Hi, my name is Youngby Lim, I am a doctoral candidate at George Mason University, and I'm also a Baltimore Underground Science Space Community Lab member, and I am super thrilled to be here to give you this talk. I think that it's fairly apparent when you look at the title, what I'm going to talk about, and that's about the dangers as assumptions. So let's get on with this talk about you know what they say when you assume. So as a brief background about who I am, just from a professional vantage point, I'm clearly a guy that's into some style. I love glasses and I love wooden bow ties. I've been involved in national security and looking into it for about the past decade. Also, I am involved in community labs and community organizations, so I've been very fortunate the past few years to be involved with the Global Bio Summit. Just so you know, Global Bio Summit 4.0 is coming up, biosummit.org, so go check it out and register while you still can. And like I mentioned previously, I am a doctoral candidate at George Mason University looking at DIY Bio. So the thing that I also wanted to point out, because everybody is a multifaceted individual, is I wanted to see what the internet would pull up when I decided to talk about things that are personal about me. So interestingly enough, these are the images that came up, and the first one to the upper right should be pretty obvious. It's me hanging out with a friend of mine, Natalie Ma. This is actually at Santoka Raman in Boston, so I'm a huge fan of Raman. In the bottom right hand corner, it shows me being involved in a community lab project called Bark Coding the Inner Harbor, along with other members such as Syrah, and also actually the founder of Bugs, Tom Burkett in the photo in the lower right there. In the lower left hand corner, you can see that I think of myself, I guess, as a flamingo. I just thought this was a really fun picture because this photo was taken when I was traveling in Seoul, South Korea. I'm a person that really loves to travel. And interestingly enough, this focaccia bread picture popped up in the internet search, and so it seems to show that I have a real appreciation for baking and for carbohydrates, which shouldn't be terribly surprising given the Robman photo. So, you know, that's a bit more about me, apparently, according to the internet. So I really want to now get into the meat of this particular talk, which deals with this idea of assuming. So you know what they say when you assume, and I think that Moira Rose does a fantastic job in this animated gif of explaining that.  So what do assumptions have to do with kind of my talk and my life story here? Well, to get to that, we need to start with an origin story.  It's at George Mason University in 2015. That's when the Force Awakens came out. I just really like that animated gif. So I decided to put that in there. So when I was a PhD student at George Mason University in 2015, that's where I had my first exposure to these concepts of do it yourself biology, community labs, people doing the life sciences outside of conventional traditional areas like academia, industry and government. And this was my first exposure to it. So if you look through any of these particular images, you can see that the image presented of do it yourself biology, community labs, amateur science is a pretty horrifying one. There's this idea that amateurs could create mutant viruses. There's this idea that these people are actually creating bio security issues. There's an idea that non state actors could use these technologies that people are using in unconventional ways to exploit synthetic biology for terrorist purposes. And as more people engage in these types of activities, it's possible that according to this 2018 New York Times article that people will get hurt as they continue to do these DIY gene editing experiments. So my first impression of do it yourself biology and community labs is not terribly surprising. I think Archer explains it best here with welcome to the danger zone, because it certainly feels like a danger zone type situation. You know, it feels very dangerous. It's about people that I don't understand. And, you know, that's the that's the impression that I initially had. So clearly I'm speaking to you here right now from the comfort of my own home. During this virtual conference and I've clearly had a change of heart. And how did that change of heart happen well I think that there are three precipitating reasons. The first is, I'm a home brewer, starting in 2012, I go visit Korea, I try to visit once sometimes twice a year, and I really got into home brewing. They have a rice wine there called Makgeolli. And if you listen to my interview podcast episode with Nina and Bo on white, white hats and lab coats. I talk about a little bit about my home brewing experience. But I kind of came to realize and I use this book I realized that sake is Japanese Makgeolli is Korean. But I kind of came to realize that home brewing in itself is a form of, you know, doing biology outside of conventional spaces. And so, you know, that kind of got me open to this idea that maybe biology and unconventional spaces is not only something that's desirable, but it can be something that's delicious. So the second thing that kind of got me thinking about how biology in unconventional spaces could be a good thing was this idea that I was talking about myself as this kind of emerging tech, as a security expert, but the more that I got into the biology of it all, the more that I realized that biology is actually really hard. I kept having to go back through basic biology textbooks to just get a basic understanding of a lot of these very complex ideas and complex technologies that were coming down the pike that I was supposed to be able to understand. I wasn't sure at one point if it was that biology is hard or that I'm just a horrible student. But I eventually realized that having community lab spaces as a place where people could learn biology at their own pace would actually be helpful to me from a professional and educational standpoint. And finally, the third thing that changed was I was very fortunate to get a research assistantship in California at Lawrence, Lawrence Livermore National Lab. And I met this gentleman to the upper in the upper right hand corner, Patrick Dacilleur. He is a founder of one of the first few community labs in the United States counterculture labs in Oakland, California. And he learned it through the great find at Lawrence Livermore National Lab that I was interested in do it yourself biology. And he at one point came up to me and he asked me hey, so I hear that you're interested in community labs. And I said yes. And then he asked me have you ever been to a community lab. And I said no. And so he offered me literally a life changing opportunity with an invitation very akin to Arnold Schwarzenegger in the lower right hand corner. Come with me if you want to live or at least come with me if you want to learn more about community labs. So actually getting that initial introduction actually getting that invitation to come and participate and observe was a really eye opening experience for me in 2016 and over the past five years. I think that it's really developed a number of changes in the way that I think about community labs and DIY bio that are you know very much with me to this day. So, I know some of the people in the audience at this point are saying, you know, origin stories are great, but if you get to the point that would be great. So here's the point. This is often the situation. You know there's a major problem when we assume things. So, as much as we like to think that we know everything under the sun that is not a true fact that is fiction. There are the known knowns that we know of, but if we're not willing to push ourselves beyond the known knowns into the other areas, particularly in my case, in regards to DIY bio, the known unknown so you know we know that there are like particular issues that may be existent, but we don't necessarily understand what this phenomenon is that we're observing in the first place. Unless we're willing to push ourselves to expand our idea of the known knowns, we often work off of assumptions, and once again, TLDR remember what Moira says, it makes an ass out of both of us. So I just, you know, as the start to this whole entire talk, I wanted to get people to think about this idea of assumptions and understanding that assumptions aren't facts. Assumptions aren't truth. What we need to do as responsible citizens and responsible scientists is to when we run into a particular situation that we don't know very much about. We have the willingness to be curious and open minded and go into that new area this kind of like, you know, this strange new world with, you know, an open mind, and be willing to kind of process information as we go along and allow that information to help inform us as we, you know, expand our knowledge and arrive at particular conclusions and policy recommendations. So we are finally here now. My talk is on understanding the do it yourself biology and community labs scene, and it is a bit unusual, I think, in the biohacking village context because a lot of you people are like incredibly technical people, and I would not be able to do half the things, actually even a quarter of the things that the people do in this audience on a regular basis. So, you know, testing vulnerabilities and various types of software imagining, you know, all of these kind of like red teaming like cybersecurity type events. It is amazing. It is amazing that you can do it. I really hope that you find this to be an interesting talk because social science, I think is often referred to as a soft science and sometimes kind of push to the side but I think there's real insights here that could be helpful not only from a policy standpoint but from a community standpoint. So I'm going to go forward with that kind of perspective in mind. So here we are finally at the main event. No crazy animated GIF here I just wanted to go over a few basic facts about the do it yourself biology community from my research. There aren't very many reports about the do it yourself biology community. One of the main ones was from 2013, authored by Dan Grushkin, Todd quicken and peers millet. So, in terms of its history, it appeared to emerge somewhere in the United States from about 2005 to 2008. It's now a global phenomenon with community labs popping up all around the world. And a lot of people associated with the do it yourself biology movement in the early days include Rob Carlson, who built his own bio lab in 2005, and he talked about in a wired article, how people could maybe start doing their own community lab learning community lab skills from the comfort of their own home. And then Jason Bob and Matt Cowell in 2008. They were based in Cambridge, Massachusetts, and they had this idea of making biology more accessible and easier to do particularly from the angle of synthetic biology. So, having people, you know, providing people with the knowledge and the tools to be able to engage in biology and do some really fun and cool things, you know, from the comfort of their own home or from community lab settings. So the 2013 report discusses how this community started as a small online forum. It was an online Google group called DIY bio current estimates estimated at three to 4000 individuals associated with the movement. It's highly decentralized consisting of actors ranging from individuals to regional communities. The individuals from that 2013 report. They, they noted that people tended to be more educated and younger than the general population. And these community labs and these kind of garage labs tend to be centered and highly developed urban locations with higher education academic institutions. So in terms of DIY bio, in terms of its values and goals. It's very much about democratizing technology. And when we talk about democratizing technology. I see it as four separate but interrelated concepts so there's increasing access to technology, increasing access to knowledge. So the internet, but also increasing access between people to have conversations to talk about science, distributing scientific practices to a broader community and distributing capability for a broader community so broader in terms of the number of individuals and broader in terms of ways of usage. So I think that it's very much the idea of DIY bio that people see the democratization of science as good news as Professor Farmsworth clearly acknowledges and, you know, this idea that not only do academics and industrialists and government have science but we as citizens have science and should have access to science and should be able to do science. So in terms of my research, what I found in terms of DIY bio activities where they encompass four general categories. So the first is exploration. The DIY bio community like to explore, you know, everything from within themselves to their local and regional environments. So that's, you know, a vehicle that DIY bio uses to enable people to explore their surroundings. And clearly with the I have the power indicates that DIY bio also really believes in empowering individuals to be able to engage in biology and to be able to leverage biology for their own particular sets of purposes. In terms of another activity that DIY bio does. There's a lot of education that happens in do it yourself biology context. So there are lectures, there are hands on lab skills classes. There are casual conversations where people just talk about various topics and before you know it they've talked about this entire area of science that they're really excited about, and really excited to collaborate on. And finally, there's an entrepreneurial element. So there are a number of community labs that function as early stage incubators for small groups and individuals to come in and maybe develop a proof of concept or get some data that hopefully they can then use to develop a product.  So, question here is, how do national security professionals and practitioners typically feel about what I described. If you remember back maybe about 15 minutes ago. Surprise, we're back to the danger zone again. There's this real concern that as people have access to these technologies that they can do all sorts of things with them and they're not necessarily benign. Things that you know people can do. So, scouring through the WMD literature, especially as it relates to non state actors. But, you know, particular, you know, the WMD context. There's three general trends or three general considerations that national security experts seem to be focused on when they think about the change in risk associated with the development of WMD and the use of WMD in the modern day. So, in terms of capability as capabilities increase as people can do more things with the technology. That means that people are then able to leverage that technology to do lots of things. So, if people are able to do lots of things that increases the playing field of not only could they use the increased capabilities for good, but also for nefarious purposes. The second major trend that I noticed in terms of assessing WMD risk is increases in convergence so there are lots of different players that are getting involved in science nowadays. And it's not just, you know, citizen scientists, but disciplines are also converging. So, synthetic biology is actually a convergence between biology, you know, the traditional life sciences, and the application of engineering principles to biology, trying to make it easier to design, easier to test, easier to build, making it easier to produce products with. So, as these different groups and different communities engage with each other, there's less certainty about what the outcomes will be. And it's harder to predict what outcomes will come from what interactions. And so, the lack of certainty also contributes to the sense of concern that, you know, as as more communities work together with each other or different disciplines work with each other.  And finally, in terms of increased accessibility technologies, you know, people talk, talk often about how gene sequencing and gene synthesis prices are consistently falling rapidly. So that makes them financially more accessible to a broader audience. So these technologies also are becoming more available secondhand on secondhand markets, because there are a fair number of biotech companies that, you know, there's a high rate of failure in biotech. So when a company goes out of business, they often set things up so that they either donate their equipment to other people that, you know, are interested in them they sell them on eBay. So as these technologies become more accessible to a broader audience, there's also this perception that there's a loss of control of the equipment of the reagents of all of these things, which then contributes to this idea that the the risk of weapons of mass destruction development research and use are increasing. And these are just some examples from the state actor perspective. So in the upper left hand corner, you have a 3d printer, the, you know, one of the concerns with 3d printing is, as it becomes more capable as we're able to do more granular things with it. Maybe states or potentially non state actors could use that granularity that specificity to develop nuclear weapons parts or parts for a nuclear centrifuge. In the upper right hand corner, we have, you know, a graphical image of CRISPR so this idea of gene editing. And as you know gene editing becomes more prevalent as gene editing becomes more accessible to a broader audience. It becomes not only harder to control the technology but it also is just really hard for people to arrive at what would be approved and unapproved uses of gene editing technologies because as you broaden the pool, you know, you have an expansion of opinions, opinions are like assholes everybody has one.  And then, you know, within the non state actor context, here's that concern again about the use of weapons of mass destruction or the facilitation of uses of weapons of mass destruction so as drone technology becomes more prevalent. It may be possible to use drone technologies themselves as a weapon of mass destruction in terms of, you know, if you have a concentrated number that's swarming, attacking a particular position that could, you know, result in massive, massive casualties and massive damage. So looking at the fact that drones with swarming technologies may aggregate and be able to be used by non state actors to do significant damage to infrastructure to individuals, things along those lines to the upper right hand that image. So the non state actor space that was a sarin factory in Japan. That was being run by a group called on machine Rico, the bottom image is in reference to a marathon X a domestic event that happened in 2001. Largely believed to have been done by a single individual. And that kind of anthrax to the postal system.  So where does do it yourself biology fit and I would argue that if you look through the lens of a national security person looking through this framework that you could argue that do it yourself biology appears to mean a greater perceived WMD threat to the national security space. So, you know, you have people getting access to, you know, use lab equipment that contributes to a diminished sense of control over being able to control the supply of equipment reagents things along those lines. You also have an increased convergence so you have not only traditional people doing the life sciences, but you also have regular citizen scientists contributing towards, you know, various kind of life sciences projects, which means you're not necessarily knowing how, you know, what what the outcome will be of the types of work that these people are doing. And, you know, technology is only getting not only cheaper but more efficient more capable so as technologies become smaller as technologies become faster as technologies become more things like gene sequencing devices that are, you know, tabletop gene sequencing devices, or potentially even genes, gene synthesis devices that are tabletop. So, unfortunately, it seems like doing yourself biology from a national security angle is a thing that deserves some concern and, you know, increases the potential for WMD threats from that perspective. And that is, you know, this typical perspective that you see in national security circles. So here are a few quotes. You can read through them, but mostly they're about how technology is becoming more accessible specifically gene editing. People may be able to do all sorts of things with these technologies as they become more available. And, you know, these are communities that have traditionally not necessarily been involved in life sciences so there may be security and safety implications that go along with that kind of naivete that amateur element. So, I saw this issue, and I was trying to balance it with my perceptions and my experience being involved with the community for five years at this point. It was very frustrating to be honest to sit in and listen to people talking about do it yourself biology as a threat. When I from my personal observations and interactions. I thought there was a more complex picture at play. So, you know, with the support of my committee with the support of the do it yourself biology community. I developed a dissertation project looking to understand do it yourself biology community labs from a social science aspect. Following very much in line with what Dr. Farnsworth recommends in terms of how to proceed with the scientific method. So I developed a one year study. It looked at 10 community labs across the United States as well as major spaces that are associated with community labs. So for example, MIT Media Lab is a place that is not necessarily a community lab it is a major convening space for community labs. In terms of the activities that I engaged in I did in depth interviews. I also actively participated in projects, classes, labs throughout that year, and I also did observations. I gathered field notes and I highlighted observations over the course of a year to develop a very deep understanding of the community labs that I was able to associate with. So this study really focuses on four things. How people find out about community labs what motivates people to participate in community labs, how they are organized, and how people learn and teach in these spaces. So getting to how people find community labs. Interestingly, actually not interestingly because it's, it's, you know, it's I think it's a pretty obvious phenomenon. Nowadays, the most prevalent method that people find community labs is through the internet. As Homer Simpson points out, they now have the internet on computers. So that seems to be the most popular method people are interested in finding lab spaces and so they look online people are interested in finding science spaces. So they look online. So that's a typical method that was the most prevalent method from what I saw in the study, but other methods include interpersonal connections so friends telling other friends about community labs. Professional connections as well so individuals that are interested in say bio art, and they're like instructors of art at various institutions. They hear about community labs as these kinds of innovative spaces for bio artists, and then that's how they then go to these community labs. There's also direct community lab outreach so community labs often have web pages, they have meet up sites, you know, things like that. And then sometimes it's just the role of the dice it's serendipity. So, you know, there were a number of people that I talked with throughout the process that said hey, I was going to this one place because a friend told me about a poetry slam. That was happening in this building. And then I looked around the corner and I found out that there was this lab that was in this building as well so serendipity also does play a role. It's not exactly empirical but I think it's just a really interesting interesting little factoid to toss in there sometimes it's a little random. So what motivates people to participate in community labs, the main one is a passion for science. These individuals are very passionate about science they want to learn about science, maybe they want to engage in science, but there's this fundamental desire to engage in science, and that's what motivates people to not only start going to community labs, but continue participating in them. And then you know there are a number of other elements to you know these are some just some of the top ones. Social interaction so you know community labs, the word community is in there. Community members come together and they talk so social interaction is considered a very positive motivation for why people go. People also believe in the mission of community labs and democratizing science so there's an alignment of values with the organization. People also like to engage in community spaces because there's community engagement you get to engage in community projects and work with community people to build things for the community. And another major one is just this idea that outside of a traditional institution like academia industry and government. You have access to an actual BSL one lab. So you can actually have hands on experience rather than just read from a book, you can actually you know get your hands a little dirty and do you know learn and do some science. So how are community labs organized. This is a blatant steal from Alex Perlman's Twitter, Alex Perlman is an amazing bio ethicist who works closely with the DIY bio community this was from global bio summit. I believe 3.0 it may have been 2.0 Alex can correct me. I'm sure she's involved in bio hacking village this year. But in this picture, David Kong at MIT Media Lab is presenting how he sees community labs being organized, which is as an armada of pirate ships. So this, you know, these pirates, they loosely associate with each other as a group, but they also kind of go their own path in their own direction, depending on their own particular whims and their own particular desires. The idea here of course is also that there isn't there is a loose organization, but it's not exactly hierarchical and entrenched in stone. So you know, community labs are often organized this way, you know, not only from a community lab to community lab basis like an organizational basis, but also just like within a community lab itself. So what are some of the advantages and disadvantages of having this loose organization style. Well, I see some of the advantages as being autonomy. People can do what they want. Individuals can do what they want. Community labs can engage in projects that they want. So both of these community labs are volunteer based. So they actually have a really incredible ability to operate with exceptionally low budgets. What often comes up in conversations with community lab leads and individuals is they run shoe string budgets. And finally, with the autonomy element connected with it. So community labs can engage in activities that are reflective of the unique local and regional communities that they're a part of. So in the case of bugs, for example, based in Baltimore, Maryland, they're really interested in barcoding or understanding what lives on a genetic level in the inner harbor, which is a body of water that is very significant to, you know, the Baltimore ecosystem. One of the disadvantages, though, is because each group is autonomous and they're so distant. Sometimes they're coordination difficulties. You could have issues with coordination across even the United States because there are time zone differences. You also have coordination difficulties within organizations in terms of this because of the fact that they're volunteer based. The thing with volunteer based is while you have a lot of people that are willing to do work for no money. When there are situations that are take precedence over your hobby of engaging in the community. That means that DIY bio activities won't always be a top priority. So things can fall through the cracks. And just as I mentioned that they're able to operate in shoestring budgets, there are severe resource limitations and it's not just financial. So a lot of community labs depend very heavily on the lab leadership to do a lot of the heavy lifting and that's usually one to two to three people that are essentially in charge of making sure that a shoestring budget organization continues onward. So that's a really large burden. There's a significant concern in the community for burnout people that eventually get burned out because they've taken on too much for a long period of time and there's no respite. So in terms of finally how do people learn and teach in these spaces. We divided out the activities as structured so versus unstructured. So in terms of how people learn in these spaces. There are the structured styles that actually reflect a lot of traditional academic teaching styles so they're pure lectures. There's hybrid lecture and lab courses and there's project participation unstructured styles include you know just casual conversations impromptu conversations impromptu demonstrations where people just engage with each other and then just kind of take take things as they come and you know just explore with each other in an unstructured fashion. And in terms of the style of teaching in these spaces. Once again it's very reflective of a traditional academic style and the thing I want to emphasize here is the traditional academic style is not random. A lot of these community labs are run or founded by individuals that have advanced degrees and from academic from academia. So you when you look at a board or a leadership of a community lab more often than not you will see individuals with PhDs and molecular biology, electrical engineering bioinformatics just, you know, these are highly educated individuals and so it's not surprising that that traditional academic style bleeds into how they then structure the learning and teaching environments in, you know, in community labs. So, you know, in terms of like groups. They use traditional academic academic approaches like lecturing small group demonstration and practice. And then you also have these mentorship. One on one interaction so when people are learning like a significant number of lab skills they're really trying to beat themselves up learning from a PhD in, you know, in traditional science, then you get into more of these like hardcore mentorship relationships where they interact one on one, the person that is learning shadows their mentor, the person that's learning practices consistently, and the mentor is there often in the beginning to monitor the progress of the individual. So, I talked a lot about, you know, how people learn about these spaces motivation. How people learn in these spaces and how these places are organized so is there an implication to these kind of like social elements. And I would argue, yeah there is let's revisit that framework of in, you know, of perceiving as it relates to, you know, from from the from the do it yourself biology community. So does increase potential capability lead to a greater efficacy for do it yourself biology can you do more things as capabilities increase. And you know what on the one hand yes. So people can construct you know, self made Arduino board guided incubators for plants. So DIY constructs people can engage in their own sample preparation and analysis. And, and people can even, you know, in high school, through programs like I gem engaged in synthetic biology projects in a DIY bio context. However, I would also argue that from some of the observations and some of the data that I acquired. It's not necessarily just because potential, just because there's an increased potential capability does not necessarily lead to greater efficacy in the DIY bio context. The DIY bio context like I mentioned, there's a lot of second hand third hand equipment self made equipment. There's a lot of equipment breakages, which interferes directly with the ability to do science. Also because DIY bio places are places of learning and of education. There are lots of errors that happen along the way it's not just professionals doing the sampling and the analysis. It's people that are being taught as well by these professionals by these you know knowledgeable people. And guess what the students learning they make lots of mistakes. I can tell you for a fact that I made a ton of mistakes, as I was learning how to just even basically pipette things. Also community lab lab suffer from environmental contamination issues. We're talking about places where biology is being in being done in unconventional spaces, you know, whether it's in a warehouse, or it's in, you know, a building, or whether it's a place that doesn't have a separate room for your PCR machine that's being kept sterile, so that you can get lots of environmental contamination that way. And then you know you just have issues with supplies and logistics so there's this from my understanding from the research, there's a very negative conceptualization of the term bio hacking. So any place that refers to themselves as a bio hacking place so whether it has bio hacking in the name, or things like that companies that produce reagents are very wary about sending reagents to such spaces so you know that could be a limiting factor as well. So does also, you know, in terms of that second risk issue does greater convergence lead to less certainty of outcomes in the DIY bio context. So, on the one hand, yes. People engage in lots of really cool independent projects that you don't necessarily see in academia so there's this really interesting. It's almost like it's almost looks like a photo that they took on a leaf of a particular logo. I don't quite remember how they did it, but it looks like magic to me but that's not something that I would expect coming out of an academic lab. Once again, there's that barcoding the inner harbor project, the open insulin project also is a really interesting example of having citizens get engaged in science. So not only is open insulin about finding ways to develop and distribute insulin, given the insulin crisis in the United States and across the globe. Nowadays, but it also sends a political message of saying that, you know, big pharma is holding the lives of diabetics in its hands and trying to find a way to disrupt that. So, yeah, you know, there are, you know, there is a certain type of less certainty that comes from an increased convergence but on the other hand, no. One of the things that I found as I was doing my research was there are definite limiting factors, it's almost like a path dependence model for community labs, where community labs are shaped by the environments that they exist in and the organizational factors that, you know, that they have. So in terms of leadership expertise, the individual that runs the lab depending on their expertise may be more inclined or less inclined to do certain projects because they might not necessarily be comfortable with doing things that fall outside of their expertise. There's also the expertise of the community if you don't have a particular type of expertise that you need to run a particular type of project you're probably not going to pursue that project. There's also community interest and resources. So, is there an interest in the community to actually do a particular type of project or not. And, you know, in the case of, in the case of bugs for example, like I said they're really focused on that inner harbor. And so they're interested in doing projects that reflect the community but they might be less interested in doing another type of project that does not reflect the community. And finally, there are a number of community labs that actually have higher education affiliations and being connected with these higher education affiliation, you know, these higher education affiliates. And finally, because higher education, you know, affiliates tend to be a bit risk averse when it comes to interactions with outside entities, it, you know, inherently acts as a limiting factor to make sure that community labs don't just do whatever they want. If they want to participate and get kind of like the validation from higher education, they need to play by certain rules. Okay. Does the increase accessibility of technology and knowledge lead to less control in the DIY bio context. So, yes, right. People can do independent research, people can learn how to do lab skills and techniques, potentially on their own at least basic ones like pipetting, particularly through online resources. You know, there's readily equipment and tools available online for people that want to engage in do it yourself biology projects. However, I would also argue that the increase accessibility of technology so technology and knowledge alone. They don't necessarily lead to less control because there are other factors to take into account than just these capabilities of like knowledge and capabilities of technology. So, once again, community labs are limited by several factors. There needs to be a sufficient amount of scientific expertise in the community to be able to engage as a community lab. You know, a lot of this as I discussed before is addressed by the fact that a lot of these community labs are founded by people that are experts in science so PhDs and molecular biology, things along those lines. But there also needs to be a desire or a need for a community lab space. So you're not going to find community lab space popping up literally everywhere. It's not going to be easy yourself for a community lab space in Silicon Valley, for example, where bio curious is based, or in Boston where boss lab is based or Baltimore where there's a biotech hub in the Rockville area. But you're not going to, you're not going to, you're going to have a lot of difficulty finding a community lab space in, say, Cairo, Illinois, which is predominantly farmland. It's not that much of an, you know, that much of a resource and interest in science. You know, and then there are a couple of other issues, availability of resources and then there's networking communications issues, which I've previously discussed. So what are we left with. It's not like I'm saying that there aren't changes that happen with the introduction of do-it-yourself biology to the national security landscape. You know, the implications exist. There are potential risks on biosafety, biosecurity, cybersecurity elements, which I'd be more than happy to talk about during the Q&A. And, you know, the thing is, national security experts have a lot of things to deal with with very little time. And so having a framework to be able to assess risk is very helpful. These frameworks are like heuristics. They're fast. They work as a mental shortcut. They can be correct. And they're based on the information available. And that said, they may lead experts and policymakers astray. The focus may be diverted from more pressing issues and we may be missing opportunities by, you know, throwing DIY bio out with the bathwater. So don't pull a run.  So I think most of the opportunities that I think that we're missing by not fully leveraging DIY bio, one of them is grassroots education, community building and science communication. I think that particularly in an age of misinformation and disinformation, having a community-based science resource could be very helpful in terms of dealing with misinformation and disinformation campaigns. It can function as trusted sources of science information and hopefully communicate proper information that may be helpful in addressing those kind of misinformation and disinformation campaigns. I also see it as a supplemental education resource. So it's not a resource that is taking away from traditional education mechanisms. Rather, it is supplementing the things that people are learning in school. Particularly the way that I see it being helpful is it offers hands-on experience to individuals. Traditionally, when in academic institutions, they learn a lot of theory. And finally, I see it as an accelerative education resource. So community labs can function very well as places that could expose people that are younger to STEM and critical thinking. Providing individuals with opportunities to see if science is their passion when they're five or six, rather than having to wait, you know, until they're more in their teens. And the other thing that I think that we're missing when we don't highlight and lift up DIY bio is its potential contributions to the bioeconomy. So the nasum 20, there was a nasum 2020 press release that said that the bioeconomy comprises 5% of us GDP, which when you crank the numbers out comes out to be nearly $1 trillion. It was 950 billion, but I think nearly one trillion just sounds that much more impressive. So, you know, given the large amount of money at stake, I think it's interesting that we aren't talking more about leveraging community labs as incubators for future biotech innovation. So we already have some proofs of concepts of this from several community labs, including the open trans project from gen space, which is automating lab technologies, as well as over 30 companies that were incubated a bio curious which is based in Sunnyvale, California. So, in the context of the talk, what do I think we need to think about. And there are two main lanes that I think we need to think about the first thing is addressing DIY bio community obstacles. So we talked about how there is burnout and heavy leadership reliance issues so bandwidth issues. And so, particularly being volunteer run means that individuals have very little bandwidth to work with when they're, you know, in this context so we need to be very cognizant and find out solutions to deal with those bandwidth issues. So I think we need to use the resource issues. Like I talked about financial issues, access to good equipment access to reagents, things along those lines, and something that I particularly want to emphasize is balancing the economic needs of the community so understanding that is a very important element of making sure that community labs are available and are open and can operate, but also making sure that we don't lose track of its of its of its spirit of its desire to not necessarily be all about capitalism and efficiency, but for it to be a place where people can explore and build communities because I think there's value in both. And then finally, I think the other thing that we really need to look into is part of the issue with the DIY bio image in the national security arena and other areas is, I don't feel like it's had proper exposure. There's a lot of hearsay and a lot of like media articles rather than direct connections between the DIY bio community and other life sciences stakeholders so building those bridges building that collaboration I think it's incredibly important with members of industry governments, governance institutions and public health. If you survive this long, I first want to congratulate you. That was a lot. I hope that it was a lot of good food for thought. So I want to first, you know, take a moment to acknowledge the do it yourself biology community members and organizations that really helped me out in understanding the community lab scene. I really see this as a community based project. I really see this as my contribution to DIY bio by engaging in a community based project with community buy in. I want to make sure that I think the community labs and DIY bio members at bio curious bio design challenge, biologic, biotech without borders, boss lab bugs, counterculture labs, gen space, indie lab, MIT media lab and open bio labs. I really do thank you from the bottom of my heart. And I use that RuPaul animated GIF to show that. And then finally, you know, there's this other side to like I said, I'm in that sec, a national security person as well and my, my thinking about the community and my drive to be able to engage with the community to fill what I feel is a very serious gap in the national security perspective would not have been possible without all of the people that are here as well on the security and safety side. So I really want to thank Nina bow knowledge Sydney, Josh, and everyone at bio hacking village I really do appreciate you giving me this platform to, you know, have these conversations to build connections and see what comes out of it. I also really wanted to thank Gregory Copeland, Sonya Ben-Walgam Gormley and Trevor Trevor Thrall George Mason University, Natasha Bajima at nuclear spin cycle. Hi, quick and at NCSU, Seth Karris Diane view list Gerald Epstein at the Center for the study of weapons of mass destruction. GG quick rumble at Johns Hopkins Center for Health Security, as well as Matt Watson and Crystal Watson and Michael Montague, and then a special shout out a little shout out to my Friday LB night crew, Nicholas Evans, Emily Kelly, Mary Lancaster, Amanda Moody, Sasha Popescu and Emily ricotta. And with that, I'm sure that everybody has questions comments. If you want to also even engage in a bit of old fashioned trolling I'm available for available for Q&A. You can have you have my email right there and you also have my Twitter. And with that, we are done. And I want to thank everyone for hanging for hanging in there with me.


Welcome back to HPE Discover 2021. My name is Dave Vellante and you're watching theCUBE's virtual coverage of Discover 21 and we're excited to welcome back Arwa Kadura, she's the vice president and worldwide go-to-market leader for HPE's Smoke and Hot Green Lake Cloud Services. Arwa, welcome back to theCUBE, good to see you again. Thank you for having me, good to be with you. So, talk about how your products and services are supporting customer transformations. I'm interested in the experience that everybody's been dreaming about. Describe how you're giving your customer that competitive advantage and if you got any examples, that would be awesome. Yeah, you got it. I think as we heard Antonio say, the cloud is an experience, not a destination, right? And what we're doing with Green Lake is bringing those cloud capabilities and the cloud experience to our customers. We like to say co-locations, data center and edge, of course. So, this is the cloud on-prem. And so rather than forcing customers to only have to go up to cloud to get modern cloud capabilities or the benefits of things like pay as you go for consumption, et cetera. Cloud-native capabilities like containers, leveraging Kubernetes. We now bring all of that to Green Lake and to our customers' edge locations and co-locations and data centers. We've been able to dramatically transform many of our customers' businesses, right? And you'll probably see it discover some of those examples come to life. For example, Care Stream, who is in the electronic medical imaging world, right? They have all of the X-ray equipment that capture X-rays and different sort of diagnostics for patients. And we work with them to not only craft a ML solution to better read and diagnose these images, but also all of the underlying infrastructure with the HPE Green Lake ML Ops platform that allows them to instantly leverage the capabilities of machine learning and the infrastructure to go with it. And so tell me, so how is it resonating with customers?  What do they tell you? You know, I think what our customers appreciate about HPE Green Lake is it's not sort of, look, it's either all on-prem in my data center and I have to fully manage it, build it, implement it, take care of it. Or it's fully public cloud, I have little control and basically I get whatever the public cloud gives me, right? HPE Green Lake gives our customers the flexibility and control that they require, right? And so you can think of many use cases where customers have a need to have the, you know, compute storage sort of processing need to happen closer to where their data and apps live. And so for that exact reason, our customers love the flexibility, right? Cloud 1.0 was public cloud, Cloud 2.0 I think is the cloud that comes to our customers at their convenience. And to me, you know, what I tell CIOs and CTOs and sort of other lines of business leaders when I meet with them is you shouldn't be forced to have to take your data and apps elsewhere to get the transformation that you need. We want to be able to bring that directly to our customers. Of course, a lot of the transformation is around data. We love talking about data on the cube. And it's funny. I mean, we talked about big data last decade. We don't use that term much anymore. And it was kind of overhyped. But as oftentimes as the case maybe in the early days it's overhyped, but then it's underhyped when it actually starts to kick in. And I feel like we're entering a new age of data and insights with the ascendancy of machine learning and AI. What does this mean from HPE's perspective and what are customers telling you that it means for them? Yeah, no, data I think we often hear data is the new currency, right? It's the new gold. We've heard Antonio even say things like, look, data could even become something that maybe over time companies start to put some kind of value on their balance sheet behind, right? The same way that maybe brands represented this value on a balance sheet. Effectively what's happened with data is a lot of people have a lot of data but there's not been a lot of ability to extract insights from data, right? And I think this is the new revolution that we're all undergoing is we finally have the modern analytics tools to actually turn the data into insights. And what we bring to the table from an HPE perspective is the fact that we have the best infrastructure. We obviously now have the cloud capabilities mixed in with our data fabric, our container platform, our machine learning operations platform to then be able to process that data. Again, integrated with many of the great ISV partners that we have on the data side, allow our customers to turn that into real insights for their business. And effectively data is becoming a huge competitive advantage, right? I think many of us are, you know, leveraging some, you know, pretty interesting tools or gadgets these days, right? Like I wear one of those, you know, sleep rings. You can imagine a company like that in the future that's able to collect so much data from the folks that purchase their products, then being able to give us insights about, you know, where's the best zip code that, you know, people get the most amount of sleep in or, you know, which zip codes are the healthiest in, you know, the United States or countries, et cetera. But data really is becoming, you know, a competitive advantage. And one of the things that we care most about at HPE is also using it as a force for good and making sure that there is a sort of ethical AI capability. That's a great message and very important one. And it's interesting what you're saying about data and the value, how we, it's clearly, it's clearly being valued in terms of companies' market caps. I mean, it's, you know, maybe it's not in the balance sheet yet, but it's on the income statement in terms of data products and data services, that's happening. So we'll see if Antonia is right in the next, you know, several years. But so let's talk more about the specific data challenges that you're solving for your customers. They talk about silos. They talk about they haven't got as much value out of their data initiatives as they wanted to. What are they telling you? Are there challenges and how are you approaching it? Yeah, I think, you know, data's everywhere, right? The ability for customers to store the right amount of data is a huge challenge because obviously there's, you know, a huge cost associated with collecting, keeping, cleansing, processing, you know, all the way to sort of analyzing your data. There tends to be a ton of data silos, right? So customers are looking for a common data fabric that they can then process their data sources across and then be able to sort of tap into that data from an analytics perspective. So much of the technology, again, that we're focused on is be able to store the data, right? Our data fabric layer with Esmeral, right? Being able to process that data, capture that data, and then allow the analytics tools to then harness the power of that data and turn that into real business insights for our customers.  And, you know, the real sort of challenge for them is how do I build a common data platform that allows me to tap into that data in effective ways for my business users? You talk a little bit about how you're changing the way you're providing solutions, maybe you could contrast it with the way HPE has done it in the past, because I think that's important when you think about, when you talk a lot about GreenLake and as a service, but if the products are still, you know, kind of boxes and lawns and gigahertz and ports, then, you know, that's a discontinuity. So what's changed from the past and how are you feeding into the way customers are transforming their business and supporting their outcomes? That's exactly right. You know, at some point in time, right, if you think maybe 10 or 20 years back, it used to be very much about the infrastructure for HPE. What's exciting about what we're doing differently for our customers is, look, we have the best infrastructure in the business, right? HPE has been doing this, you know, longer than anyone has, probably almost 60 years now. But being able to vertically integrate, right, move up in that value chain so that our customers can get more complete solutions is the more interesting part for our customers. Our customers love our technology, yes, the gigahertz and the speeds and feeds, all of that do matter because they, you know, make for some very powerful infrastructure. However, what makes it easier is the fact that we are building platform stacks on top of that hardware that help abstract away the complexity of that infrastructure and the ability to use it far more seamlessly. And then, if you think about it, we of course have also one of the most advanced services organizations. So being able to leverage our services capabilities, our platform capabilities on top of that hardware, again, deliver it back to our customers in a consumption model, which they've come to expect from a cloud model, and then surrounded by a very rich ecosystem of partners. And we're talking about system integrators that now have capabilities on helping our customers run their GreenLake environments. We're talking about ISVs, right, so software stacks and platforms that fully integrate with the GreenLake platform for completely seamless solutions, as well as channel partners and global distributors. So I think that's where we can truly deliver the ultimate end-to-end solution. It's not just the hardware, right, but it's being complemented with the right services, being complemented with the right platform capabilities, the software integrations to deliver that workload that the customer expects. As partners, they got to place bets. They got to put resources, time, money, and align their resources with their partners and their suppliers, like HPE. So when they ask you, hey, okay, HPE, tell me, Arwa, what's your overall strategy? Why is it compelling, and why do you give me competitive advantage relative to some of your peers in the industry? Yeah, I think what partners are gonna be most excited about is the openness of the platform, right? Being able to allow our partners to leverage GreenLake Central with OpenAPI so that they can integrate some of their own technologies into our platform, the ability to allow them to also layer in their own managed services on top of the platform is key. And of course, being able to build sort of these win-win solutions with the system integrators, right? The system integrators have some fantastic capabilities all the way from an application development, all the way down to the infrastructure management and data center delivery centers that they have. And so leveraging HPE GreenLake really helps them have access to core technologies that they need to deliver these solutions. I wonder if I could take a little sort of side road here and ask you because there's so many changes going on. HPE itself is transforming, your customers are transforming, the pandemic has accelerated all these transformations. Can you talk a little bit about how you've transformed go-to-market specifically in the context of as a service?  Yeah, no, go-to-market transformations in support of sort of moving from traditional go-to-markets to cloud go-to-markets are significant. They required us to really think through what does delivering as a service solutions mean for our direct sales force? What does it mean for our partners and their transformations in being able to support as a service solutions? For HPE specifically, it also means thinking about our customer outcomes, not just our ability to ship them, the requisite hardware and say, look, once it's left our job is done, right? It really takes our obligation all the way to the customer using the technology on a day-by-day basis, as well as supporting them in making sure that everything from implementation to set up to the ongoing monitoring operations of the technology is working for them in the way that they'd expect in an as-a-service way, right? We don't expect them to operate it. We don't expect them to do anything more than pick up the phone and call us if something doesn't go as planned. And how about your sellers and your partners? How do they respond? I mean, you just wake up one day, say, okay, guys, here we go, new compensation scheme, new way to sell, new way to market. That took some thought and some time and where are you in that journey? That's right. I always say, if you expect people to wake up one day and be transformed, right? You're kidding yourself. So everything from sort of the way that we think about our customers' use cases, right? And empowering our sellers to understand the outcomes that our customers expect and demand from us to things like compensation, to the partner rebate program that we leverage through the channel partners in order to give them the right incentives to also allow them to make the right investments to support GreenLake. HPE has a fairly significant field, sales, and solution team. And so not thinking about this only as a single person that represents GreenLake, but looking at our capabilities across the board, right? We have fantastic advisory consultants on the ground with PhDs and data science. We have folks that understand high performance computing. So making sure that we're embedding the expertise in all of the right personas that support our customers, not just from a comp perspective, but also from an understanding of the end-to-end solutions that we're bringing to those markets. So what gets you stoked in the morning?  What are you most excited about for HPE and its future? You know, there's so much happening right now in this sort of cloud world, right? To me, the most exciting portion is the fact that given that we've now introduced on-prem cloud to the world, our ability to ship new services and new capabilities, but also do that via a very rich partner ecosystem honestly is what probably has me most excited. This is no longer the age of go at it alone, right? So not only are our engineering and product teams hard at work in the engine room producing capabilities at sort of lightning fast speeds, but it's also our ability to partner, whether it's with platform providers, software providers or system integrators and services providers. That ecosystem is starting to come together to deliver highly meaningful solutions to our customers and all in a very open way. The number one thing that I personally care about is that our customers never feel like they are being locked in or that they are sort of being forced to have to give up certain levels of capabilities. We want to give them the best of what's out there and allow them to then have that flexibility in their solution. And one of the challenges of course with virtual events is you don't have the hallway track. You know, somebody can say, hey, have you seen that IoT zone? It's amazing. They got all these robots going around. So what would you say that people should be focused on at Discover, maybe things that you want to call out, specific highlights or segments that you think are relevant? Yeah, there's going to be a ton of fantastic stuff. I think, you know, really looking for that edge to cloud strategy that we're going to be spending a lot of time talking about looking at some of our vertical workload solutions. Right, we're going to be talking about quite a few from electronic healthcare records to payment solutions and many more. I think depending on what folks are interested in, there's going to be something for everyone. You know, Project Aurora, which now starts to announce our new security capabilities, you know, the zero trust capabilities that we're delivering is probably interesting to a lot of our customers. So lots of exciting things coming and I'm excited for our customers to check those out. No doubt that's a hot topic, especially given what's been happening in the news these past several months. Arwa, thanks so much for coming back to theCUBE. It was great to see you. Hopefully face to face next time. I sure hope so. Thanks so much for having me. It's our pleasure. And thank you for watching and thank you for being with us in our ongoing coverage of HPE Discover 2021. This is Dave Vellante. You're watching theCUBE, the leader digital tech coverage.


Hi! Welcome to OISOM Academy. Let's begin with all you need to know about PM1. Particular matter is not a single air pollutant but refers to a complex mixture of solids and aerosols of varying shape, size and chemical composition. They are composed of various chemical species like organic compounds, inorganic ions, metallic compounds, elementary carbon, etc. They are either directly emitted from a source or are formed through chemical reactions of other air pollutants such as NOx, SOx, VOCs in the atmosphere. As the impact of particulate matter exposure on human health directly depends on the size of the particles, they are classified by the diameter for air quality regulatory purposes. The particles with a diameter of 1 micron or less are collectively known as PM1. Sources of PM1 include marine aerosol, soil erosion, volcanic eruptions and forest fires. Other sources are burning fossil fuels, agricultural processes, cooking and cigarette smoke, emission from diesel powered vehicles, power generation, industrial processes and so on. These ultra fine, inhalable particles remain suspended into the air due to their negligible mass making humans more susceptible to exposure. PM1 particles are 400 times thinner than a human hair and travel deep into the lungs to the alveoli and may enter the bloodstream reaching other parts of the body. Now initially it causes irritation to eyes, nose, throat and upper respiratory tracts, cuffing, sneezing and shortness of breath aggravating already present respiratory diseases. Prolonged exposure causes permanent respiratory diseases such as asthma, chronic bronchitis, heart attacks, lung cancer, edema, etc leading to premature death. PM1 alters the absorption and scattering of light in the atmosphere affecting visibility. They majorly contribute to small formation. PM1 monitoring is an efficient way to detect high concentrations of particulate matter and prevent high level exposures. Now different working principles for monitoring particulate matter of all sizes in the ambient environment are gravimetric, TOM, beta attenuation and laser scattering. OISOM's PM sensor works on the active sampling method of laser scattering that counts particulate matter using a highly accurate laser beam. OISOM's DESTROID is an online particulate monitoring system that measures the concentration of various particulate sizes ranging from 1 micron to 100 microns such as PM1, PM2.5, PM10 and PM100 in the ambient air. DESTROID can be used for dust monitoring in areas with dust lead in activities like construction, mining, quarrying, ports, metallurgical processes and many more. Real-time particulate matter monitoring using DESTROID can assist in dust separation automation. For instance, to activate suppressants at a location once the threshold is breached. I hope you now know all about PM1. For any questions or suggestions, please contact us. Thank you and happy learning.


Selamat pagi, selamat datang kembali. Nama saya GameGaum. Saya adalah pembangunan pembangunan untuk kerunom dan pembangunan platform. Seperti biasa, saya mulai mengambil sponsor Microsoft Open Sousa. Gary bekerja untuk Sousa. Oracle, MySQL, Devleta dan beberapa nama lain saya tidak pasti apa-apa. Okey. Okey, so the talk by Gary Lee, who works for Sousa, is a developed UEFI with Open Sousa. In the bio-style firmware was usually obscure and always developers had to deal with it by experience. Nowadays, most of the firmware hardware vendors share the code from Open Source Project, EDK II, in their own UEFI implementations. So it's easier to understand how the firmware works, especially the hardware-independent software stack. And the EDK II contains software jack, OBMF, to provide firmware for Qmoo, the virtual machine. So we don't need band metal to implement features of the hardware-independent issues anymore. Okey, no need to flash program, just copy the file to update the firmware immediately. The talk will present how to develop and debug OBMF with Open Sousa and introduce new UEFI features in Open Sousa lead 42.2. So Gary Lee is a Sousa engineer based in Taiwan, long-time leading user, participates in Open Sousa gunung development or participator. Participator or participates? Participate. Okey, and mainly focuses on UEFI related issues now. Okey. Hello everyone and I'm Gary Lee and I work for Sousa. And I'm from the Sousa Taipei. And so I've been able, as I said, my mother will say that I've been able to work on the UEFI stack. So today I want to share with you my experience of developing what UEFI is Open Sousa as best in my daily life. So our topic today is UEFI. So what is UEFI? And it's an acronym of the unified Firmware Interface. So since that is the Firmware Interface between Firmware and our existence. And there is an organization called UEFI Forum and they were made the UEFI spec for the Firmware vendor so they can follow us back to implement Firmware. And as a Firmware vendor and we can we can just use the protocol defined by Firmware to access the hardware resource. So it's more like a easier to a unified way to access the hardware resource among the different firmware. So for the for all its vendors to look like so in the beginning we will load the UEFI from its fresh rom and UEFI will start to load the bloater and UEFI load the bloater and the bloater will load the Nines kernel and Nines kernel will start to start any other service so you can test out the server or whatever. So it looks like BIOS and starts like BIOS and smells like BIOS but it's kind of different. So what very different things from the differences from the UEFI from the BIOS is that there's an open source project called EDK2 and it's actually hosted by Intel and EDK2 is actually a basically licensed reference implementation so every time there's a new UEFI spec then they will add the new features into the IDK2 and nowadays the Firmware vendor just merge the code from EDK2 into their own firmware so maybe the UI will simply render but actually some features they actually use the same code and this is very good for us but we can just check the code in EDK2 and to know what really happened like there are some drivers it doesn't include driver maybe for hybrid driver but basically most of the things are in EDK2 but not for the driver so like your GPU driver or the Neocard driver you will not have it and some maybe the BSP for the bold so you need driver in the firmware? BSP more like the first program for the firmware for the motherboard you will need lab to put into your own EDK2 you need driver to read the hard drive and also to do a network booter? hard drive will maybe not mostly for the network driver and GPU driver so for EDK2 and it's open source project so it's very good for us we can just look into the code and know what happened not like the old BIOS days i heard old firmware assembly code so maybe even open source to you and you will not really understand so and it also it also uses a modularized design so you don't have to build everything into your firmware so you can design which part of the feature you need and just enable it and you also support the multi-core architecture so it's quite good and basically on average there will be one release every year but as i said it's an open source project so actually every day there will be a lot of patches committed into the GPU so for me i am testing the UEFI stuff and i would like to test a new feature as soon as possible so i cannot wait the firmware vendor to provide their own firmware to me too slow because they will have a long QA process and maybe after the UEFI spec maybe after a year they just provide a feature so they will be too late for us so i would need a kind of development board and the development board is a special board you can just flash the firmware and update very frequently and any version you need so they are 2 kind of solution so first is bare mental just physical machine you can buy from intel or indeed they have this kind of thing and the advantage is it's very very close to the production machine and you can add the real name of car new GPU to the machine so you can test it if you want cost of money and also you need a space for the board especially if you buy from intel it's actually an old station so you need a space for that and you cannot buy every generation so it's quite expensive and not very expensive but it's still money maybe $1,300 so you may ask for your and it also can be very slow to flash to program the flash wrong and for example like the Minopo and the SPI if you use this kind of solution you took a wrong 5 minutes you make a vice vice and very slow if you just want to add a debug message and you have to wait 5 minutes and it's not very efficient so this is the solution I choose zero cost I don't ask for my to buy anything for me so it's much easier and it's very very fast to update firmware because you just copy the file so it's very easy and you also can share your settings with your colleagues and especially it's very useful for QA because if you want to verify issue or fix verify bug and QA must know how to set the firmware and with virtual machine you can just tell him how to use virtual machine and what purchasing you are using and that's it but that's the downside if you need something very special like a special CPU or like a TPN it's not very good now and you may have some problem with the virtual machine but for me most of you are working on the software app kind of independent from the hardware so this is not a big issue for me so most of you are using virtual machine so virtual machine so what is my virtual machine solution it's a QMU plus a copy F very standard standard virtual machine nowadays everything is default and OVF is what is OVF OVF is open virtual machine firmware as an example you can see it's a firmware for the virtual machine best is it's an EDK sub-project so actually it shares the codes in the EDK 2 so it also shares the code among all those firmware so this is very good for me I can just test software stack box or software stack features with EDK 2 and with OVF and I can make sure it all works on all those firmware and this is very good now we know OVF and how can we use it so first you have to do the firmware so it's very easy just a few steps so first you chrome the source code from the Github so you can just google the EDK 2 Github and you'll find it and the next step just from the field script in OVF you can add dash D and some new options new options you have to check with me and the field script and so today because I don't have much time for this so if you are really interesting you can check it with me and so if everything goes well field script just force for me force for you and you will get two firmware files first there is an OVF code the other is an OVF bus OVF code is a compiled machine code and the bus is a very kind of special section for the UEFI UEFI you need the tool you need to store the non-monetized data in the fresh run so you need a section in the fresh run message so so the bus is how to immobilize the writeable fresh run so if you are using OpenSloser then you don't have to view it by yourself if you just want to try that you just need to install OVF that dash x8664 and I already package for you so if you want to try that and you can just download and install it it's very easy just one comment and then you will see those files in your systems so I separated the code part and the bus part as I say the bus is kind of special section UEFI has to be writeable and you will see there are some the first NS and it's for the secure boot because the secure boot you have to enroll some key into the firmware and NS is the firmware in order Microsoft key and the other OpenSloser key so I can just put the firmware and test it secure boot was for me after you install that you can try to start your own virtual machine so first you create the firmware the variable store has to be writeable originally it's in the system directory so you have to copy to somewhere you can write so you start virtual machine and you can write it to the bus store and the next you can just create a virtual UEFI system partition this status is not really necessary but I always use it because it's very convenient for testing the UEFI application you can just copy the UEFI application into the virtual UEFI system partition and the firmware can recognize it's writeable so you don't have to create it's convenient for the virtual machine to start your test and the next is to start QEMU so this command looks quite complicated but actually just to those two lines are really matters so first you have to specify the P-flash device for your code code firmware so OVM code part and the other one so you can see the code part has to be read only because it's just code so it's not supposed to be write but in 20 days or you will work and it will firmware so the other one is to specify your bus store and you can see here no read only parameter so it's writeable and readable and this one that's the line is how I create the virtual UEFI system partition so I just specify the directory as a as a fat partition so the firmware can just read the content so if you do it right then you will see screen and Tiana told logo show so you can start your work and to load your UEFI application ok so now we have virtual machine solution and the next question is how can I debug it is a very important question for me so first as C programmer you will very familiar just print the message maybe you do your like you do your C programming and add some printf or printf to print the error message and to try to identify which part is wrong and it's very the same as maybe they do it and add debug message so it's very easy to add debug message there's a markable define in EDK 2 it's called debug, very straightforward and so if you are trying to use debug and you have to specify debug label and then the format is much the same as the printf so if you are C programmer so then what is debug label it's more like it's actually a big mask for the debug message so it's defined in OVF PKG S64 this file it's actually hard hold in the firmware so you cannot change it after you build the firmware so you have to specify value in the very beginning and by default it's 0x8 0,0,0,0 4F then what it means and so like this here so it's more like you just hold all the debug labels so it means you turn on the initialization error or initialize an add message and the warning message you debug it by default you use debug info here usually I use this and actually you can turn on all the debug messages you like but I would not recommend that you can turn on by aside from the OVF to this value but I usually I would not recommend to turn everything on because it will cause your system very very very slow because it's always printing something and it's not very useful unless you are trying to debug some very difficult issues and you really need that then after you have the after you add a debug message then you can you can capture the debug message with a special command from the you can add a debug console so by default you can use you can add this command to the QEM QEM settings and usually I would redirect the error like a debug.loop this kind of file you can also redirect into like a socket or some SEDI or whatever but redirect to the file is the most convenient way for me because I can check the error message later and to make sure what happens so then after you start your after you start your virtual machine and with a debug console and you can check the debug message with another console with a tl-f debug double so I can capture the error message right away so usually you can debug this kind of debug message but sometimes you may have a crash or a serious problem and so you will need another way to catch a crash because sometimes it's crash and it's too fast so the debug message cannot be printed and so it's happened before but sometimes it's very difficult so you will need another another way to debug it and another debug is source-label debugging so actually like you debug OVNF with 3DB so if you don't 3DB and you can debug with that but it's not very easy to setup this because source-label debugging actually but it never works for me and I don't know I never heard anyone really successfully use it so basically I would suggest to download external debug from another and build it by yourself so it's quite a complicated thing and at least if you have I think this slide will be available so if you are really interesting in this thing and it helps in whichever the link later so but if you are using the OVNF and I already take you the debug package for you so you don't have to build all the things by yourself it's very easy just install the debug package and that's it so after you have a debug package and the next thing it's kind of complicated more complicated from another because you have a few steps to setup you need a few steps to setup the debug so first you have to start Qmea with the Dash S or you can use the Dash GDB and specify the TCP code 1234 those two command are actually equal so by default you can just specify Dash S then it means you open the 1234 code for debug and then you have to specify your architecture I usually use S64 so I usually specify so and then use target target remote is a GDB command to connect to a debug in the market but like a GDB server and so in this case it's more like QEMU open a GDB server for software inside the virtual machine so you have to target remote the localhost because I do it in localhost then after this command you will connect to the GDB server and you will see your virtual machine start here because it connect to the GDB server and you will start the virtual machine so after you you type continue and you start to do anything next so after you connect to the virtual machine and you have to include a special a special GDB script is a Python script and GDB can read it and next is to use the command reload the dash and this is the debug signal so it actually is not a real GDB signal start for a GDB signal so after you load the single signal start to pass all the signals in the firmware so you can connect to all the sources for the firmware and after this complicated steps you can debug your just with GDB so it's very useful you can attach GDB and produce your crash and when the crash happen you will just go to GDB and you can use GDB to see the backtrack and do whatever you want variables very useful summary for me i will recommend if you want to try the debug in the UBFI stuff and i will recommend to use virtual machine as you will zero cost development because it's free and you can modify firmware by yourself it's very useful and i will recommend to use GDB development because you can just check a local file and you will know how the firmware works and if you have a crash happen and try to attach GDB basically my suggestion so crash test


Hello New York City! Thank you so much for coming! I heard there were in New York 3,000 people We have some adults who are not at work today either This is an emergency Our house is on fire People's house We all live here It affects all of us And we will not just stand aside and watch We are united behind science and we will do everything in our power to stop this crisis from getting worse from skipping school or work Because this is more important a future that has been taken away from us from scientists or politicians so that we can in the future solve the climate crisis But by then it will be too late We need to do this than here But when it comes to the climate and ecological emergency and the people in power it is pretty much the same In fact everywhere I have been the situation is more or less the same The people in power the beautiful words are the same the number of politicians and celebrities who wants to take selfies with us are the same The empty promises are the same The lies are the same and the inaction is the same Anyone in power who dares to tell it like it is Because no matter where you are even that burden they leave to us us teenagers, us children It is going to be gathered here in New York City for the United Nations Climate Action Summit The eyes of the world will be on them They have a chance to prove that they too are united behind the science They have a chance to take leadership to prove they actually hear us Do you think they hear us? Our education for the adults and politicians to take selfies with us and tell us that they really really admire what we do To get them to act we deserve a safe future a safe future Is that really too much to us? If no one else will take action then we will the ones who are fighting for the future and yet here we are not just some young people skipping school adults who are not going to work we are a way of change this crisis that we have some very bad news for you