 Hi, this is your host Abhinav Bhatian. Today we have with us, Abrahim Midat, Executive Director of LFEI and Data. Abrahim, first of all, welcome to the show. Thank you very much. Thank you for having me. Right. A lot of consolidation is happening within the Linux Foundation regarding all the AI ML projects. So before that, what I do want to understand, there are a couple of projects that are forcing deep learning, machine learning AI too. Can you talk about what projects are there under the Linux Foundation umbrella right now? So if you think of Linux Foundation, it is kind of a foundation of foundations. And under the LF, there are multiple what we call umbrella foundations. There's the CNCF, Cloud-Mated Computing Foundations, there's LF Edge, there's the Hyperledger Foundation, Automotive, etc. And LFAI and Data is one of these umbrella foundations. And actually, across the board, we shared the same goal. Our goal is to accelerate the development of open source project and innovation. However, we each do it in our specific domains. So CNCF, for instance, is focused on Cloud-Mated Computing. LF Edge is focused on Edge Computing. We're focused on AI, Machine Learning, Deep Learning, and the data aspect of AI. So the LFAI and Data Foundation was initially picked off as LF Deep Learning, quite interesting in March of 2018. And then we rebranded in 2019 to reflect the growth of our scope and to become LFAI. So we're not deeply focused only on Deep Learning, so we grew a bit and we started to host projects in other sub-domains within the AI umbrella. And then we just recently, actually as of yesterday, we rebranded again to LFAI and Data to reflect also additional growth in our portfolio. So as of today, we host 22 projects across multiple domains of Machine Learning, Deep Learning, Data Models, and Trusted AI. And we have, I believe, 36 member companies that are involved in our foundation. There are a lot of, within Linux Foundation, there are a lot of projects that at times overlap and that is natural for the kind of foundation. Linux Foundation is, you know, Linux Foundation is a body, you know, which kind of makes it easier for organizations to put their own open source under a neutral body. And of course, there are so many projects or so many products that overlap within the industry. So there is nothing Linux Foundation can do about that. But once their projects find their home within Linux Foundation, then you try to consolidate to better use resources. So within the AI ML space, where do you see there are still gaps that you do feel, hey, you know what? These are the gaps that still have to bridge. And where do you still see some overlap where, you know, beyond this consolidation, do you still see some possibilities of either further consolidation or you're like, hey, no, we still need projects to address this need? Yeah, so I think there are two aspects to your question. The first one I will address is, you know, when a project comes to the installation, we try to look where does it fit if it fits under a specific umbrella that you already have. So if it's a cloud project, goes under the cloud native computing foundation, if it's AI, it goes under AI and so on. But there are a lot of projects that you mentioned, they provide different functionalities and they may be fit for either, you know, maybe one of, you know, it may be fit for either of the foundation that we have. And of course, in cases like that, we provide a recommendation to the company or the projects that's coming to the foundation where we say, you know, we believe that you are a better fit under a given umbrella foundation, where you're able to kind of interconnect and to get to other projects and build up. And at the end of the day, it's really that decision, you know, if somebody really wants to come under an FAI, although they are better fit somewhere else, it really depends on the scope and, you know, where that projects would like to be within which umbrella community. So this is completely their call. We of course help them in the process to understand the workings of each umbrella and so on, but it's ultimately that decision. And it has to be definitely within the scope. And since you mentioned it may overlap, then it becomes really their call on how they want it to go. In terms of consolidation, we're actually in the process of doing this, you know, at least in the AI space. So we've recently announced the formation of LFAI and data, which is basically the two umbrellas, LFAI foundation and ODPI coming together. As we realized that, you know, we focus on AI machine learning, deep learning, ODPI is focused on the data side. And also there are at the Linux foundation level, three other projects that are hosted as projects under the LF directory. So we're going through that kind of consolidation, if you want to use this word of gathering and putting together these joint efforts under a single umbrella, not just to use the resources better, because as you know, we offer the same services to all of our projects. Of course, at this scale, we're able to provide more efficient resources and resource usage. However, it's also about putting this project and community together under a single technical advisory council, receiving the same services from the same providers and enabling additional collaboration, given the various collaboration opportunities that we cater and support. Can you also talk about that, what are the new goals or new areas that the foundation is looking at after this consolidation measure? So this is a very timely question as we will be discussing this very specific topic next week as part of our board discussions. You know, we're almost at the end of the year and we're looking at 2021, the general strategy and focus areas, both the technical and business perspective. However, there are two main areas that would be our focus that I can guarantee for 2021. The first one is increasing the collaboration between the projects that are on the data side and the traditional open source AI projects that we host. About seven projects that force on the data and 15 projects in the general AI domain. And one of the activities we have, we launched and we're going to accelerate in 2021 is creating integration across these different projects. So that if you are a company looking from the outside and you want to adopt project A, for instance, you will be like, oh, hey, you know, project A is already integrated with project B and C and both B and C are foundation project, mutual governance, multiple companies involved in them. So it creates that attraction, right? So building that integrated stack is with the focus on data, of course. And the second area is trusted AI. So building trust and building responsible AI system is really a hot topic across, you know, if you look at all governments at different NGOs, different companies, they all put and are putting emphasis on building fair systems, systems that don't create bias, systems that are transparent, systems that are robust and building trust with the consumer of these systems is a very critical thing. So trusted and responsible AI would be a key area in addition to the integration and growing the data slash AI collaborations. Brian, thank you so much for talking to me today about the consolidation that is going on within the Lynx Foundation in terms of these projects. I would love to talk to you again because a lot of things are going on in this space. So to keep up with all of that, I will look forward to have you again on the show. So once again, thank you for your time today. Thank you very much. Thank you for having me. Thank you.