 Listen closely now. Pay attention. I will play you two sounds. If you have earphones, put them on. Okay, ready? First sound. A cow, huh? Okay, let's hear the second sound. Again, a cow. Yeah, that's right. No extra points for that, but did you notice the difference? Probably not, but there is one. A very important difference. The first moon is, well, just a cow saying moon. The second one is a cow in estrus, so time for insemination. Very important information for the farmer. Otherwise, no calf, no milk. With simple microphones and machine learning technologies, they have achieved 94% accuracy in understanding the difference between one moon and another. Today's topic is not horny cows, but the future of health. Today I'm in Zurich to speak at a leadership conference about artificial intelligence in healthcare. If you want to know more about the cows, I'll leave a link to the case in the description down below and you can check it out. This is just one out of many examples telling us how machine learning and AI can help us improve healthcare in the future. Okay, cows aside. Let's talk about us and death. I mean, after all, death is the most unhealthy you can get. It's the ultimate opposite of health. So why do we die if not from old age? Well, if we die from health problems, especially in this part of the world, these health issues have one thing in common, heart disease, cancer. These conditions depend on early detection for successful treatment and survival. Of course, healthcare is much more than just screenings and detections, but let's focus on that for a while. The most common form of cancer among women is breast cancer. Two million new cases detected each year globally. And to avoid this, as you know, millions of women worldwide go into mammograms, breast x-rays. And then experts, radiologists, they study these x-rays to find problems. Just like with the cows, this is a very difficult task. And the scorecard even among professionals isn't that impressive, to be honest. On average, during a 10-year period, 50% half of the women screened will get what is referred to as a false positive. And as you know in screening, nothing positive about getting a positive. A false positive is very costly. First and foremost for the individual who now have a cancer diagnosis, all the suffering, an agony, new treatments, maybe biopsy or even chemotherapy. And then, of course, a false positive is a huge problem from a cost perspective. If we want great healthcare for everybody, then, of course, we can't afford to spend half the budget on people who frankly don't need it. This is where machine learning and AI and all these new technologies is starting to look very interesting. A growing number of tech companies are now using AI to try to get better at reading breast cancer screenings. There is even an annual competition, the Digital Mammography Challenge. Last year, more than 1,200 organizations and corporations participated. One of these programs, I'll link to it below as well, they proved 99% accuracy in detecting breast cancer from these screening results. And they did it at a speed of 30 times faster than human beings. So 99% correct, 30 times faster. Sounds like a no-brainer, huh? It's quite obvious how computers will change the world of detection. I mean, we're talking pattern recognition, small details, nuances and then putting it all together in a huge memory data bank that never forgets anything. Of course, no doctor in the world could ever compete with a computer at doing... Oh my God! Does this mean that all the doctors will be unemployed? We don't need them anymore? I don't think so. But I do think that doctors finally will be able to spend their time with patients who actually do need them. If we have faster handling and much better accuracy and more efficient healthcare. To me, this all sounds like a good reason for a happy and healthy move. What do you say? Do you get scared by things like AI or smart machines or do you see opportunity? Please share your comments or thoughts in the section below. And as always, if you like these short speeches about future trends, then hit subscribe and I'll see you in the future.