn out to be extremely difficult. You require to determine which is a problem that we are currently working on to determine whether a product enters or leaves the store. You require a combination of face to ray antennas and certain algorithms. We're trying machine learning, we're trying more simple algorithms but it's very hard with a high reliability distinguish between an object that is leaving the store entering the store or just sitting next to the door. Because even a 1% false positive means that the mannequins next to the door are going to be creating false events all the time. So we're going to need parts per million in that detection. We want that to be useful at all. Getting to 90% is easy, fairly easy. Getting to very accurate results is very, very challenging. Well also the payment is very important because at the end at the end online measures through clickstream all the conversion ratios and conversion ratios are finally in the denominator we have how many of these initial shopping processes ended up in a sale. So if we had the payment point we detect, let me just show you a video it's not very from a technology point of view this is not very important or very interesting but from data analysis point of view is crucial to detect when the item leaves. So right now we are able to sit with the big retailers, with Inditext and with Deconon and say ok we have the technology that allows you to know that particular product that went that checked out at a certain time did it go through the fitting room or not. In exactly what shelf was it sitting so we can measure the productivity of every single fixture or part of the store we can assign Euro value in sales per hour for every shelf and you can understand this is immensely valuable to shoppers we can also we can calculate conversion ratios of fitting rooms, they have no idea now they have the fitting rooms because they have to help them but they don't know how many sales if fitting rooms are increasing the conversion ratio maybe they need to put twice as many as they need to close half of them they have no idea now because they are not measuring anything so see how a simple technology can extract so much information some of it might be easier to analyze, some of it is much more difficult to analyze and requires much more complicated algorithms also after payment checking what happens in the door is important too if you are more interested in our research in detecting objects coming in and out there is an entire industry dedicated to analyzing people coming in and out which turns out to be also a surprisingly difficult problem because the light of day the shadows, the lighting counting how many people what's called footfall counting how many people enter the store should be an easy problem well it's not but people that know about it tell me it's complicated there's no more slides I guess well there are more but it's late so let me conclude let me conclude the idea of our research basically it's an ambitious it's an ambitious goal we have it's an ambitious goal we have and not a lot of research groups that are doing this problem it's basically developing the systems made of hardware and software algorithms that will extract the data sets from consumer activity in the retail store that will allow an analysis of the same level of affecting business and business impact is available to online stores and that starts in knowing what we have and where we have it in the stores and just to illustrate how these apparently simple systems problems are actually hard to solve is just to know what products and where they are in a store we need to develop a robot that explores, that plans that applies sophisticated algorithms to from the antenna readings honing into the position of the objects or another simple object and another simple data set is interactions that happened in a shelf we need to apply machine learning algorithms to the different features of the RFID parameters such as power read counts phase in order to decide whether it's just random fluctuations or it's actually an interaction and happening because even we have the products sitting there all day even a small percentage, very small percentage of false positive is going to be creating false events all day all day the problem is complicated because of the level of precision F factor of 0.8 that's not nearly that gets you a paper published, in fact it did for us but it's not nearly good enough for actual use in an actual retail well, thank you for your attention thank you for being here can you hear me? I was wondering about the role of humans that work in the shops in this technology because that's something there's no online shops where there's no human being present in which way can maybe integrate well first, the change in the role of humans in the shopping it's part of the reason why we're doing that it used to be people working in stores were knowledgeable, had been working there for a long time and were actually helpful well, that is part of the past they are just most of the time people working or are just human mannequins they are just hired to wear clothes and to be part of the decoration I'm exaggerating a little bit but there's a part of truth in that exactly, but these people they need some tools so all these tools they can be targeted to the customer but it turns out that in many cases they are targeted as tools to help these people are called associates in the retail lingo to help associates do their job better without a need for training or long term experience for instance if just give you an example certain customer enters a fitting room and that person is going with a certain garment then that event triggers an order to one of the associates to say this person would probably like to try out the associate goes find it takes it to the fitting room and it turns out that person ends up buying that the customer is happy the associate is happy because their variable pay increase their commission increase the retailer is happy the brand is happy it's a win or a round situation it's a little bit like creating cyber associates associates that are not very smart or very experienced or very good at what they're doing but they have the technology that tells them exactly what to do when to do it and where to do it so all they need to do is execute that and they create more sales and they do their job better and that's actually happening not so precise RFID technology is so good that it's almost magic that's a reaction that people have when they see it working wow and there was a time long time ago when RFID we were worried about not detecting enough now the problem is exactly the opposite our problem with RFID technology it reads too much too much it's too good so we need to write a lot of software code to tell from the interesting reads to the stray reads as we call them for instance techniques for an antenna overhead a fitting room it's also going to be reading from the other so we need to compare the reads from the different antennas apply algorithms and filter and make decisions decision making based on this product cannot be in two fitting rooms at the same so which is the most likely we use probabilistic algorithms to decide in which fitting room it's actually so RFID technology being too good and about price is incredibly cheap you have a attack that costs 5 cents and it has a radio frequency transceiver in it that can run four sessions at the same time can be talking to four different readers at the same time to me it's mind blowing you can do that for 5 cents thank you


I welcome you to my presentation on the ELISA project. In the next half an hour, we are going to talk about the required activities and challenges to enable Linux and safety applications, rather than going into all the required activities that are required from system engineering, safety, engineering, quality management and quality assurance. I'll quickly just summarize the work required to develop a safe system with the following simple statement. To assess whether your system is safe, you need to understand your system sufficiently. So when you build a system based on Linux and your system safety depends on Linux, you will need to understand Linux sufficiently for your system's context and use. This can be broken down into two activities. First of all, you need to understand your system and you need to understand the way your applications use Linux. This includes understanding which kind of interfaces of Linux are used, which kind of libraries are used, how your applications are start up and shut down, but also which hardware you are using and how does Linux interact with the hardware you are using. If you take all this together and you understand this in greater detail, then you can really argue that you understand the system and how Linux is incorporated into that. With that at hand, you can now assure that the selected properties of Linux meet your expectation. For that, you look into the two details of how the Linux kernel and glipc implement and ensure the selected properties that are relevant for your system. Of course, these two activities are very challenging for an individual because you need a lot of knowledge about system engineering, about the system, about the applications running on Linux, but also about Linux, how it is developed and which kind of properties it actually holds. And this is not only a challenge for an individual, this is actually also a challenge for single companies and the ecosystem in general, and hence to face this challenge and to work towards this goal, a number of companies have come together and formed in the LF, the collaborative project called IRISA. You can see that there are companies from hardware vendors, companies from the OEM side, companies from the automotive and companies with deeper Linux knowledge. These members have come together and want to tackle the problem of enabling Linux and safety applications, and we have formulated the following mission statement to work towards that. We want to define and maintain a common set of elements, processes and tools that can be incorporated into specific Linux-based safety critical systems, amenable to safety certification. Let me explain this in a bit more detail. When we talk about elements, processes and tools, we mean software source code that has been developed with its documentation and with its test suits. Processes means that we give you certain recommendations and methods that you can use when you want to build a Linux-based system and the tools that allow you to do so efficiently. If you take all these parts, you can use them and incorporate them in a specific Linux-based system to build a safety critical system and provide that to safety certification and reach the goals of that safety certification. So when this project is successful, we will build up assets for safety certification of Linux-based systems. This can consist of a complete process with selected kernel features and tools and previous process assessments that have been done in different other contexts. It will be shown feasible with reference systems. It is usable by properly educated system integrators. It is maintained over an industrial-grade product lifetime. It is well known and accepted by safety community, by certification authorities and standardization bodies in multiple industries. It has been positively recognized and has been positively impacting the Linux kernel community and it comes with hardware collateral from multiple supporting vendors. To work towards that goal, the ELISA project has formed a number of working groups. There are two working groups working on reference use cases, one in the area of medical devices and the other in the area of automotive. A second group is working on safety architecture. This means they investigate specific features and functionality of the kernel and investigate what it does and why they believe it does what it does. A third working group is working on the kernel development process. They are investigating how the kernel is developed, what the expectation of safety standards is and how this gap between those two expectations and execution can be overcome. The working group has two further subgroups. One is the tool investigation and code improvement subgroup that is investigating tools and learning how to create kernel patches in order to interact with the kernel community. A second subgroup is currently under discussion that we'll be looking into development metrics and how to create evidences from these metrics that certain activities have been done with due diligence. Besides these working groups, there are some tool developments that are related to the project itself. There is the call graph tool, a tool to visualize and analyze call graphs in the kernel, stressed in G, a tool that stresses the hardware and the kernel interactions with that hardware, contributions to the SUSCO project, a fuzzing tool for the SUSCO API of the kernel, some tool developments in the area of the open source tool code checker, a management tool for static analysis findings, some contributions to pasta, which is a tool to analyze and mine kernel mailing lists and some contributions to GDM, a tool to visualize the flow of Git commits during the kernel development. So instead of going into the details of all the activities that are happening in these subgroups and working groups, I'll just pick out one selected question that the kernel development process group is facing. And we are asking ourselves in this group, is Linux good enough for our use? So we can look into the use of Linux and we find out that Linux based systems are almost everywhere. So Linux seems to be good enough for very expensive supercomputers, banking and trading computers, highly secure company servers, ground based air control systems, critical civil and stress culture, telecommunication systems and various user systems. So the question now is why are we even concerned about answering this question? And this goes down to the problem of proving software quality. The problem we face is that we don't evidently know if a software X is high quality or not. And this holds in general for any software that you can consider. So once you came to come to the conclusion, well, this software X is high quality and someone convinced you. You might ask yourself a question, but why is this software X high quality? And usually you come to a conclusion that it is high quality because the development team does some specific activity or a set of activities or combines various tools and activities during their development and testing and verification that leads to high quality. But with that, you of course face the problem. But why does this make the software, why do these steps make the software X high quality? And of course to answer that question, you have to, you're facing a challenge in empirical software engineering where there's very little evidence to show that specific activities or specific methods actually lead to higher quality. Despite various software development projects, there's very little evidence that shows that a specific method has contributed to higher quality compared to its absence. So when you want to show that something is high quality, you have to work with a very weak empirical basis. And this leads to a significant quality mismatch between two areas. There's an evident quality in business practice. You can see that critical applications are running on Linux for many years without regressions, even with multiple major version updates. Linux is extended and it's refactored, cleaned up and released without causing significant regressions for many years. And any kind of fixes are rolled out without causing significant regressions as well. On the other hand, we have quality expectations from development process norms. They expect that all requirements are described sufficiently to be implemented. They expect that products never ship a functionality they don't need. They believe that very specific documentation efforts lead to software quality and they're based on a development process where there's only one final release to be shipped, which needs to be good. And the maintenance of that shift software is reduced to minimal needed changes. This kind of mismatch between business practice and development process norms, we want to overcome in the development process group. So to bridge this gap between these two worlds, we have the following plan. We want to show that we are evidently developing high quality software. To do so, you can refer to traditional software development process norms like ASPIS, ISO 26262 or others. And they explain how to develop software to be high quality and to provide evidences for that. On the other side, we have the kernel community that develops and releases the kernel. Product teams integrate and test this kernel and hence create products based on Linux. And our goal now is to show that the norm that these traditional software development process norms describe are met by the activities of the kernel community. So the first step in this process is to understand what do development process norms expect. The second step in this endeavor is to understand what does the kernel community development and Linux based product development actually do. Once you have these two things straightened out and a good understanding of them, you can understand the gap. And once you have understood the gap fully and honestly, you probably have to acknowledge that this gap cannot be overcome. So is this a dead end for bridging the gap between these two worlds? By no means. You can just consider the history of both these communities. So why do development process norms have these expectations? And also, why does the kernel community development do what they do? And again, now we can again understand the gap between those two and see that development process norms have very different expectations for various reasons compared to the kernel community. And once we have done that, again, we have to acknowledge that this gap cannot be overcome. So I'll be again at a dead end by no means. So why does the kernel community development not intend to meet the norms expectations? And what are the intents and goals that the kernel community development intends to meet instead? And once we have concluded on that and understand the gap, we will have to acknowledge finally that this gap cannot be overcome. When all of this is understood, it's clear how we can show that the norm is met. You just need to develop a kernel community development norm that describes the intent, the goals and the criteria of the kernel community development. With that at hand, we now can explain why this kernel community development norm leads to develop high quality software. And we can provide evidences that these activities that are executed actually lead to high quality software. By empirical studies and evidences from the past that these activities had positive impact on the quality of the software development. And with that at hand we can do the final step to show that this new norm is met by the kernel community that develops and releases the kernel. And by specific product teams that integrate and test the kernel following best practices that have been developed by the community and the product teams over years. Of course to do that, we need to reach out to the safety community. This means that we need to work with the safety certification authorities and standardization bodies in multiple industries to establish how Linux can be used in a component and safety critical system. We have to evaluate the potential system architectures that are available. We have to document the methodology and limitations. We have to define the state of art for working with open source upstream projects and provide access to the technical review meetings with certification authorities. Of course we need to include not only the certification authorities, but the larger safety community to gain acceptance of these project results. We have to present and critically discuss open source in the safety community. We have to present the methods and tools that we develop for peer review. We have to establish an acceptance for use of open source in the safety community and we need to submit amendments and full standards to relevant committees. But this outreach is not limited to the safety community. This outreach is also to the open source community to which we want to provide continuous feedback and receive continuous feedback on our activities. And we want to contribute to the open source community as well. We want to build awareness on safety and its relation to reliability and availability. Build consensus around the activities within a safety expert community related to the kernel, improve the development workflows and traceability and contribute to quality assurance and quality measurement with the open source community. This also includes outreach by education within the companies. We provide workshops and opportunities for knowledge sharing. We want to create courses on safety engineering and backspractices for building Linux based systems. Teach the safety concepts in safety case, documented in pre-existing elements. And we want to train safety engineers in the use of the analysis tools and handling the limitations in order that companies can incorporate the results that we have into their own system engineer. Of course, this project will not resolve all engineering efforts required to build a safety critical system. This collaboration cannot engineer your system to be safe. We simply don't know how your system looks like. We cannot ensure that you know how to apply describe processes and methods. We'll try our best to educate companies and active individuals in our project. But there's no guarantee that you finally understand the required concepts within a limited time. The collaboration will also not create an out of three Linux kernel for safety critical applications. Kernel and its development is moving so fast that the attempt of an out of three kernel for safety critical applications will quickly determine it feasible. And lastly, we cannot believe you from your responsibilities, legal obligations and liabilities. Safety engineering is about risk management and we can provide you all the lists of risks and problems we identified in our engineering efforts. But in the end it's your responsibility and your legal obligation to critically review this and to ensure that you have no liabilities that are beyond the risk that you're willing to take. Besides these limitations and acknowledging these limitations, this project will provide a path forward for you and peers to collaborate on the challenging questions we're facing. In case you want to have more information about this project, we have quarterly workshops and the next workshop will be taking place in January 2021. It's taking place virtually and is a three day event. You just need to register for this event but there are no further fees or registration costs. In case you cannot wait until this three day event in January, you can visit our website, join the mailing lists on the general development discussions or the subgroups that I have mentioned. You find more information in the Google Drive where we have collected our meeting notes and are drafting our argumentation and investigations and you find further information also on our GitHub space that you especially find tools and code that we're developing. So with that, thank you for your attention and I open the stage for questions.