 We've had policy makers, if you will, international organizations, innovators, and now coming from a different perspective, Patrick Nicollé of course with Capgemini, the industry to see how the subject matter, which I'm sure is taken up a lot of thought and time, immersing yourself and your colleagues. So Patrick, take it away. Yeah. Ali, absolutely. So, Capgemini is the largest IT services company in Europe, so I will present the practitioners of you, but before that I will express an absolute personal conviction. As Holger highlighted it, machine performed tasks. They never replace human beings, and there is unclearity in our taxonomy today when we debate about artificial intelligence and where the age of the machine, a machine is a machine. And when you look at the component of the machines and especially in artificial intelligence, it starts with algorithm, the heart of the artificial intelligence technology. And an algorithm is a mathematical answer to a clearly defined problem. The problem can be complex. Some are not solved. The salesman trip is one good example, are not solved, and some are solved, sorting data. There are many algorithms to sort data. And then you have a lot of technologies around it, like speech recognition, natural language processes, semantic biometrics, deep learning, swarm technologies, which might be very funny, is how drones fly together, for instance, it's nice to see, chatbots, et cetera. But at the heart is the algorithm, which is a strength and a limitation. So what do we see now in terms of implementation in the enterprise? So the first thing is something that started with the first industrial revolution is touch and unmoved. So what we had, the robot. And we started not by robot, but by automation, because for economic reason, it's better to invest in a technology that does something simple in a repetitive manner, so you depreciate your investment much faster. And then came more sophisticated robot, like painting cars in assembly lines. This is complex. And these robots are much more expensive. And now we have developed capabilities so that they can interact and co-work with human beings. So they have tasks, everybody, so you divide the task. So this was the first sense, if you want, of human being, because all these developments can be categorized along human senses. So this is the first that we've seen for a while, and that is gaining pace. It is gaining pace, for instance, in IT, in information technology, because the first deployment of artificial intelligence was called robot process automation, which is nothing else than doing automatically a script that another program is asking you to run to make it simple. So the machine does what another machine asks you to do. But it's very simple. It's a very repetitive. The next era that is coming is around listen and talking. This is a second sense that artificial intelligence is going after. This is the most advanced in terms of technology development. And when you discuss with R&D from vendors, such as Microsoft, Google, in that space, they believe that in five years from now, speech recognition, language capabilities from machines will be better than the human beings. We all do mistakes when we speak, when we interpret, when we understand, and they believe in five years from now. It would be a huge leap because today, when you ask and you can try with your phone, you all have my phone with me, but if you all ask Siri or whoever on Android, the rate of response is 30%. Of course, if you ask what is the weather in Marrakesh, you will have an answer. If you ask a more complex question, you won't have an answer. You will have a polite answer, but not the answer you want. That's one thing, by the way, socially, is that virtual assistants are very polite. These create problems in human interactions afterwards. So that's where we go. So that's the first area of development. So it touches, in terms of activities, of course, everything related to call centers, help desk, which is an important part of the activity. So the third one in development, but it's more ten years away from now, we see where, again, the timeline is defined by when the technology will be better than human being, is watching and monitoring. So you've seen a lot about face recognition, about what you can do. It will completely change elements related to cybersecurity. But today, the application we see in terms of what the eye, the vision, can do, it's about self-healing. So you can detect default, be it on hardware, be it in systems, through this technology, and then you can anticipate and automatically launch, for instance, the self-healing of a system through this. There are big developments, as you know, in cybersecurity, because this is a much more advanced capability than what we have today, notably when it comes to human being identification. And there is a startup in India called Fluid AI, where you can open a bank account just on your, watching your screen. And through the recognition, you don't need to touch your PC anymore. You just talk, you move, the machine recognizes you, and it's good enough to go. So this is the next development, but again, it's 10 years from now, but it will accelerate. The impact on the employment will be more limited than the first two. The first two, everything that is about moving, touching, and everything that is about listening, talking will have bigger impact. Here it opens new field. I'll come back on this. The next area is about knowledge. And here, this is, my view, big revolution because we used to look as human being, and Google started like this, is we build knowledge repository. Libraries are knowledge repository. We build knowledge repository. And in fact, with AI, this is meaningless. You don't need to build a repository. You need to build the ability to ask the question and access the data wherever they are. We had the question yesterday about the fake news to many data. There are many data that are structured and unstructured. And the structured one are not structured the same everywhere. So you can consider that overall it's all unstructured. And so you scroll through this, and there is a huge increase in data. And 80% of this is totally irrelevant. But it is produced by the machines. So how do you build your knowledge? And I think we'll come back on this. It has a profound implication on education. The next one is about analytics. So that's the next area of development. It is another of our human capabilities. Here, we started with so-called business intelligence. Business intelligence is trying to understand some patterns from structured data, not to be your accounting system. There is a set of structured data. It's historical. Analytics is forward-looking. So you must understand trend and adapt to it. Here, we are making quite a lot of progress. And a lot of the human-to-machine interaction is driven by analytics, the type of service you propose, the customization, et cetera. And this is primarily what is changing the business model of almost all industries, this part. And then you have, in analytics, probably we won't discuss it today, it's machine learning. It's where you can program a machine to learn by itself to execute the best task. And the latest breakthrough, you probably all read through, is AlphaGo Zero from DeepMind, a subsidiary of Google. It's a machine that could learn the game of Go without human interaction, because you train a robot. When you launch a robot, you program, you always have human beings that accompany the robot. That's a 30, 70% question. So what do you do when you cannot answer the 70%? Someone is doing it. And then the machine is learning from the answers they get, and they progressively improve. AlphaGo Zero is really a breakthrough, because this machine started to learn the game of Go without human interaction, without human training. So that's a new frontier. That's what we will see. So these are the areas where we see the application. In recent, thanks to Thierry, I could join the World Press conference on such session two times. So I talk about the impact for employment. I talk about the social impact. But I think the biggest one is in education. And Marie Eloudi too, she concluded the presentation. I'm convinced. And it starts from the very early age. The way we will have to look at the world compared to the way we were looking at it is fundamentally different in the way you interact. The type of working organization will be completely distributed as well. So the hierarchical, the social model, all the institutions we have built are not geared to address these elements. I'll stop here, because I see your look. And I think it's about my time to leave open to the question. It's a polite look. Very nice look. Thank you. Yes, yes.