 The old model, the goal was to commercialize first. In the new model, it's really looking at your business model. How can you take the value added of that collaboration and make money? The old model, you had to invest a lot up front. In the new model, your R&D is more likely to come from outside your firm, that it may in fact come from very diverse disciplines outside of your own. And that in going to market and being successful, a public cloud will often provide you a way to reduce those investment costs that investors are very sensitive about as they look to get startups and get new businesses going. And I think in the old model, and Graham touched on this this morning, one of the primary goals in the old model was to really produce IP. You wanted more IP, and you thought that by managing it in a very close way, you were going to succeed. In the new model, it's about the distribution. The sharing of that to build communities, networks of users and developers that will make you succeed very well. I think that it's important to understand that this is not academic, that there are real enterprises that are out there being successful, providing a return to shareholders, building jobs, building new products based on this model. It's not an academic thought. In fact, I think it's, I'm proud to say that this month Forrest Magazine rated Red Hat as number four in its list of the most innovative companies around the world, recognizing that our model of collaboration has really transformed the IT sector, the economy, and the way that IT is implemented. This is in fact a model developed by my colleagues about how our model works. And I think it's important to walk through some of this and give you a feeling about why we are successful in an open collaborative model. It all starts at the upstream community. That is the center, it is the way that we benefit from the new developments and the innovative ideas. And it's true whether you're talking about the well-known Linux kernel, whether you're talking about JBoss, whether you're talking about any of the kind of products that we are in the business of providing to enterprise users. We benefit and that circle identifies the value added that we provide. Our customers want to know that those projects are now becoming products that they can rely on. So we invest in the testing. We invest in the work with the sophisticated enterprises and hardware companies and chip makers and others who are central to making those projects become real products in the real world of enterprise software development. It's hard to under estimate the role that that circular process provides in the collaborative innovative model because it's not just about depending on the upstream community. It's having an affirmative policy and look to make sure that we contribute back to that community in a meaningful way. I think by any measure if you look at the standard measurements for how those contributions occur, we're certainly very proud to be doing that, but we are not the only ones. We're very glad to see that the number of corporate sponsors and individual contributors, certainly in the Linux kernel, is growing on a regular basis. So this is I think a good example of where the rubber meets the road, taking the open innovation model, realizing what is occurring and turning a project to a product and seeing where we go from there. I think I'd be remiss if we did not talk about OpenStack in the context of cloud, open source, and open innovation. We obviously I think see most of the discussion about cloud frankly in the context of a public cloud, but I think the recent developments and announcements around OpenStack, which will provide an open source, very strong open source solution to the private cloud infrastructure is one that we should all be following and as able to participate effectively. OpenStack has been a process for several months. I concluded this month by setting up the foundation, major announcement, Red Head is glad to be one of the leaders, but we are not the only. Very pleased with the number of vendors that are actually participating in this. And I think in the end, OpenStack will be a very strong open source cloud solution that will allow individuals to be able to have a private cloud, perhaps even a public cloud, focus really is on a private cloud open source solution so that you are not dependent on any particular vendor or solution provider in owning what is going on in your cloud. This is just getting, I mean, there's many of you know, this is based on work that has been going on for many years. It's an open development model under the Apache 2.0 license. It's an open design process and a very open community that we look forward to seeing and build and grow in the years to come. Let me just say that I know we're gonna hear later from government folks about the cloud or what is going on in cloud. And I wanna leave you with a few thoughts as we think about where cloud open source and innovation are going. Some of you have heard me say before that I hate the term the cloud. And I think it's a misunderstanding on the part of a lot of policy makers as they look at these issues to assume that the cloud is one thing. As we all know, cloud is not a one size fits all solution in any case. You have public clouds, you have private clouds, hybrid clouds. And even last year, the National Institute of Standards and Technology has updated their definition to include community clouds. A year from now, I'm sure we will have other definitions that will fit into this. The cloud is not a one size all. It is neither about consumers uploading their information, nor is it about fundamental infrastructures that will empower the future of IT delivery. It's about using the vast resources of distributed computing in ways that we probably cannot even manage today, but which I think will get us new insights, new products and new skills across the board. One of the most amazing stories to me if you haven't followed it is how today the Mars curiosity project is delivering 1200 by 1200 pixels in tetra bytes by second. It's doing it by using the cloud. It's doing it by also using open source stack to deliver that, including Gluster, which is an open source big data storage tool that allows the massive distribution of those data sets across a wide variety of audiences around the world. I used to work in the US government. I remember the days when data sets used to take weeks and months to get out to the public. We're now talking about using the power of collaborative innovation to get that information out in tetra bytes per second that can be analyzed, used in creative ways, and facilitating a deeper understanding of what is going on in our universe. But it's also important to understand that the cloud is not a radical technical development. It's in fact the modern evolution of IT infrastructure. It's changing the way business is being done, but technologically it is really a natural evolution of what is going on. And the final thing I think policymakers need to understand is that the cloud is a global phenomenon. But the cloud allows communities to come together from multiple jurisdictions, from multiple sectors, from multiple disciplines, and that in thinking through what needs to be done around the cloud, making sure that that global phenomenon of the cloud and its ability to bring people together from around the world is not dissipated. With that, it's been a pleasure to talk to you today. I look forward to the panelists remaining on my panel and appreciate the opportunity to bring you up to date on what is going on at Red Hat and give you a few short thoughts about cloud open source and innovation. Thank you very much. Thank you very much, Mark. And two minutes ahead of schedule there. Well done. So now we're going to come back down to Earth briefly and visit some of the thoughts from IBM Research Zurich. So Matthews, if you could take this stage. Matthews is going to talk to us about four technologies that will change the world, which is obviously going to be a small talk about unambitious things. So as he takes the stage, I just point out that we are going to have our questions after the talks and when we get to that point, I'm going to kick off with the first one. So brace yourselves. Clearly one of the technologies that will change the world is not this particular laptop. It might drive, it will inspire future innovators. So basically, it's not four new technologies per se. It's basically when you look at our industry the last 40 years, we've really tracked Moore's law quite nicely and we've seen computers really take over the world in some way more than one would ever think and when you really follow such a development where the capabilities of our systems double roughly in performance every year, every 18 months and then you look at this over a 10-year period, you see this is a thousandfold roughly improvement, that doubling, that exponential growth and that makes things possible that you can only dream about. We could only dream about 10 years ago, we now have and I'm going to talk about what we can dream about going forward the next 10 years. And so the four areas of technologies that I will briefly cover and I will say why this is in fact something that requires open collaboration, open source to some extent and why it requires also, to some extent, government funding to move along that track and open data is shown here on this picture. It starts from the very bottom, the chips, the transistors actually or the switches that we have on computer chips. When now we have on a commercial mid-range processor about a billion transistors, we expect to see a thousandfold growth in the next 10 years to about a trillion devices. I'm not saying transistors anymore because it's not entirely clear whether those will be transistors in the traditional sense or whether this will be other ways of doing things. And then it certainly enables new applications which is here something called DNA transistor which is in fact a diagnostic device my colleagues are working on with rush diagnostic systems to come up with a way of sequencing the human genome in order of magnitude cheaper than you can currently do it and that allows then really proteomics and genomics really to be rolled out widely. Moving up one level where it says here workload optimized systems, that's just a buzzword but it's basically the systems that you build from these chips and those systems can be high performance computers, they can be clouds, all sorts of things that you can imagine. And then one layer up what we now call in our industry big data that over the next 10 years you will see also grow by either anywhere from a thousand