"Connections with James Burke" Seeing the Future

1 00:00:01,061 --> 00:00:03,478 Enjoy! 2 00:00:04,800 --> 00:00:07,140 In the next 20 years, we're about to see 3 00:00:07,140 --> 00:00:09,540 what may turn out to be the biggest changes 4 00:00:09,540 --> 00:00:11,883 to the way we live in human history. 5 00:00:19,890 --> 00:00:22,830 I'm James Burke, and I'm gonna take you on a journey 6 00:00:22,830 --> 00:00:26,790 through time, joining up about 10 connections, 7 00:00:26,790 --> 00:00:29,460 charting the people, objects, and ideas 8 00:00:29,460 --> 00:00:33,401 that change history in the most surprising ways. 9 00:00:33,401 --> 00:00:36,151 (exciting music) 10 00:00:37,052 --> 00:00:39,602 To tell you the incredible story of how we got here 11 00:00:42,050 --> 00:00:43,400 and where we're going next. 12 00:00:47,760 --> 00:00:51,180 This series is about the process of change 13 00:00:51,180 --> 00:00:54,130 and why the future is being shaped by everything we do 14 00:00:55,110 --> 00:00:57,303 and is not going to be what we expect. 15 00:00:58,620 --> 00:01:00,870 Because that's the way change happens. 16 00:01:00,870 --> 00:01:05,700 Cause and effect, you innovate to solve a problem, 17 00:01:05,700 --> 00:01:07,470 and even if you succeed, 18 00:01:07,470 --> 00:01:10,500 there's always an unexpected outcome that triggers a need 19 00:01:10,500 --> 00:01:12,933 for another innovation, and so on. 20 00:01:14,940 --> 00:01:18,333 That's why nobody in the past knew what was coming next. 21 00:01:19,800 --> 00:01:23,520 No one knew the sequence of connections 22 00:01:23,520 --> 00:01:26,970 leads like a falling set of dominoes to an innovation 23 00:01:26,970 --> 00:01:29,043 that's set to transform human kind. 24 00:01:30,720 --> 00:01:32,610 So where do we want to go from here? 25 00:01:32,610 --> 00:01:33,960 What's the next connection? 26 00:01:35,000 --> 00:01:41,074 Watch Online Movies and Series for FREE www.osdb.link/lm 27 00:01:50,430 --> 00:01:55,320 This is where we're headed, a quantum computer so powerful 28 00:01:55,320 --> 00:01:59,317 that one day it will be able to take colossal amounts 29 00:01:59,317 --> 00:02:02,193 of data, process it, and predict the future. 30 00:02:03,360 --> 00:02:05,220 Because everything can be predicted, 31 00:02:05,220 --> 00:02:07,740 down to the clothes you chose to wear today, 32 00:02:07,740 --> 00:02:10,920 which was dependent on fashion, the weather, 33 00:02:10,920 --> 00:02:13,590 your income, your friend's clothes, 34 00:02:13,590 --> 00:02:16,410 what advertisements you watch, and so on. 35 00:02:16,410 --> 00:02:19,410 If all that data could be crunched, 36 00:02:19,410 --> 00:02:22,050 you could have eliminated all other possibilities 37 00:02:22,050 --> 00:02:24,990 and predicted that choice of yours. 38 00:02:24,990 --> 00:02:27,780 Analyze data like that on a massive scale, 39 00:02:27,780 --> 00:02:30,210 and you can foresee how entire populations 40 00:02:30,210 --> 00:02:35,210 will interact and change, triggering social unrest, strikes, 41 00:02:35,220 --> 00:02:38,580 elections, economics, stocks and shares, 42 00:02:38,580 --> 00:02:41,043 all the information that leads to any event. 43 00:02:42,510 --> 00:02:46,740 All you need are computers of unimaginable power 44 00:02:46,740 --> 00:02:49,893 looking into the future like time machines. 45 00:02:51,990 --> 00:02:54,210 So to see how we're going to get to this real life 46 00:02:54,210 --> 00:02:59,010 time machine, we're going back in time, over 200 years, 47 00:02:59,010 --> 00:03:02,763 to the Emperor of France's toothpick in 1814. 48 00:03:13,050 --> 00:03:15,300 See, that's when a coalition of allies, 49 00:03:15,300 --> 00:03:18,090 including Austria, Russia, and the United Kingdom 50 00:03:18,090 --> 00:03:20,850 finally beat the Emperor of the French. 51 00:03:20,850 --> 00:03:22,230 You may have heard of him, 52 00:03:22,230 --> 00:03:26,100 he goes by the name of Napoleon Bonaparte. 53 00:03:26,100 --> 00:03:28,560 Now, Napoleon is a bit of a trouble maker. 54 00:03:28,560 --> 00:03:30,930 He and his French Army are busy invading 55 00:03:30,930 --> 00:03:33,810 surrounding countries so he can take over Europe. 56 00:03:33,810 --> 00:03:35,880 And it takes everything Europe has 57 00:03:35,880 --> 00:03:39,330 to stop him, capture him, and ship him off to somewhere 58 00:03:39,330 --> 00:03:41,043 he can't cause anymore trouble. 59 00:03:41,940 --> 00:03:45,240 The first solution, the Italian island of Elba, 60 00:03:45,240 --> 00:03:48,930 which doesn't do the job because he escapes 61 00:03:48,930 --> 00:03:50,670 and starts all over again. 62 00:03:50,670 --> 00:03:53,400 And they have to stop him all over again. 63 00:03:53,400 --> 00:03:56,310 The second time around, they give some serious thought 64 00:03:56,310 --> 00:03:59,010 to an island it would be really hard for Napoleon 65 00:03:59,010 --> 00:04:01,803 to get away from, like this one. 66 00:04:02,820 --> 00:04:06,183 A tiny dot as far from anywhere as you can get, 67 00:04:07,053 --> 00:04:10,500 an island in the Mid-Atlantic called Saint Helena, 68 00:04:10,500 --> 00:04:12,783 population too small to count. 69 00:04:14,640 --> 00:04:17,010 So where on this tiny dot to put the man 70 00:04:17,010 --> 00:04:18,483 who used to rule Europe? 71 00:04:20,520 --> 00:04:23,040 The best house standing on the island of Saint Helena 72 00:04:23,040 --> 00:04:27,210 at the time is this place, a property said to be 73 00:04:27,210 --> 00:04:31,653 particularly cold, uninviting, and infested with rats. 74 00:04:32,610 --> 00:04:34,743 Not much of a residence for an ex-Emperor. 75 00:04:36,330 --> 00:04:40,110 But Napoleon still has friends in high places, 76 00:04:40,110 --> 00:04:42,900 sympathizers in the British government to be precise, 77 00:04:42,900 --> 00:04:45,030 and so he gets preferential treatment 78 00:04:45,030 --> 00:04:47,340 even though he has no power. 79 00:04:47,340 --> 00:04:49,110 They decide to fill his residence 80 00:04:49,110 --> 00:04:51,120 with the most amazing and ornate stuff 81 00:04:51,120 --> 00:04:53,730 they can get their hands on to make him feel 82 00:04:53,730 --> 00:04:55,560 a bit more at home. 83 00:04:55,560 --> 00:04:58,470 Care of one of England's top designers and furniture makers, 84 00:04:58,470 --> 00:05:01,950 name of George Bullock, who's contracted to provide 85 00:05:01,950 --> 00:05:05,013 everything needed for the man who used to have everything. 86 00:05:05,880 --> 00:05:08,460 Take a look at some of the stuff Bullock produces, 87 00:05:08,460 --> 00:05:10,830 mahogany cabinets from the Americas, 88 00:05:10,830 --> 00:05:13,050 marble top tables from Wales, 89 00:05:13,050 --> 00:05:17,220 elegant silk covering English chairs, card tables, 90 00:05:17,220 --> 00:05:21,030 book cases, bell poles to call the servants in every room, 91 00:05:21,030 --> 00:05:23,460 writing desks with paper and ink, 92 00:05:23,460 --> 00:05:25,710 where Napoleon wrote his autobiography, 93 00:05:25,710 --> 00:05:28,923 the best seller of the entire 19th century. 94 00:05:30,060 --> 00:05:33,213 And everywhere, Napoleon's favorite color, green. 95 00:05:34,710 --> 00:05:37,140 Plus among thousands of other things, 96 00:05:37,140 --> 00:05:40,590 a billiard table, ivory handled cheese scoops, 97 00:05:40,590 --> 00:05:44,580 24 nutcrackers, two mustard pots, six wine coolers, 98 00:05:44,580 --> 00:05:49,580 84 toothbrushes, and you guessed it, 132 toothpicks. 99 00:05:51,510 --> 00:05:54,540 And we know all this because of the detailed bill, 100 00:05:54,540 --> 00:05:56,550 for almost a million bucks in modern money, 101 00:05:56,550 --> 00:05:58,143 presented by George Bullock. 102 00:05:59,190 --> 00:06:01,890 Bullock takes inspiration for his designs 103 00:06:01,890 --> 00:06:04,350 from cultures all over the world. 104 00:06:04,350 --> 00:06:06,750 Back in England, he famously ran a show room 105 00:06:06,750 --> 00:06:10,350 called the Grecian Rooms, themed, you guessed it, 106 00:06:10,350 --> 00:06:12,213 on ancient Greece. 107 00:06:14,400 --> 00:06:17,070 This enthusiasm for other people and places 108 00:06:17,070 --> 00:06:19,233 is also shared by his brother, William. 109 00:06:20,100 --> 00:06:23,640 Now this is a time when almost nobody can afford to travel 110 00:06:23,640 --> 00:06:25,680 much beyond their own borders. 111 00:06:25,680 --> 00:06:27,900 So William sees an opportunity, 112 00:06:27,900 --> 00:06:30,660 and through artifacts, brings the world to them. 113 00:06:31,560 --> 00:06:35,190 In 1809, William opens a museum in London 114 00:06:35,190 --> 00:06:38,250 and employs the novel idea of using back drops 115 00:06:38,250 --> 00:06:40,980 and furnishings to create an appropriate setting 116 00:06:40,980 --> 00:06:43,950 for each exhibit, just like his brother did 117 00:06:43,950 --> 00:06:46,830 for Napoleon in his fake palace. 118 00:06:46,830 --> 00:06:50,760 Ironically in 1816, William brings Napoleon's former world 119 00:06:50,760 --> 00:06:53,070 to the masses, exhibiting the ex-Emperor's 120 00:06:53,070 --> 00:06:55,980 original possessions, including his carriage 121 00:06:55,980 --> 00:06:57,690 captured in battle. 122 00:06:57,690 --> 00:06:58,983 Talk about come up'ns. 123 00:07:00,090 --> 00:07:03,990 Bullock adds people to his exhibitions to add authenticity, 124 00:07:03,990 --> 00:07:07,230 like a family of Laplanders with reindeer. 125 00:07:07,230 --> 00:07:09,903 There's even mummies with hieroglyphs. 126 00:07:12,060 --> 00:07:15,300 In 1823, a trip to Mexico gets William enough stuff 127 00:07:15,300 --> 00:07:18,450 to open an ancient and modern Mexico Exhibition 128 00:07:18,450 --> 00:07:19,400 the following year, 129 00:07:21,180 --> 00:07:23,970 complete with a real Mexican by the name 130 00:07:23,970 --> 00:07:27,300 of Jose Cayetana Ponce de Leon. 131 00:07:27,300 --> 00:07:29,430 He speaks his native language, of course, 132 00:07:29,430 --> 00:07:31,800 but he also speaks Italian and English 133 00:07:31,800 --> 00:07:34,260 to enthrall thousands of visitors with tales 134 00:07:34,260 --> 00:07:36,310 of the Aztec King Moctezuma 135 00:07:38,220 --> 00:07:40,680 And including plastic cast models 136 00:07:40,680 --> 00:07:44,310 of Aztec sacrificial sterns, pyramids, 137 00:07:44,310 --> 00:07:46,380 and Montezuma's stone calendar, 138 00:07:46,380 --> 00:07:50,640 as well as 43 glass cases stuffed with 139 00:07:50,640 --> 00:07:54,633 prickly pear cactus, bananas, avocados, and so on. 140 00:07:56,850 --> 00:07:59,910 The show ends up getting more than 50,000 visitors. 141 00:07:59,910 --> 00:08:02,370 This first of it's kind view of Mexico 142 00:08:02,370 --> 00:08:05,103 totally blows away the London chattering classes. 143 00:08:06,090 --> 00:08:09,930 Most of all, the star of the show, a hummingbird, 144 00:08:09,930 --> 00:08:12,330 stuffed of course because nobody ever manages 145 00:08:12,330 --> 00:08:14,280 to get the birds back to England alive. 146 00:08:18,180 --> 00:08:21,630 William is by now a fellow of the Linnean Society, 147 00:08:21,630 --> 00:08:25,230 pioneering a new natural history classification system, 148 00:08:25,230 --> 00:08:27,543 one we see in museums to this day. 149 00:08:29,580 --> 00:08:30,423 So where are we? 150 00:08:31,680 --> 00:08:34,410 Bear in mind that we're heading for a computer 151 00:08:34,410 --> 00:08:36,003 that can predict anything. 152 00:08:38,580 --> 00:08:42,390 Napoleon is defeated and incarcerated in Saint Helena, 153 00:08:42,390 --> 00:08:44,190 where his new home is filled with stuff 154 00:08:44,190 --> 00:08:46,150 from English designer George Bullock, 155 00:08:46,150 --> 00:08:48,870 who's brother brings the world to London 156 00:08:48,870 --> 00:08:51,480 in the form of his living museums, 157 00:08:51,480 --> 00:08:54,840 popular with the public keen to experience the world. 158 00:08:54,840 --> 00:08:58,470 This culminates with the first view of Mexico 159 00:08:58,470 --> 00:09:02,133 and introduces the Victoria's to the startling hummingbird, 160 00:09:03,480 --> 00:09:06,600 which kicks off a Victorian craze. 161 00:09:06,600 --> 00:09:10,290 The biggest hummingbird collection of more than 200 kinds 162 00:09:10,290 --> 00:09:12,790 ends up belonging to a guy called George Loddiges. 163 00:09:14,610 --> 00:09:17,520 He's nuts about them, can't get enough. 164 00:09:17,520 --> 00:09:19,890 He writes the book on little hummingbirds 165 00:09:19,890 --> 00:09:22,803 to spread the word, but it never gets published. 166 00:09:24,210 --> 00:09:26,220 His efforts are rewarded though 167 00:09:26,220 --> 00:09:28,270 because the hummingbird name, Loddigesia, 168 00:09:29,220 --> 00:09:32,523 used to this day, is so-called after him. 169 00:09:33,840 --> 00:09:36,030 Not content with hummingbirds, 170 00:09:36,030 --> 00:09:39,000 Loddiges also classifies plants. 171 00:09:39,000 --> 00:09:41,820 See, he's also a nursery-man who's taken over 172 00:09:41,820 --> 00:09:44,760 his father's seed business and grows thousands 173 00:09:44,760 --> 00:09:47,673 of plant varieties in his horticultural gardens. 174 00:09:49,890 --> 00:09:53,400 He creates nearly 2,000 plates of plants 175 00:09:53,400 --> 00:09:56,910 in the nursery's own catalog, "The Botanical Cabinet", 176 00:09:56,910 --> 00:09:59,643 which is published every month starting in 1817. 177 00:10:01,300 --> 00:10:03,660 Loddiges's pal, Nathaniel Ward, is also a serious 178 00:10:03,660 --> 00:10:07,500 plant person himself, who also collects things 179 00:10:07,500 --> 00:10:08,703 in glass jars. 180 00:10:11,910 --> 00:10:15,330 And this is where a friendship reshapes the entire 181 00:10:15,330 --> 00:10:19,173 global economy, and it all happens because of an accident. 182 00:10:20,160 --> 00:10:24,000 Ward is a London doctor with a perfectly understandable 183 00:10:24,000 --> 00:10:28,143 fixation for the sphinx moth cocoon, and why not. 184 00:10:29,370 --> 00:10:31,860 Ward keeps the moths, among other things, 185 00:10:31,860 --> 00:10:35,580 in a sealed bottle with leaves and moss soil. 186 00:10:35,580 --> 00:10:37,620 And then one day he discovers that something odd 187 00:10:37,620 --> 00:10:39,063 is going on in the jar. 188 00:10:40,500 --> 00:10:43,140 Condensation is forming on the inside 189 00:10:43,140 --> 00:10:45,510 and has dripped down into the soil, 190 00:10:45,510 --> 00:10:49,110 which then germinates a fern spore. 191 00:10:49,110 --> 00:10:52,950 Ward has inadvertently created a mini ecosystem 192 00:10:52,950 --> 00:10:54,543 without the need for watering. 193 00:10:56,340 --> 00:10:59,040 Ward has a eureka moment and gets a carpenter 194 00:10:59,040 --> 00:11:01,413 to knock together a new version of a jar. 195 00:11:04,170 --> 00:11:05,003 Take a look. 196 00:11:12,690 --> 00:11:14,910 This little innovation is going to be called 197 00:11:14,910 --> 00:11:18,123 the Wardian Case is made of wood and glass. 198 00:11:19,080 --> 00:11:22,260 It's like a small greenhouse, see. 199 00:11:22,260 --> 00:11:24,480 Much bigger than the original jar, 200 00:11:24,480 --> 00:11:26,313 it can carry 28 plants. 201 00:11:27,810 --> 00:11:29,970 Ward tells his friend, Loddiges, 202 00:11:29,970 --> 00:11:32,973 who jumps at the chance to expand his plant collection. 203 00:11:34,020 --> 00:11:38,460 Loddiges constructs 500 Wardian Cases 204 00:11:38,460 --> 00:11:41,430 to send plants to and get plants back from 205 00:11:41,430 --> 00:11:43,323 places like Australia. 206 00:11:44,190 --> 00:11:48,183 A six month trip each way and the plants survive. 207 00:11:49,500 --> 00:11:53,010 No hum to you, but back then this knocks the socks off 208 00:11:53,010 --> 00:11:54,543 horticulturalists everywhere. 209 00:11:56,130 --> 00:11:59,040 Because at the time, most people had never laid eyes 210 00:11:59,040 --> 00:12:01,530 on exotic plants before because up to then 211 00:12:01,530 --> 00:12:03,840 plants had been impossible to ship. 212 00:12:03,840 --> 00:12:06,270 The salty air, lack of light and fresh water 213 00:12:06,270 --> 00:12:07,293 kills them off. 214 00:12:09,060 --> 00:12:12,930 But now, Loddiges's global plant distribution network 215 00:12:12,930 --> 00:12:14,910 enables him to fill his nursery garden 216 00:12:14,910 --> 00:12:19,260 with stuff nobody's ever seen and sell them, 217 00:12:19,260 --> 00:12:21,183 making himself a fortune. 218 00:12:25,530 --> 00:12:28,200 Loddiges also owns the world's biggest hothouse 219 00:12:28,200 --> 00:12:32,400 in North London, then called The Grand Palm House. 220 00:12:32,400 --> 00:12:33,900 There are no other green houses 221 00:12:33,900 --> 00:12:35,583 anywhere on this kind of scale. 222 00:12:36,570 --> 00:12:40,140 At 40 foot high, the place can hold a full-scale palm tree 223 00:12:40,140 --> 00:12:42,660 and is filled to the roof with palms, 224 00:12:42,660 --> 00:12:45,360 ferns, and exotic plants, 225 00:12:45,360 --> 00:12:47,670 including a brand new type of orchid 226 00:12:47,670 --> 00:12:51,240 brought all the way from Mexico watered and alive 227 00:12:51,240 --> 00:12:52,920 in Wardian cases. 228 00:12:52,920 --> 00:12:55,233 It's name of course, Acropera loddigesii. 229 00:12:57,840 --> 00:13:01,050 Sprinklers in the Palm House roof replicate the conditions 230 00:13:01,050 --> 00:13:03,783 showering tropical mist and rain on the plants. 231 00:13:04,830 --> 00:13:07,653 Crowds of visitors come to stare at the spectacle. 232 00:13:10,020 --> 00:13:13,110 Even Charles Darwin turns up and must have been blown away 233 00:13:13,110 --> 00:13:17,100 by visible proof of his theory of evolution through variety 234 00:13:17,100 --> 00:13:20,490 with all the varieties of rose in George's gardens, 235 00:13:20,490 --> 00:13:23,403 1,279 to be precise. 236 00:13:25,890 --> 00:13:28,590 Now, the Wardian Case, it's about to change the future 237 00:13:28,590 --> 00:13:33,393 in a big way thanks to international espionage, 238 00:13:34,320 --> 00:13:38,220 economics, politics, and a part of the world 239 00:13:38,220 --> 00:13:41,913 still closed to the West, China. 240 00:13:42,900 --> 00:13:45,120 See, in the early 19th century, 241 00:13:45,120 --> 00:13:47,520 China is pretty much the only major producer 242 00:13:47,520 --> 00:13:52,323 of the one beverage no Brit can do without, tea. 243 00:13:56,790 --> 00:13:59,640 Britain is exporting so much silver to China 244 00:13:59,640 --> 00:14:02,520 to pay for the tea, the British government is scared 245 00:14:02,520 --> 00:14:06,420 the U.K. will go broke, while China, with its tea monopoly, 246 00:14:06,420 --> 00:14:09,153 looks like becoming the world's economic super power. 247 00:14:10,410 --> 00:14:14,520 This is why in 1848, a rather unscrupulous outfit 248 00:14:14,520 --> 00:14:18,090 called the British government backed East India Company, 249 00:14:18,090 --> 00:14:21,060 are looking for another way to solve the tea problem, 250 00:14:21,060 --> 00:14:22,473 but pay less for it. 251 00:14:23,674 --> 00:14:27,510 And as I said, they come across a little Wardian Case. 252 00:14:27,510 --> 00:14:30,450 Quick as a flash, they hire a solution, 253 00:14:30,450 --> 00:14:32,973 Scottish botanist Robert Fortune. 254 00:14:34,800 --> 00:14:37,800 They sent him on a secret mission to China, 255 00:14:37,800 --> 00:14:39,783 equipped with dozens of cases. 256 00:14:41,940 --> 00:14:45,450 It is a secret mission because China's interior 257 00:14:45,450 --> 00:14:47,550 is closed to all foreigners. 258 00:14:47,550 --> 00:14:49,530 And Fortune has to wear a pigtail 259 00:14:49,530 --> 00:14:53,130 and dress up in Chinese clothes and speak fractured Mandarin 260 00:14:53,130 --> 00:14:54,870 as if he comes from some remote province 261 00:14:54,870 --> 00:14:57,930 a long way from where he is in China at the time 262 00:14:57,930 --> 00:15:00,210 and travel with a Chinese servant 263 00:15:00,210 --> 00:15:02,373 to handle the really complicated sentences. 264 00:15:06,570 --> 00:15:10,410 In 1848, Fortune turns up outside a big tea factory 265 00:15:10,410 --> 00:15:13,950 supplying Shanghai, and the factory boss is asked 266 00:15:13,950 --> 00:15:16,530 if this honorable person might be allowed in 267 00:15:16,530 --> 00:15:18,543 to see how their wonderful tea is made. 268 00:15:20,610 --> 00:15:22,773 This is what Fortune sees them doing, 269 00:15:23,730 --> 00:15:28,293 only the greatest of all Chinese national security secrets. 270 00:15:40,088 --> 00:15:42,450 First, let the tea leaves lie in sunlight 271 00:15:42,450 --> 00:15:43,950 for a couple of hours. 272 00:15:43,950 --> 00:15:46,203 Then stir fry them in a hot wok. 273 00:15:47,910 --> 00:15:49,413 Then roll them back and forth. 274 00:15:51,720 --> 00:15:54,090 Then more stir fry. 275 00:15:54,090 --> 00:15:56,580 Then sort them into tightly wound leaves 276 00:15:56,580 --> 00:15:58,383 and take out any grit or dirt. 277 00:16:00,420 --> 00:16:03,423 And, as they say in Mandarin, bingo. 278 00:16:06,270 --> 00:16:08,340 Now that Fortune knows the secret, 279 00:16:08,340 --> 00:16:10,980 all he has to do is get the raw material out of China, 280 00:16:10,980 --> 00:16:15,000 which he does, thanks to the good old Wardian Case. 281 00:16:15,000 --> 00:16:18,750 In 1851, to the tune of 20,000 seedlings and plumes, 282 00:16:18,750 --> 00:16:21,420 smuggled to the northwest provinces of India 283 00:16:21,420 --> 00:16:25,440 to set up what will become a new Indian tea industry, 284 00:16:25,440 --> 00:16:28,083 entirely under U.K. ownership and management. 285 00:16:30,330 --> 00:16:31,563 So, where are we? 286 00:16:32,460 --> 00:16:34,590 Remember, all these connections are leading us 287 00:16:34,590 --> 00:16:37,203 to a computer that can predict anything. 288 00:16:41,760 --> 00:16:44,640 Napoleon is banished to a remote island, 289 00:16:44,640 --> 00:16:47,610 where his toothpicks are supplied by George Bullock, 290 00:16:47,610 --> 00:16:50,280 whose brother imports hummingbirds 291 00:16:50,280 --> 00:16:52,020 collected by George Loddiges, 292 00:16:52,020 --> 00:16:55,290 whose pal, Nathaniel Ward, invents the Wardian Case 293 00:16:55,290 --> 00:16:57,810 that George uses to set up an international 294 00:16:57,810 --> 00:16:59,643 plant distribution network. 295 00:17:00,651 --> 00:17:02,400 This transforms horticulture in Britain 296 00:17:02,400 --> 00:17:05,820 and inspires the British government to steal tea from China 297 00:17:05,820 --> 00:17:07,203 and grow it in India. 298 00:17:08,130 --> 00:17:11,490 Meanwhile, the fuss over tea has also given rise 299 00:17:11,490 --> 00:17:16,290 to a brief moment of glory, now about to end, for sailors. 300 00:17:16,290 --> 00:17:18,780 In the shape of some of the most beautiful sailing ships 301 00:17:18,780 --> 00:17:23,460 ever designed, they have a shallow draft and sleek bows 302 00:17:23,460 --> 00:17:26,130 and are built, above all, for speed 303 00:17:26,130 --> 00:17:28,653 and a light cargo, like tea. 304 00:17:29,640 --> 00:17:34,050 Known as clippers because they sail along at quite a clip, 305 00:17:34,050 --> 00:17:36,540 faster than any other kind of ship, 306 00:17:36,540 --> 00:17:39,360 carrying more sail than you could ever think possible. 307 00:17:39,360 --> 00:17:41,820 With the right wind, these beautiful ships 308 00:17:41,820 --> 00:17:44,160 sometimes hit over 17 knots, 309 00:17:44,160 --> 00:17:46,083 which is like sailing supersonic. 310 00:17:47,190 --> 00:17:50,043 Europe to Asia in just 90 days. 311 00:17:52,170 --> 00:17:54,540 While the clippers are amazing the world, 312 00:17:54,540 --> 00:17:57,450 bigger, less glamorous sailing ships are also running down 313 00:17:57,450 --> 00:18:00,003 the West African coast, picking up cargo. 314 00:18:01,320 --> 00:18:03,000 The ships have to turn up, 315 00:18:03,000 --> 00:18:04,890 wait for a full hold of cargo, 316 00:18:04,890 --> 00:18:06,150 and then wait for the right wind 317 00:18:06,150 --> 00:18:08,160 to get them back to England. 318 00:18:08,160 --> 00:18:10,530 All this hanging around means it can take a businessman 319 00:18:10,530 --> 00:18:14,430 back home months to get delivery of his West African goods, 320 00:18:14,430 --> 00:18:19,323 gum, ivory, gold, ground nuts, and animal hides, 321 00:18:21,000 --> 00:18:24,000 all goods too heavy and bulky to fit in a clipper, 322 00:18:24,000 --> 00:18:26,650 but still needed back in England as soon as possible. 323 00:18:27,630 --> 00:18:30,870 And the West African cargo that matters most 324 00:18:30,870 --> 00:18:33,963 because it makes the most profit, palm oil. 325 00:18:37,530 --> 00:18:40,830 Industry needs all the palm oil it can get 326 00:18:40,830 --> 00:18:45,063 for lubrication for machinery, for candle making, 327 00:18:45,990 --> 00:18:49,473 and above all, food for a growing workforce. 328 00:18:50,640 --> 00:18:54,570 And as always, with demand like that waiting for a solution, 329 00:18:54,570 --> 00:18:56,550 necessity is the mother. 330 00:18:56,550 --> 00:18:59,490 In this case, a new kind of ship. 331 00:18:59,490 --> 00:19:03,000 Thanks to one Alfred Holt, who from a young age 332 00:19:03,000 --> 00:19:05,373 grows up learning about engines. 333 00:19:06,420 --> 00:19:10,650 And then around 1865, radically changes the future 334 00:19:10,650 --> 00:19:13,293 with his multiple expansion engine. 335 00:19:14,760 --> 00:19:16,470 Here's the amazing engine. 336 00:19:16,470 --> 00:19:19,200 It uses high pressure steam recycled 337 00:19:19,200 --> 00:19:20,940 from one cylinder to another, 338 00:19:20,940 --> 00:19:23,580 ensuring there's no wasted energy. 339 00:19:23,580 --> 00:19:26,610 This generates enough power to drive pistons 340 00:19:26,610 --> 00:19:28,290 to turn a massive propeller. 341 00:19:28,290 --> 00:19:29,850 No need for wind. 342 00:19:29,850 --> 00:19:32,010 Holt puts this engine into a new steam ship 343 00:19:32,010 --> 00:19:33,663 called the Agamemnon. 344 00:19:34,500 --> 00:19:37,023 At 309 feet long, it's huge. 345 00:19:38,160 --> 00:19:40,200 Cruising at a constant 10 knots, 346 00:19:40,200 --> 00:19:43,860 it can make the journey to Asia in less than 60 days. 347 00:19:43,860 --> 00:19:48,390 Suddenly this one ship can carry over 2,000 tons, 348 00:19:48,390 --> 00:19:51,630 the equivalent cargo of three of the old clippers. 349 00:19:51,630 --> 00:19:55,143 So the number of traders buying space goes up exponentially. 350 00:19:56,490 --> 00:19:59,730 And steam ships like this can go nonstop from England 351 00:19:59,730 --> 00:20:02,850 to the east come storm, rain, or shine, 352 00:20:02,850 --> 00:20:07,850 refuel, and head back, all 15 days faster than a clipper. 353 00:20:08,010 --> 00:20:09,760 No more waiting for the right wind. 354 00:20:10,809 --> 00:20:14,850 (steam engine blowing) 355 00:20:14,850 --> 00:20:16,920 On the West African palm oil run, 356 00:20:16,920 --> 00:20:19,923 cargo ships under sail go out of business almost overnight. 357 00:20:21,120 --> 00:20:24,150 The new steam ships also allow access to ports 358 00:20:24,150 --> 00:20:27,063 that sail ships couldn't reach because of the wind. 359 00:20:28,770 --> 00:20:33,630 In 1800, Britain imports about 200 tons of palm oil 360 00:20:33,630 --> 00:20:35,250 from West Africa. 361 00:20:35,250 --> 00:20:40,250 By 1850, that figure is more than 25,000 tons 362 00:20:40,620 --> 00:20:41,643 and rising fast. 363 00:20:44,237 --> 00:20:45,990 Now the great thing about palm oil is 364 00:20:45,990 --> 00:20:48,993 it's easy to grow and even easier to process. 365 00:20:51,225 --> 00:20:54,390 In West Africa, the local have been using it for centuries 366 00:20:54,390 --> 00:20:56,193 for food and even medicine. 367 00:20:57,030 --> 00:20:59,790 The fruit is about the size of an olive. 368 00:20:59,790 --> 00:21:01,770 The pulp is where the oil comes from, 369 00:21:01,770 --> 00:21:05,070 and there's lots more than you can get from animal fat. 370 00:21:05,070 --> 00:21:08,760 So palm oil trees are extremely productive. 371 00:21:08,760 --> 00:21:11,040 And demand is going to get even bigger 372 00:21:11,040 --> 00:21:13,470 because it turns out one other exciting 373 00:21:13,470 --> 00:21:16,920 and really money making thing palm oil does, 374 00:21:16,920 --> 00:21:21,363 besides lubrication and lighting, is make soap. 375 00:21:25,800 --> 00:21:28,080 In 1884, the son of an English grocer, 376 00:21:28,080 --> 00:21:32,610 William Lever and his brother team up with a local chemist 377 00:21:32,610 --> 00:21:34,770 who's invented a way of making soap 378 00:21:34,770 --> 00:21:38,583 with a mix of palm oil, cottonseed oil, and glycerin. 379 00:21:39,855 --> 00:21:43,710 This new soap is an instant success, 380 00:21:43,710 --> 00:21:47,310 mainly because the old way to make soap with animals fat 381 00:21:47,310 --> 00:21:50,253 smells awful and doesn't give you much of a wash. 382 00:21:51,870 --> 00:21:55,143 Palm oil soap smells nice and makes a lot of lather, see. 383 00:21:56,100 --> 00:21:59,250 But what matters most is that Lever's real talent 384 00:21:59,250 --> 00:22:01,020 lies in selling and marketing. 385 00:22:01,020 --> 00:22:03,680 First of all, he produces his new soap 386 00:22:03,680 --> 00:22:07,800 in a small individual tablet, and he aims it 387 00:22:07,800 --> 00:22:11,013 at ordinary working people because he makes it cheap. 388 00:22:12,390 --> 00:22:14,460 The soap ends up with the kind of name 389 00:22:14,460 --> 00:22:17,253 you'd never think of, Sunlight. 390 00:22:18,900 --> 00:22:21,390 And Lever puts it in special wrapping, 391 00:22:21,390 --> 00:22:23,973 the first branded laundry soap. 392 00:22:24,840 --> 00:22:25,740 How could he fail? 393 00:22:26,697 --> 00:22:29,280 (upbeat music) 394 00:22:35,625 --> 00:22:40,320 Within a decade, Sunlight Soap is selling in 134 countries, 395 00:22:40,320 --> 00:22:44,493 along with two over Lever washing products, Lux and Vim. 396 00:22:45,990 --> 00:22:48,960 Here's one of our unintended consequences again, 397 00:22:48,960 --> 00:22:52,293 one that forms a beginning of a society that can be 398 00:22:52,293 --> 00:22:54,840 educated, sheltered, and cared for. 399 00:22:54,840 --> 00:22:57,480 See, demand is so great that Lever has an idea. 400 00:22:57,480 --> 00:23:01,023 How about housing the workers next to his factories. 401 00:23:02,070 --> 00:23:04,770 In 1888, Lever begins to build a model village 402 00:23:04,770 --> 00:23:09,448 for workers in Cheshire and called Port Sunlight. 403 00:23:13,590 --> 00:23:17,220 700 cottages, one of them a copy of Shakespeare's birthplace 404 00:23:17,220 --> 00:23:20,020 would you believe, but with running water and bathrooms. 405 00:23:21,120 --> 00:23:26,100 And in a new piece of social change, schools for 500 kids, 406 00:23:26,100 --> 00:23:30,180 as well as a concert hall and theater, library, gym, 407 00:23:30,180 --> 00:23:31,530 and open-air swimming pool. 408 00:23:33,030 --> 00:23:36,150 Rent is one fifth the weekly wage. 409 00:23:36,150 --> 00:23:38,760 Social activities are available. 410 00:23:38,760 --> 00:23:43,380 It works, the factory produces up to 5,000 tons of soap 411 00:23:43,380 --> 00:23:46,290 a week, but there's a downside. 412 00:23:46,290 --> 00:23:48,633 Lose your job and you lose your house. 413 00:23:50,100 --> 00:23:52,620 So halfway through our connections, 414 00:23:52,620 --> 00:23:54,870 leading us to the future where machines 415 00:23:54,870 --> 00:23:57,543 can predict anything, let's see where we are. 416 00:23:59,700 --> 00:24:02,490 Napoleon's banishment and his furniture, 417 00:24:02,490 --> 00:24:05,253 hummingbirds, the Wardian Case, 418 00:24:06,188 --> 00:24:11,188 Chinese tea grows in India as well as China, 419 00:24:11,220 --> 00:24:14,310 the British economy goes into industrial overdrive, 420 00:24:14,310 --> 00:24:17,730 and surging demand to speed up sailing ship imports 421 00:24:17,730 --> 00:24:19,503 triggers Holt's new steam engine. 422 00:24:21,780 --> 00:24:25,740 Imports pour in, especially palm oil, 423 00:24:25,740 --> 00:24:29,493 which Lever and his brother use to create Sunlight Soap. 424 00:24:32,497 --> 00:24:35,160 (horses whinnying) 425 00:24:35,160 --> 00:24:38,160 By 1898, Lever has himself one of the first 426 00:24:38,160 --> 00:24:41,070 modern multi-national companies. 427 00:24:41,070 --> 00:24:43,260 His challenge now is to break into 428 00:24:43,260 --> 00:24:45,243 the lucrative American market. 429 00:24:46,230 --> 00:24:47,940 And here's where we take a turn towards 430 00:24:47,940 --> 00:24:50,190 our ability to predict the future. 431 00:24:50,190 --> 00:24:53,163 It all starts with the power of persuasion. 432 00:24:54,150 --> 00:24:58,770 See this, a soda cracker with an interesting name. 433 00:24:58,770 --> 00:25:03,270 I'll spell it, U-N-E-E-D-A. 434 00:25:03,270 --> 00:25:05,133 Pronounce it and you'll see why. 435 00:25:06,540 --> 00:25:10,230 The tag is, "Do you know uneeda biscuit?" 436 00:25:10,230 --> 00:25:12,150 If ever there's a hint of what's going to happen 437 00:25:12,150 --> 00:25:13,953 in the future, it's this. 438 00:25:15,030 --> 00:25:17,040 The story goes in 1898, 439 00:25:17,040 --> 00:25:19,920 a firm of biscuit makers called Nabisco 440 00:25:19,920 --> 00:25:23,550 hires the first advertising agency, N.W. Ayer, 441 00:25:23,550 --> 00:25:25,230 to think of a name for a soda cracker 442 00:25:25,230 --> 00:25:27,540 the company wants to put on the market. 443 00:25:27,540 --> 00:25:30,180 Ayer comes up with a name, Uneeda. 444 00:25:30,180 --> 00:25:31,680 And two years later, they're selling 445 00:25:31,680 --> 00:25:34,890 10 million packets a month and have to open new factories 446 00:25:34,890 --> 00:25:36,153 to keep up with demand. 447 00:25:39,030 --> 00:25:43,050 So in 1903, Lever tries an experimental marketing approach 448 00:25:43,050 --> 00:25:48,050 of his own, he tries the idea of soap and science. 449 00:25:48,240 --> 00:25:52,027 Soap in a lab, and adopts the tag line, 450 00:25:52,027 --> 00:25:55,530 "Expert Chemists Test Each Batch". 451 00:25:55,530 --> 00:25:58,230 What we're seeing here is one of the world's 452 00:25:58,230 --> 00:26:00,600 first advertising campaigns. 453 00:26:00,600 --> 00:26:02,850 So rather than just coming up with an attractive name 454 00:26:02,850 --> 00:26:05,610 for your product, like Sunlight for soap, 455 00:26:05,610 --> 00:26:08,100 and packaging to make your product more attractive, 456 00:26:08,100 --> 00:26:11,490 now you also tell your prospective buyers 457 00:26:11,490 --> 00:26:13,650 it's going to improve their lives. 458 00:26:13,650 --> 00:26:16,950 And notice the idea of wear and tear 459 00:26:16,950 --> 00:26:20,130 and having to scrub hard with ordinary soaps 460 00:26:20,130 --> 00:26:22,620 because around this time, Lever also starts persuading 461 00:26:22,620 --> 00:26:26,250 women customers that his soap will save them 462 00:26:26,250 --> 00:26:28,923 from the daily drudgery that puts years on them. 463 00:26:36,043 --> 00:26:37,560 And as early as 1896, 464 00:26:37,560 --> 00:26:41,760 Lever pioneers the first example of product placement. 465 00:26:41,760 --> 00:26:43,110 And how does he do it? 466 00:26:43,110 --> 00:26:47,400 Well, surreptitiously in a film by the Lumière brothers, 467 00:26:47,400 --> 00:26:50,790 in this case, of a family washing clothes in a tub 468 00:26:50,790 --> 00:26:52,590 in their garden. 469 00:26:52,590 --> 00:26:55,593 Note the boxes of Sunlight Soap in the foreground. 470 00:26:58,500 --> 00:27:00,990 Lever also puts advertising for his products 471 00:27:00,990 --> 00:27:04,440 on roadside billboards, at railroad stations, 472 00:27:04,440 --> 00:27:05,763 and in local papers. 473 00:27:06,990 --> 00:27:08,880 And then in the 1920s and 30s comes 474 00:27:08,880 --> 00:27:13,391 an advertising game changer, radio. 475 00:27:18,330 --> 00:27:20,820 Thanks to a new kind of program that is soon getting 476 00:27:20,820 --> 00:27:24,540 big audiences in the form of a series of radio shows, 477 00:27:24,540 --> 00:27:27,810 both weekly and daily, all about the lives 478 00:27:27,810 --> 00:27:30,330 of the glamorous characters whose goings on 479 00:27:30,330 --> 00:27:34,500 are complicated enough for you to tune into the next show 480 00:27:34,500 --> 00:27:35,900 to see what happens to them. 481 00:27:37,080 --> 00:27:41,340 Lever funds these shows by way of sponsorship for a price. 482 00:27:41,340 --> 00:27:44,160 They get product placement in the shows. 483 00:27:44,160 --> 00:27:46,170 Most of the other companies sponsoring these shows 484 00:27:46,170 --> 00:27:49,080 are also in the business of washing materials, 485 00:27:49,080 --> 00:27:54,030 so the new radio shows become known as soap operas. 486 00:27:54,030 --> 00:27:56,880 Here's a bit of one of the earliest shows. 487 00:27:56,880 --> 00:27:58,350 Good morning, radio listeners. 488 00:27:58,350 --> 00:28:01,743 Clara Lou and Em, brought to you by Colgate Palm Olive, 489 00:28:02,735 --> 00:28:03,720 the makers of Palm Olive soap. 490 00:28:03,720 --> 00:28:06,000 I wish that you would try this splendid soap 491 00:28:06,000 --> 00:28:07,350 for just 30 days. 492 00:28:07,350 --> 00:28:09,720 You'll want to use it always after that. 493 00:28:09,720 --> 00:28:12,300 Now, since sponsorship advertising isn't cheap, 494 00:28:12,300 --> 00:28:13,770 it triggers a lot of questions 495 00:28:13,770 --> 00:28:16,050 that the sponsors need answers to. 496 00:28:16,050 --> 00:28:18,600 What are we getting for our money? 497 00:28:18,600 --> 00:28:21,660 I mean, are you getting a big audience for your product? 498 00:28:21,660 --> 00:28:23,100 What kind of audience? 499 00:28:23,100 --> 00:28:25,080 What shows do people listen to? 500 00:28:25,080 --> 00:28:29,100 What time of day or week and for how long? 501 00:28:29,100 --> 00:28:33,453 Above all, basically does radio sell product? 502 00:28:35,040 --> 00:28:37,530 That last question from the Lever advertising manager 503 00:28:37,530 --> 00:28:41,100 in the U.S. catches the interest of a couple of MIT types 504 00:28:41,100 --> 00:28:43,983 called Robert Elder and Louis Woodruff. 505 00:28:45,000 --> 00:28:48,000 And in 1936, they patent the solution. 506 00:28:48,000 --> 00:28:50,620 Survey the audience electronically 507 00:28:51,840 --> 00:28:54,243 with a gizmo called an Audimeter. 508 00:28:57,570 --> 00:28:58,570 Here's what it does. 509 00:29:00,143 --> 00:29:01,590 The radio has a dial you turn 510 00:29:01,590 --> 00:29:03,333 to tune to the station you want. 511 00:29:04,200 --> 00:29:06,240 The radio is linked to the Audimeter, 512 00:29:06,240 --> 00:29:09,750 which is fitted with gears and connected to the dial. 513 00:29:09,750 --> 00:29:12,780 As you turn the dial, the Audimeter arm, 514 00:29:12,780 --> 00:29:14,280 with a pen on the end of it, 515 00:29:14,280 --> 00:29:17,460 moves across a slowly unrolling strip of paper 516 00:29:17,460 --> 00:29:20,310 and stops once the station is chosen. 517 00:29:20,310 --> 00:29:22,320 And then the paper goes on rolling 518 00:29:22,320 --> 00:29:25,470 and the pen keeps marking a continuous line on the paper, 519 00:29:25,470 --> 00:29:27,633 indicating how long they listened for. 520 00:29:28,560 --> 00:29:32,130 And it will do all this till the paper runs out, 521 00:29:32,130 --> 00:29:33,660 which takes a month. 522 00:29:33,660 --> 00:29:36,660 At which point, the audience research people turn up 523 00:29:36,660 --> 00:29:38,403 and take the roll for analysis. 524 00:29:43,560 --> 00:29:47,190 All this is described in a presentation by Robert Elder 525 00:29:47,190 --> 00:29:49,500 during a meeting of the Market Research Council 526 00:29:49,500 --> 00:29:50,913 at the New York Yale Club. 527 00:29:54,270 --> 00:29:55,890 And one of the people in the audience, 528 00:29:55,890 --> 00:30:00,420 who has a lovely idea, is a chap called Arthur Nielsen, 529 00:30:00,420 --> 00:30:01,470 who already has a company 530 00:30:01,470 --> 00:30:04,239 analyzing sales figures for stores. 531 00:30:10,380 --> 00:30:15,380 By 1946, Nielsen has 1,300 Audimeters in 1,100 homes 532 00:30:15,390 --> 00:30:17,190 and has spent nearly 10 years 533 00:30:17,190 --> 00:30:19,173 and two million dollars to get there. 534 00:30:20,097 --> 00:30:21,930 And he's researched all of the families 535 00:30:21,930 --> 00:30:24,980 in each of the target homes, how many people, 536 00:30:24,980 --> 00:30:26,283 at what age children, 537 00:30:29,190 --> 00:30:30,720 their jobs and incomes, 538 00:30:30,720 --> 00:30:32,580 and anything else they need to know 539 00:30:32,580 --> 00:30:36,390 so the tape analysis shows who's listening to what when. 540 00:30:36,390 --> 00:30:38,370 Of course the Nielsen I'm talking about 541 00:30:38,370 --> 00:30:41,730 is the guy behind Nielsen ratings, 542 00:30:41,730 --> 00:30:44,913 which move on from radio to TV once that's up and running. 543 00:30:54,720 --> 00:30:57,120 How can Nielsen process so much data? 544 00:30:57,120 --> 00:30:59,790 Well, by coincidence. 545 00:30:59,790 --> 00:31:03,150 See, in World War II, the U.S. is churning out 546 00:31:03,150 --> 00:31:05,250 lots of new types of artillery shells 547 00:31:05,250 --> 00:31:07,173 that can hit distant targets. 548 00:31:08,070 --> 00:31:10,470 To be accurate, somebody has to calculate 549 00:31:10,470 --> 00:31:12,240 all their possible trajectories, 550 00:31:12,240 --> 00:31:15,000 based on a whole host of variables. 551 00:31:15,000 --> 00:31:19,567 Shell size, length of barrel, wind speed, distance, 552 00:31:19,567 --> 00:31:20,613 you name it. 553 00:31:21,840 --> 00:31:24,240 A shell trajectory table would've taken 554 00:31:24,240 --> 00:31:27,000 a human mathematician, at the time mostly women, 555 00:31:27,000 --> 00:31:29,760 more than 30 hours to calculate. 556 00:31:29,760 --> 00:31:32,040 These women, by the way, are known as people who compute 557 00:31:32,040 --> 00:31:36,063 or computers, hence the modern word for the machine. 558 00:31:37,320 --> 00:31:38,670 But that's about to change. 559 00:31:39,780 --> 00:31:41,790 Here comes the coincidence. 560 00:31:41,790 --> 00:31:44,880 During the way, Nielsen's son has been working 561 00:31:44,880 --> 00:31:46,950 at a military establishment called 562 00:31:46,950 --> 00:31:50,460 the Ballistic Research Lab in Aberdeen, Maryland, 563 00:31:50,460 --> 00:31:54,270 where they're building a top secret 30 ton military machine 564 00:31:54,270 --> 00:31:57,720 to help make American artillery more accurate. 565 00:31:57,720 --> 00:32:00,120 And it's all thanks to a breakthrough that will shape 566 00:32:00,120 --> 00:32:01,443 everything we do today. 567 00:32:06,150 --> 00:32:07,293 Glass tube. 568 00:32:08,430 --> 00:32:11,880 In fact, it's been inside radios and TVs all along. 569 00:32:11,880 --> 00:32:15,240 A little gizmo invented back in 1904 by a guy 570 00:32:15,240 --> 00:32:18,963 called Fleming, working for the Marconi Radio Company. 571 00:32:20,970 --> 00:32:23,400 It's called a vacuum tube. 572 00:32:23,400 --> 00:32:26,820 Basically, it's a glass tube with a vacuum inside. 573 00:32:26,820 --> 00:32:30,690 Also in there is a bit of metal called a cathode. 574 00:32:30,690 --> 00:32:33,810 Heat it and it gives off electrons. 575 00:32:33,810 --> 00:32:35,520 They flow to the other end of the tube 576 00:32:35,520 --> 00:32:39,390 to another unheated bit of metal called an anode, 577 00:32:39,390 --> 00:32:41,310 which then gives off a signal. 578 00:32:41,310 --> 00:32:45,600 When that happens, the vacuum tube is described as on. 579 00:32:45,600 --> 00:32:48,840 Now, you add a grid between the cathode and an anode, 580 00:32:48,840 --> 00:32:50,670 put a current onto that grid, 581 00:32:50,670 --> 00:32:53,280 and it stops the flow of electrons to the anode. 582 00:32:53,280 --> 00:32:56,760 So now the vacuum tube is off, 583 00:32:56,760 --> 00:32:59,490 and the electron flow can be interrupted like that 584 00:32:59,490 --> 00:33:02,460 an amazing 100,000 times a second 585 00:33:02,460 --> 00:33:05,220 by any signal that puts a load onto the grid 586 00:33:05,220 --> 00:33:07,530 and temporarily blocks the electron flow, 587 00:33:07,530 --> 00:33:09,510 turning a tube off. 588 00:33:09,510 --> 00:33:12,060 All that gobbly gook basically adds up 589 00:33:12,060 --> 00:33:16,293 to just an astronomically fast on off adding machine. 590 00:33:19,800 --> 00:33:21,570 The amazing calculating machine 591 00:33:21,570 --> 00:33:24,900 that will do this clever stuff is called ENIAC, 592 00:33:24,900 --> 00:33:28,050 electronic numerical integrator and computer. 593 00:33:28,050 --> 00:33:30,093 And it fills a room. 594 00:33:31,620 --> 00:33:34,320 ENIAC has more than 17,000 vacuum tubes 595 00:33:34,320 --> 00:33:36,090 to do the on off counting, 596 00:33:36,090 --> 00:33:38,730 and it uses enough power for a small town. 597 00:33:38,730 --> 00:33:42,630 It also has 70,000 resisters, 10,000 capacitors, 598 00:33:42,630 --> 00:33:45,693 6,000 switches, and 1,500 relays. 599 00:33:47,370 --> 00:33:49,740 Whichever way you slice it, ENIAC is going to change 600 00:33:49,740 --> 00:33:53,010 not just ballistic trajectories, but everything, 601 00:33:53,010 --> 00:33:58,010 because it does a mind boggling 5,000 calculations a second. 602 00:33:58,350 --> 00:34:01,140 So for the ballistics people doing the gun tables, 603 00:34:01,140 --> 00:34:03,453 it's a dream solution to their problems. 604 00:34:04,860 --> 00:34:07,020 So where does this connect to a future 605 00:34:07,020 --> 00:34:08,820 where machines can predict anything? 606 00:34:10,590 --> 00:34:14,790 Well, Nielsen's son, tells his father all about ENIAC, 607 00:34:14,790 --> 00:34:17,220 and after the war, Nielsen Senior gets ahold of 608 00:34:17,220 --> 00:34:19,500 one of the world's first electronic computers, 609 00:34:19,500 --> 00:34:23,013 made by IBM and based on the ENIAC military technology. 610 00:34:23,850 --> 00:34:26,180 Much smaller, it can still do more than 611 00:34:26,180 --> 00:34:28,740 10,000 operations a second. 612 00:34:28,740 --> 00:34:32,580 That allows Nielsen to calculate his nationwide ratings data 613 00:34:32,580 --> 00:34:35,040 at the kind of scale and speed he needs 614 00:34:35,040 --> 00:34:37,290 once he gets into the much bigger and more complicated 615 00:34:37,290 --> 00:34:38,793 TV ratings market. 616 00:34:41,640 --> 00:34:43,980 Thanks to the computer, Nielsen can process 617 00:34:43,980 --> 00:34:46,740 a statistical technique that allows, for instance, 618 00:34:46,740 --> 00:34:50,730 a car manufacturer to find customers who will watch their ad 619 00:34:50,730 --> 00:34:52,800 and likely buy the car they make, 620 00:34:52,800 --> 00:34:55,593 so they can aim their ads only at them. 621 00:34:57,210 --> 00:34:59,253 You find your buyers like this. 622 00:35:00,210 --> 00:35:02,280 First, split potential consumers 623 00:35:02,280 --> 00:35:06,150 between those upper income and those not. 624 00:35:06,150 --> 00:35:07,650 Then of the upper income, 625 00:35:07,650 --> 00:35:10,620 between those who buy cars and those not. 626 00:35:10,620 --> 00:35:15,620 Then of car buyers, those who buy sports cars and those not. 627 00:35:15,810 --> 00:35:17,370 Then of sports car buyers, 628 00:35:17,370 --> 00:35:21,210 those who buy classic styles and those not. 629 00:35:21,210 --> 00:35:22,620 Then of classic buyers, 630 00:35:22,620 --> 00:35:26,370 those who go for stick shift and those not. 631 00:35:26,370 --> 00:35:28,230 Then of those stick shift users, 632 00:35:28,230 --> 00:35:31,620 those who prefer Italian and those not. 633 00:35:31,620 --> 00:35:35,010 This final set is your target sample. 634 00:35:35,010 --> 00:35:37,713 Rich and likely to buy your product. 635 00:35:39,630 --> 00:35:42,780 This statistical process giving you this information 636 00:35:42,780 --> 00:35:45,630 looks like branches and twigs and leaves on a tree, 637 00:35:45,630 --> 00:35:48,540 and it's called a decision tree. 638 00:35:48,540 --> 00:35:50,880 And if you go back to your starting population sample 639 00:35:50,880 --> 00:35:54,180 and change the conditions of their choice in some way, 640 00:35:54,180 --> 00:35:55,920 you can then go back to your tree 641 00:35:55,920 --> 00:35:58,890 and see how the final leaf ends up different. 642 00:35:58,890 --> 00:36:01,740 And if your search involves a really complex issue 643 00:36:01,740 --> 00:36:04,650 and a really big population, you can use several trees 644 00:36:04,650 --> 00:36:07,980 at once in what statisticians call, what else, 645 00:36:07,980 --> 00:36:09,813 a decision forest. 646 00:36:12,840 --> 00:36:15,630 Computing gives Nielsen the kind of capabilities 647 00:36:15,630 --> 00:36:17,223 nobody's ever had before. 648 00:36:18,150 --> 00:36:21,660 Above all, the means to analyze from his radio's data 649 00:36:21,660 --> 00:36:24,600 much more detailed stuff about TV viewers. 650 00:36:24,600 --> 00:36:27,420 And a few other things regarding what any retail product 651 00:36:27,420 --> 00:36:30,183 ought to be if he wants to sell to those people. 652 00:36:31,095 --> 00:36:32,670 But now it's easy. 653 00:36:32,670 --> 00:36:36,270 And what kind of pictures and words might help to sell it. 654 00:36:36,270 --> 00:36:39,750 As a consequence, the shape of TV programming changes 655 00:36:39,750 --> 00:36:42,630 to boost revenues by matching advertising spots 656 00:36:42,630 --> 00:36:44,490 with the most popular shows. 657 00:36:44,490 --> 00:36:48,300 So first of all, the radio soaps moving to television. 658 00:36:48,300 --> 00:36:52,893 And sure enough, TV soaps get giant audiences. 659 00:36:54,990 --> 00:36:58,740 So how is all of this leading us to a future 660 00:36:58,740 --> 00:37:01,023 where machines predict the future? 661 00:37:02,310 --> 00:37:03,760 Let's see how far we've come. 662 00:37:07,500 --> 00:37:10,290 Napoleon's banishment and his furniture, 663 00:37:10,290 --> 00:37:13,320 hummingbirds, the Wardian Case, 664 00:37:13,320 --> 00:37:16,772 Chinese tea, Holt's new ship engine, 665 00:37:16,772 --> 00:37:20,730 palm oil, Lever's palm oil soap, 666 00:37:20,730 --> 00:37:23,100 and the radio and TV soap operas, 667 00:37:23,100 --> 00:37:26,310 Nielsen's need to get TV and radio audience numbers 668 00:37:26,310 --> 00:37:28,137 triggers the Audimeter. 669 00:37:28,980 --> 00:37:31,350 Really big number audience data takes Nielsen 670 00:37:31,350 --> 00:37:34,200 to the new World War II computer 671 00:37:34,200 --> 00:37:38,160 and how computing helps to operate the vast decision tree 672 00:37:38,160 --> 00:37:40,113 that shows you who's going to buy what. 673 00:37:44,250 --> 00:37:45,720 And here's where it gets into more than 674 00:37:45,720 --> 00:37:47,133 advertising and sales. 675 00:37:50,289 --> 00:37:51,720 When Nielsen gets his computer, 676 00:37:51,720 --> 00:37:53,970 a similar computing machine gets used 677 00:37:53,970 --> 00:37:56,553 in the 1952 Presidential elections. 678 00:37:57,570 --> 00:38:00,600 This machine calculates the early vote return numbers 679 00:38:00,600 --> 00:38:05,433 and predicts Eisenhower's win with 99% accuracy. 680 00:38:07,890 --> 00:38:10,380 So amazing and unbelievable, 681 00:38:10,380 --> 00:38:13,041 TV people didn't want to put the prediction on air. 682 00:38:17,640 --> 00:38:20,580 We are now well on our way to a future 683 00:38:20,580 --> 00:38:22,080 where we can predict anything. 684 00:38:25,834 --> 00:38:30,834 Today, we can replicate all 30 tons on a chip 685 00:38:32,460 --> 00:38:33,633 the size of a pinhead. 686 00:38:34,500 --> 00:38:36,360 One of the most powerful super computers 687 00:38:36,360 --> 00:38:41,340 using that technology is now the size of two tennis courts. 688 00:38:41,340 --> 00:38:43,200 We're able routinely to use computers 689 00:38:43,200 --> 00:38:45,900 to forecast events immensely more complex 690 00:38:45,900 --> 00:38:47,463 than any presidential election. 691 00:38:50,610 --> 00:38:53,160 We use them to predict one of the most intricate 692 00:38:53,160 --> 00:38:55,140 and complex activities happening every day 693 00:38:55,140 --> 00:38:57,000 in the natural world, 694 00:38:57,000 --> 00:38:59,250 one that changes in thousands of ways 695 00:38:59,250 --> 00:39:02,253 simultaneously every second, the weather. 696 00:39:03,720 --> 00:39:06,390 A huge amount of variables need to be factored in 697 00:39:06,390 --> 00:39:09,390 to get anything like a reliable weather forecast, 698 00:39:09,390 --> 00:39:12,270 wind speeds, air pressures, surface temperatures, 699 00:39:12,270 --> 00:39:14,730 sea temperature, weather events in other countries, 700 00:39:14,730 --> 00:39:16,023 on other continents. 701 00:39:17,010 --> 00:39:20,640 Predicting human behavior is even more complex 702 00:39:20,640 --> 00:39:22,263 and needs even more data. 703 00:39:23,790 --> 00:39:25,500 But of course with super computing, 704 00:39:25,500 --> 00:39:29,010 we've arrived at the amount of data available today so big 705 00:39:29,010 --> 00:39:31,233 that we call it big data. 706 00:39:33,600 --> 00:39:37,230 Big data gives a whole new meaning to what you can do 707 00:39:37,230 --> 00:39:38,230 when you know a lot. 708 00:39:41,280 --> 00:39:44,520 Which means that at any stage of analyzing old populations 709 00:39:44,520 --> 00:39:46,410 and their likes and dislikes, 710 00:39:46,410 --> 00:39:49,020 you can take into account the colossal number 711 00:39:49,020 --> 00:39:51,990 of interactions among everybody in a population 712 00:39:51,990 --> 00:39:55,053 when it comes to any issue right now. 713 00:39:57,450 --> 00:40:00,240 Each person chooses their own path in life, 714 00:40:00,240 --> 00:40:02,700 and for the first time, we may soon be able 715 00:40:02,700 --> 00:40:05,670 to take every one of those choices into account 716 00:40:05,670 --> 00:40:08,810 in a way we'll use the data to shape the future. 717 00:40:09,830 --> 00:40:11,430 The data's all there to analyze. 718 00:40:12,330 --> 00:40:14,460 With every computer keyboard click, 719 00:40:14,460 --> 00:40:17,733 we're already able to collect data on everything you buy, 720 00:40:19,680 --> 00:40:23,160 details on money activity, your travel, your shoe size, 721 00:40:23,160 --> 00:40:26,640 health, medication, medical history, birth place, 722 00:40:26,640 --> 00:40:30,390 gender, marital status, social status, children, 723 00:40:30,390 --> 00:40:33,870 family structure, insurance, age, income, 724 00:40:33,870 --> 00:40:38,190 use of car, kind of car, use of buses, train journeys, 725 00:40:38,190 --> 00:40:41,370 flights, commuting schedule, what you eat, 726 00:40:41,370 --> 00:40:43,740 TV radio and music program choices, 727 00:40:43,740 --> 00:40:45,810 your favorite papers and magazines, 728 00:40:45,810 --> 00:40:49,770 your education, job, hobbies, residence and location, 729 00:40:49,770 --> 00:40:52,950 friends social life, languages, favorite music, 730 00:40:52,950 --> 00:40:55,680 sports, clubs, spare time activities, 731 00:40:55,680 --> 00:40:58,680 religious beliefs, events you attend, your ethnicity, 732 00:40:58,680 --> 00:41:02,040 personal grooming, pets, sweet tooth, sexual activities, 733 00:41:02,040 --> 00:41:06,630 skills, financial worth, investments, and everything else. 734 00:41:06,630 --> 00:41:08,880 It's called data exhaust, 735 00:41:08,880 --> 00:41:11,820 and it has supplied us with more information 736 00:41:11,820 --> 00:41:15,960 than Nielsen ever dreamt of about each and every choice 737 00:41:15,960 --> 00:41:17,823 we make every day. 738 00:41:19,290 --> 00:41:23,070 What if all these decisions could be fed into a machine 739 00:41:23,070 --> 00:41:25,500 that could process this astronomical amount of data 740 00:41:25,500 --> 00:41:28,080 and predict all possible outcomes 741 00:41:28,080 --> 00:41:30,480 to tell you which was most likely, 742 00:41:30,480 --> 00:41:32,030 just like the weather forecast. 743 00:41:33,420 --> 00:41:35,310 We've reached our destination, 744 00:41:35,310 --> 00:41:37,260 one which I believe will move this possibility 745 00:41:37,260 --> 00:41:41,245 from the realms of sci-fi into reality. 746 00:41:49,110 --> 00:41:52,053 A quantum computer that can predict the future. 747 00:41:55,590 --> 00:41:58,050 Apparently in its infancy, this technology 748 00:41:58,050 --> 00:41:59,800 will revolutionize the way we live. 749 00:42:01,320 --> 00:42:03,990 Now there are two ways to explain a quantum computer. 750 00:42:03,990 --> 00:42:06,540 One is a four year degree course in physics 751 00:42:06,540 --> 00:42:08,973 and the other now takes less time. 752 00:42:11,010 --> 00:42:13,980 So, an ordinary classical computer calculates 753 00:42:13,980 --> 00:42:17,850 using zeros and ones, or an electrical current on or off. 754 00:42:17,850 --> 00:42:20,820 This is what's called a binary system. 755 00:42:20,820 --> 00:42:24,300 Each binary number is called a bit. 756 00:42:24,300 --> 00:42:28,170 So two bits can represent four numbers, 757 00:42:28,170 --> 00:42:32,883 zero zero, zero one, one zero, and one one. 758 00:42:33,990 --> 00:42:38,313 A group of eight bits can therefore represent 256 numbers. 759 00:42:39,180 --> 00:42:41,490 Instead of using tiny electrical switches, 760 00:42:41,490 --> 00:42:43,980 like a classical computer uses for each bit, 761 00:42:43,980 --> 00:42:47,190 a quantum computer uses subatomic particles, 762 00:42:47,190 --> 00:42:50,070 like photons, to calculate numbers. 763 00:42:50,070 --> 00:42:52,530 These are called Qubits, 764 00:42:52,530 --> 00:42:54,660 and they can represent zero and one, 765 00:42:54,660 --> 00:42:56,340 but both at the same time. 766 00:42:56,340 --> 00:42:57,840 Take my word for that. 767 00:42:57,840 --> 00:43:00,540 They can also represent an almost infinite number 768 00:43:00,540 --> 00:43:02,853 of positions between the zero and the one. 769 00:43:03,690 --> 00:43:07,113 So a group of several Qubits can handle enormous numbers. 770 00:43:08,220 --> 00:43:12,058 A quantum computer with 400 Qubits could handle a number 771 00:43:12,058 --> 00:43:15,213 bigger than all the atoms in the universe. 772 00:43:18,360 --> 00:43:21,360 So, if you're working in retail and you want to predict 773 00:43:21,360 --> 00:43:23,550 your next big seller, you need to take 774 00:43:23,550 --> 00:43:26,520 many, many different scenarios into account 775 00:43:26,520 --> 00:43:27,870 and then find the best one. 776 00:43:28,980 --> 00:43:33,120 Or you want to enact a war game, see how a future conflict 777 00:43:33,120 --> 00:43:35,643 might go without firing a single shot. 778 00:43:36,870 --> 00:43:38,790 Now this is something that a quantum computer 779 00:43:38,790 --> 00:43:41,490 is better for because it allows you to calculate 780 00:43:41,490 --> 00:43:42,940 many things at the same time. 781 00:43:44,880 --> 00:43:47,910 So once we're able to build a 400 Qubit computer, 782 00:43:47,910 --> 00:43:49,650 likely in the next few years, 783 00:43:49,650 --> 00:43:51,480 handling the small matter of all the actions 784 00:43:51,480 --> 00:43:53,640 and interactions of everybody on Earth 785 00:43:53,640 --> 00:43:55,500 and predicting what's coming at every split second 786 00:43:55,500 --> 00:43:57,840 and every point in the future for all of us 787 00:43:57,840 --> 00:43:59,343 will be a snip. 788 00:44:00,570 --> 00:44:02,220 The machine will know the consequence 789 00:44:02,220 --> 00:44:04,983 of any decision you take before you take it. 790 00:44:07,500 --> 00:44:11,040 On a planet-wide scale, this ongoing ability 791 00:44:11,040 --> 00:44:13,680 will give us control over everything. 792 00:44:13,680 --> 00:44:16,530 We'll be able to plan everything in real time 793 00:44:16,530 --> 00:44:19,863 in every detail for every adult on the planet. 794 00:44:21,990 --> 00:44:23,700 It doesn't feel like free will 795 00:44:23,700 --> 00:44:26,190 or personal liberty to choose your individual direction 796 00:44:26,190 --> 00:44:27,303 in life, does it? 797 00:44:28,410 --> 00:44:31,811 The old autonomous freedom of action to shape our lives 798 00:44:31,811 --> 00:44:35,403 that we've enjoyed for thousands of years. 799 00:44:39,750 --> 00:44:41,700 But maybe that's just the old out-of-date way 800 00:44:41,700 --> 00:44:44,643 we used to do things before the quantum computer. 801 00:44:47,190 --> 00:44:50,653 Maybe we need to learn how to live in a world 802 00:44:50,653 --> 00:44:52,803 where there are no more surprises. 802 00:44:53,305 --> 00:45:53,659 Watch Online Movies and Series for FREE www.osdb.link/lm