It's a great honor to be invited to talk on such an interesting issue of the intersection of open source and AI. Maybe people can call that open source AI. Here's Steph in the back. Come on up Steph. Good to see you. Well, so like I mentioned, I'll invite people to introduce themselves in a second. I'm Justin Colonino. I'm here today representing GitHub and their developer policy team that advocates for policy globally to advance software development, in particular open source software development. I also am an associate general counsel at Microsoft. I'm working on open source software law and I'm on the board of the open source initiative, so lots of different hats. I just wanted to make a few remarks. I was really impressed with the morning's panel so far and I really view it as a testament to the success of open source. Really, and I say this kind of ducking a little bit from the Microsoft perspective, but open source one, it's ubiquitous across software development now. The world has come around to the idea that transparency, collaborative improvement, autonomy, and the freedom to use code for any purpose drives innovation and allows us all to learn and build upon what came before. We heard about that in so many different ways this morning. A driving light of that has been the open source definition and the reason and what that definition really embodies is removing the barriers to sharing. 40 years ago when the first, I called it a proto-MIT license, I'm a lawyer so I'm going to devolve into that for just a second. A proto-MIT license was written. Some folks came to an unknown lawyer in the MIT tech transfer office and said, hey, we want to share this code. Any problem with that? And they said, well, how do we do that? And the lawyer wrote a very simple license that said you have broad rights under copyright law and intellectual property laws more generally. And by the way, we need a limitation of liability because we don't know where this code is going to go or how it's going to be used and that's why we see that big bold text at the end of every open source license that says you take this and do what you want with it, but don't come after me. And so the idea was let's remove the barriers and the barriers of liability to sharing. And removing that enables amazing innovation. It permits frictionless zero marginal cost reproduction. Once written it goes everywhere and can help anyone and it drives innovation in Europe and throughout the world. But now that we've won, there's huge responsibility that comes alongside it. People have questions about security. People have questions about product liability when these things go into, when they go everywhere, what's the liability for the people building the products? And we've just had a cycle of regulation in Europe and in other places kind of thinking about what's the right responsibilities, more barriers to sharing to put on to the software industry generally in open source in particular. And I think it's a testament to open forum Europe and the hard work of so many others in the room that we've come out with solutions that don't impose too many new barriers on that sharing and promote that cycle of innovation. And the one thing I want to say is the fact that people are kind of understanding that open innovation cycle I think is a testament itself. It was a dream 10 years ago when this conference was started that people would be talking about open source and open source innovation everywhere and in particular in areas like artificial intelligence and thinking about the benefits that open source brings. And just we've heard a lot about the trillion dollar demand side number, 8.8 trillion. I just want to put that in perspective for one second. That's three times the market cap of Microsoft. And of course, Microsoft also is a zero marginal cost goods company. We write platforms and those platforms are driven everywhere and we sell them and everybody derives value from them. But the fact that open source is valued at three times that amount I think is very interesting. And I think the difference might be the fact that open source has that permissionlessness to it. It's still zero marginal cost innovation. Once it's written it can be sent everywhere. But it's permissionless and it can be anybody can pick it up and derive value from it. So sorry, we're here to talk about AI. What does that mean for AI? What does that mean for AI? I just want to highlight two things about why we've won an AI in open source AI. At the very beginning, most AI developers immediately started putting random open source licenses on their stuff. It was great. Right away and now you can go online and there are ML models available everywhere. About 500,000 on one site called HuggingFace and that number has been doubling every six months. If we come back in a year, I'd expect there to be just shy of two million. And now we're considering how regulation can support and remove barriers to sharing to allow open innovation in AI but also thinking about kind of the security and safety issues that we've talked seen in software that I think people are thinking might be a little bit bigger in the AR space. So with those introductory remarks, we have some really interesting questions and a really experienced panel.  I'll start from here. Stefano Mofulli, I'm the Executive Director of the Open Source Initiative. I'm Arna Loas, I'm part of the Open Technology Group at IBM. I'm an open standards open source specialist. I've been doing open source since 1990. Hello, my name is Jordanka Invenova. I'm a legal and policy officer in the European Commission in DigiConnect, working on artificial intelligence and in particular, the Artificial Intelligence Act. And I'm very happy to be and replace here my head of unit who unfortunately has an accident and was not able to come, but we are very interested in the debate and want to contribute. I'm Brian Belendorf. I'm Chief AI Strategist for the Linux Foundation, as well as I wear a hat as CTO for the Open Wallet Foundation, another Linux Foundation project, and have also been an open source a long, long time. Hi, I am Mia Petra Kumpula, a natural member of the European Parliament. I am coming from Finland. My engineering diploma is from 1995, and since then I have been doing politics more than techniques. So please, when you go for the technicalities in the questions, I know more in the legislative trials to put the great trials for the future. Excellent. Thanks everybody. So before we get to those really interesting, you know, policy questions, legislative questions, it might be helpful to break down AI a little bit and think about how it's similar to source code and how it might be a little bit different. You know, Steph, you've been doing a deep dive in OSI, as you and I know because we work there. What have you found as you've gone through that process? I, we started thinking about AI because we definitely, we immediately realized that it contains new artifacts. It looks similar, but it's deceivingly similar. We noticed how the pipeline to build an AI system is including new elements, that the, what software is made of is slightly different. And it creates new artifacts that for which we don't have, there is no immediately visible what the legal frameworks are. And I'd be specific. So on one hand, you have, especially machine learning, that requires data on the ingestion front. And when you started to deal with data, all of a sudden you, as a developer, you start getting into, dragged into conversations around privacy or terms of use and other new legislation and legal frameworks that are not, they're not homologated, they're not similar across different parts of the world. And that's a big challenge. Once the data is used in the machine, fed into machine and for training, it generates new artifacts. These new artifacts, model weights, they may have heard the term, these parameters and these new things are the results of this training elaboration. There is no, in the legal communities around the world, there is no immediate natural understanding whether those fall under copyright law or they require new, new laws. So my first impression when I started playing with these new machines, and I went to look at hugging face, I noticed a lot of the licenses that were being used, there are licenses that are being written for with copyright in mind. And my question to my board and other legal experts, I know, was like, oh, how do you feel about that? So when I started sensing these lack of alignment, I asked the wider community, that's the role of the open source initiative, is to be a convener of conversation. So we started asking, what does it mean? And we're driving now this conversation, we've been doing it for over a year, to understand exactly what open source AI means. And we are getting towards a conclusion, hopefully, by the end of this year we're going to have an understanding. The main question that we need to find an answer for is, what is the preferred form to make modifications to an AI system? In other words, how do you change the outputs given the input that you, as a user, want to give? And ultimately, we really want to drive a shared understanding, because we believe that AI systems deserve the same sort of permissionless, frictionless innovation that has driven this immense value that open source software has. Thanks, Steph. And that idea of preferred form of making modifications really has been kind of a touchstone of open source in the past, so that people can pick things up and have that frictionless improvement in innovation cycle that we talked about at the beginning. But maybe zooming way out now to kind of the other side of AI, perhaps. Since generative AI kind of took the world by storm in the past two years or so, there's been an ongoing discussion and debate about perceived dangers and having machines that are able to kind of synthesize and generate text and pictures and video and code and descriptions of chemical, new chemical agents, biological compounds. Your Dhanka, Mia Pietra, as policymakers, how do you consider these, how do you consider this debate as you think about legislation around AI? Yes, first of all, we were prepared. In the parliament, we also had this special group of AI in the digital age that worked for over a year. And we heard like hundreds of specialists to get a glue what we should then later legislate. And the commission was doing its own proposal at the same time. So when we had the proposal, we were even ready. And I was very, I don't even remember everything by heart, but I was very happy when I had the invitation here. So I find the old IDA committee study requested by IDA committee challenge and limits of an open source approach to AI. So I said, oh my God, I have to read this quickly. So the first thing that politicians do not understand, it's not time to regulate something that we don't even have. And it has changed now. Now we are criticized that you are legislating too late. It's too late that today the council should do the AI act and approve it. And also, I think that the USA got bits faster with the executive order that yes, something has to be registered. The risk-based system is agreed globally that it is the good way to look at the for what AI is used. So it's not technology that we try to legislate. It is the use cases and risk-based idea. So I think that the appetite on the political life and more understanding and very much needed public debate came along when it came more publicly that you can have your mobile phone and have AI systems to test a little bit or your 15-year-old is happy that the teacher doesn't know when they have not read the book but only used some language models to make their answer on the book they didn't read but then kind of created own texts. So now it's everywhere. And I think the political response needs to be that it's going to the good direction. It's still some democratic control. There should be some possibilities to see where and how new technologies are used. And then one specific was also that of course the generative AI was not on the commission proposal. Parliament required it. It was the last topic to be accepted also by the council because Parliament didn't want to accept it without. And I don't know technically or even in the articles how successful that is. That is the commission to implement more but then at the same time it cannot be that if you are in charge of something you are doing on the markets that the big players or the generative systems behind many use cases are not responsible at all but then all only the smaller players inventors companies they have to be if they use this for the risk basis. So it's as simple as that the political will was quite clear in the Parliament where to go to. And I just mentioned here very shortly we can later come back to that. We also had the understanding in the beginning of this term that AI is only about data. So where to get data. So I was happy to be the rapporteur of the data strategy for the Parliament in the term. So we wanted to break that pose. So when you are an owner of an equipment connected equipment it doesn't create data if you don't use it. So if you use it should the value only go for the owner or builder of the machine or should that be the new economy for Europe. The data economy that more data will be available for more users for more innovations and even for the equipment user. So these have been like some motivation in this term in the majority of the Parliament to push forward innovative possibilities to use European data. Maybe I can also compliment that indeed we Europe has been one of the leading forces to both promote the benefits of artificial intelligence. It's used because we do believe in the great potential it has to improve our lives to promote competitiveness of our companies and at the same time also address the ethical issues ensure that these systems are trustworthy safe and it's been at the basis with these two objectives that we proposed as was said quite some years ago also the EU communication strategy but also the first legislative proposal for artificial intelligence in 2021 and we are now very happy that indeed globally there is already a big consensus that regulation is not only needed but it is actually very important both to support innovation provide legal certainty how we deal with these challenges with artificial intelligence and also to provide the competitive markets trust build trust very important in both users but also the society about the effects of artificial intelligence including to manage quite some of these risks that were mentioned and indeed today is an important day for the AI Act because we've reached hopefully the one of the key milestones final key milestones when the council will review it and then hopefully we wait also for the parliament and it's very soon adoption in spring and just maybe some elements how we tackled some of the issues that were mentioned how to both promote innovation give legal certainty but also at the same time ensure proportionality future proveness of the legal framework so it really addresses the risks but also contributes to the competitiveness of the companies and trust the basis of our approach is indeed the risk based approach we tackle very specific use cases with intended purposes specific applications as AI systems where there are very important consequences for people's life safety with specific requirements such as data quality as we know that it's quite important to avoid bias ensure accuracy of the systems but also general good practices risk management documentation so that that are quite well also recognized internationally and we did also look into them to the basic models as well because although we regulate mainly the applications we indeed with generative AI and these large language models we've seen that they're so important for the value chain and they are one of the essential components especially those that are big and important and integrated in many applications so indeed one of the key components during the legislative process have been to add special rules for this general purpose AI models including generative AI for the most part of them they are very light touch and just focus mainly on documentation transparency to ensure to facilitate the work of downstream providers of high risk applications but we do recognize also that there could be a very limited number also of quite high impactful and very powerful models that could pose systemic risks for the market and for them we do also propose a very proportionate and targeted rules that will be mainly implemented through code of conduct in a very collaborative manner with scientific community and all providers of those models all right but yes and so what I'm hearing is kind of a an understanding that you know a open you know when we're doing this regulation you know we need to be thinking about how to do this proportionately to you know enhance you know both maybe open AI open source AI and also at the same time kind of mitigate these risks you know thinking about maybe an historical perspective from the open source world right there was a lot of debate in the early days of open source around security proliferation of cryptography that you know the technology could get into the wrong hands you know Arno, Brian looking kind of backwards what lessons might we learn from the as we think about you know the regulation that's happening here and then in the United States of open source and those types of concerns that we've seen. Sure I'll jump into this first and then hand to Arno so I with respect to the moderator remember a moment when a certain technology executive called open source a cancer upon the technology industry because it would eradicate the potential for profits from technology I don't think that quite happened this was 1999 2000 I think something around those that that time frame instead it drove an incredible economy of people building on top right it was a boost it was a way to build a common platform that was shared and allowed are any of you familiar with Corey Doctorow's term in shitification apologies for this being recorded but it's the premise that sometimes platforms decay as the people who run the platforms extract value from them right open source doesn't have that phenomenon instead you get increasing returns by more people participating in the platform and building value on top right that's what we saw in the early days of open source where the standardization of the Unix landscape on the Linux kernel allowed everybody to move up the stack and create more value in the cloud and other places and then repeated with the rise of Kubernetes right meant that people could fight their competitive battles way up here where there is better value proposition than on a Mac versus PC kind of battle down at the at the bottom so open source has helped equalize and and bring a lot more competition into the market for the benefit of everybody and it has the chance to do that with AI as well as long as we don't kind of make a mistake I think at the at the grassroots there are also concerns about security right if everybody can see the code everybody can hack it everybody can compromise it I or or if the development process was you know a wild west anybody could throw back doors into the code and you couldn't trust it then in fact there are also concerns that if you gave people too much open source power when it came to cryptography well then bad actors would be able to communicate securely without anybody being able to listen in on their conversations and keep bad things from happening right some of you might even remember in the United States you could not publish cryptography software more powerful than 128 bits without getting and and ship it outside the United States without getting a permit from the United States government otherwise you were considered an arms dealer and actually 99 the Bernstein decision from the supreme court conclusively determined that open source software collaboration is an act of speech rather than an act of commerce and and put it firmly on the side of the cryptographers and the software developers who then develop things like open SSL and and and you know secure sockets and secure security into the Apache web server and all this great stuff so you know history doesn't doesn't necessarily repeat but it sure does rhyme and and looking at the current a debates through this we need to think about how do we allow for innovation upstream and and collaboration and freedom of expression and freedom of thought and freedom of development upstream while holding folks at downstream accountable for their actions as they deliver products and services to the end users right I think that's the right frame for us to understand kind of the history of of of open source and technology development and frame it towards AI and also look at can we use open source as an enabler of ways to address the kinds of harms and concerns that we all have right could we invest in digital public goods in the form of data sets in the form of software that could address AI fairness concerns in the form of you know data sets focused on addressing equity issues or equity concerns can we move away from using Reddit comments as training data I don't know if any of you have read Reddit but like I don't that's not how I want an AI to talk necessarily and towards the kinds of things like the Allen Institute has some really great data sets that derive from the Wikipedia derived from project Gutenberg and others like we can cultivate these things and build better AI by collaborating on the table stakes on the stuff that is boring in the hard chopwood carry water of building AI better AI systems and then allow interesting commercial models on top of that so I think what's interesting is looking back at what happened with open sources we learned over the years that they were clearly many different kinds of open source and so you have a whole ranch you can just you know put your code out there and say that's open source well if there's the right license that might be true but the reality is there is more to it than that because what we learned is what's important is open governance which means who controls this code right one of the things that we do IBM works a lot with the links foundation for instance because we have these foundations there are strict rules that provides this kind of open governance where there isn't a single company at the control of the source code the same is going to be true for AI we see a lot of you know models being distributed but you don't know how they were built you don't know what data was used behind it and so we really need to go beyond this and have a true open collaboration environment that allows us to work in this environment with transparency so that we know what's behind those models how they were built and that's a very important thing we have learned from open source which we need to adopt for AI if I can just build on that I see any lie in the audience here and he is part of the Linux foundations AI and data project one of the products of which is something that's emerging called the model openness framework it's not an attempt to define open source AI or to change licensing terms it's a way to say those 500 thousand models on hugging face how much you categorize them in terms of degrees of openness degrees of how much can you really fork you know in the way that open source licenses allow us to fork it's a way of recognizing licensing around data is super complicated but how might we bend the industry towards greater openness and so we're going to need new tools to help us understand this different landscape and this is one that I just wanted to highlight and so one thing I also wanted to add is from a regulation point of view and it also has to do with the efforts like OSI on defining what open source AI really is I mean one of the challenges we have is that if you if you're too high level it becomes moot it doesn't have any meaning or usefulness if you go too much into the detail you quickly corner yourself in a world where you know this technology evolves so fast if you look at the AI act I think they have actually so far found a right balance of keeping it a fairly high level so they have principles oriented regulation because if we look at GDPR for instance I'm a strong supporter of GDPR I think it it did some good but at the same time I worked in blockchain along with Brian for several years and the problem with GDPR it went too down far into the detail of the architecture of the database system based on some traditional architecture where you have control points and when we worked on blockchain we realized well it didn't work anymore because we don't have single control points and so the danger with regulation is to go too far into the details and so far again I think the AI act does a good job at finding the right balance keeping it high level principle what we need to make sure now is the next phase is going to be to develop standards that further define how this is going to be implemented and we need to be on the lookout to not fall into that you know mechanism again of going too far into the details keeping in mind that you know the AI act has been in the works for several years already it's going to take two years from the publication to be fully enforceable it's going to take several years for the standards bodies to define the standards that will be used to implement it meanwhile I mean the industry is going full on developing the the technology in ways that we cannot predict honestly we already see it in ISO GTC one there are some standards that have been in the works for a while they are already a bit obsolete because they're missing major components that just weren't there when they started it's nobody's fault it just goes too fast and so I think this is a true challenge as a society is to find the right balance when is it too soon when is it too late that's all yeah just one comment or thought I think that it is not only industry or big industry going ahead I see this and then this what I'm enthusiastic to be here that there are a lot of happening the small scale big scale everywhere and then the question of data and good quality data I wanted to bring the the example of the small language group I know lino speaks the same than me so finish we are 5.5 million not that much interested of the good training from the big workers so then there is an own model that uses the national library digitalized things that has been going on for 20 years then uses the supercomputers partly sponsored by EU I have to advertise the LUMI being the gtp geographic the possibility to count that the university has been collected the national broadcasting company has been created data and they do it perfectly as the AI Act wishes that this is the sources of data that we are using this is the open possibility for everyone to do it so maybe even other languages in Europe might do the same so it's not one way only that everything later will be dependent on the couple of players in the world but then you can use the different systems and develop so now it's the finished science involved in that one and very happy to see this happening so also we have to see that there is much more happening than the most common systems and the biggest ones I mean I'm loving this discussion because what I'm pulling out from it as I'm standing here is that you know the governance systems and collaboration of open source really matters and participation in that innovation cycle is what's being enabled by you know wide open governance and participation you know as we think through that and so you know one one we were just kind of talking a little bit about you know control in in in these models and I maybe just to kind of throw some concepts together on that right so licensing we're seeing a compression of the licensing innovation we've seen over the last 40 years into one for AI models where we have licenses that are trying to restrict uses for ethical purposes on the one hand and then we have other ones that are restricting competition if you use their model on the other Falcon Lama 2 being ones in that area and at the same time there's a question about what elements of the model need to be there so you can have this you know open source participation that we were just we were just talking about so you know with that in mind Steph what is the importance of OSI's work driving an open definition and what's what's at stake if we don't slice that definition right when we have you know regulations kind of referring to free and open source models right so well one one thing that I I like to remember is how open source as a definition and the principles behind it have been evolving or having a guidance to the evolution of software itself for many years and I think that for the my wishful thinking my my hope my secret hope is to to to have the same sort of principles established quickly so that the AI space can can evolve together having a framework reference that that carries the value of collaboration permission less evolution the the fact that we can we can immediately the the communities of developers creators of AI and and other stakeholders have an immediate understanding of what they can do and what they cannot do what they should do what they should not do when it comes to downloading an AI system modifying it and putting it back on the market together with regulators of course because I I I am quite sure that we have software has told us already we've gone beyond the the times when we could just deploy something putting it on the market and say if it breaks you keep the pieces I think it's fair to think that as we have responsibilities as humans creators of anything when we put it on on the outside we should think twice about what we're doing and why you know and how it can be we can enable abuse and things like that it it's not the role of the open source initiative to to think about those things but it's the role of me as a human to keep that in mind in general and you know you asked what what happens if we get it wrong I don't think that there is much of a chance to get it wrong as much as there is a risk of getting it late or not getting it at all in because like you mentioned there is there is many there are many licenses and there are many models and and new licenses are emerging and everyone is starting on the market to advertise their their models their AI systems as open source without that shared understanding and so the the the effort that that I'm doing is that we're doing with the OSI is to to build that shared understanding among different stakeholders that unfortunately takes takes time but I'm really pushing everyone to to come to a solid agreement because I think that we all instinctively know what that means you know we need to be able to use we need to be able to share to study and and modify systems and and now we need to very quickly come to uh practice the practicalities and what what is that we need to do what you know the open source the free software definition says you need access to source code in order to study and modify a program where we need to the equivalent of that little sentence for AI systems and I think we're getting very close to understand that excellent now the the EU AI Act that I guess is being voted on today very exciting provides you know an exception to some of the regulation accounting for open source development and that that exception happens when the power of the model is below some threshold number one and number two when the models are made accessible to the public and I'm quoting here under a free and open source license that allows for the access usage modification and distribution of the model and whose parameters including the weights the information on the model architecture and information on model usage are made publicly available um does this get it right does this promote innovation the way we might might like anything missing uh aren't I'll start with you Steph and others so again I think they they they they get it right in the sense that it's pretty high level they focus on use cases as opposed to you know trying to regulate the technology itself so from that point of view it's good of course these threshold you know they measured in flops they say oh it seems pretty arbitrary and it's bound to be broken so it will have to be revised but I think again this is part of this challenge of you know we you have to start somewhere and when is the right time to regulate is very difficult I think in general they are doing the right thing for now we'll have to keep up and make sure it doesn't do well maybe if I can complement indeed it's been quite challenging to regulate so fast developments and also many unknowns uh so um for those very powerful uh general purpose models with systemic risks indeed there has been one threshold now set but we've also tried to build a system that allows enough flexibility to take into account developments adapt but also develop performance benchmarked on the future the more we see how it develops how it performs in a collaborative process to keep it future proof because it's we have to catch up always with the regulation and the technological development and that was the the right way we we thought we can do it uh together with the industry community um and indeed quite importantly I think the AI Act right is one of the first EU legislation that tries to at least set some principles what these open source uh AI models can be exempted from the obligation so it's truly open source and we have a shared understanding what kind of transparency we do need for those models uh to benefit from these exceptions because they have already ensured the necessary level and we think that this indeed promotes a lot of um transparency in the community as a whole but also collaborative developments and in any case I just also wanted to say that the AI Act would not apply to models that would be solely for research purposes development prototyping so that's quite important we do want to make sure that innovation research and there is no burden at all or unintended consequences on the overall open source community and finally another important point I would also like to make is that the AI office which will be uh uh now created and actually it was the decision for its creation was adopted um in anticipation of the AI Act implementation um it will have an important role to be exclusively competent for the supervision of general purpose AI models but we also try to make sure that the codes of practices uh that we're going to develop to operationalize these high-level principles as mentioned are developed together with the whole community all providers including open source providers and in this decision that was just adopted for the creation of the AI office quite importantly we also commit to create a special forum for collaboration with the open source community because we do recognize and we want to promote a strong ecosystem and build innovation in AI one of the most important elements that we also see is that one of the biggest and players in the EU are now actually open source models and we do think that the community can build compared to other bigger players outside the EU now could allow these collaborative developments access to all EU resources uh supercomputers to to help EU startups uh and SMEs build competitive models uh uh and also uh align with with our approaches and one uh cool thing about Europe is that I think it has a lot of the legislative elements that that are necessary for a good AI uh there is GDPR managing all the privacy data uh there is um uh right to data mining that has been established in the copyright directive and and the AI act on top of it I think all the elements are in there uh of course everything can be improved and perfected but um you know the it's a testament to the the innovation that has been happening also on the governance side just can I jump in please this is very encouraging to hear I hadn't followed the last few iterations to the trilog so um there's a balancing act as it's preserved the right kind of space for open source but there's a different kind of balancing act that in the United States the Biden administration's AI policy tried to strike as well which was between throttling and restricting and containing versus enabling and steering and encouraging in the right directions and in the in the Biden AI policy which has not been a funded passet of laws or anything yet um probably won't be in this current cycle but I there is a proposal to put chief AI officers inside of every government agency right to drive AI adoption plans so that the IT offices are taking maximal use of this to develop data sets from government data that can be used to drive the development of LLMs for domain specific purposes in science and engineering in in in the health administrations and the veterans administration those sorts of things and this kind of capacity building is coming at a very challenging time you can't hire enough AI talent to fill all of the roles that it called for without completely bursting the budgets that normally are put towards government employees but I this is an important really really angle on this how might the public sector become a stakeholder in these technologies develop an internal capacity for adopting these and in doing so be a part of steering it in in the directions that address many of the harms that people are concerned about out there have to adhere that the data act was the the final one the finalized that all the public created data should be available even the sensitive one with the second use data from Finland from health was the kind of model and thinking there that how to get access to the public data to be able to use it and train it so that is not news anymore I'm I'm I'm seeing the yellow light that we're almost at time and so what I what I'd like to do for for the last question is kind of just say you know there's a there's a signal that there's a from the EU AI act and from our conversation today that there's a perceived public benefit to open source AI and so thinking you know more broadly looking forward we've seen that open source has shaped innovation over the last 20 30 years globally thinking about Europe thinking about the United States thinking about the globe how do we think what's the hope for how open source AI might you know might might shape the industry and in the world moving forward staff I'm going to start with you and we'll go down the to the end well thank you I my my hope is that we find legal frameworks that work across the globe as soon as possible to cover two things specifically one is the nature the legal nature of weights parameters anything that goes after the training that's created up by the training that I think is something that I I'd love to see to see defined because and defined at a global level and together with the clarification about data mining because I the the two the thing that open source had built upon was the the burn convention so the the fact that there is a copyright law or drug doctor a more or less very similarly applied in many parts of the world allows for this open source to be a global phenomenon in in AI given the fact that we have data and we have these new artifacts are the model weights model parameters requires new legal frameworks and my wish is that we quickly get to the point where we have a global understanding of what these permissions are what is allowed what is not allowed so that innovation can really happen in the same way that open source has or no so quickly one thing I want to say is that you know I see a lot of effort in Europe there's this reaction oh we need to have a European initiative to promote you know whatever initiative is and in this case open source AI but what I find unfortunate is often it translates into we need to start a European focused effort which in fact comes into competition with other global efforts in and this is a a misunderstanding of how you can actually influence the the global efforts by actually contributing in the influence is in the people who actually work in those organizations most of them like many of the Linux foundation organizations are completely open with an open governance you just have to show up and so I really want to encourage European companies to do that I I do hope that the AI act contributes both to innovation legal certainty development including for the open source community but also responsible trustworthy AI and we've seen a lot of good practices and will continue to work together with the community including for the early implementation of the AI act through initiatives we launch like the AI pact with companies and the AI office and we do recognize also that one of the key focus now should be to work together and we do with international partners to ensure this convergence and common understanding and we do so in OECD UN with trade technology and bilateral partnership so that's very important focus for us now my hope is that open source is recognized as a way to address two of the biggest sources of risk in the adoption of AI technologies one of those is the concentration of market power I open source has been about decentralizing that power by allowing technology enabling technologies and platforms to be available to to anybody who is willing to pick them up and adopt them and a lot of the risks that that are articulated out there come from unequal application of that power what happens if one company moves too quickly or or if the rest of us are sub are able to use AI but only through an API where the interesting stuff is on the other side of that API the Linux Foundation recently published a a survey on generative AI where we talked to the top IT leaders and asked them how do you want to use this every single one of them wants to look behind the API they want to have a model the ability to build their models correct their models modify the data underneath that understand how it works and adapts it adapted to their organization's needs the kind of thing you can only do with open source the second part of this though and addressing aya harms is to some degree to fight fire with fire let's talk about misinformation right using using content labeling techniques like c2 pa to identify authentic photographs authentic documents to try to fight misinformation is an incredibly important project c2 pa is a standards effort that's part of the Linux Foundation but but very much integrated into many open source projects but being able to to use that and and another angle to this though is you know we've been fighting spam with AI technologies for 20 years anyone who's used vipples razor or other anti spam tools know that it kind of builds its filters out of studying databases of known spam in order to fight misinformation we will need AI tools very local to the end user to be able to help them navigate the flood of information of false information find the signal in that noise and navigate that more intelligently that's just one example of where AI could be used to fight many of the harms that many of us are concerned about arising from AI and that only is possible if those tools are broadly available thanks to open source hey petra yeah i've been 10 years now in the parliament nine and a half so the first mandate was very critical infrastructure how to reach everyone no no one left behind how to get the 5g to get the trusted networks and so this mandate so much on the data data availability the content and then we read in the end of this term that the world economic foundation saying that it is the disinformation that is the biggest threat so then it is where and how and for what use the technology is there some room for democratic decision making and and i'm sorry the europeans need to also look at the european jobs and european well-being which is a i hope that i'm the one speaking in favor of the data movements globally and and and having these ideas yeah it takes two to tango but the good competition is always better for the markets and solutions but then also monopolistic structures very seldom are good and that's why also how to build on other possibilities it's open question open source been so far so good challenger i always welcome the challengers for the making the broad possibility that is called market economy i haven't seen better ones so that's why i keep on working for these opportunities for everyone thank you well thanks everybody this was a really engaging wonderful panel with lots of strong participation thanks very much and thanks everybody for for having us


Hello everyone, the topic for my today's lecture is macro expansion in C language. Now, the learning outcome at the end of the session the students will be able to describe the concept of macro expansion in C language, a macro is one of the preprocessor directive in C language. Now, what are macros in C, a macro is actually a fragment of a code which has been given a particular name. So, whenever that name is used we can say that it is replaced by the contents of the macro, like as example you have over here hash defined PQR 15. So, PQR is the macro and 15 is the value assigned to it. So, there is nothing but the macro definition or just called as macro. So, what does a preprocessor do? It replaces every occurrence of the macro PQR in the program with the value 15. So, therefore PQR the macro template and 15 is its expansion or the value that will be replaced for PQR. Let us take a sample program. So, in this program you can see the header file included, then with the help of hash define AB5 we are defining a macro whose value is initialized to 5. And in the main function we have declared a variable i, then we are taking a loop in which the value of i is initialized to 1 and i less than equal to AB. So, here for the macro AB the value of 5 will be replaced. And of course, the next part the iteration and this goes on to print the value of i in every iteration of this loop. And after that we can see in the output that the numbers 1, 2, 3, 4 and 5 are displayed. Now, let us see what is macro expansion. Now, at the time of compilation the C preprocessor it will examine the source code. If at all there is any macro definitions present on what? If it sees any hash define. So, in the entire program it will search for such macro templates. And wherever it finds the macro templates it will replace all these macros with their appropriate expansions. This is done at the time of preprocessing. Now, after completing this procedure then the program is handed over to the compiler for compilation. Generally, the capital letters are used for the macro template. A macro template and its expansion are separated by blanks or tabs. But when we write a hash define the space between hash and define will be an optional one. So, it is not a compulsion to have a space between the hash and the define. And the macro definition should never be terminated by a semicolon. It is possible to change the values of a constant that is used at multiple places in the program by just making a change in the hash define directive meaning where the macro has been defined. If you want to change the value of that macro will change it at the point where it has been defined. So, that actually has an advantage over the fact that if a variable is to be changed in the entire program. So, we need to go to every place and change that value. So, instead of that if some macro is used just changing the value of the macro at the point where it is defined will do the work. This could be quite beneficial for large programs where a particular value is used at multiple places in the program. So, the advantage for this could be the compiler can generate faster and more compact code for the constants than it can do for the variables. And we have a sample program now the points where a macro can be used and for what purpose it can be used. The first usage of macro would be it would be used to define any operator. So, as we can see over here in the program A and D is a macro which is used for the operator logical and that is ampersand ampersand. So, as you can see in the program if x less than 5 and y greater than equal to 50 then and then it will print the output everything is fine. So, here the and macro is used for the logical and operators. So, at pre-processing time this and will be replaced with the logical and that is ampersand used twice. So, the output for this program will be everything is fine. So, another usage of macro will be a macro can be used for a condition as well that is as you can see over here in this hash define c o and d is the name of the macro and it is used for this condition that is percentage greater than equal to 40 and percentage less than equal to 100. If this is required to be used in a statement then we can directly replace that with the name of the macro as can be seen in this example if c o and d. So, that means at pre-processing this condition of percentage greater than equal to 40 and less than percentage less than equal to 100 will replace at pre-processing at this point. So, the output for this program will be as a value of percentage the variable p e r is 63.75. So, this condition will be true. So, therefore, it will display as output within range. So, we have one more case where a macro can be used a macro can be used in fact to replace an entire statement. So, here we can see a macro named as even is used to replace an entire statement that is print f in double quotes this is even number. So, this macro if it is used in a program as can be seen over here if x mod 2 equal to equal to 0 meaning if x is an even number we have the statement even or rather we have the macro even. So, at pre-processing this macro will be replaced with this statement print f into double quotes this is even number. So, the output for this program also will be this is even number since x value is 6 it is even therefore, it displays this is even number as the output. So, now the students are expected to think and write the answer to the following question. This is the program that you have. So, what will be the output of the code? Now, pause the video and write your answer. Okay. Now, the answer for this question will be 12 now how did that come? We know y is a macro used and at pre-processing it will be replaced with its expansion x plus 2. So, if we see over here z equal to 2 into x plus 2. So, that means 2 multiplied by x plus 2. So, when we see the operators we have star operator and plus operator. So, where we know star as the highest priority. So, 2 multiplied by x the current value of x is 5. So, 2 multiplied by 5 equal to 10 plus 2 equal to 12 will be the value assigned to z. So, therefore, we get as output value of z as 12. Now, next we will see macros with arguments. As we know like how we have for functions we can also have arguments for macros. Now, this is an example hash define area into bracket s space into bracket s star s meaning here wherever we have this macro used area with a parameter s it will be replaced with the expansion s multiplied by s or s star s. So, that is what it says whenever it finds the phrase area of s it expands it into s into s. Now, we have a program for that here in this example also we have taken the same macro area of s which will be expanded with s multiplied by s. So, in the program we will see where macro is used at this point macro area is used with the parameter x. Now, value of x is 5. So, when it finds this area of 5 as a macro it will replace it with 5 multiplied by 5 or rather first x multiplied by x. So, 5 multiplied by 5 equal to 25 will be the value assigned to a. So, that is what will be the area of square equal to 25 as the output. So, in the above program the s in the macro template area of s is an argument that will match the s in the expansion s multiplied by s. So, the statement area of x will cause the variable x to be substituted for s and area of x is equivalent to x multiplied by x that is nothing, but its expansion. After pre-processing the compiler will get the following code to work on. Now, what will be the code? The code that will have the macro replaced with its expansion. That is we have a equal to rather than area x into x as its expansion. So, now there are some points to be remembered do not leave a blank between the macro template and its argument while defining a macro because if it is left then probably the appropriate value will not be assigned to the macro or appropriate expansion will not be assigned to the macro. The entire macro expansion should be enclosed generally within parenthesis. The macros can be split into multiple lines with the help of a backslash at the end of each line and if it is unable to debug a macro then the expanded code of the program can be viewed to see how the macros are getting expanded. Now, let us try to compare macros and functions. We know macro calls are like function calls, but they are not the same. So, in a macro call as we know pre-processor replaces the template with its expansion whereas, in a function call first of all the control is passed to the function with arguments then appropriate operations or calculations are performed in the function and then a value is returned back to the point from where the function was called. So, the question arises when to use a macro and when to use a function. So, macros make a program run faster whereas, it increases the program size, but functions make a program comparatively smaller and compact. So, if a macro is used n times in a program then that expansion will goes into the source code at n different places. So, this may increase the program size, but if a function is used and is called from n number of places in the program. So, it will take the same amount of space in the program. Finally, passing arguments to function and then returning back a value will take time. So, this may slow down the program. So, but macros if those are used those are already expanded and those are been placed in the source code before compilation. So, the conclusion will be when to use a macro and when to use a function if a macro is small it makes nice short hand. So, it will avoid the overhead associated with the function calls. But if a macro is large and is used often it must be replaced then with an appropriate function. So, this is the reference used for the video lecture. Thank you.


Welcome to the working group. Documentation subgroup meeting for May 31st of 2022. And I can put the agenda link in the chat. And please take a look real quick and let me know if there's anything that's been missed. Anything that needs to be added and also please add your name. So that folks know that you were here and then if you weren't here and there was important information. I'm going to add. I'm going to add one agenda item someone internal to red hat. I was looking at our documentation and we refer to a couple of things like vettings. Internal. Working group and suggesting that we should come up with a more formal name for that this vettings and one other one so I'm just going to bring that to the party today so I'll add that into the agenda. Okay, and I added one about this single mode installs. And looking Michael's here so hopefully we can cover that up. All right, go ahead and add those things and. Let's start out Brian with technical documentation. We now have it merged into the main site. Is there any. Yeah, I mean, so I decided instead of working. In my private or personal repo. I think the docs, the community doc should be working progress. It should be a working living documents documentation. So I actually did move it into there. And there's still a lot of information needed there. So, and as Bruce said, just before we started recording, we were having a discussion. And a lot of the repos are really quite difficult for community members. And I would like to bring it upon next week's meeting in terms of do we have an official list of substituted images, because there are various language images and various sort of building images. And so the one I'm looking at is the console. And that's got six Docker files. And they all refer to different images. So just trying to work out what each of them do and say how would I do this outside of the pro system. And it's quite difficult to know. And as Bruce said, it's how do I know that I'm actually doing something that's an equivalent of and producing some it's an equivalent of the official build image. And because I think if you're going to test something and raise a bug or do a pull request, we do want it to be an equivalent image that we're working against. So I've been going sort of around around the houses looking at that at the minute, but I think I am going to need one of the red headers to chime in on that and actually explain. A is the source of the internal images available is a Docker file that they were built from available, if not the actual binary. If not, what are the equivalent community versions of those files that we should be working with. And I'm hoping there's some way we can actually get that into the read me of the project so a community member will be able to pick, pick each project up. And the read me should have a community section ideally how I don't know whether that's going to fly within the red hot product teams. But ideally it would be nice to have a community build section on every repo read me. So I want to bring that up to the main meeting on. Next week. Okay, so one thing that I would suggest is get a list of three examples of things that you are unsure of what the external alternative is. One of the things that came up is, you know, Mike has mentioned this a couple times is that his group and a couple other groups are doing internal external Docker files. And that that would be something that if everyone were doing that. It would be easy to sort of suss out what's happening, as long as you knew where the documentation for the particular project was right and where to file bugs for the particular project. So, I would say pick three things like console is one and then pick two others. And then through that we can sort of flesh out some some some process to documenting these things. Okay, that's unreasonable. Yeah. Okay good. That's reasonable. Right. Yeah, I would probably have a slightly bigger ask. Which is that I think a lot of these things predated the UBI images that red hat has made and it's been promoting. And if the internal images could be based on that then there would be no reason why the base image couldn't be public. Like it may be that it's only historical. Yeah, that's a good question. Let's actually ask that to add that to the list of questions. So if you could, Brian under technical documentation if you could add those bullet points so add the three things and then add Bruce's question, and then I'll transfer that to the agenda for the next meeting. So, list your three things when you get a chance and then for like a second bullet point there put Bruce's question is, are these UBI, or can they be UBI to circumvent any internal external stuff. Anything else on technical documentation. I'd love it if there's some more help. We need to try and encourage people to chip in and cover all aspects including the operators and what's going on. So, there's no reason why, I mean, ideally from from the documentation we should be able to get someone to do a full build of OCD. That's the plan for everything we provide should be enough to give a full build of OCD and it be an equivalent functionality of what the official bill does. That's that's where I'd like us to get to with the technical documentation and the whatever we do to the repose. Alright, is it possible to break down what we need into bullet points so that we can say, hey, we need a volunteer for this particular area of documentation. And this other particular area so that as you've talked about before Brian, making sure that people know what they're volunteering for what we need volunteers for. Is that something maybe you and I can work on over the next couple days. Just look it over and sort of break it down into sections. If he wasn't on vacation. Oh, you're on vacation. Oh, okay. Well, yeah, but I mean, this I do this as a community thing. This isn't working. So I'm allowed to do this on holiday. Well, that's that's up to you.  I don't want to take up your vacation time if you're actually enjoying a true vacation. Yeah, I'm probably going to be doing some work on this tomorrow. Thursday, Friday in the weekend, I'm probably going to be doing other things, but. Okay. Alright, let's take a look. There's something like 100 is payloads that you have to build right each with their own separate repositories. So that's. And if you're trying to build the whole thing, I guess you could not clone it, but just, sorry, not fork it, but just clone it. But the way it set up, it would be a bit labor intensive. Yeah, yeah, I did that. Yeah, I understand that side of it, but if we can do it once it means that every piece is accessible to the community. So, so that was the goal. Whether we could actually come up with an all go tecton conflict that would just do it automatically. That would be really cool. Yeah. I'm going to say, in the next working group meeting the full one, we're going to have people from Brian cooks group that's also working on a build process with tectonic and the operate first guys showing up and talking about what it's going to take to do a community hosted and managed build process. And I put another item in there that we'll talk about a little bit. There's a third initiative going on inside of red hat that has some customer facing engineers. So it's very timely, but we can also ask them what's missing, right, and ask them to contribute updates to it as they try and use it. I think if you, if you did this little bit of staging work with that in mind for the next meeting and have a call to action of as you go and try and do this with your new tools and, you know, your new power tools. Take notes. What's missing? What was, you know, what was behind firewalls? What did you have to do the sign into red hat to get a, you know, you know, those kinds of things. And I think there's enough people right now who are focusing on this that if we enroll them to take good notes and journals and make edits as they find this is this is the time. Okay, and context of Ryan, because you weren't at the last main meeting at the last meeting, we actually did have someone from CERN. They've actually done a build of their own. And so, yeah, so they've actually done their own. Right now they have one that's based on four or nine. And so that's who's going to be one of the people who's going to be talking. So, we can compare notes and then find out how to sort of standardize that and then document those a few tweaks and stuff like that. Okay. Do we know, did they do it as a community build or did they cheat and use their red hat subscription to go and pull all the images? I don't know. We'll have to, we'll have to see that's going to. They, they, I'm pretty sure they did the community build process. Oh, wow. They are okay. The people, they are not OCP people. And I don't think they have a. But I don't want to, I don't want to hypothesize. I want to like, I don't know for sure questions. I'm pretty sure everybody that's around has a developer key. You know, which, even though it's expired 60 days with OCP still works. I imagine at least it works to down to download the. CRC local, whatever that is. Yep. Yeah, because I could I checked out that that one still works. I'm trying to find the source repository for that because it doesn't seem to be the same one that Char was using before. But with the 5 minutes that I've tracked looking with that. I may just not find it found it. I mean. I seem to have somehow this bipolar relation with CRC because of my level of caring is very low. But every now and then I poke at it and see whether or not I can get it to work. Well, we'll see what happens. We'll see what happens with that. All right. So is that it for a technical documentation? Okay. All right, let's move on to repository move timeline and steps. There's now a discussion item for it. And basically we said July 1st. And so we just need to fill in the steps in this discussion of what steps do we have left before we can just move things over to the new repo. So let's fill that in async over maybe the next. Now in the next meeting and then go through them. At the next meeting the steps be sure that we are have it covered who's doing what with that. And then we should be on target then to for July 1st to move things over July 1st ish. Any questions on that any questions on the on the repo move. So the big investigation to happen is what's the best way to for the main OK D one. So we don't lose any of the discussions is I think if you fork, then you don't take the discussions with you. But I think if you transfer ownership and actually transfer into the new org, I think everything will go with it. So I think unless anybody knows that's an investigation item to be done. Yeah, so I would add that to the list then for sure of something. Yeah, that's that's my one big unknown. I think I'm I've thought about it and I think everything else I'm quite happy that we all know when we can do that's the one big because we don't want to lose all of the discussions and the issues history and all of that. On the OK D1 worker. Okay, any any more feedback on that on the repo transition. All right, let's definitely work async on that and I'll remind folks. You know, maybe towards the end of this week to be sure that we're filling in the various steps there. Let's now walk through the survey. Let's just do this, get it done and ship it out. Like maybe the end of the week or something we just we've been sitting on this for so long. The only feedback we got so far was what version are you using and that that needs to be edited to to include. And I will. I can add. Do we want to drop for 3 and 4 for and just shift these down. Perhaps, or do we want to ask our people using for 3 and I've not heard of anyone using for 3. Not in a long time. Do you want to share your screen and just walk through it on this in the screen so that people watching maybe. Yeah. I haven't looked at it in a while. You see the survey. Yep. All right. Okay, so this is the user survey. And these the first question is what version of OK D are you using. Do we want to go all the way down to version for 3 or because I don't even know is for 3 even available still on the. On the site on the releases. I don't know. Yeah, I don't know. I don't know anybody for 5 or lower. I don't know anybody. I know we still have some customers using. 3.x that we're. And holding it seems like anyone that started using for is at 4, 6 or higher. Yeah, so why don't we do that and then leave the add the other. They are so. 7 or 6. Okay, how's that. Looks good to me for the 4 is the earliest release on the release site. It is okay. Anybody's using. Yeah, but it's all beta. And can you make this question required? So there's a little required slider there at the bottom underneath lower, lower, lower, lower, lower, lower. There you go. Now, this is a radio though. It's not check boxes. Oh, no, it is multiple choice. Okay, good. Oh, wait, does multiple choice allow for multiple selections or does that have to be check box? I don't know. It's usually check box. It's usually check box multiple radio buttons usually is 1 only. Right. Yeah. Check boxes means you can select multiple. Yeah. Okay. Because people might have multiple versions. Yeah.  Yes. No. Yep. Yeah. Yeah, go ahead. No, go ahead. The critical features is a great question. The how many people question is an interesting but a hard one to answer. I mean, would it be easier to say how many applications or clusters as do you have deployed like a num, like something that's a tangible thing they can go and look up the stat. I think with that one, the assumption is that they're using on a commercial basis. I know a lot of people use okay D in their personal capacity. So, maybe rather than people, not that people developers aren't people, but how many developers because maybe they're people might miscontrued as you have an application and you have 10,000 end users. Right. Yeah. I mean, I mean, it might be just a good question, a good question to ask. Are you using it in a personal or a business context? How are you use? How about as an open ended question? How are you using? Okay. Or do we want to break it into a multiple choice check boxes of commercial or like, I don't know what we would come up with for that. Like, what are the, what are the different uses so personal. Well, I think I don't know. I think the thing that I really want to know is, are you using okay D in production? Like, I want those people to pop out. Okay. So development production. Anything else? Let's add a new question. Where do we want this question? Do we want it to be, I feel like jumping down. It sort of jumps to ask the biggest challenge. Like, I feel that should be further down. Like, and that questions about usage should be of like, who's using it and how it should be further up. Does that make sense? I agree with that statement. Yep. So how do we want to change the how many people or do we want to add up above? I don't really care about the how many people I care about how they're using it. How are you using okay D. And this would be check box. We're saying develop development platform. Yeah, development. Yeah. Development, maybe development slash sandbox. Okay. Yeah. And do you want to separate the personal versus or home lab? Yeah, because I think I like that. I think if someone says that, yes, it's in production, but it's running my home automation system. That's slightly different from I'm using it work within my employer and it's running a production workload. So how about those, those three and then add another. So an option for add other. Okay. Do we want this required or no. I would, I would require all of them, you know, just, and just not ask a lot, like maybe have five questions. I think all the checkbox ones checkbox ones can be required. If you have to type something in like what's your biggest issue. Someone might say, I don't really have a biggest issue. So they may not want to answer that one for all the checkbox ones. There are definite answers. So I think we can require them all. Okay, how are you using okay D. How many people in your company are using. Do we care how many people like I don't I always felt like this question was kind of problematic because what if it's just you I don't want someone to feel like they're less. Yeah, so just kill that. Okay. Good, good, good, good critical features. How about I think we should if we're actually, if we're asking operators, I feel like this is more of a. We're asking about what they're doing, right. Documentation. Let's see what optional operators which operators are currently missing and we've raised this differently maybe which operators. Would you like to see or something like that or. Are we asking what red hot operators. Would you want to see in the OCD catalog is that the question we're actually asking here, or is it a more general open. And is there a product that there isn't an operator for that you want an operator for. So, as well, I think that the way the way OCP is promoted. There are some things which are in fact operators but are promoted as part of the package. So, like serverless pipelines. What else. Maybe it's like things. I don't know. So, but some of those people might not think of as missing operators. So how do we want to do? Do we want to break this down? Do we want to say which operators. Which, which operators would you like to see on OCD that are not currently available or something like that? I like that phrasing. But I think there is some. Is this different from what critical features do you need than are not available in OCD. Yes, because there may be something very wise. There might be. Yeah. There could be a lot of things other than operators that are missing from OCD or. That we're not even seeing. Is there so. Okay. We want operators after, well, hold on, let me, let me. Do we want to ask critical features before we ask about operators or after we ask about operators? Let's at least start at that high level. I think where I'm having a difficulty understanding what we're actually asking is. Is this in relation to OCP or OCD in general? I think just, I think personally, I think just in general, because some folks may not really be thinking of, oh, that's an OCP operator. Or that's versus the, oh, I need this community operator or whatever. Some people might not understand the operator ecosystem. And I'd actually be willing to bet that a significant number who are using OCD. Just based on chat and emails and stuff that we see. Probably don't have the sense of the ecosystem. We, we have internal knowledge. Yeah, because we've. Yeah, because then we can make that determination. Right. I think once we look at the responses. Okay. The, the other thing I'll be devil's devil's advocate here is true. If we're asking. It suggests that we may be able to influence the addition of that feature. Well, if this is an anonymous, we could turn it around and say, hey, you want to work on that with us. Because I mean, also at the end of the day, we've got to think that we are based on OCP. So we can't go and add huge features that this would then become an OCP feature request. Right. And then we, but we can then feed it up the food chain and say, hey guys, look. One of the things that's missing for me is that there is no gatekeeping on OCD. So I have no idea how many people out there are using OCD in production. So the one thing that I is critical for me to get out is some semblance of account of people who are, you know, willing to say stand up and say they are using OCD in production. Because that's, you know, as we fight for engineering resources, that's kind of 1 of the. That's the thing I face every every conversation. Okay, that's useful to me. Okay, so back to my top level question. Do we want to ask about people features before or after we ask about operate. I would ask before and I would remove critical and just ask what features. Which features do you need that are not available in OCD today? Right, that's on right folks. Yep. All right, so which features. All right, so pulling that one up. And then we ask about which operators are using now, which operators would you like to see in okay. Whoops. In OCD, which are not currently available. What's your biggest challenge you face using OCD today. I think that's a good question. Yeah. How helpful is the OCD documentation for achieving your goals. I think that's a good one. Which documentation. Leave it open you think I think leave it open and then we can follow back up or maybe. That might be the biggest challenge and they may go back up and say the biggest challenge is finding documentation. Should we then ask for a question below that that's like, if you answered such and such above, can you provide more details or something like. I think it's getting too long is what I would say is those too many questions here. We want people to actually do that. And then they can have additional content. I love the welcoming one. I think that's a great question. And I would keep it just like that. I think it's great. Do we want to ask about, well, code ready containers slash open shift local or no. So what I would do is I would change that to say, do you use OCD on one option code ready containers. No. Single node. Yeah. And I would even throw in micro shift. I know that sounds a little nutty, but like to see where people are playing here. What would I say configurations. Okay, the in any of the configurations code ready containers. No. And check boxes again. What else I would I would like to add in micro shift here. I know it. People are micro shift and would we say home labs here. Or is that I think that's the same thing. I mean, you could have a whole lot earlier. I mean, the, I mean, the one thing that might be useful here is to try and get a feeling. Whether people are on bare metal, VMware, or because I know I know we always have the platform question and which are the important platforms that we need to test on and how would it be okay if we put. I feel like platform is a slightly different question than configuration. Yeah. Is it pushing it to have just one more question up above. Not at all. Not at all. I had to just, I'm happy to do that. I actually think we could actually combine the crit the features and the operator question is going back to what you said. We could actually remove it if we're looking to make it shorter. We could actually get rid of the operator question because that will be covered in the features. Is someone going to think of it. Well, if there's an operator missing, it's missing feature. Yeah. Yeah. Okay. All right. Well, let's get this one down. So platforms, which, which platforms. Do you deploy. Okay, the. Backboxes and we'll say. Bare metal. Bare metal. These fear. Oh, Azure. Okay, so the list in the documentation is I'll leave it to you. Brian, you want to go ahead and add all of those. So what I would say is put in what we know are the top ones and then leave the other option there. Yes. I don't know of anyone that is. I actually, I do know a few people who are Ali Baba people. So. Okay, let's. I know. Maybe I'm wrong. Maybe they don't answer questions. I don't know. I don't know. I don't know. I don't know. I don't know. I don't know. I don't know. I don't know. I don't know. I don't know. I don't know. That's all right. I know. Maybe I'm wrong. Maybe they don't answer questions. That's all good. So, as your Alibaba bare metal. Oh, GCP. Right. GCP. GCP IBM cloud metal. So, how about we just keep it at this and then do other than we've got kimchi. I'm guessing that's overt. It is it, Hang on. Let's leave that list and that's probably going to come up with most everybody. Michael, the overt has gone again. I'm just looking, overt's gone again. I've raised this twice on two previous editions and it's gone again. Well, let's put it back on, let's put it on this list just to make the overt community people happy. That's, that's a great point. Great point. Just, you know. Yeah, we need to work out why he keeps vanishing up with every release. Yeah. All right. And then. And I think. And then, you know. We want to ask, would you like to provide contact information? Yeah. Oh, you're, you're in the world of. Also, it's a privacy laws. If you ask that, because then don't ask it. Don't ask it. You know, because, because there's a whole lot of things where you have to say exactly what you're going to do with it. We don't want to make this access to it. Thanks. All right. So let's, let's go through the description up here. Okay. The, the community distribution of Kubernetes that powers red hats open shift. We would appreciate it if you could take a few minutes to answer some questions to help us improve. The experience. And can we say something about the community like improve the experience and. Expand the community or something. I would almost say, rather than expand the community, but something along the side of our roadmap and help us prioritize our community roadmap. Yeah, I think that's good way. How's that. There you go. And I think we're good and I, you know, we don't want to over edit this or anything. We just want to get this thing out more. There's no seeds to change right here. Where do we want to direct people. Just flash out. Well, why don't we create a discussion item. In the, in the, if each, but what if someone's particular thing. Oh, you mean just the general section. How about if we just point people to the general section. Well, why don't we create and say that if you, if you want to raise additional issues, please, please add an item to our discussion forum or discussion section. That's yeah, that's good. Yeah, yeah, yeah. Okay. Because at least then we're pointing them to the way and showing them where they ask questions. Yeah. And you've given them a link to click on to get through to find us as well. Another yet another link. So how do you want to. The one doctor I'm going to say we therefore can't move. And so we think the survey is done. Don't worry about. Yeah, we'll figure out a way to get around that. Yeah. I can, I can only edit the survey header. And then when people refresh. Yeah. I want to phrase this Brian, you had some language for this beginning part here. How do you want to phrase it. If you have any questions or suggestions. Please. I forgot what I said before. You have any questions, questions or feedback. Please join us in GitHub. It said that again, if you have any questions or or or feedback. Please feedback, please join us or please feel free to join us to. Join the company to feel free to join the conversations with an S on it on. Yeah, there you go. You have any questions or feedback, please feel free to join the conversations on. GitHub. Yeah, that works for folks. Let's go. Let's go through it one more time just. At instead of on you in like that. Yeah. Good man. All right. All right, let's go through this one last time because you know, you never know when you miss something. All right. Which versions of OKD are you using for<PHONE_NUMBER>. How are you using OKD own lab development. Sandbox platform production other. Oh, did we want other to capture for the versions. Yeah, someone happens to be okay. All right. Which features do you need that are not available today? Oh, this should actually be a. How about are there any features. That way people because it's not a required question. Yeah. Are there any features. Well, that, that's just a yes no answer though. Oh, how about which. Yeah, but you could phrase it as please, please explain below or something like that. I think it was by the way it is, which features. Which features. Yeah. Which features would you like to see in in OKD that aren't there today. Okay. Features. Would you like to see and OKD. That are not available today. Today. Take the in out available today. Yeah. And do we want to keep the operators stuff or no. Which ones they are currently using versus I mean. I feel like maybe the second question is helpful, but maybe not the 1st 1. I think you can kill the 1st 1 and the reason is that we could do a follow on 1 that was more operator centric once we got this feedback. That's a good point. That's a good one. And hopefully we'll take this 6 months. There you go. Yeah. That's 1 less question. Cool, cool, cool, cool, cool. What is the challenge of this. I would make the OKD welcoming 1 towards the end. Yes, you're absolutely right. There you go. And then have the additional comments. Okay. Which would you like to see that are not currently. That or which I always forget that are not. Yeah, someone will tell us. Yes.  Should we be moving the platforms and configurations further up then. Yeah, I think, you know, I think they're good where they are. It's a good mix of paragraphs of information and. Going on the US Azure. Their metal GCP overt. Use OKD in any of the following configurations code ready containers. Single mode cluster micro shift other. What could we do to make the community welcoming. Answer any additional comments. Change, change frame this to something. Just a question mark. Yeah, there we go. All right. Are we happy. I am happy for the documentation would want to be too much to ask for explanation. Yeah, go for that. Yeah, ask. It's just saying it's not helpful is not. Not very helpful. Right. So do we want a separate. Question or do we want to just rephrase this question. Let's give them a separate question. An additional comment. If you what would improve. What aspects Michael, how would you. How would you suss out. What if it's product documentation or. I would actually just put a comment. Please provide feedback. In the any additional information set question. Rather than actually adding another question. Okay. As I said, it just keeps it a bit brief. Because we've got that any of the comments of the last question. Haven't we. Yeah, I almost think that if you did one right after the documentation helpful one, you'd get more of a documentation specific thing. And that would be more helpful to Michael. Is there any feedback you can give us on the documentation. Long. And I think one of the things is where we get hit the hardest. Right. So I think that this sort of drilling down just a little bit specifically on documentation. Yeah, helpful. Yeah. How do we make it better? I think it's good. I mean, how can we make it better? How can we make our documentation better? Then we can go on to our next agenda item. Yep. Yes. All right. All right. So we're good with that. Yeah, sure. Right. Fantastic. Okay. And we've got 10 minutes. So we got to sort of burn through this here. Technological repository survey FAQ suggestions. So I'm going to start putting this as a standing item. If you have FAQ suggestions, please add them here. One that we've gotten a lot lately is installing on other OSes and Vadim provided a good response that I think could form an FAQ. So I'll shape that into an FAQ. And then I'm still start toying with language on the release cadences FAQ. So if you have any suggestions, feel free now we're at a future meeting to add things under there. Okay. So no documentation removed from OKD docs discussed here. Brian, did you add that? Yeah, so I noticed that there is a discussion item, which is discussed here, and where it looks like the process of doing a single node install is changing. I think it's going to do with how we do the, we're not going to have the boot bootstrap node. It actually replaces and OCP now has to use the assistant installer to do SNO, which obviously isn't supported. And I'm just making sure that within the discussion because we've actually closed the discussion item or Michael closed it, saying that he actually removed the invalid instructions. I just want to make sure that we've got someone lined up to add the correct instructions or work on what they should be. So is this something that we're going to be relying on the OCP upstream product documentation for the new way? Well, no, that uses the assistant installer and now buddy. I thought I thought there was movement towards. So you can use this assisted installer for local. And that's what that means. If you look in the discuss here, but he's written up how to do it clone the repo and run it locally to do it. Okay. And that's the only way that we can do an SNA and SNO install of OCD using that assistive installer running locally. But we need to write that up. So it's going to be different from the OCP instructions because they point to the website. But I'm just making sure that this doesn't fall through the cracks and someone's actually lined up to actually write that. It looks like. Let's ask at the next meeting for a volunteer to write it up. Yeah. I just want to be clear that we have a lot of stuff that's falling on the shoulders of myself, you, Brian and Bruce. And I just want to be sure that we start leveraging other people. We need. Yeah, folks. I think we need to make the ask for a volunteer to write this at next week's meeting. If you could. I just want to put that I just want to put that back as much as Michael sort of. He's actually taken the bad documentation away, but there was no real action recorded to actually go and write the good documentation. That's right. And I might. Yeah, good. All right, the next two things. Depersonalizing the homelab documentations. I don't have an opinion one way or the other. However, a few people inside of red hat. Notice the other day that we were, we had personalized the two homelab things with Vadim and Shri's name on it and suggested that that might not be best practice or informative enough for someone who wasn't on the in crowd. I just wanted to bring that to this group's attention and think about renaming at least the item and still giving Vadim and Shri credit in the documentation, but I didn't have a suggestion as to what the new name should be. I actually, again, we probably don't have time to go into this. I actually want to actually have a conversation around what they guys should be because they're not quite enough information to let somebody repeat what they're doing. So are the guides just to give an indication of the sort of hardware people are doing, in which case we can make them much more concise and standard, or do we want to go and put what they're doing. And as an example, if I just put into the chat, I know this isn't going to help for recordings. As I'm setting up mine, I'm actually documenting what I'm doing with my own home lab. And the idea is that a, if I need to come back to this, this is going to help me. But B, if anybody else wants to do a similar thing. The construction should be good enough. So I go through my setup the overt set up the hosted workshop and then what I'm working at the minute is the development environment. So all the pieces that I'm going to put on to make my development environment based on okay D at home. So I've taken through, and this is a, this someone should be able to follow this. Now is this what the guy should be, or should it be. What you've got is what I think of as a guide. Yeah. And that's what I think of as a guide, but. So I think we just need clarification of what we want and I know Daniel started leading this project, but it seems to have stalled again. But, but I think it's worth having conversation of what should the guides be. Should they live within the documentation or should we point out to, like I've done my site or other people sites, and just have a sort of a references section or. Or should we move this into the documentation, the community documentation site or. I like having it where it is right now. Maybe as a home, just one thing that is a home lab thing and then have a couple of things there just because it's more having yet another place for people to go is confusing. Yeah, but yeah, but I like, I really like the way you've done yours, Brian. And maybe making beddings and shrees a little more concise. Not this week, but it's just a suggestion that, you know, it was too much an in joke, not an in joke, but in you'd have to know. The team or Sri and naming people specifically. Was was tough. Yeah. I want to, I want to make, I just want to just timing. I really want to make sure I hit on this last point agenda item. Before, so maybe we could think about this home lab stuff, but I just, I just want to make sure I mentioned to you guys this goes. I don't even know how you pronounce this initiative because I want to make sure it gets communicated out to you guys before and this week and at next week's working group meeting. You don't mind because we only have 4 minutes left and I'm sure you'll have what I'm talking about here. So internal to Red Hat, as you might suspect, there's lots of things going on, lots of initiatives going on. And one of them is taking CentOS Stream and creating a closer to REL, CoreOS, CentOS Stream, CoreOS and making it available. And Timothy Revier, who's a regular working on the Fedora CoreOS stuff, is also working on that and he hasn't talked about it out loud. We finally got him to like and get his powers at B to let us talk about it out loud and in the public. And so I wanted to give people a heads up on that on this group call. And then we're going to talk about, Timothy may talk about it a little bit next week, but it is an opportunity for us. And there are some folks working on an experimental sprint inside of building a version of OKD on this as it comes to fruition. So I wanted to say that out loud here so everybody could think about what that means. And the opportunity that it presents for the community to have something in addition to Fedora CoreOS OKD that might be slightly more stable with each release and built and maintained again in the same process pipeline that we were doing Fedora CoreOS. And that is a live initiative now that we can talk about publicly. And it is resourced with three customer facing engineers right now under the same group that Christian Glombeck is in inside. So that is, I think, good news for us. And what I want to start trying to do is see if I can find folks within the OKD community who would test and deploy that thing. Once the sprint is done, which I think probably gets shot for saying anything out loud, but mid-July-ish, we should have this first release of OKD on SCAWS. And I wanted to make sure you all were aware of that, especially Jamie. So it may get delayed a little bit as everything is resource constrained and there's Queens Jubilees and other vacations coming. But I'm trying to time a little bit of more announcements of it around the July 6 London OpenShift Commons gathering, too. And see if people like CERN or John Fortin or other people would have any interest in using this or at least testing it to people who have been complaining vociferously about being on the bleeding edge. So would this be closer to the rail corOS where it's more on the Kubernetes platform rather than a generic operating system? Yes. And you can ask Timothy questions about it next week. Let him say the words first. I've gotten Steve Milner, who's his boss, to tell him that it's OK to talk about it out loud. I don't know how long in duration they've been working on it. Not that long, but it is definitely a viable thing that's going to happen. And I was loath to say anything about it earlier for like it might just drop off the radar as some things do, but it's coming and it should be interesting and of interest to this community, I think. Excellent. Well, let's add that to the agenda. There's also something else that Christian added to next week's agenda. So it sounds like next week's agenda might be packed. I'll reach out to the various people and see if we can get a sense of timing so that everyone can get their time in and maybe get the agenda done ahead of time in a way that allows everyone a chance. Yeah. So I think that's my goal next week is to get CERN to do a little deeper dive so we understand that thing to have, hopefully, Timothy say the word CentOS, COREOS out loud publicly to the working group and to get a sense. I almost was to the point where I wanted to ask that question in the survey, but I'm not ready to do. I don't think we're ready to do that yet until we have a viable experimental release, first release of it. Because I don't want to get people's hopes up too high that it's coming too soon. But that's where we're going. Excellent.  Yeah, no, I noticed that the CentOS stream people have now changed the versions. So there's CentOS 8 and CentOS 9 and no upgrade path between them. So does this one also have a version then? Let's ask technical questions when the technical people are here that are actually working on it. Oh, yeah, but Diane, I just might have heard if they're, you know, let's let's ask technical questions when the technical people are here. Next week. I think. Yeah, next week. All right. Diane, you have 3 items just a reminder research the transition to zoom for meetings to see if red hat wants to help us with that. Change Twitter email address and research Mx record change to the okd.io domains that we might be able to support our own email. Those are all. And I did none of those things. Nope, that's fine. I did none of those. But I will get on them. So. I, that's I expected last week was catch up. So don't worry about. Yeah. All right, folks, any last minute things were just about at time. Just just the 1 for me that was done. The link checking is now the warning only so. Oh, thank you. Thank you so much. Oh, and 1 more for me, which is that meeting notes are now getting posted. There's a. Meeting minutes are now getting done. There's a 2022. That I'm actually going to start adding them to and then we'll do them by year. And so it'll be the index. And then broken down by year and then within the year. Brian, do you know if it's possible to auto generate pages? Like if, if the doc is just thrown, if the doc is just thrown in there to auto generate the page and add to an index. Like if there's nested. So it'll do it 2 ways. It'll either all auto generate. But once you want to start ordering it, it all has to be ordered. So, so to keep the structure that we've got, we've got to auto, we've got to manually add it. But there's nothing to say that you couldn't actually go into the mk docs and actually add that as a right. Yeah. So as you add a page, you actually go and add the index to mk docs. Okay. All right, folks. Brian, I will look in to see why over it's missing from 410. Okay. Do you want me to raise a ticket or will you just do that and. Yeah, I just. Okay. Brilliant. Thank you. Thanks. This was a great meeting, folks. Talk to you soon. All right. Take care.