WEBVTT 1 00:00:01.639 --> 00:00:04.120 Have you ever taken a ride in a driverless car? 2 00:00:04.720 --> 00:00:07.900 Has your computer ever written a text on its own? 3 00:00:08.400 --> 00:00:10.870 Or have you ever used facial recognition to unlock 4 00:00:10.880 --> 00:00:11.980 your cell phone? 5 00:00:12.119 --> 00:00:16.760 If so, you've used artificial intelligence, unseen and unheard, 6 00:00:16.880 --> 00:00:18.850 like a ghost in the machine. 7 00:00:19.360 --> 00:00:22.640 The military is using it more and more often, but will things stay 8 00:00:22.640 --> 00:00:24.869 the same strategically, except carried out by 9 00:00:24.880 --> 00:00:26.389 intelligent robots? 10 00:00:26.400 --> 00:00:27.380 Not quite. 11 00:00:27.440 --> 00:00:29.820 AI is revolutionizing everything. 12 00:00:35.430 --> 00:00:39.070 Also coming up in the show, pilots and training, the long journey 13 00:00:39.070 --> 00:00:44.310 to the cockpit, luxury watches, a safe investment and trending 14 00:00:44.310 --> 00:00:47.250 superfood water Lily pops from India. 15 00:00:57.600 --> 00:00:59.420 Robots can be friendly. 16 00:00:59.830 --> 00:01:03.590 They can entertain and some can even act as caregivers. 17 00:01:05.750 --> 00:01:09.110 And then there are the others, so-called killer robots, 18 00:01:09.470 --> 00:01:12.550 the kind we've only seen in Hollywood movies that destroy 19 00:01:12.550 --> 00:01:14.770 and kill without human emotion. 20 00:01:15.870 --> 00:01:20.550 Killer robots sound like something out of a science fiction movie. 21 00:01:20.910 --> 00:01:23.860 The problem is that they're turning into reality, and then they're 22 00:01:23.870 --> 00:01:25.300 not the Terminator robot. 23 00:01:25.310 --> 00:01:26.899 They're not sophisticated robots. 24 00:01:26.910 --> 00:01:30.069 They're the sorts of drones that we're starting to see turning 25 00:01:30.069 --> 00:01:31.899 up on the battlefield in Ukraine. 26 00:01:31.910 --> 00:01:35.630 And increasingly, it's not humans that are controlling those drones, 27 00:01:35.630 --> 00:01:36.860 but it's computers. 28 00:01:36.870 --> 00:01:40.830 It's very it's a simple technical matter to remove any humans from 29 00:01:40.830 --> 00:01:43.490 the control loop and replace them by algorithms. 30 00:01:44.510 --> 00:01:46.819 Tanks, soldiers and trenches. 31 00:01:46.830 --> 00:01:50.670 That's how it looked in Russia's invasion of Ukraine until 32 00:01:50.670 --> 00:01:53.950 artificial intelligence began to be used on both sides, 33 00:01:54.390 --> 00:01:57.130 such as with the Bairaktar drones. 34 00:01:57.830 --> 00:02:00.130 A single one costs over €11 million. 35 00:02:04.753 --> 00:02:09.020 Then the legacy weapon systems of both the Ukrainians and the Russians, 36 00:02:09.120 --> 00:02:12.560 that is, those systems previously not equipped with AI, 37 00:02:13.070 --> 00:02:17.750 were equipped with it. And these systems changed the war. 38 00:02:18.630 --> 00:02:21.500 On the Russian side, for example, there were glide bombs 39 00:02:21.510 --> 00:02:23.410 that are equipped with AI. 40 00:02:25.200 --> 00:02:28.440 On the Ukrainian side, we see the equipment with AI, 41 00:02:28.639 --> 00:02:35.040 such as drones or, and this is key, the fact that Ukraine was able 42 00:02:35.040 --> 00:02:39.440 to be so effective and successful in the first few months has to do with 43 00:02:39.440 --> 00:02:42.700 the fact that they had very good situational awareness. 44 00:02:44.110 --> 00:02:47.389 Military conflicts are all about data and evaluating it. 45 00:02:47.389 --> 00:02:49.020 Processing speed is critical. 46 00:02:49.030 --> 00:02:52.270 AI can achieve this and make technical decisions. 47 00:02:54.040 --> 00:02:58.120 With highly automated systems, we have to think carefully about 48 00:02:58.120 --> 00:03:00.830 how we organize the division of Labor between 49 00:03:00.840 --> 00:03:02.580 human and machine. 50 00:03:03.080 --> 00:03:06.639 People have intentions, machines do not have intentions, 51 00:03:06.800 --> 00:03:11.919 and we use these machines, these automated systems, as tools. 52 00:03:13.470 --> 00:03:16.590 Can a drone become a humanoid killer robot? 53 00:03:16.790 --> 00:03:17.890 A Terminator? 54 00:03:21.160 --> 00:03:24.520 The Terminator? No, that's not possible. 55 00:03:24.760 --> 00:03:27.500 We haven't reached that level of technology yet. 56 00:03:27.639 --> 00:03:31.680 So we do see fascinating YouTube videos from Boston Dynamics, 57 00:03:31.680 --> 00:03:32.780 for example. 58 00:03:33.120 --> 00:03:36.880 We can see that these are machines that have a high level of performance 59 00:03:36.880 --> 00:03:41.120 in the area of motion control when they do a somersault or 60 00:03:41.120 --> 00:03:42.300 things like that. 61 00:03:42.310 --> 00:03:45.390 That doesn't make them dangerous killer robots, though. 62 00:03:47.800 --> 00:03:51.000 Last year, military spending worldwide rose to more than 63 00:03:51.000 --> 00:03:53.820 €2 trillion, a new record. 64 00:03:54.200 --> 00:03:57.560 the US is in first place with almost €750 billion. 65 00:03:58.360 --> 00:04:00.300 But China is also catching up. 66 00:04:00.920 --> 00:04:05.920 Russia increased its military budget by around 9% in 2022. 67 00:04:07.687 --> 00:04:10.880 If you have an army that works with AI, 68 00:04:10.880 --> 00:04:13.660 you have different tactics than one that works without it. 69 00:04:14.950 --> 00:04:18.580 That is, it's not about putting artificial intelligence into a weapon system. 70 00:04:18.589 --> 00:04:24.810 It's about changing the whole system, training, tactics, organization. 71 00:04:24.990 --> 00:04:28.110 And it could be that smaller countries that are more agile in 72 00:04:28.110 --> 00:04:32.020 terms of the composition of their military, the cooperation between 73 00:04:32.029 --> 00:04:36.270 civil military and industry, that they suddenly have a head start 74 00:04:36.270 --> 00:04:37.930 in bringing data together. 75 00:04:42.320 --> 00:04:46.200 Companies that develop robots for peaceful purposes are also working 76 00:04:46.200 --> 00:04:48.500 on autonomous weapons systems. 77 00:04:48.800 --> 00:04:51.570 And receive money from governments to do so. 78 00:04:52.029 --> 00:04:55.130 Around 60 countries are working on such systems. 79 00:04:58.839 --> 00:05:01.350 The technologies is going to exist. They're going to be part of our lives. 80 00:05:01.360 --> 00:05:04.790 We're going to have autonomous cars, autonomous trucks, autonomous buses. 81 00:05:04.800 --> 00:05:08.600 There's going to be lots of AI in our lives, and that technology 82 00:05:08.610 --> 00:05:11.070 could be repurposed, turned into autonomous weapons. 83 00:05:11.080 --> 00:05:15.350 So we can't stop that happening. Because we want all those positive uses of AI in our lives, 84 00:05:15.350 --> 00:05:20.333 but we can at least stop arms companies openly developing and selling 85 00:05:20.333 --> 00:05:23.130 such weapons and making them like the Kalashnikovs of today. 86 00:05:23.800 --> 00:05:25.140 One possible solution? 87 00:05:25.150 --> 00:05:26.700 Stricter regulations. 88 00:05:26.710 --> 00:05:28.370 But this is controversial. 89 00:05:28.430 --> 00:05:31.670 A few EU nations, led by France, are calling for extensive 90 00:05:31.670 --> 00:05:34.710 exemptions for some AI uses in the military. 91 00:05:40.580 --> 00:05:42.010 Smoking tanks? 92 00:05:42.020 --> 00:05:45.120 Burning battlefields, fighter jets ablaze. 93 00:05:45.220 --> 00:05:49.300 Do you know how much pollution and CO2 such military equipment emits? 94 00:05:49.620 --> 00:05:50.440 No? 95 00:05:50.660 --> 00:05:53.740 No wonder hardly any data is collected. 96 00:05:53.980 --> 00:05:57.060 The military practically flies under the radar of climate 97 00:05:57.060 --> 00:05:58.360 protection measures. 98 00:05:58.620 --> 00:05:59.410 But why? 99 00:05:59.420 --> 00:06:00.960 And does it have to be this way? 100 00:06:03.040 --> 00:06:06.180 Why is nobody talking about the military and CO2? 101 00:06:08.110 --> 00:06:12.830 We're all supposed to avoid emitting CO2 by flying less on vacation, 102 00:06:12.830 --> 00:06:15.830 eating less meat, and not using gas for heating. 103 00:06:15.990 --> 00:06:19.230 Industry is also supposed to become climate neutral. 104 00:06:19.910 --> 00:06:23.070 But why doesn't anyone actually ask how harmful the military 105 00:06:23.070 --> 00:06:24.500 is to the climate? 106 00:06:24.510 --> 00:06:27.710 The military has been excluded from all climate protection 107 00:06:27.710 --> 00:06:34.640 agreements from Rio 1992 to Paris 2015. 108 00:06:34.640 --> 00:06:38.440 One reason the special task of protecting society makes 109 00:06:38.440 --> 00:06:40.340 the military an exception. 110 00:06:40.750 --> 00:06:44.310 Another states hardly provide any data because they want to keep 111 00:06:44.310 --> 00:06:48.790 the strengths, armaments and tactics of their armed forces secret. 112 00:06:50.510 --> 00:06:53.589 Even so, a london-based think tank has now published 113 00:06:53.589 --> 00:06:56.130 an estimate based on limited data. 114 00:06:56.150 --> 00:07:01.470 It says that the military causes around 5.5% of all greenhouse 115 00:07:01.470 --> 00:07:03.730 gas emissions worldwide. 116 00:07:04.550 --> 00:07:07.550 By way of comparison, international air traffic accounts 117 00:07:07.550 --> 00:07:12.630 for just over 3%, so around 28 million soldiers worldwide leave 118 00:07:12.630 --> 00:07:15.090 a huge CO2 boot print. 119 00:07:15.510 --> 00:07:17.890 This is mainly due to their heavy equipment. 120 00:07:19.440 --> 00:07:22.600 While environmentalists are upset about an SUV that consumes 121 00:07:22.600 --> 00:07:26.040 15 litres of diesel per 100 kilometres in the city, 122 00:07:26.320 --> 00:07:31.040 a Russian tank needs 240 litres for the same distance. 123 00:07:32.980 --> 00:07:37.740 The American counterpart even consumes 455 litres. 124 00:07:39.230 --> 00:07:42.350 It's no wonder that military equipment used in war harms 125 00:07:42.350 --> 00:07:43.300 the climate. 126 00:07:43.310 --> 00:07:46.830 In the first year alone, the war in Ukraine is said to have caused 127 00:07:46.830 --> 00:07:50.390 more emissions than Portugal and Greece combined. 128 00:07:52.200 --> 00:07:56.200 War also increases emissions through more forest fires, 129 00:07:56.400 --> 00:08:01.240 the destruction of oil refineries and gas pipelines, damage to homes 130 00:08:01.240 --> 00:08:02.710 and their reconstruction. 131 00:08:02.720 --> 00:08:05.510 The loss of life in war is more serious, 132 00:08:05.520 --> 00:08:07.620 but the climate also suffers. 133 00:08:07.830 --> 00:08:11.470 Emissions could be reduced, such as through hydrogen powered 134 00:08:11.470 --> 00:08:16.270 tanks and fighter planes, as well as army vehicles with electric drives. 135 00:08:18.600 --> 00:08:22.240 The EU now wants to include the military in the plan to become 136 00:08:22.240 --> 00:08:24.670 climate neutral by 2050. 137 00:08:24.680 --> 00:08:28.320 The best way, of course, would be to end all wars. 138 00:08:38.230 --> 00:08:40.809 Did you ever dream about flying as a kid? 139 00:08:40.840 --> 00:08:43.660 About unlimited freedom above the clouds? 140 00:08:43.670 --> 00:08:48.300 Well, some grownups try to realize such dreams with homemade aircraft. 141 00:08:48.790 --> 00:08:51.070 But flying isn't quite so easy. 142 00:08:51.080 --> 00:08:54.300 It's much better to get proper training aboard real airplanes, 143 00:08:54.309 --> 00:08:57.050 according to two young aviation enthusiasts. 144 00:09:03.429 --> 00:09:07.030 Lucas Heim had to fight for this moment for a long time. 145 00:09:10.510 --> 00:09:13.220 The student pilot is currently completing his training as 146 00:09:13.230 --> 00:09:14.650 a commercial pilot. 147 00:09:14.750 --> 00:09:17.910 Today, he's flying from Goodyear in Arizona towards 148 00:09:17.910 --> 00:09:19.370 the Grand Canyon. 149 00:09:23.309 --> 00:09:27.540 At the European Flight Academy in the US, the 26 year old is learning 150 00:09:27.550 --> 00:09:32.300 to fly small aircraft together with around 100 other student pilots. 151 00:09:35.720 --> 00:09:38.630 Later, he wants to fly passenger jets for Germany's 152 00:09:38.640 --> 00:09:43.280 largest airline Lufthansa and take passengers to all continents. 153 00:09:46.670 --> 00:09:49.340 We'll be here for another month or so, flying 154 00:09:49.350 --> 00:09:52.630 by site the whole time with the flight instructor to prepare 155 00:09:52.630 --> 00:09:57.070 ourselves to fly solo without an instructor, which is an incredible 156 00:09:57.080 --> 00:09:58.170 experience. 157 00:09:58.429 --> 00:10:02.070 And then we'll go into the simulator here to learn to fly after 158 00:10:02.080 --> 00:10:03.290 instrument flight. 159 00:10:06.679 --> 00:10:09.300 About three years ago, things were different. 160 00:10:09.330 --> 00:10:11.910 Lucas had to move out of his apartment in Bremen on 161 00:10:11.920 --> 00:10:13.420 the spur of the moment. 162 00:10:13.670 --> 00:10:16.540 During the pandemic, Lufthansa had stopped training 163 00:10:16.550 --> 00:10:17.959 its new pilots. 164 00:10:18.030 --> 00:10:21.390 Aviation had come to a virtual standstill worldwide. 165 00:10:22.030 --> 00:10:24.980 When and whether pilots would be needed again was completely 166 00:10:24.990 --> 00:10:26.100 up in the air. 167 00:10:26.110 --> 00:10:29.870 Lucas's lifelong dream of becoming a pilot seemed to be over. 168 00:10:32.470 --> 00:10:37.350 It's not at all clear that we'll be hired after we've been trained. 169 00:10:37.550 --> 00:10:39.329 That's not a good prospect. 170 00:10:39.710 --> 00:10:42.910 And in the end, our tests wouldn't be recognized in the future. 171 00:10:42.910 --> 00:10:44.650 They couldn't guarantee it. 172 00:10:44.790 --> 00:10:46.209 That's how I understand it. 173 00:10:46.270 --> 00:10:48.500 That means you've worked for a year and a half towards 174 00:10:48.510 --> 00:10:51.449 this goal and you have nothing at all to take with you. 175 00:10:54.330 --> 00:10:57.339 Caroline Bursner also didn't know what would happen. 176 00:10:58.080 --> 00:11:01.440 The Leipzig native was at flight school in the US when she heard 177 00:11:01.440 --> 00:11:03.820 that her training was being put on hold. 178 00:11:05.110 --> 00:11:07.969 She took a job at Amazon to survive. 179 00:11:10.429 --> 00:11:13.510 Her goal was to somehow complete her pilot training on 180 00:11:13.510 --> 00:11:15.089 her own if necessary. 181 00:11:17.950 --> 00:11:20.546 It's not easy to cope with. For someone who 182 00:11:20.631 --> 00:11:24.010 really wants to do it, it destroys dreams. 183 00:11:24.429 --> 00:11:27.380 At some point I really want to sit in the cockpit. 184 00:11:27.390 --> 00:11:29.860 But in the meantime, I think you should make the best of 185 00:11:29.870 --> 00:11:33.350 the resources you have available and what paths are open to you. 186 00:11:35.470 --> 00:11:38.210 Today, three years later, she has made it. 187 00:11:38.230 --> 00:11:41.309 Kaolin has been flying for the logistics giant DHL for 188 00:11:41.309 --> 00:11:42.650 four months. 189 00:11:42.750 --> 00:11:43.860 As a copilot. 190 00:11:43.870 --> 00:11:47.710 She flies tons of freight from Leipzig to African or other 191 00:11:47.710 --> 00:11:49.569 European destinations. 192 00:11:53.500 --> 00:11:58.460 I sometimes get up and go to work and think to myself on the way, 193 00:11:58.700 --> 00:12:02.140 Cool, you're really doing this now and I'm super grateful 194 00:12:02.140 --> 00:12:05.280 that my family has helped me so much and supported me. 195 00:12:07.440 --> 00:12:10.880 I would sometimes do a kind of double shift. 196 00:12:11.720 --> 00:12:16.440 I'd come in from the late shift, do flight preparation until 2:00 AM. 197 00:12:17.760 --> 00:12:22.320 I'd sleep, but get up again at 6:00 AM to drive to Berlin, to 198 00:12:22.320 --> 00:12:25.380 Schönhagen, to take a flying lesson there. 199 00:12:27.150 --> 00:12:31.670 And then drive back home and get to Amazon, an hour late, for a late shift. 200 00:12:34.480 --> 00:12:37.480 Just after midnight, the logistics hub outside at 201 00:12:37.480 --> 00:12:40.140 Leipzig/Halle airport comes to life. 202 00:12:40.440 --> 00:12:43.960 Rows and rows of DHL's, yellow and red plains are waiting. 203 00:12:43.960 --> 00:12:48.280 10s of thousands of parcels and packages are sorted and packed into 204 00:12:48.280 --> 00:12:51.460 containers for dispatch right next to the tarmac. 205 00:12:53.170 --> 00:12:55.293 At about 2:00 AM, they arrive minute by minute 206 00:12:55.293 --> 00:12:57.270 at the waiting airplanes. 207 00:12:58.390 --> 00:13:02.110 Most flights take place at night. 208 00:13:02.270 --> 00:13:06.510 You have to like that and be able to cope with it, as we fly out of 209 00:13:06.510 --> 00:13:07.729 here at night. 210 00:13:09.350 --> 00:13:13.830 We reach our destinations during the day, anywhere in Europe, Africa 211 00:13:13.830 --> 00:13:16.610 or the Middle East, at least with the plane I'm flying. 212 00:13:18.120 --> 00:13:21.200 We sleep there during the day and usually fly back via 213 00:13:21.200 --> 00:13:22.670 Leipzig in the evening. 214 00:13:22.679 --> 00:13:25.900 We're in Leipzig briefly and then we're off somewhere else again. 215 00:13:27.640 --> 00:13:30.020 Caroline Bösner is heading to Athens today. 216 00:13:30.040 --> 00:13:34.720 Her Airbus is still empty, but just like the plane next door, 217 00:13:35.040 --> 00:13:38.100 almost 40 tons of freight will soon fill the hold. 218 00:13:38.990 --> 00:13:42.390 The fact that she is only flying parcels and packages doesn't bother 219 00:13:42.390 --> 00:13:43.729 the pilot at all. 220 00:13:47.040 --> 00:13:51.720 What I fly doesn't matter in the end, the flying 221 00:13:51.720 --> 00:13:53.380 itself is the same. 222 00:13:53.679 --> 00:13:56.260 I do the same approach, the same take off. 223 00:13:57.150 --> 00:14:01.110 It just means that I don't have any passengers to look after. 224 00:14:01.710 --> 00:14:03.569 Cargo doesn't complain. 225 00:14:04.270 --> 00:14:06.940 Cargo doesn't grumble that the food isn't alright. 226 00:14:06.950 --> 00:14:07.900 It doesn't get angry. 227 00:14:07.910 --> 00:14:10.410 I don't have to call the police because of Cargo. 228 00:14:12.040 --> 00:14:15.720 In Goodyear, AZ, Lucas Heim has just returned from 229 00:14:15.720 --> 00:14:17.660 a 2 hour training flight. 230 00:14:18.160 --> 00:14:21.640 Before landing, he has to concentrate fully once again, 231 00:14:21.880 --> 00:14:25.960 correctly assessing speed, wind distance and altitude. 232 00:14:26.950 --> 00:14:30.630 The flight instructor only intervenes if something threatens to go wrong. 233 00:14:32.230 --> 00:14:33.890 But everything works out. 234 00:14:34.110 --> 00:14:36.380 Lucas lands without any problems. 235 00:14:36.390 --> 00:14:39.430 Still, they discuss the entire flight afterwards. 236 00:14:41.080 --> 00:14:43.950 And he practices especially tricky situations 237 00:14:43.960 --> 00:14:45.780 once again in the simulator. 238 00:14:47.280 --> 00:14:50.600 The simulator is less helpful with flight training itself, 239 00:14:50.880 --> 00:14:53.500 but it's great for training for emergencies. 240 00:14:53.840 --> 00:14:56.020 What can I really do in an emergency? 241 00:14:56.400 --> 00:14:59.560 There are things that you might not want to practice or demonstrate 242 00:14:59.560 --> 00:15:01.750 in flight, but you can do it here. 243 00:15:01.760 --> 00:15:03.340 It's a big advantage. 244 00:15:05.160 --> 00:15:08.480 Then the next mission awaits the next flight task. 245 00:15:09.080 --> 00:15:13.700 Lucas checks if the rudder, landing gear and lights are working properly. 246 00:15:13.790 --> 00:15:17.110 Or if anything is damaged, sometimes he has to take to 247 00:15:17.110 --> 00:15:18.930 the air three times a day. 248 00:15:20.510 --> 00:15:24.590 It's very special, you think about it every day. 249 00:15:25.310 --> 00:15:27.860 Now that we're getting used to flying, we know that it's out 250 00:15:27.870 --> 00:15:29.010 of the ordinary. 251 00:15:29.350 --> 00:15:32.330 You notice it in the people and in what we do here. 252 00:15:34.760 --> 00:15:40.360 If all goes to plan, Lucas Heim could complete his training by early 2025 253 00:15:40.360 --> 00:15:44.360 and fly passengers all over the world from the cockpit of a jet. 254 00:15:50.710 --> 00:15:53.580 Nothing has changed our lives as profoundly as 255 00:15:53.590 --> 00:15:55.180 the invention of the clock. 256 00:15:55.190 --> 00:15:58.990 Whether the seasons or even biological rhythms have been replaced 257 00:15:58.990 --> 00:16:02.030 with a non-stop March of seconds, minutes and hours. 258 00:16:03.310 --> 00:16:06.830 The dictatorship of the clock spurred the industrial revolution. 259 00:16:07.110 --> 00:16:10.270 Time is money became a motto for speed and growth, 260 00:16:11.270 --> 00:16:14.870 but timepieces themselves have become ever more valuable, 261 00:16:15.110 --> 00:16:16.900 even a speculative investments. 262 00:16:20.077 --> 00:16:26.310 40,000, 100,000 up to €1,000,000 for used watches. 263 00:16:27.430 --> 00:16:30.580 Luxury watches are booming even during a crisis, 264 00:16:30.590 --> 00:16:32.450 and they have become an investment. 265 00:16:32.590 --> 00:16:35.020 A unique market has emerged for people who like to show off 266 00:16:35.030 --> 00:16:36.290 what they have. 267 00:16:36.870 --> 00:16:42.430 People that can afford a luxury watch that could easily cost €10,000 or 268 00:16:42.430 --> 00:16:46.710 more are probably less impacted by high energy prices or inflation. 269 00:16:47.670 --> 00:16:51.150 Why do people buy luxury watches and how does this market work? 270 00:16:57.230 --> 00:17:00.430 Based in southern Germany, Chrono 24 is one of the largest 271 00:17:00.430 --> 00:17:02.770 online retailers for luxury watches. 272 00:17:03.390 --> 00:17:07.580 On its website, nearly 500 employees advise private and commercial buyers 273 00:17:07.590 --> 00:17:10.750 and sellers on how to price and classify watches correctly. 274 00:17:10.750 --> 00:17:16.150 €143,000 for a Pedic Philippe Nautilus, for example, 275 00:17:16.510 --> 00:17:19.730 the retailer received 6.5% of the sale. 276 00:17:19.750 --> 00:17:22.260 In most cases, these are pre-owned watches. 277 00:17:22.270 --> 00:17:24.290 They're usually cheaper than new ones. 278 00:17:24.869 --> 00:17:27.730 For a lot of people, it's also that that. 279 00:17:27.990 --> 00:17:31.510 The price is sometimes better than the retail price. 280 00:17:32.400 --> 00:17:34.340 So it's availability, it's price. 281 00:17:34.350 --> 00:17:36.780 And of course there's so many to choose from, 282 00:17:36.790 --> 00:17:40.150 even models that are not in the regular catalogue anymore. 283 00:17:41.070 --> 00:17:44.630 Handmade watches have up to 1500 individual parts. 284 00:17:45.070 --> 00:17:47.820 They are one-of-a-kind technical masterpieces, which makes 285 00:17:47.830 --> 00:17:49.730 them objects of speculation. 286 00:17:50.400 --> 00:17:55.670 Chrono 24 has an annual trading volume of €2 billion and 25,000 287 00:17:55.670 --> 00:17:58.850 to 30,000 watches are traded on the website every month. 288 00:17:59.310 --> 00:18:02.580 The luxury group LVMH also has a stake in the company. 289 00:18:04.470 --> 00:18:08.030 For years, prices for pre owned luxury watches kept rising. 290 00:18:10.720 --> 00:18:13.030 This was because the demand among wealthy buyers for 291 00:18:13.040 --> 00:18:15.180 investment opportunities was high. 292 00:18:15.680 --> 00:18:17.409 But then the bubble burst. 293 00:18:19.400 --> 00:18:20.980 And what happens when prices go up? 294 00:18:20.990 --> 00:18:24.580 It attracts even more people interested in the category, 295 00:18:24.590 --> 00:18:25.460 even more buyers. 296 00:18:25.470 --> 00:18:26.690 And that created. 297 00:18:28.119 --> 00:18:31.400 A vicious circle that drove prices really, really high, 298 00:18:31.410 --> 00:18:34.580 especially with availability of very cheap money. 299 00:18:34.680 --> 00:18:37.760 And when they're turned and money became more expensive, 300 00:18:38.119 --> 00:18:41.320 a lot of people were reconsidering their decision. 301 00:18:43.480 --> 00:18:47.960 As a result, prices have now fallen somewhat, but it is still worthwhile 302 00:18:47.960 --> 00:18:50.619 for many customers to buy luxury watches. 303 00:18:51.869 --> 00:18:53.850 We ask people on the street. 304 00:18:54.950 --> 00:18:57.580 Yes, around 5 I think by now. 305 00:18:57.590 --> 00:19:00.780 It used to be 5000 Deutsche Marks and then a bit more. 306 00:19:00.790 --> 00:19:02.740 Most of them are for keeping it a safe though, 307 00:19:02.750 --> 00:19:05.580 because nowadays you get mugged for a gold Rolex. 308 00:19:05.590 --> 00:19:07.810 That's why I wear cheap watches. 309 00:19:07.869 --> 00:19:10.090 I used to just be able to afford them. 310 00:19:10.270 --> 00:19:13.750 Now I collect them as an investment. 311 00:19:14.869 --> 00:19:16.700 And does that work as an investment? 312 00:19:16.710 --> 00:19:17.460 Yeah, it works. 313 00:19:17.470 --> 00:19:18.420 You don't lose anything. 314 00:19:18.430 --> 00:19:20.420 Is it more likely to increase? 315 00:19:20.430 --> 00:19:21.570 Have you sold any? 316 00:19:21.950 --> 00:19:23.330 They tend to go up. 317 00:19:23.590 --> 00:19:26.250 Some of them are rare models and then that works. 318 00:19:26.270 --> 00:19:30.790 The online retailer Chrono 24, has its own workshop with 319 00:19:30.790 --> 00:19:32.330 35 employees. 320 00:19:32.710 --> 00:19:35.990 This is where customers watches are overhauled and quality checks 321 00:19:35.990 --> 00:19:37.050 are carried out. 322 00:19:39.890 --> 00:19:44.320 This model cost €40,000. 323 00:19:44.320 --> 00:19:48.640 This is a Rolex Daytona and it's so expensive because it's made 324 00:19:48.650 --> 00:19:50.780 of white gold completely. 325 00:19:51.000 --> 00:19:54.880 It's had a movement overhaul and the case has been refurbished. 326 00:19:56.070 --> 00:19:59.630 The watches are polished. 327 00:19:59.920 --> 00:20:02.100 If it has been worn for more than five years, 328 00:20:02.109 --> 00:20:04.770 a watch's quality is checked before it is sold. 329 00:20:05.670 --> 00:20:08.490 The seller pays the several $100 fees. 330 00:20:09.230 --> 00:20:12.510 Finally, a beauty shot for the website. 331 00:20:14.550 --> 00:20:18.310 Luxury watches as an investment with an increase in value like 332 00:20:18.310 --> 00:20:21.550 gold or securities, can work for some buyers. 333 00:20:30.550 --> 00:20:34.270 Can you resist the sweet siren call of a bag of potato chips? 334 00:20:34.550 --> 00:20:38.270 You shouldn't give in too often, as highly processed foods such as 335 00:20:38.270 --> 00:20:42.670 soft drinks, chips or ice cream often contain large amounts of sugar, 336 00:20:42.670 --> 00:20:43.970 salt and fat. 337 00:20:44.030 --> 00:20:47.310 And junk food won't just make you overweight, it can shorten 338 00:20:47.310 --> 00:20:48.250 your life. 339 00:20:50.150 --> 00:20:52.810 A healthy alternative, water Lily pops. 340 00:20:52.820 --> 00:20:56.060 They contain no added sweeteners, only natural ingredients. 341 00:20:56.300 --> 00:20:59.700 A young entrepreneur has introduced her favorite snack to Europe. 342 00:21:00.260 --> 00:21:03.480 Hi, I'm Shweta, the founder of Just Nosh. 343 00:21:03.700 --> 00:21:07.060 I bring snacks with an Indian influence to Germany. 344 00:21:13.260 --> 00:21:17.609 I am a snack lover and this is what drove me to bring 345 00:21:17.619 --> 00:21:22.330 snacks with a purpose, with good nutrition to 346 00:21:22.420 --> 00:21:24.240 the European market. 347 00:21:31.180 --> 00:21:36.460 I personally had a stomach issue many years ago when when I was living 348 00:21:36.460 --> 00:21:37.140 in India. 349 00:21:37.150 --> 00:21:41.180 This is the main reason that I launched the company with 350 00:21:41.180 --> 00:21:47.330 attributes free of allergens that can be enjoyed by anyone who has 351 00:21:47.340 --> 00:21:52.260 trouble finding a product or just anybody can enjoy it. 352 00:21:55.790 --> 00:21:58.580 Full Makhana is a very very popular snack in India. 353 00:21:58.590 --> 00:22:02.630 We call it Makhana or fox snacks or water Lily pops. 354 00:22:02.630 --> 00:22:08.840 15 years ago it was found in every household because your mother 355 00:22:08.840 --> 00:22:13.800 or your grandmother prepared it for you on a pan very simply and gave 356 00:22:13.800 --> 00:22:15.300 it to you to eat. 357 00:22:15.480 --> 00:22:18.960 But now, as people have started becoming more health conscious, 358 00:22:18.960 --> 00:22:21.820 we find it at every supermarket. 359 00:22:22.040 --> 00:22:25.560 The farmers harvest the seeds once a year. 360 00:22:25.560 --> 00:22:29.200 They collect the seeds from the bottom of the pond after 361 00:22:29.200 --> 00:22:32.340 the farmers finish popping the seeds. 362 00:22:32.740 --> 00:22:39.973 They are then taken to a factory where the producers roast and season 363 00:22:40.700 --> 00:22:44.340 the snacks the makhanas based on our recipes. 364 00:22:46.830 --> 00:22:49.620 And once they are, they are seasoned, 365 00:22:49.630 --> 00:22:54.350 they are packed in these in these packets and then they 366 00:22:54.350 --> 00:23:00.950 are shipped in these boxes to us, to Germany. 367 00:23:02.630 --> 00:23:08.270 We have round about 100 people with farmers to production working 368 00:23:08.270 --> 00:23:12.109 for us. And if the season is not good or we don't have enough water, 369 00:23:12.510 --> 00:23:14.619 then you also see that the crop is bad. 370 00:23:14.630 --> 00:23:20.790 So this year in 2023 the the crop, there was a heavy rains, and because 371 00:23:20.790 --> 00:23:25.790 of that the price of the product in the market is very high. 372 00:23:30.390 --> 00:23:36.700 I originally come from Mumbai, India and I moved to Germany in 2016. 373 00:23:36.700 --> 00:23:39.740 Because I fell in love, I met my husband while 374 00:23:39.740 --> 00:23:40.850 we were studying. 375 00:23:40.859 --> 00:23:43.050 Since I come from an entrepreneur family, 376 00:23:43.060 --> 00:23:46.940 I have seen my father, having his own business. 377 00:23:46.950 --> 00:23:50.190 I have always wanted to have my own company. 378 00:23:55.270 --> 00:23:59.030 When I started the company in 2020, it was in the midst of COVID and 379 00:23:59.030 --> 00:24:03.310 even the first batch that came, came literally with my parents trying 380 00:24:03.310 --> 00:24:07.070 the flavours and it being shipped to Germany directly to me because 381 00:24:07.070 --> 00:24:08.060 that was possible. 382 00:24:08.070 --> 00:24:10.250 We also support the communities in India. 383 00:24:10.580 --> 00:24:12.250 The products are produced in India. 384 00:24:12.260 --> 00:24:14.480 It's a way for me to give back to my country. 385 00:24:21.990 --> 00:24:24.740 The winter does not make it so easy in Germany. 386 00:24:24.750 --> 00:24:29.590 The winter, the language, all of the things are something 387 00:24:29.590 --> 00:24:32.580 that you have to get used to when you're coming here. 388 00:24:32.590 --> 00:24:37.590 My heart lies in India, but now I feel very comfortable 389 00:24:37.590 --> 00:24:40.409 here in Germany. 390 00:24:49.390 --> 00:24:52.917 When you have your own company, you often don't have a break, 391 00:24:53.186 --> 00:24:56.560 so I use my free time to spend it with my family. 392 00:24:57.950 --> 00:25:03.350 Talking to people in India, exercising, watching movies and 393 00:25:03.350 --> 00:25:05.210 sometimes doing nothing at all. 394 00:25:07.310 --> 00:25:09.530 Because sometimes I just need to switch off. 395 00:25:16.670 --> 00:25:19.890 There's one message that I will just give is, 396 00:25:21.390 --> 00:25:23.090 Dran bleiben, continue. 397 00:25:23.220 --> 00:25:26.700 Working towards your goals, be persistent and 398 00:25:26.700 --> 00:25:30.180 it's not the destination but it's the journey. 399 00:25:30.540 --> 00:25:35.140 Yes, there will be a lot of hurdles on your way but don't give up 400 00:25:35.140 --> 00:25:38.260 because you will see ligh at the end of the tunnel. 401 00:25:39.820 --> 00:25:40.600 Good luck. 402 00:25:43.790 --> 00:25:45.460 And that's all for today. 403 00:25:45.470 --> 00:25:48.590 We hope you enjoyed your flight and watching what makes 404 00:25:48.590 --> 00:25:50.540 luxury timepieces tick. 405 00:25:50.550 --> 00:25:53.570 Maybe we even inspired you to seek out healthy snacks. 406 00:25:54.340 --> 00:25:56.100 Till next time, bye bye.