 So, we're here at the ITU in Geneva and we're at the Machine Learning and 5G workshop and I'm very pleased to be joined by Slavomir Stancek, who is also the chairman of the newly formed Machine Learning and 5G focus group. Slavomir, welcome and thank you very much indeed for joining us here today. Thank you for inviting me. It's a pleasure to be here and to have an interview with you. Pleasure. So, can you please explain to our viewers, you know, what are some of the advances in machine learning and what are some of the applications that are most useful to the ICT industry? Okay, so, many methods in machine learning was invented in the 80s, 70s, so they are not so new and yeah, there were some, there have been some advantages in the context of deep neural networks, but I think that the most important thing, I mean, that happens, that happened in recent years is that we have now computational power and then also we have access to the data, you know, there's no machine learning without data and this is what has changed and then, you know, enabled, you know, now this boom and push to this field. And, you know, what are some of the most promising opportunities and challenges as well for operators, but also for different verticals like the auto industry, for example? Okay, so, we are mainly talking about 5G, you know, the next generation of wireless networks and what is new about 5G when compared to 4G, that we will have that's called verticals, you know, car manufacturers and things like this. So, not only network operators, but, you know, verticals, vertical industry. And so, it means that, you know, 5G networks will have to enable new applications and so it includes, for example, ultra reliable communications or massive access, so you have, you know, massively deployed sensors and then, you know, this means, for example, you know, increased overhead, protocol overhead and then it means also that you have a lot of uncertainty in the network. And here, the problem is that, you know, what we do right now is that we try to estimate all these unknown parameters and then if we continue to do this in the future, then probably, you know, the solutions, I mean, if we proceed to do this in the future, then the solution would be efficient and then here machine learning can help to, you know, to increase, you know, efficiency and to enable new applications. And speaking of machine learning, I know you're working on a machine learning project at the Fraunhofer Institute. Can you say a few words about this project? Okay, so I am the head of the wireless communications and network department at Fraunhofer Heinrich Hess Institute in Berlin and also I am professor at TU Berlin. So I work in the area of machine learning but only in connection with wireless communications or communication networks. So I'm not expert in, you know, in, say, in machine learning in general, like, you know, data mining or what companies like Google and Facebook do. So that's why just, you know, I, for me machine learning is just, you know, key ingredient, you know, to enable some applications and some, say, and to improve efficiency of mobile networks. Our projects, you know, are not, you know, like, you know, machine learning, pure machine learning projects. It's just, always, it's about, you know, how to apply machine learning to problems in wireless networks. And, you know, you're also the new chairman of the new machine learning 5G focus group at ITU. What are some of the challenges that the focus group will address, some of the goals of the focus group and how might the focus group help the discipline to advance in the years going forward? Yes. I mean, we have some interesting players there. I mean, in this area of network operators, network vendors, and service providers. And the focus group, I mean, the focus group is not about research. So the goal, I mean, the main goal of the focus group is to identify standardization gaps. Okay, what the question is, what needs to be standardized in this area? And also, we can also identify research gaps. And, and then another important topic is just related to data formats. I mean, we have to, we have to clarify, you know, which data needs to be collected. How do we need to proceed the data or process the data in the network? Or question, you know, about the quality of the data and things like this. This is, you know, the goal of the, of the focus group. And, and this is what we are going to discuss. That sounds very interesting. And I'd like to wish you the best of luck with the workshop and the focus group. And thank you very much indeed for your time. Thank you very much.