 Hi Nikolas, hi, thanks. Hello. Hi, Michael, very good to see you again. Nice to see you again after such a long time. Exactly. Thank you for having us here and we've been working with Michael and Silica for a number of years and now I'd like Michael to show some of the products that we've been collaborating together and they have on their son. Very good to have you. So maybe just to mention this is the Avnet Silica booth we have here. So we are a distributor, we work very close with ST Microelectronics. So we have a very, very good cooperation with them. So in fact what we have here is a kind of AI, so artificial intelligence, machine learning, vision, experience. So what I would do maybe is to explain a bit more in detail about the demos we have. In fact what we do here is we show case 2 demos. So we have one specifically focused on vision. The other one is focused on machine learning with kind of classification. So this is the demo we have for people talking. So you see here an SD board where we have an STM32H747. So this is the discovery board so this is used for development purposes. You also have a miniature camera module which is put on a board which is connected to the discovery board. So what we do here is, so as you can see we capture people around here. So it's people counting, it can be used for access control for example. It can also be used for occupancy detection in a room so to know how many people enter a room and to limit the maximum amount of people for example. And so by the way what you see here is the output, you can see the output on the screen but it's very small, it's very limited. But you'll see it also here the number of people it's recognized. So it's an object detection tool in fact and this is how you can see it as a demo. In addition we also have another demo so this is focused on anomaly detection. So it's a nuclear board, so it's also an SD micro electronics board. And what we have here is there is a kind of fan connected to this board. And we can detect if there is an issue with the fan for example and that's why we call it Klocht Fan. So that means for example what you can see here and I don't know if you need to zoom in. But you see for example here the results when you for example put something in front of the fan then there is an issue, it's Klocht so. The background of this is or the most important to tell about this is that in fact here you can implement machine learning by using a standard algorithm but you can also implement it that it's completely automatic learning itself. And then afterwards when there is a kind of anomaly which is not typically happening then it will do the detection. So this is very nice because then you even do not have to create your algorithm in detail. In fact you have it then available already. You just restart the board, it will start learning and after a while when it learns the algorithm itself automatically it will be able to detect if there is an anomaly for example if you have something in front of it and then it knows there is an issue. This can be of course with the fan but you can imagine this also is like a motor control for example where you have an issue. So this is in fact how it is implemented. So you have a lot of business going on with ST? Yeah absolutely. We've worked with ST for many years. So it's a very nice and very good cooperation we had especially also with Marceli. So Marceli is the guy that supports us a lot. So he's in the neighborhood again. So yeah we have a very close relationship. Of course. Already many years. I remember we've been working in AI for what? Three years now more? No it's even more. Even more. Before COVID. Yeah before COVID exactly. But I think like it's about four or five years at least. We also organized like what we called an AI Discovery day. Webinars seminars and seminars. And also live physical events. Before COVID. Before COVID. And hopefully we'll return to that. Maybe we'll do it again. I'm quite sure though. Hopefully it doesn't take too long. At least we are here now today so it's very nice to meet. And you can show the customers. Exactly. How does it feel to be in a real show with real people? Well it's a kind of relief I would say because after getting stuck and being stuck at home I would say it's really nice to be here and to see so many people because now you recognize what it feels to have physical contact. We have not seen each other for three years and now we can see each other here. So it's great to be here. It's very nice. And it's so nice to see the ST booth. Yeah absolutely.