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These are the user uploaded subtitles that are being translated: 1 00:00:00,000 --> 00:00:02,300 wasn't just confident, he was impatient. 2 00:00:02,840 --> 00:00:07,260 When the recruiter asked for his thoughts on the firm, Larry didn't give 3 00:00:07,260 --> 00:00:08,920 you, he gave a consultation. 4 00:00:09,520 --> 00:00:11,800 He pointed out the flaws in their system. 5 00:00:12,180 --> 00:00:14,160 At Goldman, they wanted a soldier. 6 00:00:14,660 --> 00:00:17,300 Larry was already acting like a general. 7 00:00:21,160 --> 00:00:26,040 In that room, the rigid Goldman way clashed with the unfiltered Fink way. 8 00:00:26,640 --> 00:00:30,980 Before he could even hail a cab back to his hotel, The offer was dead. 9 00:00:31,540 --> 00:00:36,760 The most coveted job in Wall Street history had vanished, all because Larry 10 00:00:36,760 --> 00:00:41,200 couldn't stop himself from trying to fix a system he hadn't even joined yet. 11 00:00:41,580 --> 00:00:43,220 It was a crushing blow. 12 00:00:43,860 --> 00:00:48,820 But in the shadow of that rejection, the door opened at a scrappy second -tier 13 00:00:48,820 --> 00:00:50,320 firm called First Boston. 14 00:00:50,640 --> 00:00:54,420 It was a place with less prestige, but more white space. 15 00:00:55,160 --> 00:00:58,840 At Goldman, he would have been a cog in a perfect machine. 16 00:00:59,550 --> 00:01:01,770 At First Boston, he was the architect. 17 00:01:02,170 --> 00:01:06,910 He was given a desk, a telephone, and the freedom to build something entirely 18 00:01:06,910 --> 00:01:09,570 new, the mortgage -backed security. 19 00:01:10,210 --> 00:01:15,070 He didn't know it yet, but that recruiters know was the foundation upon 20 00:01:15,070 --> 00:01:18,950 the $14 trillion empire of BlackRock would be built. 21 00:01:26,670 --> 00:01:30,650 It's 1976 when Larry Fink arrives at First Boston. 22 00:01:30,970 --> 00:01:35,250 At the time, the firm was the scrappy underdog of investment banking. 23 00:01:35,610 --> 00:01:40,110 It wasn't as stiff as Morgan Stanley or as elitist as Goldman. 24 00:01:40,570 --> 00:01:44,430 It was the perfect laboratory for a man who didn't fit the mold. 25 00:01:45,250 --> 00:01:47,470 Larry was assigned to the bond department. 26 00:01:48,050 --> 00:01:51,850 Back then, bonds were considered the boring corner of finance. 27 00:01:52,370 --> 00:01:54,330 It was where you went to retire. 28 00:01:55,130 --> 00:02:00,910 Stocks were sexy, bonds were for grandmothers, but Larry saw something 29 00:02:00,910 --> 00:02:01,910 else missed. 30 00:02:02,730 --> 00:02:08,350 He looked at the American dream, the suburban house, the white picket fence, 31 00:02:08,350 --> 00:02:11,410 30 -year mortgage, and he saw a math problem. 32 00:02:12,090 --> 00:02:16,950 He realized that if you took thousands of individual home mortgages, bundled 33 00:02:16,950 --> 00:02:21,290 them together like a deck of cards, and sold slices of that deck to investors, 34 00:02:21,410 --> 00:02:23,590 you created a money machine. 35 00:02:24,620 --> 00:02:28,000 This was the birth of the securitization market. 36 00:02:28,760 --> 00:02:32,860 What Larry Fink helped create was more than a financial product. 37 00:02:33,180 --> 00:02:35,120 It was a structural shift. 38 00:02:38,120 --> 00:02:40,900 Securitization didn't just bundle mortgages. 39 00:02:41,140 --> 00:02:43,580 It separated risk from reality. 40 00:02:44,120 --> 00:02:48,780 For the first time, financial value could travel faster than the underlying 41 00:02:48,780 --> 00:02:50,460 economy that supported it. 42 00:02:51,150 --> 00:02:55,990 A house in California became a line in a spreadsheet in New York, which became a 43 00:02:55,990 --> 00:02:58,250 yield sold to an investor in Tokyo. 44 00:02:59,010 --> 00:03:01,930 Risk no longer lived where decisions were made. 45 00:03:02,310 --> 00:03:07,350 It was abstracted, sliced, repackaged, and distributed across the system. 46 00:03:07,830 --> 00:03:12,450 This was the moment when finance stopped reflecting the real economy and began 47 00:03:12,450 --> 00:03:14,070 building a parallel one. 48 00:03:14,490 --> 00:03:19,270 A system that could grow without limits, as long as everyone believed the models 49 00:03:19,270 --> 00:03:20,270 were right. 50 00:03:20,440 --> 00:03:22,260 And for a while, they were. 51 00:03:23,520 --> 00:03:26,620 By the early 80s, Larry was the golden ball. 52 00:03:26,900 --> 00:03:29,960 He wasn't just hitting targets, he was chattering them. 53 00:03:30,300 --> 00:03:34,660 In one year, his department was responsible for nearly one -third of 54 00:03:34,660 --> 00:03:36,120 Boston's total profits. 55 00:03:36,580 --> 00:03:42,300 At age 31, he became the youngest managing director the firm had ever 56 00:03:42,300 --> 00:03:43,300 was earning millions. 57 00:03:43,460 --> 00:03:47,660 He was the successor, the prodigy, the man who could do no wrong. 58 00:03:48,360 --> 00:03:51,020 He had moved to his family through a sprawling estate. 59 00:03:51,280 --> 00:03:52,800 He was flying private. 60 00:03:53,180 --> 00:03:56,380 He had conquered the grip -cover battlefield of Manhattan. 61 00:03:59,140 --> 00:04:03,940 But in the world of high finance, the higher you fly, the thinner the air 62 00:04:03,940 --> 00:04:04,940 becomes. 63 00:04:08,340 --> 00:04:12,960 Larry was making hundreds of millions for the bank, but there was a ghost in 64 00:04:12,960 --> 00:04:16,399 machine, a variable he hadn't accounted for. 65 00:04:17,100 --> 00:04:18,579 The year was 1986. 66 00:04:19,380 --> 00:04:22,200 Larry had made a massive bet on interest rates. 67 00:04:22,700 --> 00:04:25,000 He believed they would stay stable. 68 00:04:25,600 --> 00:04:30,500 He was so sure of his math, so confident in his track record, that he didn't 69 00:04:30,500 --> 00:04:33,120 realize the ground was shifting beneath his feet. 70 00:04:34,180 --> 00:04:38,640 In just three months, the Golden Boys department went from profit to a 71 00:04:38,640 --> 00:04:41,120 catastrophic $100 million loss. 72 00:04:41,780 --> 00:04:45,060 In the 80s, $100 million wasn't just a loss. 73 00:04:45,500 --> 00:04:46,720 It was a national scandal. 74 00:04:47,820 --> 00:04:52,380 Overnight, the man who was supposed to run the bank was a pariah. The phones 75 00:04:52,380 --> 00:04:53,199 stopped ringing. 76 00:04:53,200 --> 00:04:56,620 The friends on the trading floor looked away when he walked by. 77 00:04:57,000 --> 00:05:00,720 He had been the smartest man in the room until he wasn't. 78 00:05:01,400 --> 00:05:05,880 He would later describe this moment as the most painful experience of my life. 79 00:05:06,540 --> 00:05:09,120 But as he sat in the ruins of his reputation, 80 00:05:09,840 --> 00:05:14,540 Larry Fink wasn't just mourning his career. He was obsessed with one 81 00:05:15,470 --> 00:05:17,470 How did I not see the risk? 82 00:05:18,210 --> 00:05:23,410 That obsession, the fear of the unknown variable, would become the cornerstone 83 00:05:23,410 --> 00:05:24,430 of BlackRock. 84 00:05:29,830 --> 00:05:35,870 By 1983, Larry wasn't just selling bonds, he was a pioneer of the CMOs, 85 00:05:36,050 --> 00:05:38,610 Collateralized Mortgage Obligation. 86 00:05:40,790 --> 00:05:42,590 Think of it like a waterfall. 87 00:05:43,260 --> 00:05:46,880 Larry took thousands of mortgages and sliced them into tranches. 88 00:05:47,380 --> 00:05:51,320 Some investors took the top slice, low risk, low reward. 89 00:05:51,580 --> 00:05:54,740 Others took the bottom, high risk, high yield. 90 00:05:55,080 --> 00:05:57,600 It was a masterpiece of financial engineering. 91 00:05:58,000 --> 00:06:00,160 It made the illiquid liquid. 92 00:06:00,600 --> 00:06:04,100 It made First Boston the center of the universe. 93 00:06:05,660 --> 00:06:10,160 But there was a flaw, a tiny mathematical ghost in his models. 94 00:06:11,030 --> 00:06:15,530 Larry's team had predicted the interest rates would rise, and they hedged their 95 00:06:15,530 --> 00:06:16,530 bets accordingly. 96 00:06:16,810 --> 00:06:21,870 But in the second quarter of 1986, rates did something the models said was 97 00:06:21,870 --> 00:06:24,010 impossible. They plummeted. 98 00:06:24,670 --> 00:06:29,190 Because they didn't have a system to track their real -time exposure, Larry 99 00:06:29,190 --> 00:06:30,190 climbed blind. 100 00:06:30,250 --> 00:06:36,050 He was the pilot of a Boeing 747, trying to land in a storm using nothing but a 101 00:06:36,050 --> 00:06:37,250 compass and a prayer. 102 00:06:37,950 --> 00:06:42,230 By the time he realized the engines were on fire, the plane had already hit the 103 00:06:42,230 --> 00:06:44,730 mountain. 100 million dollars. 104 00:06:45,190 --> 00:06:46,250 All gone. 105 00:06:50,730 --> 00:06:53,570 He wasn't just fired, he was a rave. 106 00:06:54,070 --> 00:06:58,570 After the dust settled, Larry found himself in a peculiar kind of exile. 107 00:06:58,950 --> 00:07:01,790 He wasn't just unemployed, he was haunted. 108 00:07:02,150 --> 00:07:06,630 He realized that the 100 million dollar loss wasn't a failure of talent. 109 00:07:07,040 --> 00:07:08,580 It was a failure of vision. 110 00:07:09,000 --> 00:07:14,900 What happened in 1986 wasn't a personal miscalculation. It was a systemic 111 00:07:14,900 --> 00:07:15,900 blindness. 112 00:07:16,460 --> 00:07:21,640 At the time, every major financial institution operated the same way. 113 00:07:22,040 --> 00:07:23,540 Positions were fragmented. 114 00:07:24,240 --> 00:07:26,560 Exposure was estimated, not measured. 115 00:07:26,800 --> 00:07:29,320 Risk was inferred after the fact. 116 00:07:29,760 --> 00:07:34,240 Banks knew what they bought yesterday, but not what it was worth right now. 117 00:07:34,830 --> 00:07:39,370 The system rewarded speed, volume, and confidence, not understanding. 118 00:07:39,870 --> 00:07:43,250 And as long as markets moved slowly, the illusion held. 119 00:07:43,850 --> 00:07:48,330 But once volatility entered the market, no one truly knew where the danger was, 120 00:07:48,630 --> 00:07:50,750 or how large it had become. 121 00:07:51,730 --> 00:07:56,630 Larry didn't just lose money. He realized the entire financial system was 122 00:07:56,630 --> 00:07:57,630 without instruments. 123 00:07:58,370 --> 00:08:01,910 Wall Street was essentially a collection of blind giants. 124 00:08:02,390 --> 00:08:03,950 Every major firm. 125 00:08:04,400 --> 00:08:09,580 Goldman, Lehman, Merrill Lynch were standing just one inch away from total 126 00:08:09,580 --> 00:08:11,680 collapse at any given second. 127 00:08:12,240 --> 00:08:16,080 Why? Because they didn't actually know what they owned. 128 00:08:16,520 --> 00:08:18,920 This was information blindness. 129 00:08:20,900 --> 00:08:26,040 In the 1980s, you knew what you bought yesterday, but you had no idea what it 130 00:08:26,040 --> 00:08:27,180 was worth right now. 131 00:08:27,560 --> 00:08:33,220 A sudden shift in interest rates, or a political coup across the ocean, could 132 00:08:33,220 --> 00:08:36,919 vaporize a billion dollars before the morning coffee was poured. 133 00:08:38,600 --> 00:08:41,140 Larry understood a terrifying truth. 134 00:08:41,539 --> 00:08:46,960 The entire global financial system was built on a foundation of guesswork. 135 00:08:47,800 --> 00:08:50,620 It hit him with the force of an epiphany. 136 00:08:51,100 --> 00:08:55,880 If he could build a brain, a machine that could see the risk that humans were 137 00:08:55,880 --> 00:08:58,940 too slow to calculate, he wouldn't just be a banker. 138 00:08:59,630 --> 00:09:03,990 He would be the only man in the world with a flashlight in a dark room. 139 00:09:04,530 --> 00:09:08,550 This realization changed his entire philosophy of investing. 140 00:09:09,110 --> 00:09:13,610 He stopped looking for the big score and started looking for the safe passage. 141 00:09:13,870 --> 00:09:18,510 He didn't want to beat the market anymore. He wanted to measure it. 142 00:09:20,290 --> 00:09:24,830 He would later tell his partners, we are never going to be blind again. 143 00:09:25,900 --> 00:09:31,900 That vow, born from the humiliation of 1986, became the blueprint for a new 144 00:09:31,900 --> 00:09:37,880 of firm, a firm that didn't rely on the ego of a star trader, but on the cold, 145 00:09:37,960 --> 00:09:39,460 unblinking eye of technology. 146 00:09:46,740 --> 00:09:52,100 Larry Fink was a man with a vision, but he was also a man with a tainted resume. 147 00:09:52,640 --> 00:09:56,330 To the rest of Wall Street, He was the guy who lost 100 million. 148 00:09:56,750 --> 00:10:02,190 But to a small circle of insiders at First Boston, he was the only one who 149 00:10:02,190 --> 00:10:04,090 understood why it happened. 150 00:10:04,670 --> 00:10:06,390 He began making calls. 151 00:10:06,830 --> 00:10:09,990 He wasn't offering high salaries or flashy offices. 152 00:10:10,370 --> 00:10:15,250 He was offering a chance to build a holy grail, a financial firm where 153 00:10:15,250 --> 00:10:18,610 technology governed the ego, not the other way around. 154 00:10:19,260 --> 00:10:23,900 and he eventually found the right people to help him build that holy grail. 155 00:10:26,820 --> 00:10:29,720 Rob Capito, the enforcer. 156 00:10:29,940 --> 00:10:34,680 A powerhouse trader who knew the plumbing of the bond market better than 157 00:10:34,680 --> 00:10:39,000 else. He provided the muscle Larry needed to execute the vision. 158 00:10:39,720 --> 00:10:45,120 Ben Golub, the oracle. A PhD with a mind like a supercomputer. 159 00:10:46,120 --> 00:10:50,800 While other bankers were focused on lunch reservations, Golub was thinking 160 00:10:50,800 --> 00:10:53,440 value at risk and Monte Carlo simulations. 161 00:10:55,040 --> 00:10:58,060 Susan Wagner, the mastermind. 162 00:10:58,660 --> 00:11:03,280 Brilliant, calculating, and capable of seeing structural flaws in a multi 163 00:11:03,280 --> 00:11:06,360 -billion dollar merger before a single paper was signed. 164 00:11:06,680 --> 00:11:11,180 Along with Barbara Novick, Ralph Schlossstein, Chew Freighter, and Keith 165 00:11:11,180 --> 00:11:13,940 Anderson, they became the original eight. 166 00:11:14,700 --> 00:11:18,800 Fink wasn't looking for bankers who would run after the money. He wanted 167 00:11:18,800 --> 00:11:22,260 architects, people who were tired of being blind. 168 00:11:23,380 --> 00:11:26,780 When he found them, they met in living rooms and coffee shops. 169 00:11:27,420 --> 00:11:33,020 They had the blueprints for a system they called Aladdin, an acronym for 170 00:11:33,040 --> 00:11:36,880 Liability, Debt and Derivative Investment Network. 171 00:11:37,600 --> 00:11:42,500 It was designed to be the unblinking eye Larry had dreamed of in his exile. 172 00:11:43,500 --> 00:11:45,980 But a brain without a body is just a dream. 173 00:11:46,460 --> 00:11:50,560 To build Aladdin, they needed hardware. They needed offices. 174 00:11:51,060 --> 00:11:55,720 And most importantly, they needed the one thing Larry's reputation had cost 175 00:11:56,060 --> 00:12:01,060 Capital. Aladdin was not designed to beat the market. It was designed to 176 00:12:01,060 --> 00:12:05,760 understand it. But its real power emerged when others started using it. 177 00:12:06,240 --> 00:12:11,720 Banks, insurance companies, pension funds, sovereign institutions. 178 00:12:12,590 --> 00:12:15,190 As Aladdin spread, something subtle happened. 179 00:12:15,670 --> 00:12:17,650 Risk stopped being subjective. 180 00:12:18,170 --> 00:12:19,610 It became standardized. 181 00:12:20,250 --> 00:12:25,650 When Aladdin flagged an asset as dangerous, entire markets adjusted 182 00:12:27,850 --> 00:12:32,650 Not because Larry Fink said so, but because the system trusted the models. 183 00:12:32,990 --> 00:12:36,570 At that point, BlackRock was no longer just managing money. 184 00:12:36,810 --> 00:12:40,130 It was helping define how risk itself was understood. 185 00:12:40,920 --> 00:12:44,900 And whoever defines risk defines the boundaries of decision -making. 186 00:12:55,220 --> 00:13:01,300 Enter Stephen Schwarzman. In 1988, Schwarzman was the rising king of 187 00:13:01,300 --> 00:13:05,940 equity. His firm, Blackstone, was aggressive, wealthy, and hungry. 188 00:13:07,460 --> 00:13:08,860 The meeting was tense. 189 00:13:09,530 --> 00:13:13,910 Schwarzman knew Larry's history. He knew about the 1986 disaster. 190 00:13:14,770 --> 00:13:19,670 But Larry didn't hide from it. He used it as his primary selling point. 191 00:13:20,550 --> 00:13:25,210 Because Larry had seen the end of the world already, he knew exactly how the 192 00:13:25,210 --> 00:13:29,510 lights went out. And because of that, he was the only one who knew how to keep 193 00:13:29,510 --> 00:13:30,510 them on. 194 00:13:31,570 --> 00:13:33,370 Larry's pitch was revolutionary. 195 00:13:33,870 --> 00:13:38,430 He didn't want to start a hedge fund. He wanted to create a fiduciary company. 196 00:13:39,150 --> 00:13:43,370 a firm that managed other people's money with the same technological rigour 197 00:13:43,370 --> 00:13:44,910 usually reserved for NASA. 198 00:13:45,770 --> 00:13:49,650 He asked for a $5 million credit line and a partnership. 199 00:13:50,010 --> 00:13:54,070 In exchange, Schwarzman would own 50 % of the new venture. 200 00:13:54,450 --> 00:13:58,650 He knew he was buying cheap because he was buying on a distressed asset. 201 00:13:59,010 --> 00:14:00,630 Fink's damaged reputation. 202 00:14:01,710 --> 00:14:06,290 But he did so betting on the idea that the experience had turned Larry Fink 203 00:14:06,290 --> 00:14:08,070 some sort of financial genius. 204 00:14:10,570 --> 00:14:11,690 The deal was done. 205 00:14:12,190 --> 00:14:17,650 On a Friday in March 1988, the team moved into a single cramped room within 206 00:14:17,650 --> 00:14:18,690 Blackstone's offices. 207 00:14:19,730 --> 00:14:24,650 They were five computers, a few folding chairs, and a mountain of cables on the 208 00:14:24,650 --> 00:14:29,750 floor. They were under the Blackstone umbrella, but Larry knew that this was 209 00:14:29,750 --> 00:14:30,930 just a temporary shelter. 210 00:14:31,170 --> 00:14:33,010 He didn't just want a department. 211 00:14:33,290 --> 00:14:34,910 He wanted an empire. 212 00:14:35,430 --> 00:14:40,560 He had the money. He had the team. And in the corner of that small room, The 213 00:14:40,560 --> 00:14:43,240 first lines of code for Aladdin were being written. 214 00:14:45,060 --> 00:14:50,440 The information blindness was over. The era of Black Rock, though it didn't have 215 00:14:50,440 --> 00:14:52,140 that name yet, had begun. 216 00:14:58,580 --> 00:15:03,160 The first office at Blackstone Financial Management wasn't a glass tower. 217 00:15:03,420 --> 00:15:05,320 It was a glorified closet. 218 00:15:06,000 --> 00:15:11,060 Because of the heat generated by the early Sun Microsystems workstations, the 219 00:15:11,060 --> 00:15:16,100 temperature in the room rarely dropped below 80 degrees, 27 degrees Celsius. 220 00:15:17,000 --> 00:15:21,440 While the rest of the Blackstone group went out at expensive lunches, closing 221 00:15:21,440 --> 00:15:26,640 leveraged buyers, Larry's original eight were building a digital fortress. 222 00:15:28,100 --> 00:15:30,260 They were the weirdos in the basement. 223 00:15:30,500 --> 00:15:33,940 It was here that the name Aladdin became a living thing. 224 00:15:34,650 --> 00:15:38,010 Every day, Ben Golub and his team fed it data. 225 00:15:38,230 --> 00:15:41,630 Interest rates, housing prices, historical crashes. 226 00:15:42,030 --> 00:15:46,590 They were teaching the machine to be afraid of everything Larry hadn't seen 227 00:15:46,590 --> 00:15:47,590 1986. 228 00:15:52,810 --> 00:15:57,850 By 1992, the department inside Blackstone was no longer a startup. 229 00:15:58,130 --> 00:15:59,470 It was a powerhouse. 230 00:16:00,050 --> 00:16:02,790 Larry's team was managing $17 billion. 231 00:16:04,460 --> 00:16:08,880 They weren't just a side project anymore. They were a significant engine 232 00:16:08,880 --> 00:16:09,880 Blackstone's growth. 233 00:16:10,060 --> 00:16:13,000 But with success came a toxic byproduct. 234 00:16:13,840 --> 00:16:14,900 Identity confusion. 235 00:16:16,000 --> 00:16:17,620 Clients were getting confused. 236 00:16:18,240 --> 00:16:22,800 They would call Blackstone looking for Larry's bond expertise or call Larry 237 00:16:22,800 --> 00:16:24,560 looking for Schwarzman's buyout. 238 00:16:24,880 --> 00:16:29,440 But the friction went deeper than a name. It was a war of philosophies. 239 00:16:29,860 --> 00:16:31,360 Schwarzman was a dealmaker. 240 00:16:31,660 --> 00:16:33,440 He wanted to own companies. 241 00:16:34,090 --> 00:16:38,130 Think was a fiduciary. He wanted to manage risk for others. 242 00:16:39,390 --> 00:16:44,570 The tension was similar to having two predators in a cage too small to fit 243 00:16:44,850 --> 00:16:46,990 The breaking point came over equity. 244 00:16:47,830 --> 00:16:52,250 Larry wanted to use stocks to attract and keep the original eight and new 245 00:16:52,250 --> 00:16:53,250 talent. 246 00:16:53,390 --> 00:16:57,630 Schwartzman, holding 50 % of the firm, didn't want to dilute his stake. 247 00:16:58,310 --> 00:17:02,390 The partnership that saved Larry's career was now suffocating his vision. 248 00:17:03,020 --> 00:17:05,460 In 1994, they reached a deal. 249 00:17:08,099 --> 00:17:11,839 Schwarzman agreed to sell Blackstone Stakes for $240 million. 250 00:17:12,660 --> 00:17:17,500 At the time, it seemed like a win for Schwarzman, a massive return on his $5 251 00:17:17,500 --> 00:17:18,619 million investment. 252 00:17:19,420 --> 00:17:22,260 It wasn't just about money, it was about the spotlight. 253 00:17:22,920 --> 00:17:27,880 Schwarzman was the king of Wall Street, but his sub -tenant, Larry Fink, was the 254 00:17:27,880 --> 00:17:30,020 one the New York Times wanted to interview. 255 00:17:30,400 --> 00:17:32,540 But for Larry, it was the price. 256 00:17:32,860 --> 00:17:38,500 for freedom schwartzman would later call selling black rock the worst mistake of 257 00:17:38,500 --> 00:17:44,080 my career for larry the divorce was the moment the training wheels came off he 258 00:17:44,080 --> 00:17:49,780 was no longer under anyone's umbrella he was the ceo of an independent firm now 259 00:17:49,780 --> 00:17:53,620 he just had to prove he could survive the coming storm of the late nineties 260 00:18:03,760 --> 00:18:05,040 It is 2008. 261 00:18:05,500 --> 00:18:08,660 The financial world was experiencing a heart attack. 262 00:18:09,060 --> 00:18:13,840 The financial smoothies that mortgage -backed securities Larry had helped 263 00:18:13,840 --> 00:18:16,980 30 years earlier had turned into a global poison. 264 00:18:17,620 --> 00:18:22,220 Banks didn't know what they owned. And more importantly, they didn't know what 265 00:18:22,220 --> 00:18:23,220 their neighbors owned. 266 00:18:23,380 --> 00:18:25,260 Trust had evaporated. 267 00:18:26,000 --> 00:18:30,040 When the U .S. government realized the economy was on the brink of a total 268 00:18:30,040 --> 00:18:32,640 blackout, they didn't call Goldman Sachs. 269 00:18:33,070 --> 00:18:34,810 They didn't call J .P. Morgan. 270 00:18:35,550 --> 00:18:40,390 While the CEOs of Lehman and Merrill were begging for government checks, 271 00:18:40,390 --> 00:18:43,430 Fink was the one the government called to write the checks. 272 00:18:44,490 --> 00:18:48,250 He was the only titan left standing with a clean balance sheet. 273 00:18:49,170 --> 00:18:53,590 The United States government didn't just seek advice, it delegated 274 00:18:53,590 --> 00:18:54,590 responsibility. 275 00:18:55,530 --> 00:19:00,650 BlackRock was tasked with valuing assets no one understood, managing risks no 276 00:19:00,650 --> 00:19:01,650 one could measure. 277 00:19:01,740 --> 00:19:04,800 and stabilizing markets that were collapsing real -time. 278 00:19:06,620 --> 00:19:08,420 This wasn't a bailout. 279 00:19:08,660 --> 00:19:11,700 It was an outsourcing of core sovereign functions. 280 00:19:12,100 --> 00:19:16,680 For the first time, a private firm played a central role in maintaining 281 00:19:16,680 --> 00:19:21,800 financial stability, not through political authority, but through 282 00:19:21,800 --> 00:19:22,800 capability. 283 00:19:23,260 --> 00:19:27,920 From that moment on, power was no longer just about laws and institutions. 284 00:19:28,750 --> 00:19:31,910 It was about who had the tools to see the system clearly. 285 00:19:33,550 --> 00:19:36,830 Blackbots were hired to manage the toxic waste of the crisis. 286 00:19:37,550 --> 00:19:43,390 They became the official cleaner for the US government, managing $130 billion of 287 00:19:43,390 --> 00:19:44,390 troubled assets. 288 00:19:46,910 --> 00:19:52,090 Suddenly, Larry Fink was the most powerful man in the room, acting as an 289 00:19:52,090 --> 00:19:53,810 to the President and the Treasury. 290 00:19:54,690 --> 00:19:59,390 But while he was saving the system, he saw a once -in -a -lifetime opportunity 291 00:19:59,390 --> 00:20:00,870 to dominate it. 292 00:20:01,230 --> 00:20:06,050 In the middle of the carnage, Barclays Bank in the UK was desperate for cash. 293 00:20:06,430 --> 00:20:10,830 They needed to sell their crown jewels, a division called Barclays Global 294 00:20:10,830 --> 00:20:15,150 Investors, which included a revolutionary product called iShares. 295 00:20:16,130 --> 00:20:21,590 iShares represented passive investing, ETFs that cracked the whole market 296 00:20:21,590 --> 00:20:22,730 than trying to beat it. 297 00:20:23,390 --> 00:20:26,090 It was the ultimate expression of Larry's philosophy. 298 00:20:26,960 --> 00:20:29,740 Stop betting on stars and start owning the system. 299 00:20:30,300 --> 00:20:34,340 It was a massive $13 .5 billion gamble. 300 00:20:35,120 --> 00:20:38,900 If the markets continued to fall, the deal could sink BlackRock. 301 00:20:39,380 --> 00:20:41,960 But Larry knew something the others didn't. 302 00:20:42,200 --> 00:20:47,180 He had looked into the eye of Aladdin, and Aladdin told him that the bottom was 303 00:20:47,180 --> 00:20:52,900 near. With the acquisition of iShares in 2009, BlackRock doubled its size 304 00:20:52,900 --> 00:20:55,940 overnight. They weren't just a bond shop anymore. 305 00:20:56,410 --> 00:20:59,710 They were now the largest money manager on the planet. 306 00:21:00,130 --> 00:21:05,610 They had gone into the crisis as a respective firm. They came out of it as 307 00:21:05,610 --> 00:21:07,310 shadow government of finance. 308 00:21:14,150 --> 00:21:17,390 By 2012, Larry Fink had built the machine. 309 00:21:17,790 --> 00:21:20,630 He had the assets, the data, and the influence. 310 00:21:21,050 --> 00:21:24,830 But he realized that being king of Wall Street wasn't enough. 311 00:21:25,680 --> 00:21:28,340 He wanted to change the way the world did business. 312 00:21:28,960 --> 00:21:33,660 Every January, a ritual began that would send tremors through boardrooms from 313 00:21:33,660 --> 00:21:34,920 Detroit to Frankfurt. 314 00:21:35,880 --> 00:21:37,400 Larry started writing letters. 315 00:21:37,680 --> 00:21:39,520 They weren't just annual reports. 316 00:21:39,920 --> 00:21:42,500 They were the BlackRock manifestos. 317 00:21:44,900 --> 00:21:47,860 In 2018, he dropped a bomb. 318 00:21:48,120 --> 00:21:52,720 He told the world's CEOs that if they wanted BlackRock's money, they had to 319 00:21:52,720 --> 00:21:54,820 prove they served a social purpose. 320 00:21:55,640 --> 00:21:59,540 He wasn't just asking for profits, he was asking for a soul. 321 00:22:00,080 --> 00:22:05,360 He was mainstreaming ESG, environmental, social and governance. 322 00:22:05,740 --> 00:22:09,560 And he was doing it with a $10 trillion hammer. 323 00:22:10,120 --> 00:22:13,540 But Larry's new gospel didn't sit well with everyone. 324 00:22:13,980 --> 00:22:19,220 By 2021, the golden boy was finding himself in the middle of a two -front 325 00:22:21,020 --> 00:22:23,680 The ESG debate was never cultural. 326 00:22:24,350 --> 00:22:25,350 It was economic. 327 00:22:25,830 --> 00:22:31,790 At its core, ESG was about risk management anticipating regulation, 328 00:22:31,790 --> 00:22:33,790 disruption and social instability. 329 00:22:34,830 --> 00:22:39,390 For BlackRock, ignoring those factors wasn't neutral. It was dangerous. 330 00:22:39,770 --> 00:22:44,430 But when capital begins to price the future, it also begins to shape it. 331 00:22:44,650 --> 00:22:47,010 That's why the backlash was so intense. 332 00:22:47,910 --> 00:22:50,630 To the left, Larry was a hypocrite. 333 00:22:50,940 --> 00:22:55,320 They called him a greenwasher because BlackRock still held billions in oil and 334 00:22:55,320 --> 00:22:56,259 gas stocks. 335 00:22:56,260 --> 00:23:00,840 To the right, he was a globalist villain who was using other people's money to 336 00:23:00,840 --> 00:23:02,980 push a radical environmental agenda. 337 00:23:03,500 --> 00:23:07,100 The backlash turned into a full -scale political assault. 338 00:23:09,520 --> 00:23:14,840 State treasurers in Florida, Texas and Mississippi began pulling billions out 339 00:23:14,840 --> 00:23:20,180 BlackRock. They accused Larry of boycotting energy and violating his duty 340 00:23:20,180 --> 00:23:21,180 investors. 341 00:23:21,680 --> 00:23:26,680 For the first time, the man who had mastered risk found himself in a risk he 342 00:23:26,680 --> 00:23:29,180 couldn't calculate, the culture war. 343 00:23:33,080 --> 00:23:37,520 He told a crowd in Aspen that he was ashamed to be a part of the debate. 344 00:23:37,720 --> 00:23:42,780 He even stopped using the term ESG altogether, calling it weaponized. 345 00:23:43,440 --> 00:23:45,840 He had tried to become the conscience of capitalism. 346 00:23:46,280 --> 00:23:49,360 Instead, he became its most controversial target. 347 00:23:49,780 --> 00:23:54,840 But even as the politicians shouted at the protesters' march, the assets kept 348 00:23:54,840 --> 00:23:55,840 growing. 349 00:23:57,700 --> 00:24:02,020 Because in the end, whether you loved him or hated him, you couldn't escape 350 00:24:02,020 --> 00:24:03,040 machine he built. 351 00:24:13,780 --> 00:24:15,220 January 2026. 352 00:24:15,600 --> 00:24:20,240 The number flashes on a terminal in BlackRock's Hudson Yards headquarters. 353 00:24:21,320 --> 00:24:22,460 $14 trillion. 354 00:24:23,460 --> 00:24:27,580 It is a number so vast it defies human comprehension. 355 00:24:28,300 --> 00:24:33,600 If Larry Fink's assets under management were a country's GDP, it would be the 356 00:24:33,600 --> 00:24:38,520 third largest economy on Earth, surpassed only by the United States and 357 00:24:39,280 --> 00:24:43,750 But as Larry looks out from his office, He isn't looking at stock tickets. 358 00:24:44,050 --> 00:24:47,090 He is looking at the very bones of civilization. 359 00:24:50,790 --> 00:24:55,670 In 2024, Larry made his final, most aggressive pivot. 360 00:24:56,130 --> 00:25:01,090 He realized that the next decade won't be one with bits on a screen, but with 361 00:25:01,090 --> 00:25:02,170 atoms in the ground. 362 00:25:02,570 --> 00:25:08,510 With the $12 .5 billion acquisition of global infrastructure partners, Larry 363 00:25:08,510 --> 00:25:11,030 signaled the end of the old Wall Street era. 364 00:25:11,580 --> 00:25:15,920 Larry saw the AI revolution coming, but he didn't buy the chip makers. 365 00:25:16,240 --> 00:25:19,300 He bought the power plants that feed the chips. 366 00:25:24,440 --> 00:25:28,060 But every empire faces the same inevitable question. 367 00:25:28,980 --> 00:25:29,980 Succession. 368 00:25:32,820 --> 00:25:37,500 For years, Wall Street has whispered about who could possibly replace the man 369 00:25:37,500 --> 00:25:38,980 who is Blackrock. 370 00:25:39,669 --> 00:25:44,650 Names like Rob Capito, Mark Weirman, and Jennifer Johnson swirl in the press. 371 00:25:44,890 --> 00:25:46,890 But the truth is more complex. 372 00:25:47,370 --> 00:25:50,730 Larry hasn't just built a company, he's built an organism. 373 00:25:51,030 --> 00:25:56,730 A system where Aladdin, now a very sophisticated AI entity, handles the 374 00:25:56,730 --> 00:26:00,590 while a legion of 20 ,000 employees executes the vision. 375 00:26:01,090 --> 00:26:03,470 Aladdin is no longer just a calculator. 376 00:26:03,870 --> 00:26:08,170 It is a predictive engine that runs millions of simulations every second. 377 00:26:08,590 --> 00:26:12,790 anticipating everything from a war in the Middle East to a crop failure in 378 00:26:12,790 --> 00:26:13,790 Brazil. 379 00:26:14,870 --> 00:26:17,030 Some call him the king of the world. 380 00:26:17,350 --> 00:26:19,750 Others call him the shadow architect. 381 00:26:20,450 --> 00:26:25,270 But if you ask Larry, he'll tell you he's still that kid from the Van Nuys 382 00:26:25,270 --> 00:26:28,630 store, just trying to make sure that the math sat up. 383 00:26:31,430 --> 00:26:36,010 He took the greatest humiliation of his life and turned it into a shield for the 384 00:26:36,010 --> 00:26:37,010 global economy. 385 00:26:37,960 --> 00:26:42,740 He taught the world that profit without a plan is just a gamble, and that in the 386 00:26:42,740 --> 00:26:45,280 dark, the man with the flashlight is king. 387 00:26:47,480 --> 00:26:51,160 There is one financial question the system cannot answer. 388 00:26:51,480 --> 00:26:56,560 What happens when everyone measures risk the same way? When models converge? 389 00:26:56,940 --> 00:26:58,160 When assumptions align? 390 00:26:58,580 --> 00:27:00,600 When diversity of judgment disappears? 391 00:27:01,600 --> 00:27:04,960 A system optimized for stability can become fragile. 392 00:27:05,460 --> 00:27:09,720 Not because it is wrong, but because it leaves no room for the unexpected. 393 00:27:10,460 --> 00:27:14,920 When the supervisor becomes invisible and the rules are embedded in code, 394 00:27:15,140 --> 00:27:17,540 accountability becomes harder to locate. 395 00:27:18,160 --> 00:27:21,100 The system works until it doesn't. 396 00:27:21,340 --> 00:27:25,220 And that's why BlackRock isn't just a shareholder in your company. 397 00:27:25,500 --> 00:27:30,880 They are the landlord of your power plant, the owner of your airport, the 398 00:27:30,880 --> 00:27:32,460 architect of your retirement. 399 00:27:33,130 --> 00:27:37,430 It is a level of centralized influence the world has never seen in a private 400 00:27:37,430 --> 00:27:38,430 individual. 401 00:27:38,950 --> 00:27:44,290 Lawrence D. Fink didn't just build a bank, he built the unblinking eye of 402 00:27:44,290 --> 00:27:45,290 capitalism. 403 00:27:45,610 --> 00:27:50,310 And as the world moves into the era of AI, climate shift, and global 404 00:27:50,310 --> 00:27:52,450 restructuring, one thing is certain, 405 00:27:53,190 --> 00:27:58,430 BlackRock will be there, watching, calculating, and growing. 406 00:29:21,450 --> 00:29:23,450 It's just a small plastic brick. 407 00:29:24,530 --> 00:29:29,470 Lightweight, simple, unchanged since 1958. 408 00:29:30,850 --> 00:29:35,010 And yet, it has built entire universes. 409 00:29:35,670 --> 00:29:38,170 Lego constructions truly take us back to childhood. 410 00:29:39,630 --> 00:29:42,670 But they stay with us throughout our entire life. 411 00:29:42,890 --> 00:29:49,390 From bedrooms to boardrooms, from playgrounds to Hollywood, Lego has 412 00:29:49,390 --> 00:29:50,390 generations. 413 00:29:51,020 --> 00:29:55,380 When I design something from scratch, I start with an idea that occurs to me at 414 00:29:55,380 --> 00:29:56,380 any time of day. 415 00:29:57,480 --> 00:30:00,280 I try to build it with Lego and see what I come up with. 416 00:30:00,780 --> 00:30:07,260 In a global toy market worth more than $120 billion, Lego stands alone. 417 00:30:07,700 --> 00:30:13,800 A single company controlling nearly one in every $10 spent on toys worldwide. 418 00:30:14,520 --> 00:30:18,520 Lego holds a leading position worldwide, recognized above all for its 419 00:30:18,520 --> 00:30:19,520 playability. 420 00:30:19,980 --> 00:30:24,160 What if the most beloved toy in the world almost didn't exist? 421 00:30:26,140 --> 00:30:31,840 Discover the incredible journey of a small, struggling carpentry shop that 422 00:30:31,840 --> 00:30:34,260 to dream bigger than anyone thought possible. 423 00:30:34,700 --> 00:30:41,460 This is the untold story of the visionary who built Lego, transforming 424 00:30:41,460 --> 00:30:47,560 simple wooden bricks into a multi -billion dollar empire and forever 425 00:30:47,560 --> 00:30:48,560 how we play. 426 00:30:50,060 --> 00:30:54,380 But none of this began with billion -dollar charts or cinematic universes. 427 00:30:55,240 --> 00:30:58,260 It began with a carpenter with a vision. 428 00:30:59,060 --> 00:31:05,960 In a tiny Danish village, one man had a dream, building toys out of scraps of 429 00:31:05,960 --> 00:31:06,960 wood. 430 00:31:15,610 --> 00:31:21,930 Eker Kristiansen was born in 1891 in western Denmark, a place defined by 431 00:31:21,930 --> 00:31:24,670 silence, soil, and hard work. 432 00:31:25,550 --> 00:31:29,630 He grew up poor, like most children in the Jutland countryside. 433 00:31:30,430 --> 00:31:33,330 But he learned the value of craftsmanship early. 434 00:31:33,790 --> 00:31:36,810 When you made something, it had to last. 435 00:31:38,030 --> 00:31:39,990 He apprenticed as a carpenter. 436 00:31:40,350 --> 00:31:44,950 It was not a really glamorous work, but meticulous, honest. 437 00:31:45,610 --> 00:31:48,610 A craft that matched Ola's character and manners. 438 00:31:49,950 --> 00:31:53,290 Ola travelled through Denmark, Germany and Norway. 439 00:31:53,970 --> 00:31:56,870 Everywhere he went, he left a reputation. 440 00:31:57,670 --> 00:31:59,950 Precise, patient, relentless. 441 00:32:01,210 --> 00:32:07,210 In 1916, Ola returned home and bought a workshop in a place that barely existed 442 00:32:07,210 --> 00:32:08,210 on the map. 443 00:32:08,450 --> 00:32:11,930 Billund. No shops, no train station. 444 00:32:12,620 --> 00:32:16,840 Just a handful of families trying to survive the Danish winds. Don't worry, 445 00:32:16,840 --> 00:32:20,520 fine. I'm fine. But eight years later, disaster struck. 446 00:32:20,940 --> 00:32:22,680 Oh, oh, oh no. 447 00:32:23,020 --> 00:32:26,640 In 1924, a fire tore through his workshop. 448 00:32:26,980 --> 00:32:28,360 Oh God, no, please no. 449 00:32:28,580 --> 00:32:30,600 Oh my God. Everything burned. 450 00:32:31,120 --> 00:32:33,720 Tools, wood, orders. 451 00:32:34,360 --> 00:32:36,020 And a lifetime of saving. 452 00:32:36,680 --> 00:32:37,680 All gone. 453 00:32:38,760 --> 00:32:40,320 But Oller didn't quit. 454 00:32:41,070 --> 00:32:42,070 He rebuilt. 455 00:32:42,630 --> 00:32:44,490 And rebuilt bigger than before. 456 00:32:44,970 --> 00:32:50,090 Not because it was safe, but because he refused to let villains disappear into 457 00:32:50,090 --> 00:32:51,090 the wind. 458 00:32:51,970 --> 00:32:53,610 Then came the Great Depression. 459 00:32:54,510 --> 00:32:56,130 Houses weren't being built. 460 00:32:56,630 --> 00:32:58,090 Doors weren't being ordered. 461 00:32:58,550 --> 00:33:00,350 Bills weren't being paid. 462 00:33:01,490 --> 00:33:03,870 Oller had workers depending on him. 463 00:33:04,250 --> 00:33:05,950 Families depending on him. 464 00:33:06,470 --> 00:33:08,090 So he did something unexpected. 465 00:33:09,000 --> 00:33:11,500 He began crafting small wooden toys. 466 00:33:12,300 --> 00:33:16,100 They were simple, durable, and beautiful. 467 00:33:17,720 --> 00:33:21,760 Locals mocked him. A grown man making toys for children? 468 00:33:21,980 --> 00:33:23,160 You'll never survive. 469 00:33:24,140 --> 00:33:28,520 But Oller believed that play, and fun, was a serious business. 470 00:33:29,440 --> 00:33:33,740 In 1934, he held a contest to name the new toy company. 471 00:33:34,300 --> 00:33:36,920 He chose a short word, Lego. 472 00:33:37,930 --> 00:33:42,750 It was not only a simple idea, but a philosophy and a promise. 473 00:33:43,630 --> 00:33:45,510 He hung a sign in the workshop. 474 00:33:45,910 --> 00:33:47,830 Only the best is good enough. 475 00:33:48,430 --> 00:33:49,870 It wasn't marketing. 476 00:33:50,150 --> 00:33:51,810 It was his identity. 477 00:33:55,910 --> 00:34:01,130 Oh, God, not again. In 1942, Oller faced another fire. 478 00:34:01,890 --> 00:34:04,450 This time it was bigger, more devastating. 479 00:34:05,010 --> 00:34:06,030 Every blueprint. 480 00:34:06,560 --> 00:34:10,199 Every toy, every dream he had turned into smoke. 481 00:34:11,420 --> 00:34:13,540 But he had built himself the hardship. 482 00:34:14,280 --> 00:34:20,159 And once more, he rebuilt the factory, stronger than the two previous ones. 483 00:34:20,980 --> 00:34:24,639 In 1947, at the worst economic moment, 484 00:34:25,340 --> 00:34:27,639 Oller made the riskiest choice of his life. 485 00:34:28,360 --> 00:34:33,159 He spent more than twice the company's annual profits on a strange new machine, 486 00:34:33,500 --> 00:34:36,860 one that worked not with wood, but with plastic. 487 00:34:38,360 --> 00:34:39,739 Retailers hated plastic. 488 00:34:40,300 --> 00:34:44,219 Parents distrusted it. But Oller saw something they didn't. 489 00:34:44,739 --> 00:34:47,960 Precision, repeatability, and possibilities. 490 00:34:48,699 --> 00:34:50,060 Endless possibilities. 491 00:34:51,540 --> 00:34:57,700 Only two years later, in 1949, Lego released the first plastic bricks of its 492 00:34:57,700 --> 00:34:59,700 history. They didn't click. 493 00:35:00,000 --> 00:35:01,320 They weren't perfect. 494 00:35:01,800 --> 00:35:03,660 But they were the beginning. 495 00:35:10,670 --> 00:35:15,390 The idea was good, but Ola and his team faced setbacks while designing the brick 496 00:35:15,390 --> 00:35:18,170 that had cemented Lego's identity through the years. 497 00:35:18,690 --> 00:35:21,230 The plastic brick didn't grip. 498 00:35:21,970 --> 00:35:26,170 This was a major problem for a building set because buildings collapsed. 499 00:35:26,890 --> 00:35:28,950 Towers fell in front of their eyes. 500 00:35:29,490 --> 00:35:32,350 Apparently Lego wasn't created to build. 501 00:35:32,930 --> 00:35:37,350 And then, in 1958, everything changed. 502 00:35:38,570 --> 00:35:43,370 Unlike 20 years ago, LEGO today allows us to build many more things because 503 00:35:43,370 --> 00:35:46,030 have released more realistic colors and shapes. 504 00:35:48,690 --> 00:35:51,510 In the past, the pieces were mostly square. 505 00:35:51,790 --> 00:35:56,710 Today, there is a much wider variety of shapes, including more rounded elements, 506 00:35:56,850 --> 00:36:01,950 which allow us to create more ergonomic forms, ones that more closely resemble 507 00:36:01,950 --> 00:36:05,670 the kinds of buildings and structures we see in everyday life. 508 00:36:06,930 --> 00:36:10,990 Engineers at LEGO perfected a simple but ingenious solution. 509 00:36:11,630 --> 00:36:13,790 Hollow tubes inside the brick. 510 00:36:15,130 --> 00:36:20,410 Paired with the studs on top, the geometry created what LEGO calls clutch 511 00:36:20,850 --> 00:36:24,810 Not too tight, not too loose, just perfect. 512 00:36:25,990 --> 00:36:28,550 This was not just an adjustment or improvement. 513 00:36:29,010 --> 00:36:32,690 It was the birth of what we know today as the LEGO brick. 514 00:36:33,370 --> 00:36:37,130 The brick that, today, can still be used with the modern one. 515 00:36:38,290 --> 00:36:42,730 The brick that was the foundation of a company that still makes history today. 516 00:36:43,910 --> 00:36:46,670 That same year, Lego filed the patent. 517 00:36:47,350 --> 00:36:51,970 They had something worth protecting, and Ollie knew that sooner or later, it 518 00:36:51,970 --> 00:36:52,970 would be replicated. 519 00:36:54,750 --> 00:36:59,610 It was January the 28th, 1958, when the patent was filed. 520 00:37:00,290 --> 00:37:03,770 Later that year, Oleg Kirk -Christensen passed away. 521 00:37:04,750 --> 00:37:09,450 And sadly, he never lived to see how far his brick would travel. 522 00:37:19,330 --> 00:37:23,430 After his father died, Gottfried Kirk -Christensen stepped in. 523 00:37:24,170 --> 00:37:26,390 He wasn't inheriting the company. 524 00:37:26,650 --> 00:37:28,570 He was inheriting a philosophy. 525 00:37:29,250 --> 00:37:30,950 One he had been raised with. 526 00:37:31,580 --> 00:37:36,580 His father wasn't around anymore, but the original spirit of Lego lived on in 527 00:37:36,580 --> 00:37:37,980 second Christensen generation. 528 00:37:39,220 --> 00:37:41,200 But he also had something to add. 529 00:37:41,860 --> 00:37:46,400 Godfrey believed Lego should be more than toys. It should be a system. 530 00:37:46,800 --> 00:37:52,460 A system where every piece connected with every other piece, across every 531 00:37:53,300 --> 00:37:56,580 This created a language of creativity and possibilities. 532 00:37:57,220 --> 00:37:59,620 And a single idea changed everything. 533 00:38:00,710 --> 00:38:05,630 Suddenly, Lego wasn't a collection of toys, but an entire universe. 534 00:38:06,850 --> 00:38:10,790 The company began to grow far beyond its original frontiers. 535 00:38:11,390 --> 00:38:18,050 During the 1960s and 70s, Lego expanded across Europe, Germany, Sweden, 536 00:38:18,270 --> 00:38:19,270 the UK. 537 00:38:19,970 --> 00:38:24,190 Billund, once a small village, became a global hub of play. 538 00:38:24,810 --> 00:38:29,490 Lego then built its own airports, factories, and distribution centers. 539 00:38:30,040 --> 00:38:34,320 In the world of construction toys, we know that LEGO isn't the only brand 540 00:38:34,320 --> 00:38:35,320 around. 541 00:38:36,420 --> 00:38:38,800 What LEGO provides is a quality product. 542 00:38:41,020 --> 00:38:46,480 Maybe one part is wrong for every 10 ,000 or 100 ,000 items, and if you are 543 00:38:46,480 --> 00:38:50,940 missing an item from a box, or if it is faulty, the company's after -sales 544 00:38:50,940 --> 00:38:53,840 service will not question the fact that you are missing a part. 545 00:38:57,100 --> 00:38:58,100 And then? 546 00:38:58,560 --> 00:38:59,740 the magic happened. 547 00:39:00,620 --> 00:39:04,460 Lego introduced something no toy company had done at scale. 548 00:39:05,060 --> 00:39:06,860 Fully themed worlds. 549 00:39:07,480 --> 00:39:10,440 Base, town, castles. 550 00:39:11,300 --> 00:39:13,780 Children weren't just building structures anymore. 551 00:39:14,100 --> 00:39:15,760 They were building stories. 552 00:39:16,880 --> 00:39:22,860 In 1978, Lego released its most iconic invention since the brick, the 553 00:39:22,860 --> 00:39:27,860 minifigure. It had a simple face, hands shaped like a C. 554 00:39:28,350 --> 00:39:30,370 and feet made to stand on studs. 555 00:39:30,610 --> 00:39:35,870 A tiny character that let kids project themselves into entire universes. 556 00:39:36,830 --> 00:39:40,310 Stories now had heroes, and Lego had a heartbeat. 557 00:39:41,010 --> 00:39:46,330 In the late 1970s, Lego was already run by the third Christensen generation. 558 00:39:47,150 --> 00:39:53,090 Ole's grandson, Kjeld, began shaping the company into the global powerhouse we 559 00:39:53,090 --> 00:39:54,090 know today. 560 00:39:54,390 --> 00:39:57,550 He did so by creating more sophisticated lines. 561 00:39:58,160 --> 00:39:59,600 bringing in new universes. 562 00:40:00,340 --> 00:40:05,540 Technic brought mechanics, pirates brought adventure, and trains brought 563 00:40:06,200 --> 00:40:12,440 By the late 20th century, the global toy market was becoming massive, tens of 564 00:40:12,440 --> 00:40:14,220 billions of dollars a year worth. 565 00:40:14,880 --> 00:40:20,380 The United States spent more on toys than any country on Earth, and China 566 00:40:20,380 --> 00:40:24,000 produced most of them, nearly three -quarters of the world's total. 567 00:40:24,980 --> 00:40:26,680 In this booming landscape, 568 00:40:27,400 --> 00:40:29,340 Lego wasn't just another toy. 569 00:40:29,740 --> 00:40:31,500 It was the toy. 570 00:40:38,400 --> 00:40:42,040 By the late 1990s, Lego was flying high. 571 00:40:42,280 --> 00:40:45,580 It had become one of the most admired companies in Europe. 572 00:40:45,780 --> 00:40:50,300 A creative powerhouse built on the philosophy of imagination and creation. 573 00:40:50,920 --> 00:40:54,840 We're not focused only on childhood, but on something that has quite literally 574 00:40:54,840 --> 00:40:59,680 built us, pun intended, shaping our personalities through Lego from an early 575 00:40:59,680 --> 00:41:04,160 age. Those memories became a foundation we've kept building on over time. 576 00:41:06,500 --> 00:41:10,560 That's why exhibitions like this bring us straight back to childhood. The 577 00:41:10,560 --> 00:41:15,680 audience here is very diverse, but once people walk in, they all become the boy 578 00:41:15,680 --> 00:41:16,980 or girl they once were. 579 00:41:17,500 --> 00:41:19,880 But it's not all gold that glitters. 580 00:41:20,670 --> 00:41:23,930 Under the surface, something dangerous was creeping in. 581 00:41:24,390 --> 00:41:26,770 The toy market was changing fast. 582 00:41:27,150 --> 00:41:31,030 Children were spending more and more time with video games and early computer 583 00:41:31,030 --> 00:41:32,030 entertainment. 584 00:41:32,470 --> 00:41:37,030 Sony's PlayStation, Nintendo and Hasbro's electronic toys were capturing 585 00:41:37,030 --> 00:41:43,550 attention. And Lego, determined not to fall behind, expanded too far, too fast. 586 00:41:44,530 --> 00:41:49,890 Throughout the 1990s, Lego began introducing thousands of completely new 587 00:41:50,570 --> 00:41:53,410 specialized parts that not only worked in one set. 588 00:41:53,910 --> 00:42:00,330 A single year could bring more than 350 new designs, each of them costing tens 589 00:42:00,330 --> 00:42:04,050 of thousands of dollars in steel, machining, and precision engineering. 590 00:42:05,510 --> 00:42:10,450 In 2002, LEGO had more than 12 ,000 active elements. 591 00:42:10,930 --> 00:42:16,450 The system of play, once simple and universal, was becoming chaotic and 592 00:42:16,450 --> 00:42:17,450 difficult to follow. 593 00:42:18,090 --> 00:42:20,890 Lego also tried becoming a lifestyle brand. 594 00:42:21,370 --> 00:42:23,250 New ventures appeared everywhere. 595 00:42:23,490 --> 00:42:29,290 Clothing lines, theme parks, home goods, cartoon series, even watches and 596 00:42:29,290 --> 00:42:30,290 sneakers. 597 00:42:30,370 --> 00:42:35,850 But these projects drained resources without reinforcing the core product, 598 00:42:35,850 --> 00:42:39,870 brick. And between 1999 and 2003, 599 00:42:40,590 --> 00:42:42,230 Lego sales collapsed. 600 00:42:42,910 --> 00:42:47,670 During these years, the company went from double -digit growth to struggling, 601 00:42:47,870 --> 00:42:53,470 and by 2003, the company was losing the equivalent of $1 million a day. 602 00:42:54,130 --> 00:43:00,970 In a global toy market, still worth more than $70 billion at the time, Lego, 603 00:43:01,230 --> 00:43:05,110 once the king of the toy box, was only a few steps away from bankruptcy. 604 00:43:06,150 --> 00:43:09,790 Times were dark, but the spark of genius appeared. 605 00:43:10,430 --> 00:43:11,650 In 1999, 606 00:43:12,520 --> 00:43:16,780 Lego signed its first ever licensing deal with no other than Lucasfilm. 607 00:43:17,600 --> 00:43:19,240 The timing was perfect. 608 00:43:20,020 --> 00:43:23,440 Star Wars Episode I was about to hit theaters. 609 00:43:24,080 --> 00:43:28,680 Hype was global, and the first Lego Star Wars sets were instant hits. 610 00:43:29,360 --> 00:43:31,880 Not just with children, with adults. 611 00:43:32,660 --> 00:43:36,900 Collectors lined up to buy the X -Wing, the Snow Speeder, or the first 612 00:43:36,900 --> 00:43:37,900 Millennium Falcon. 613 00:43:38,460 --> 00:43:41,120 For the first time in Lego's history, 614 00:43:42,100 --> 00:43:46,680 Adults, including those in their 30s and 40s, were buying sets for themselves. 615 00:43:47,220 --> 00:43:49,860 The adult fan of LEGO community is getting bigger. 616 00:43:50,140 --> 00:43:54,480 This is because LEGO is not the same as it was 20 or 30 years ago. 617 00:43:56,400 --> 00:44:00,760 Before, LEGO was only seen as a toy to play with when it was cold and you were 618 00:44:00,760 --> 00:44:01,760 indoors. 619 00:44:03,930 --> 00:44:08,830 Today, LEGO is much more than a toy. It's used to create logos, to design 620 00:44:08,830 --> 00:44:13,270 dynamic group activities, and it also represents a shift in how we see it. 621 00:44:14,050 --> 00:44:18,890 Years ago, if you said you played with LEGO or built LEGO, you almost had to 622 00:44:18,890 --> 00:44:23,110 explain yourself that you were at home, playing with little figures, making up 623 00:44:23,110 --> 00:44:27,810 battles. What we do today is different. We come together as a community of 624 00:44:27,810 --> 00:44:30,090 adults, and LEGO has recognized that. 625 00:44:31,040 --> 00:44:35,880 That's why more and more products are now designed specifically for adults, 626 00:44:35,880 --> 00:44:38,800 complex to build, and also more expensive. 627 00:44:41,980 --> 00:44:46,680 This piddled demographic would later become one of LEGO's most profitable 628 00:44:46,680 --> 00:44:49,440 segments. More licenses followed. 629 00:44:49,660 --> 00:44:55,580 Harry Potter, Spider -Man, Batman, Indiana Jones, and later the newest 630 00:44:55,580 --> 00:44:56,600 Cinematic Universe. 631 00:44:57,710 --> 00:45:03,350 Even though Lego learned that storytelling sells, in 2004 losses were 632 00:45:03,350 --> 00:45:05,090 and survival was uncertain. 633 00:45:05,750 --> 00:45:08,990 And then the company made a radical decision. 634 00:45:09,770 --> 00:45:15,110 For the first time in its history, the company appointed a CEO from outside the 635 00:45:15,110 --> 00:45:21,090 Christensen family, JĂ¼rgen Big Knudstorp, a 35 -year -old former 636 00:45:21,090 --> 00:45:28,020 consultant. He was calm, precise, analytical, and... brutally honest. 637 00:45:28,540 --> 00:45:30,440 His diagnosis was simple. 638 00:45:30,960 --> 00:45:34,260 Lego had forgotten what made it Lego. 639 00:45:35,480 --> 00:45:41,140 Knut Storp cut the number of unique elements by nearly 50%. He sold off the 640 00:45:41,140 --> 00:45:44,940 theme park. He shut down unprofitable production facilities. 641 00:45:45,480 --> 00:45:50,640 He centralized supply chains, standardized materials, and brought back 642 00:45:50,640 --> 00:45:51,780 discipline to the system. 643 00:45:52,120 --> 00:45:55,240 But more important, he put the brakes back. 644 00:45:55,580 --> 00:45:56,640 at the center of the company. 645 00:46:00,560 --> 00:46:03,260 This turnaround didn't happen in isolation. 646 00:46:03,740 --> 00:46:07,500 The global toy industry was undergoing a seismic change. 647 00:46:08,300 --> 00:46:13,580 China was producing nearly 75 % of the world's toys, being the largest 648 00:46:13,580 --> 00:46:16,120 manufacturing consolidation in toy history. 649 00:46:17,160 --> 00:46:22,000 Meanwhile, the United States had become the single largest consumer, responsible 650 00:46:22,000 --> 00:46:24,700 for nearly one -third of the global toy spending. 651 00:46:27,500 --> 00:46:32,860 By 2005, the toy market was worth close to 80 billion US dollars. 652 00:46:33,240 --> 00:46:35,940 But it was brutally competitive as well. 653 00:46:37,160 --> 00:46:38,500 Seasonality was extreme. 654 00:46:38,780 --> 00:46:43,920 Nearly half of the annual toy sales occurred in just three months, from 655 00:46:43,920 --> 00:46:44,920 to December. 656 00:46:45,900 --> 00:46:48,380 Companies lived or died by Christmas. 657 00:46:49,140 --> 00:46:51,560 Mattel was battling declining Barbie sales. 658 00:46:52,020 --> 00:46:56,180 Hasbro was betting its future on Transformers and board game 659 00:46:56,990 --> 00:47:00,450 electronics were eating market share across every age group. 660 00:47:00,870 --> 00:47:07,130 In this scenario, LEGO rebuilt and refocused, and then began 661 00:47:07,130 --> 00:47:09,490 rising above all of them. 662 00:47:14,850 --> 00:47:21,430 Between 2008 and 2015, LEGO entered a new era, a renaissance 663 00:47:21,430 --> 00:47:26,910 driven by design, storytelling, digital engagement, and adults' passions. 664 00:47:27,690 --> 00:47:33,150 The company launched the ultimate collective series, producing the 665 00:47:33,150 --> 00:47:35,190 detailed models in toy history. 666 00:47:36,310 --> 00:47:39,310 LEGO Architectler brought landmarks to coffee tables. 667 00:47:39,990 --> 00:47:45,290 Modular buildings turned living rooms into miniature cities, and adults were 668 00:47:45,290 --> 00:47:48,290 longer hiding their LEGO hobby with embracing it. 669 00:47:48,530 --> 00:47:52,770 My story with LEGO began in the early 90s when I was a small child. 670 00:47:54,410 --> 00:47:57,130 I started playing, but then I stopped for a while. 671 00:47:58,170 --> 00:48:02,230 This is what most of us want to do when we are teenagers, to do other hobbies 672 00:48:02,230 --> 00:48:04,050 and spend less time playing with LEGO. 673 00:48:06,910 --> 00:48:10,870 After that, when I was in my early 20s, I started collecting LEGO. 674 00:48:11,810 --> 00:48:15,370 I met people from the Valencian community and founded Valbrek. 675 00:48:16,010 --> 00:48:20,930 That eventually led me to a television show where I took part and won. 676 00:48:21,500 --> 00:48:24,880 From there, companies began approaching me to develop projects. 677 00:48:27,980 --> 00:48:30,920 At first, this hadn't even occurred to me. 678 00:48:32,160 --> 00:48:36,780 But I started to see a growing demand, whether it was building a corporate kit, 679 00:48:36,820 --> 00:48:41,120 like a transport company's truck, or even a company's logistics headquarters. 680 00:48:42,080 --> 00:48:45,060 This market opened up a professional path for me. 681 00:48:46,000 --> 00:48:50,380 It supports me financially, but more importantly, it's deeply rewarding. 682 00:48:51,440 --> 00:48:55,400 Many of these projects challenge me to build things I would never choose on my 683 00:48:55,400 --> 00:48:56,400 own. 684 00:48:56,720 --> 00:49:01,380 But once the challenge is set, build this, my mind immediately starts 685 00:49:01,380 --> 00:49:06,560 ideas, figuring out how to shape them and bring the project to life in the 686 00:49:06,560 --> 00:49:07,560 possible way. 687 00:49:11,240 --> 00:49:14,240 The adult fans of LEGO skyrocketed. 688 00:49:14,660 --> 00:49:20,640 Forums, conventions, fan events, engineering cups, a global movement 689 00:49:21,460 --> 00:49:26,440 By 2014, Adolf accounted for nearly one -third of Lego sales. 690 00:49:27,120 --> 00:49:32,180 To anyone who thinks Lego is only for children, I'd say, come and see the 691 00:49:32,180 --> 00:49:33,180 exhibition. 692 00:49:33,360 --> 00:49:37,920 See what we're capable of creating with Lego pieces and how imagination develops 693 00:49:37,920 --> 00:49:39,860 in both children and adults. 694 00:49:42,060 --> 00:49:47,500 Children work within certain limits and see things differently, but adults, with 695 00:49:47,500 --> 00:49:52,940 a wider range of colors, shapes and ways to use the pieces can explore just how 696 00:49:52,940 --> 00:49:53,940 much is possible. 697 00:49:55,500 --> 00:50:00,660 It was a radical shift in the economics of play, and then came the cultural 698 00:50:00,660 --> 00:50:01,660 explosion. 699 00:50:02,160 --> 00:50:06,000 In 2014, the Lego movie shattered expectations, 700 00:50:06,720 --> 00:50:10,820 earning nearly 500 million US dollars at the box office. 701 00:50:11,680 --> 00:50:15,380 What started as a toy was now pop culture. 702 00:50:15,700 --> 00:50:21,940 By the mid -2010s, Lego was the world's most valuable toy company, even 703 00:50:21,940 --> 00:50:25,140 surpassing Mattel, Hasbro, and every other competitor. 704 00:50:26,100 --> 00:50:30,060 The brick that started it all was no longer just a product. 705 00:50:30,400 --> 00:50:32,640 It was a global icon. 706 00:50:36,960 --> 00:50:41,600 The Lego Group stands today as one of the most efficient, profitable, and 707 00:50:41,600 --> 00:50:43,920 culturally influential toy companies on Earth. 708 00:50:44,240 --> 00:50:46,920 Its factories run with near -perfect precision. 709 00:50:48,270 --> 00:50:51,890 Its design teams develop thousands of prototypes each year. 710 00:50:52,350 --> 00:50:56,770 Its supply chain delivers billions of bricks that must all fit together 711 00:50:56,770 --> 00:50:58,890 flawlessly across decades. 712 00:50:59,990 --> 00:51:06,990 In a global toy market worth roughly $120 billion a year, LEGO commands 713 00:51:06,990 --> 00:51:10,050 nearly 9 % of all worldwide toy sales. 714 00:51:10,690 --> 00:51:16,420 No other toy brand, not Barbie, not Marvel figures, Not Nintendo merchandise 715 00:51:16,420 --> 00:51:21,740 maintains such consistency across continents, genders, and generations. 716 00:51:22,600 --> 00:51:28,160 And unlike most toy companies that outsource manufacturing, LEGO controls a 717 00:51:28,160 --> 00:51:33,080 significant portion of its own production, with major hubs in Denmark, 718 00:51:33,320 --> 00:51:35,580 Mexico, China, and the Czech Republic. 719 00:51:36,800 --> 00:51:41,080 This vertical integration reduces risk, stabilizes quality, 720 00:51:41,820 --> 00:51:46,460 and protects one of the most important values in the company's DNA, precision. 721 00:51:47,480 --> 00:51:52,500 Every LEGO brick must be manufactured with tolerances thinner than a strand of 722 00:51:52,500 --> 00:51:56,120 hair. If the clutch is too tight, the model breaks. 723 00:51:56,560 --> 00:51:59,340 If it's too loose, towers collapse. 724 00:52:00,100 --> 00:52:04,080 Across billions of pieces, perfection is not an ambition. 725 00:52:04,480 --> 00:52:07,360 It is an engineering reality for LEGO. 726 00:52:08,880 --> 00:52:13,520 This level of detail gives the company one of the highest brand trust ratings 727 00:52:13,520 --> 00:52:14,520 the world. 728 00:52:14,580 --> 00:52:16,500 Parents know the bricks will last. 729 00:52:17,040 --> 00:52:18,800 Adults know the sets will impress. 730 00:52:19,640 --> 00:52:22,280 Collectors know the investment will hold value. 731 00:52:23,280 --> 00:52:28,680 The modern toy market is a machine of impulse, tradition, celebration, and 732 00:52:28,680 --> 00:52:29,680 nostalgia. 733 00:52:29,980 --> 00:52:36,120 In 2025, global spending on toys approaches $120 billion. 734 00:52:37,050 --> 00:52:39,570 nearly double what it was two decades earlier. 735 00:52:40,190 --> 00:52:45,030 The United States remains the world's largest consumer, accounting for roughly 736 00:52:45,030 --> 00:52:46,530 one -third of global sales. 737 00:52:47,270 --> 00:52:53,470 A typical American household with children may spend $300 to $400 per 738 00:52:53,470 --> 00:52:54,470 year on toys. 739 00:52:54,850 --> 00:52:57,730 This is more than five times the global average. 740 00:52:59,070 --> 00:53:03,830 Europe forms the second largest bloc, with strong purchasing power in Germany, 741 00:53:03,970 --> 00:53:05,690 the United Kingdom, and France. 742 00:53:06,760 --> 00:53:12,060 Asia -Pacific is rapidly growing, especially in China, South Korea and 743 00:53:12,420 --> 00:53:16,080 driven by rising middle classes and urban lifestyles. 744 00:53:16,900 --> 00:53:21,440 But the most important shift of the last decade is not geographic. 745 00:53:21,800 --> 00:53:23,500 It is demographic. 746 00:53:29,940 --> 00:53:35,260 Adults, once considered irrelevant to the toy industry, are now one of the 747 00:53:35,260 --> 00:53:36,470 most... powerful forces. 748 00:53:37,090 --> 00:53:41,910 This growing segment, commonly called the kid -old market, now represents 749 00:53:41,910 --> 00:53:45,930 between 25 and 30 % of all toy purchases worldwide. 750 00:53:47,310 --> 00:53:53,390 Adults buy toys for nostalgia, for stress relief, for display, for 751 00:53:54,350 --> 00:53:57,230 Lego is the undisputed champion of this movement. 752 00:53:57,710 --> 00:54:01,070 Unlike other hobbies, Lego gives me a sense of calm. 753 00:54:04,570 --> 00:54:09,710 It lets me take ideas from my mind, bring them to life, think them through, 754 00:54:09,710 --> 00:54:11,110 simply enjoy the process. 755 00:54:11,850 --> 00:54:17,510 Right now, I'm trying to instill that in my son, to enjoy himself, to learn, to 756 00:54:17,510 --> 00:54:21,570 see colors and shapes, and to understand that with imagination anything is 757 00:54:21,570 --> 00:54:22,570 possible. 758 00:54:30,910 --> 00:54:35,510 Regularly exceed prices of $300, $500, even $800. 759 00:54:36,310 --> 00:54:38,210 They sell out within hours. 760 00:54:38,550 --> 00:54:41,950 They hold aftermarket values like fine collectibles. 761 00:54:42,390 --> 00:54:47,110 This adult segment has reshaped the entire financial landscape of the 762 00:54:47,650 --> 00:54:51,090 It provides stability when children's trends shift. 763 00:54:51,370 --> 00:54:54,490 It creates recurring revenue from loyal fans. 764 00:54:54,930 --> 00:54:59,230 And it strengthens LEGO's position as a cross -generational brand. 765 00:55:00,170 --> 00:55:02,610 something few toy companies have ever achieved. 766 00:55:03,850 --> 00:55:07,130 Seasonality still dictates much of the global toy market. 767 00:55:07,510 --> 00:55:12,570 Every year, nearly half of all toy sales occur between October and December. 768 00:55:13,270 --> 00:55:19,030 Companies live or die by holiday forecasting, inventory strategy, and 769 00:55:19,030 --> 00:55:22,210 timing. But Lego has become the exception. 770 00:55:22,930 --> 00:55:25,210 Adult collectors buy year -round. 771 00:55:25,880 --> 00:55:29,620 Digital experiences drive sales outside the holiday season. 772 00:55:30,220 --> 00:55:34,140 Licensed launches create anticipation even in slow quarters. 773 00:55:35,000 --> 00:55:39,940 Lego has effectively freed itself, or at least partially, from the seasonal 774 00:55:39,940 --> 00:55:43,580 dependency that has defined the toy industry for over a century. 775 00:55:44,340 --> 00:55:48,000 The brick is physical, tangible, mechanical. 776 00:55:48,500 --> 00:55:53,700 But Lego's success in the 21st century extends into digital worlds. 777 00:55:54,000 --> 00:55:55,060 Star Wars. 778 00:55:55,530 --> 00:55:56,890 Batman, Marvel. 779 00:55:57,350 --> 00:56:01,670 These games defined an entire generation of family -friendly titles. 780 00:56:02,070 --> 00:56:04,650 They sold tens of millions of copies. 781 00:56:04,930 --> 00:56:10,830 They introduced humor, storytelling, and simplicity to a medium often dominated 782 00:56:10,830 --> 00:56:11,830 by complexity. 783 00:56:12,570 --> 00:56:18,050 For many children born after the year 2000, Lego was not discovered in a toy 784 00:56:18,050 --> 00:56:19,710 box, but on a screen. 785 00:56:20,270 --> 00:56:23,070 The cinematic leap came in 2014. 786 00:56:23,950 --> 00:56:28,950 when the Lego movie premiered to global acclaim. It earned nearly half a billion 787 00:56:28,950 --> 00:56:35,070 dollars. Most importantly, it reframed Lego as a cultural idea, not a product. 788 00:56:35,550 --> 00:56:40,950 The film taught a global audience that creativity matters, that imperfection is 789 00:56:40,950 --> 00:56:46,230 beautiful, that building and rebuilding are not failures, they are the process 790 00:56:46,230 --> 00:56:47,230 of play. 791 00:56:47,470 --> 00:56:49,830 Lego Batman expanded the concept. 792 00:56:50,440 --> 00:56:56,360 Lego Ninjago created an entirely new generation of fans, and Lego Masters on 793 00:56:56,360 --> 00:56:59,560 television turned building into a competitive art form. 794 00:57:00,200 --> 00:57:05,200 The brand had moved beyond toys, beyond stories, beyond bricks. 795 00:57:05,520 --> 00:57:09,760 It had become part of the cultural grammar of the 21st century. 796 00:57:15,500 --> 00:57:20,790 Long before STEM became a global movement, Lego was already teaching 797 00:57:20,790 --> 00:57:22,330 how to think like engineers. 798 00:57:22,890 --> 00:57:29,110 In the 1990s, Lego Mindstorms introduced programmable robotics to students 799 00:57:29,110 --> 00:57:30,110 around the world. 800 00:57:30,770 --> 00:57:37,250 Later sets, WeDo, Fight Prime, Boost, brought coding, sensors, and motors into 801 00:57:37,250 --> 00:57:38,290 classrooms and homes. 802 00:57:38,870 --> 00:57:44,910 Today, Lego Education works with governments, schools, and universities 803 00:57:44,910 --> 00:57:46,970 hands -on learning to millions of students. 804 00:57:47,980 --> 00:57:49,320 The philosophy is simple. 805 00:57:49,620 --> 00:57:51,540 Children learn best through play. 806 00:57:51,920 --> 00:57:56,880 This approach shapes future engineers, designers, and problem solvers. 807 00:57:57,300 --> 00:58:00,760 It helps children experiment in ways that textbooks cannot. 808 00:58:01,320 --> 00:58:06,380 And it continues Oleg Kirk's belief that play is not a distraction from 809 00:58:06,380 --> 00:58:08,640 learning, but the foundation of it. 810 00:58:10,350 --> 00:58:14,550 In a world increasingly focused on sustainability... From my experience, 811 00:58:14,550 --> 00:58:18,830 makes LEGO different from other construction toys is its growing 812 00:58:18,830 --> 00:58:23,790 inclusion. In recent years, LEGO has actively embraced people with different 813 00:58:23,790 --> 00:58:28,210 abilities, for example, by including figures in wheelchairs and releasing 814 00:58:28,210 --> 00:58:29,210 in Braille. 815 00:58:29,550 --> 00:58:33,110 These are things most other brands simply don't offer, but LEGO does. 816 00:58:34,330 --> 00:58:37,530 In addition, LEGO is strongly committed to the environment. 817 00:58:38,510 --> 00:58:42,470 They're producing more and more pieces using recycled plastic and replacing 818 00:58:42,470 --> 00:58:46,830 plastic packaging with paper to reduce weight, something other brands simply 819 00:58:46,830 --> 00:58:47,910 don't do. 820 00:58:49,630 --> 00:58:51,830 LEGO faces a unique challenge. 821 00:58:52,370 --> 00:58:54,530 Its bricks are made to last forever. 822 00:58:55,230 --> 00:58:59,490 A blessing for creativity, but a concern in an era of plastic waste. 823 00:59:00,010 --> 00:59:05,170 In response, LEGO has invested hundreds of millions of dollars into developing 824 00:59:05,170 --> 00:59:06,530 more sustainable materials. 825 00:59:07,410 --> 00:59:11,490 Plant -based polyethylene is already used for leaves and trees. 826 00:59:12,390 --> 00:59:15,490 Recycled PET prototypes continue to advance. 827 00:59:16,610 --> 00:59:19,470 Recycled PET prototypes continue to advance. 828 00:59:20,400 --> 00:59:26,520 New polymer engineering aims to create bricks as durable as ABS without the 829 00:59:26,520 --> 00:59:27,520 environmental cost. 830 00:59:28,400 --> 00:59:30,820 This transition is not simple. 831 00:59:31,360 --> 00:59:34,660 A Lego brick must interlock with perfect precision. 832 00:59:34,980 --> 00:59:39,320 A fraction of a millimeter can make the difference between wonder and 833 00:59:39,320 --> 00:59:41,980 frustration. But the mission is clear. 834 00:59:42,600 --> 00:59:47,200 A toy that lasts forever should also protect the world it is played in. 835 00:59:47,780 --> 00:59:49,500 Play is not a luxury. 836 00:59:50,190 --> 00:59:51,190 Play is exploration. 837 00:59:51,650 --> 00:59:53,230 Play is curiosity. 838 00:59:53,950 --> 00:59:57,170 Play is the earliest form of human creativity. 839 00:59:58,110 --> 01:00:03,450 From wooden ducks in a small Danish workshop, to interlocking bricks that 840 01:00:03,450 --> 01:00:09,810 generations, to movies, video games, robotics, and global fan community, 841 01:00:10,390 --> 01:00:13,190 LEGO has remained loyal to a simple truth. 842 01:00:13,450 --> 01:00:18,350 When we build, we grow. When we imagine, we expand. 843 01:00:19,240 --> 01:00:22,020 When we play, we become more human. 844 01:00:28,240 --> 01:00:33,340 More than a century ago, a carpenter rebuilt his workshop after a fire. 845 01:00:33,760 --> 01:00:35,920 He rebuilt it again after another. 846 01:00:36,780 --> 01:00:41,700 Not because it was easy, but because he believed in the power of making things, 847 01:00:41,900 --> 01:00:43,680 and in the power of play. 848 01:00:44,640 --> 01:00:48,400 Today, billions of creations have risen from that belief. 849 01:00:49,020 --> 01:00:50,880 Cities. Castles. 850 01:00:51,300 --> 01:00:52,300 Bayships. 851 01:00:53,000 --> 01:00:57,100 Dreams that exist nowhere else but in the minds of the people who build them. 852 01:00:58,100 --> 01:01:00,120 Lego is not perfect. 853 01:01:00,440 --> 01:01:04,740 It has faced crises, challenges, and impossible decisions. 854 01:01:05,240 --> 01:01:11,480 But it endures. Through war, through technological revolutions, through 855 01:01:11,480 --> 01:01:15,760 storms. Because imagination always endures. 856 01:01:16,520 --> 01:01:21,160 And as long as there are hands reaching the brick, as long as there are minds 857 01:01:21,160 --> 01:01:25,920 ready to create, the legacy of Oleg Kirk -Christensen will continue. 858 01:01:27,140 --> 01:01:30,400 Every dream starts with a single piece. 859 01:02:59,120 --> 01:03:02,280 Jensen Huang, the software moat. 860 01:03:03,100 --> 01:03:05,420 June 18th, 2024. 861 01:03:06,440 --> 01:03:11,160 For a brief historic moment, the world had a new king. 862 01:03:12,400 --> 01:03:19,180 Jensen Huang, the co -founder and CEO of NVIDIA, stood at the peak of a $3 .4 863 01:03:19,180 --> 01:03:20,420 trillion mountain. 864 01:03:22,560 --> 01:03:25,820 Analysts whispered that he wasn't just leading a company. 865 01:03:26,570 --> 01:03:31,810 He was leading the first entity destined for a $4 trillion valuation. 866 01:03:33,990 --> 01:03:39,110 But to understand the man in the leather jacket, you cannot look at the triumph. 867 01:03:39,330 --> 01:03:41,630 You must look at the fear. 868 01:03:42,550 --> 01:03:48,790 Behind the 250 % revenue jumps and the sold -out age 100 backlog 869 01:03:48,790 --> 01:03:52,530 lies a leader obsessed with the cyclical trap. 870 01:03:53,870 --> 01:03:59,710 In a 60 -year history of semiconductors, giants like Texas Instruments, Intel, 871 01:03:59,990 --> 01:04:05,310 and Samsung have all held the crown only to see it slip away. 872 01:04:06,950 --> 01:04:08,790 Jensen's mission is simple. 873 01:04:09,270 --> 01:04:12,570 Break the cycle before it breaks him. 874 01:04:14,830 --> 01:04:17,010 Flashback to September 1996. 875 01:04:17,630 --> 01:04:22,230 The golden era of the Internet is dawning for everyone else. 876 01:04:22,680 --> 01:04:25,260 But for NVIDIA, it is a death knell. 877 01:04:26,580 --> 01:04:32,820 Their first chip, the NV1, is a technical ghost, rejected by Microsoft 878 01:04:32,820 --> 01:04:33,900 DirectX. 879 01:04:35,180 --> 01:04:40,940 Jensen stands before a dwindling team and delivers the most famous mantra in 880 01:04:40,940 --> 01:04:42,100 Silicon Valley history. 881 01:04:43,020 --> 01:04:46,620 We have exactly 30 days of oxygen left. 882 01:04:46,960 --> 01:04:49,520 We are 30 days from bankruptcy. 883 01:04:50,920 --> 01:04:55,840 How does a man go from cleaning toilets in a Kentucky reform school to 884 01:04:55,840 --> 01:04:59,400 controlling the foundational layer of the global AI economy? 885 01:05:00,540 --> 01:05:06,040 From a red leather booth at a Denny's to a legal showdown in the U .S. Supreme 886 01:05:06,040 --> 01:05:09,900 Court over the very intellectual honesty of his empire. 887 01:05:10,700 --> 01:05:14,060 This is not just a story of silicon and software. 888 01:05:15,120 --> 01:05:20,080 This is the chronicle of the man who decided to manufacture intelligence 889 01:05:20,840 --> 01:05:25,860 This is Jensen Huang, the architect of the digital brain. 890 01:05:33,420 --> 01:05:36,000 Invidia was not born from abundance. 891 01:05:36,480 --> 01:05:40,100 Its DNA was forged in the raw fires of survival. 892 01:05:41,520 --> 01:05:47,360 Jensen Huang arrived in the United States as a young migrant, but his 893 01:05:47,360 --> 01:05:49,880 destination wasn't an elite prep school. 894 01:05:50,440 --> 01:05:56,040 Due to a clerical misunderstanding by his parents, he was sent to Oneida 895 01:05:56,040 --> 01:06:02,420 Institute in rural Kentucky, a place that, at the time, functioned more as a 896 01:06:02,420 --> 01:06:05,780 reform school for troubled youth than a traditional academy. 897 01:06:06,680 --> 01:06:11,990 At nine years old, The future CEO of one of the world's most valuable companies 898 01:06:11,990 --> 01:06:13,050 wasn't coding. 899 01:06:13,490 --> 01:06:18,590 He was cleaning the toilets of 150 teenagers every single afternoon. 900 01:06:19,870 --> 01:06:24,970 In his personal transcript, Jensen reflects on this with a chilling 901 01:06:25,470 --> 01:06:26,750 I didn't complain. 902 01:06:27,030 --> 01:06:29,090 I just learned to work hard. 903 01:06:29,890 --> 01:06:34,950 That boy learned the first law of accelerated computing decades before it 904 01:06:34,950 --> 01:06:41,000 existed. For a system to be efficient, it must be able to process chaos under 905 01:06:41,000 --> 01:06:42,060 extreme pressure. 906 01:06:43,960 --> 01:06:49,760 By 15, Jensen was the most efficient dishwasher and waiter at a Denny's in 907 01:06:49,760 --> 01:06:50,760 Portland. 908 01:06:50,780 --> 01:06:56,320 I was incredibly shy, he admits, but the chaos of the kitchen forced me out of 909 01:06:56,320 --> 01:06:57,320 my shell. 910 01:06:57,960 --> 01:07:04,780 It is no coincidence that NVIDIA was founded in 1993 inside a booth at that 911 01:07:04,780 --> 01:07:06,060 same restaurant chain. 912 01:07:06,960 --> 01:07:11,600 While the world saw the dawn of the PC as an office tool for spreadsheets, 913 01:07:11,800 --> 01:07:17,180 Jensen, Chris Malachowski, and Curtis Priam saw a fatal weakness. 914 01:07:19,260 --> 01:07:25,360 In 1993, Intel's general -purpose CPU was hitting a physical wall. 915 01:07:26,060 --> 01:07:31,260 In the future of computing with visual and immersive, the traditional serial 916 01:07:31,260 --> 01:07:34,560 architecture would become the bottleneck of human progress. 917 01:07:35,760 --> 01:07:41,980 With only $40 ,000 in startup capital, they founded NVIDIA to chase a ghost, 918 01:07:42,220 --> 01:07:43,560 accelerated computing. 919 01:07:44,620 --> 01:07:49,280 They bet on a market the rest of the industry dismissed as a niche for toys, 920 01:07:49,780 --> 01:07:50,780 video games. 921 01:07:51,360 --> 01:07:56,060 Before Jensen, video games were the ultimate technological flywheel. 922 01:07:56,660 --> 01:08:01,460 He knew that if you could master the massive, real -time rendering of pixels, 923 01:08:01,600 --> 01:08:04,540 you could eventually simulate reality itself. 924 01:08:06,190 --> 01:08:11,030 But before they could reach that glory, they had to survive their first massive 925 01:08:11,030 --> 01:08:13,410 technical abyss, the NV -1. 926 01:08:22,569 --> 01:08:29,470 By 1995, NVIDIA's first massive bet, the NV -1 chip, was ready 927 01:08:29,470 --> 01:08:30,510 to conquer the market. 928 01:08:30,930 --> 01:08:34,490 But Jensen Huang had made a catastrophic technical gamble. 929 01:08:35,790 --> 01:08:40,990 At a time when the industry was undecided, he bet on quadratic texture 930 01:08:41,330 --> 01:08:44,990 a method that used curved surfaces to create 3D images. 931 01:08:45,950 --> 01:08:50,450 It was mathematically intelligent, but it was a lonely path. 932 01:08:51,270 --> 01:08:56,029 The industry hammer dropped when Microsoft released its first DirectX 933 01:08:56,390 --> 01:09:02,149 Microsoft chose triangles, not quads, as the universal language for PC gaming. 934 01:09:03,500 --> 01:09:07,520 This decision rendered NVIDIA's technology instantly obsolete. 935 01:09:08,380 --> 01:09:12,540 The NV1 wasn't just a failure, it was a dead end. 936 01:09:12,979 --> 01:09:18,880 The company was bleeding cash, and as Jensen famously put it, they were 937 01:09:18,880 --> 01:09:21,359 at exactly 30 days of oxygen. 938 01:09:24,359 --> 01:09:29,520 NVIDIA's only lifeline was a strategic contract with the Japanese giant Sega to 939 01:09:29,520 --> 01:09:31,760 build the graphics engine for the Sega Saturn. 940 01:09:32,680 --> 01:09:35,819 but Jensen was trapped in a moral and business dilemma. 941 01:09:36,899 --> 01:09:41,760 He knew that if they continued building the chip for Sega using NVIDIA's flawed 942 01:09:41,760 --> 01:09:47,819 quad technology, Sega would lose the console war to Sony's PlayStation, and 943 01:09:47,819 --> 01:09:49,979 NVIDIA would eventually perish anyway. 944 01:09:50,760 --> 01:09:55,580 In an act of intellectual honesty, or as many at the time called corporate 945 01:09:55,580 --> 01:09:56,580 suicide, 946 01:09:57,080 --> 01:09:58,240 Jensen flew to Japan. 947 01:09:58,960 --> 01:10:05,530 He sat across from Shoichiro Irimajiri, the CEO of Sega, and told him the brutal 948 01:10:05,530 --> 01:10:09,050 truth. Our technology is on the wrong path. 949 01:10:09,370 --> 01:10:13,390 If we finish this project, you will produce an inferior product. 950 01:10:15,050 --> 01:10:16,970 Jensen asked for the impossible. 951 01:10:17,550 --> 01:10:22,530 He asked Sega to terminate the contract, but to pay the remaining $5 million 952 01:10:22,530 --> 01:10:28,430 anyway. If you don't pay us, Jensen pleaded, NVIDIA will cease to exist 953 01:10:28,430 --> 01:10:29,430 tomorrow. 954 01:10:30,380 --> 01:10:34,400 Through the astonishment of the tech world, Irimajiri -san agreed. 955 01:10:35,000 --> 01:10:37,020 He didn't pay for a working chip. 956 01:10:37,240 --> 01:10:39,300 He paid for Jensen's integrity. 957 01:10:41,020 --> 01:10:45,500 That $5 million was the most expensive oxygen in history. 958 01:10:46,420 --> 01:10:50,320 To make it last, Jensen had to fire half of his workforce. 959 01:10:50,940 --> 01:10:54,680 These weren't just employees. They were friends who had shared the Denny's 960 01:10:54,680 --> 01:10:55,680 dream. 961 01:10:55,840 --> 01:11:00,080 This trauma institutionalized a permanent state of emergency at NVIDIA. 962 01:11:01,480 --> 01:11:06,920 With the remaining team, Jensen funneled every cent into the Reva 128. 963 01:11:08,000 --> 01:11:12,680 They abandoned quads and embraced Microsoft's triangles with a vengeance. 964 01:11:13,200 --> 01:11:19,860 When it launched in 1997, the Reva 128 was 400 % faster 965 01:11:19,860 --> 01:11:21,600 than anything else on the market. 966 01:11:22,670 --> 01:11:25,070 It was a dive catch of epic proportions. 967 01:11:25,930 --> 01:11:28,030 NVIDIA was no longer just a survivor. 968 01:11:28,370 --> 01:11:30,410 It had become a hunter. 969 01:11:31,570 --> 01:11:37,270 But as Jensen looked at the horizon, he saw 70 rivals waiting to kill him. 970 01:11:37,530 --> 01:11:39,770 The war was only beginning. 971 01:11:47,230 --> 01:11:51,130 The success of the Reval 128 was a dive catch. 972 01:11:51,740 --> 01:11:54,740 but it placed NVIDIA in the middle of a slaughterhouse. 973 01:11:55,540 --> 01:12:01,480 By 1997, there were over 70 companies fighting for the soul of the 3D graphics 974 01:12:01,480 --> 01:12:02,480 market. 975 01:12:02,840 --> 01:12:07,020 It was a commodity war where price -cutting was the only weapon for most. 976 01:12:08,180 --> 01:12:13,120 Jensen Huang realized that if NVIDIA played by the industry's rules, they 977 01:12:13,120 --> 01:12:14,660 eventually be ground into dust. 978 01:12:16,160 --> 01:12:18,620 He decided to break the laws of time. 979 01:12:19,720 --> 01:12:25,180 The industry standard for developing a new chip was 18 to 24 months, following 980 01:12:25,180 --> 01:12:26,740 the steady beat of Moore's Law. 981 01:12:27,660 --> 01:12:31,640 Jensen gathered his engineers and imposed a suicidal mandate. 982 01:12:32,300 --> 01:12:37,780 NVIDIA would release a brand new, groundbreaking architecture every six 983 01:12:39,700 --> 01:12:42,440 It was a strategy of relentless execution. 984 01:12:43,220 --> 01:12:50,100 By the time a competitor like 3DFX or S3 could react to one NVIDIA chip, Jensen 985 01:12:50,100 --> 01:12:51,820 had already launched two more. 986 01:12:52,720 --> 01:12:56,600 This forced the competition into a permanent state of obsolescence. 987 01:12:57,220 --> 01:13:03,020 To achieve this, NVIDIA had to reinvent its internal engineering, running 988 01:13:03,020 --> 01:13:07,660 multiple design teams in parallel, a massive financial risk that pushed the 989 01:13:07,660 --> 01:13:09,900 company to the edge of its operational capacity. 990 01:13:10,440 --> 01:13:14,520 In 1999, the war reached its climax. 991 01:13:15,220 --> 01:13:18,060 NVIDIA released the GeForce 256. 992 01:13:20,140 --> 01:13:23,180 Jensen didn't just market it as a faster card. 993 01:13:23,440 --> 01:13:26,600 He coined a term that would redefine computing history. 994 01:13:27,120 --> 01:13:30,420 The GPU, Graphic Processing Unit. 995 01:13:31,100 --> 01:13:32,700 This wasn't just branding. 996 01:13:33,480 --> 01:13:40,480 Technically, the G4 -256 moved the transformer -like in calculation, the 997 01:13:40,480 --> 01:13:45,340 heavy mathematical lifting of 3D, off the CPU and onto the chip itself. 998 01:13:45,940 --> 01:13:48,180 It was the birth of a new era. 999 01:13:49,350 --> 01:13:53,710 This performance leap was so massive that NVIDIA secured the prestigious 1000 01:13:53,710 --> 01:13:59,350 contract for the original Microsoft Xbox, receiving a crucial $200 million 1001 01:13:59,350 --> 01:14:00,350 advance. 1002 01:14:01,850 --> 01:14:03,810 The six -month cycle worked. 1003 01:14:04,230 --> 01:14:10,610 By the early 2000s, the 70 competitors had been reduced to just two, NVIDIA and 1004 01:14:10,610 --> 01:14:11,610 API. 1005 01:14:11,970 --> 01:14:17,750 In a final act of dominance, NVIDIA acquired the assets of its former idol 1006 01:14:17,750 --> 01:14:20,540 arch -rival, 3DFX in 2000. 1007 01:14:21,860 --> 01:14:23,780 Jensen had cleared the board. 1008 01:14:24,060 --> 01:14:27,080 He was the undisputed king of gaming. 1009 01:14:27,660 --> 01:14:32,660 But at the very moment of his greatest triumph, he began to look at the high 1010 01:14:32,660 --> 01:14:34,060 -performance computing market. 1011 01:14:34,640 --> 01:14:39,460 He realized that the GPU's massive parallel math could do more than just 1012 01:14:39,460 --> 01:14:43,280 pixels. It could solve the world's most complex problems. 1013 01:14:44,000 --> 01:14:48,120 The seeds of CUDA and the $10 billion gamble. 1014 01:14:48,670 --> 01:14:49,670 were being planted. 1015 01:14:57,010 --> 01:15:02,290 By 2006, NVIDIA was the undisputed king of the gaming world. 1016 01:15:02,750 --> 01:15:04,890 But Jensen Huang was reckless. 1017 01:15:05,230 --> 01:15:09,710 He realized that the same parallel processing power that rendered pixels 1018 01:15:09,710 --> 01:15:13,930 World of Warcraft could be used to solve the world's most complex mathematical 1019 01:15:13,930 --> 01:15:14,930 problems. 1020 01:15:15,690 --> 01:15:17,390 He launched CUDA. 1021 01:15:18,010 --> 01:15:20,150 compute -unified device architecture. 1022 01:15:20,670 --> 01:15:24,510 It was a declaration of war against the CPU -centric world. 1023 01:15:25,370 --> 01:15:27,770 The goal was simple, yet insane. 1024 01:15:28,350 --> 01:15:32,770 Transform every NVIDIA GPU into a general -purpose supercomputer. 1025 01:15:33,930 --> 01:15:36,810 But this decision came with a staggering cost. 1026 01:15:37,610 --> 01:15:43,330 Jensen mandated that every single GPU NVIDIA manufactured, from the high -end 1027 01:15:43,330 --> 01:15:47,930 workstation cards to the cheapest laptop chips, must include the extra 1028 01:15:47,930 --> 01:15:50,910 transistors and hardware logic to support CUDA. 1029 01:15:52,070 --> 01:15:54,250 Wall Street was horrified. 1030 01:15:55,650 --> 01:16:02,450 For nearly a decade, NVIDIA spent billions, estimated at over $10 billion 1031 01:16:02,450 --> 01:16:07,050 cumulative R &D, on a software platform that almost no one was using. 1032 01:16:08,070 --> 01:16:13,390 Profit margins, which once sat comfortably high, were sacrificed at the 1033 01:16:13,390 --> 01:16:14,390 this vision. 1034 01:16:15,139 --> 01:16:19,280 Analysts mocked the strategy, calling it the bridge to nowhere. 1035 01:16:20,040 --> 01:16:26,000 During the 2008 financial crisis, NVIDIA's market cap plummeted and the 1036 01:16:26,000 --> 01:16:28,460 was once again staring into the abyss. 1037 01:16:29,860 --> 01:16:32,260 But Jensen wasn't just building hardware. 1038 01:16:32,480 --> 01:16:35,140 He was building a software moat. 1039 01:16:35,520 --> 01:16:40,780 He sent NVIDIA engineers to universities around the world, helping professors 1040 01:16:40,780 --> 01:16:43,380 teach parallel programming using CUDA. 1041 01:16:44,520 --> 01:16:45,940 He was ceding the ground. 1042 01:16:46,520 --> 01:16:52,780 While competitors like Intel and AMD focused on making faster chips, Jensen 1043 01:16:52,780 --> 01:16:54,220 building an entire language. 1044 01:16:55,000 --> 01:16:58,660 By the time a developer learned CUDA, they were locked in. 1045 01:16:59,320 --> 01:17:02,800 Switching to a competitor wouldn't just mean buying a new chip. 1046 01:17:03,060 --> 01:17:06,280 It would mean rewriting millions of lines of code. 1047 01:17:07,740 --> 01:17:12,720 Year after year, Jensen defended CUDA in boardrooms and earning calls. 1048 01:17:13,550 --> 01:17:18,450 He practiced what he called long -term commitment to revision, even when the 1049 01:17:18,450 --> 01:17:19,790 data didn't yet support it. 1050 01:17:20,470 --> 01:17:23,830 He was waiting for a killer app for accelerated computing. 1051 01:17:24,730 --> 01:17:29,190 He didn't know what it would be, but he knew that if data grew exponentially, 1052 01:17:29,710 --> 01:17:33,130 the serial processing of the CPU would eventually fail. 1053 01:17:34,070 --> 01:17:37,470 The silence of the cuda winter was about to be broken. 1054 01:17:38,370 --> 01:17:44,630 In a lab at the University of Toronto, A PhD student named Alex Krusevsky was 1055 01:17:44,630 --> 01:17:49,130 about to feed a neural network called AlexNet into those NVIDIA GPUs. 1056 01:17:49,910 --> 01:17:55,750 The big bang of artificial intelligence was seconds away, and Jensen Huang was 1057 01:17:55,750 --> 01:17:59,970 the only person on Earth who had already built the engine to power it. 1058 01:18:07,730 --> 01:18:09,430 The year was 2012. 1059 01:18:10,390 --> 01:18:15,250 While the world saw just another academic competition, Jensen Huang saw 1060 01:18:15,250 --> 01:18:17,670 spark that would ignite a global revolution. 1061 01:18:18,350 --> 01:18:25,330 A neural network called AlexNet, powered by NVIDIA GPUs, crushed the competition 1062 01:18:25,330 --> 01:18:26,570 in image recognition. 1063 01:18:27,110 --> 01:18:30,050 It was the big bang of deep learning. 1064 01:18:30,950 --> 01:18:35,210 Jensen didn't just celebrate, he pivoted the entire company. 1065 01:18:35,690 --> 01:18:41,100 He realized that the $10 billion gamble on CUDA had finally found its goal, 1066 01:18:41,400 --> 01:18:42,920 artificial intelligence. 1067 01:18:44,120 --> 01:18:49,480 This pivot transformed NVIDIA from a graphics card company into the 1068 01:18:49,480 --> 01:18:52,560 engine of the world's most powerful data centers. 1069 01:18:54,160 --> 01:18:56,860 Jensen's vision was no longer about drawing pixels. 1070 01:18:57,060 --> 01:18:59,540 It was about generative AI. 1071 01:19:00,300 --> 01:19:07,020 By the time ChatGPT launched in late 2022, NVIDIA didn't just have a head 1072 01:19:07,790 --> 01:19:09,870 They were the only ones at the starting line. 1073 01:19:12,310 --> 01:19:15,470 Jensen acted with a speed that terrified his competitors. 1074 01:19:15,910 --> 01:19:20,890 He didn't just wait for orders. He re -engineered NVIDIA's entire roadmap. 1075 01:19:21,730 --> 01:19:28,730 In 2016, he personally delivered the first NVIDIA DGX -1, the world's first 1076 01:19:28,730 --> 01:19:33,990 AI supercomputer in a box, to a then -small non -profit called OpenAI. 1077 01:19:34,470 --> 01:19:35,850 He was very clear. 1078 01:19:36,510 --> 01:19:38,230 This will change the world. 1079 01:19:41,490 --> 01:19:44,150 Technically, this period was about specialization. 1080 01:19:44,930 --> 01:19:47,850 NVIDIA began adding tensor cores to its chips. 1081 01:19:48,370 --> 01:19:51,950 These weren't for graphics. They were designed specifically for the deep 1082 01:19:51,950 --> 01:19:54,270 learning math that powers neural networks. 1083 01:19:55,470 --> 01:20:00,070 NVIDIA was no longer just making a faster graphics card. It was building a 1084 01:20:00,070 --> 01:20:01,070 specialized brain. 1085 01:20:01,890 --> 01:20:05,110 By 2017, the momentum was unstoppable. 1086 01:20:06,030 --> 01:20:10,730 Every major tech giant was building AI labs, and they all had one thing in 1087 01:20:10,730 --> 01:20:13,310 common. They were built on NVIDIA's stack. 1088 01:20:14,410 --> 01:20:17,870 This was the era when the software moat became a fortress. 1089 01:20:18,790 --> 01:20:22,750 Thousands of researchers were now writing their doctoral thesis on CUDA. 1090 01:20:24,050 --> 01:20:28,570 If a competitor wanted to challenge NVIDIA, they wouldn't just need a better 1091 01:20:28,570 --> 01:20:33,430 chip. They would have to convince the world's brightest minds to forget 1092 01:20:33,430 --> 01:20:34,890 everything they had learned. 1093 01:20:36,390 --> 01:20:40,650 But as the AI revolution took hold, an unexpected shadow emerged. 1094 01:20:41,210 --> 01:20:46,310 A new craze called Bitcoin and Ethereum began to consume NVIDIA's supply. 1095 01:20:47,130 --> 01:20:52,870 To the world, NVIDIA looked invincible, but internally, Jensen was wary. 1096 01:20:53,510 --> 01:20:56,330 Jensen knew that every bubble eventually burned. 1097 01:20:57,250 --> 01:21:02,290 This period of explosive, accidental growth from crypto miners was creating a 1098 01:21:02,290 --> 01:21:04,210 shadow over the company's true mission. 1099 01:21:05,260 --> 01:21:09,500 Setting the stage for a high -stakes legal battle over corporate transparency 1100 01:21:09,500 --> 01:21:13,800 and a financial storm that would test the very foundations of its leadership. 1101 01:21:19,760 --> 01:21:26,160 In 2018, NVIDIA was riding a wave that looked like a miracle, but felt like a 1102 01:21:26,160 --> 01:21:31,320 mirage. The explosion of cryptocurrency mining had created an insatiable hunger 1103 01:21:31,320 --> 01:21:32,480 for G -Force cards. 1104 01:21:33,900 --> 01:21:38,080 To the outside world, NVIDIA's revenue was reaching historic heights. 1105 01:21:38,500 --> 01:21:42,860 However, beneath the surface, a dangerous ambiguity was growing. 1106 01:21:43,860 --> 01:21:48,520 Jensen Huang insisted that the growth was driven by a gaming renaissance, but 1107 01:21:48,520 --> 01:21:50,040 the reality was more volatile. 1108 01:21:50,620 --> 01:21:54,220 The mirage evaporated in late 2018. 1109 01:21:54,940 --> 01:22:00,180 The crypto winter arrived, and the demand for mining chips vanished 1110 01:22:01,570 --> 01:22:05,770 NVIDIA was left with a massive surplus of inventory, and the market's reaction 1111 01:22:05,770 --> 01:22:06,770 was brutal. 1112 01:22:06,890 --> 01:22:11,350 The company's stock price plummeted by 28 % in a single day. 1113 01:22:12,490 --> 01:22:17,270 The invincible architect of AI was suddenly facing a crisis of credibility. 1114 01:22:19,030 --> 01:22:22,870 This financial collapse ignited a high -stakes legal battle that would 1115 01:22:22,870 --> 01:22:25,490 eventually reach the steps of the US Supreme Court. 1116 01:22:26,450 --> 01:22:30,150 A group of institutional investors filed a class -action lawsuit. 1117 01:22:30,860 --> 01:22:34,280 alleging that Jensen Huang had deliberately misled the market. 1118 01:22:34,740 --> 01:22:38,500 The core of the case rested on a single, devastating word. 1119 01:22:39,500 --> 01:22:42,100 Scienza. The intense disease. 1120 01:22:43,240 --> 01:22:45,080 The accusation was sharp. 1121 01:22:45,440 --> 01:22:49,720 Investors claimed that internal NVIDIA reports clearly showed over a billion 1122 01:22:49,720 --> 01:22:54,400 dollars in revenue attributed to gamers was actually coming from crypto miners. 1123 01:22:55,260 --> 01:22:58,840 Jensen fought back, defending his intellectual honesty. 1124 01:22:59,450 --> 01:23:03,190 and arguing that the expert opinions used against him were nothing more than 1125 01:23:03,190 --> 01:23:04,190 speculation. 1126 01:23:04,930 --> 01:23:07,270 This battle, known as Petition No. 1127 01:23:07,510 --> 01:23:14,410 23 -970, became a landmark moment for Silicon Valley, questioning how much a 1128 01:23:14,410 --> 01:23:18,530 must disclose when their technology accidentally conquered the market they 1129 01:23:18,530 --> 01:23:19,770 didn't intend to lead. 1130 01:23:21,490 --> 01:23:23,470 While lawyers argued in Washington, 1131 01:23:24,310 --> 01:23:26,550 Jensen was already looking past the wreckage. 1132 01:23:27,120 --> 01:23:31,460 He didn't let the legal storm or the inventory crisis blow down his ultimate 1133 01:23:31,460 --> 01:23:37,240 plan. He doubled down on the data center, acquiring Mellanox for $7 1134 01:23:37,240 --> 01:23:39,620 control the highways between his chips. 1135 01:23:40,460 --> 01:23:45,340 He was preparing for a world where AI wouldn't just be a research project, but 1136 01:23:45,340 --> 01:23:47,580 the operating system of the entire planet. 1137 01:23:48,660 --> 01:23:54,200 The storm of 2018 had been a warning. The era of generative AI was about to 1138 01:23:54,200 --> 01:23:55,200 provide the answer. 1139 01:24:01,610 --> 01:24:04,810 By 2022, the world had changed. 1140 01:24:05,470 --> 01:24:11,190 The launch of ChatGPT signaled the arrival of the generative AI era, and 1141 01:24:11,190 --> 01:24:13,570 was the only company prepared to power it. 1142 01:24:14,530 --> 01:24:20,170 But as Jensen Huang stood on the brink of total market dominance, a new wall 1143 01:24:20,170 --> 01:24:23,970 built, not by a competitor, but by the US government. 1144 01:24:24,930 --> 01:24:28,710 Washington imposed strict export controls on high -end AI chips. 1145 01:24:29,110 --> 01:24:31,910 For NVIDIA, the stakes were astronomical. 1146 01:24:33,430 --> 01:24:38,870 According to the geographical revenue data, China accounted for approximately 1147 01:24:38,870 --> 01:24:42,210 % to 25 % of the company's total business. 1148 01:24:43,590 --> 01:24:49,050 Overnight, Jensen had to navigate a geopolitical minefield, redesigning 1149 01:24:49,050 --> 01:24:53,350 specifically to comply with regulations while trying to keep his most important 1150 01:24:53,350 --> 01:24:54,730 market from slipping away. 1151 01:24:56,590 --> 01:25:00,900 Jensen's answer to the geopolitical and technical pressure was the Blackwell 1152 01:25:00,900 --> 01:25:01,900 architecture. 1153 01:25:02,060 --> 01:25:06,320 If the H100 was a spark, Blackwell was the sun. 1154 01:25:07,180 --> 01:25:13,080 Packing an incredible 208 billion transistors, it delivered up to 30 times 1155 01:25:13,080 --> 01:25:15,700 performance of its predecessor for certain AI tasks. 1156 01:25:16,780 --> 01:25:19,960 But Blackwell represented a deeper strategic shift. 1157 01:25:20,420 --> 01:25:22,820 NVIDIA was no longer just a chipmaker. 1158 01:25:24,500 --> 01:25:28,120 Jensen was now building entire AI factories. 1159 01:25:29,160 --> 01:25:34,100 By integrating Mellanox networking technology, he controlled the highways 1160 01:25:34,100 --> 01:25:38,140 allowed thousands of chips to talk to each other as if they were a single 1161 01:25:38,140 --> 01:25:39,140 brain. 1162 01:25:40,080 --> 01:25:44,640 This system -on -a -cluster approach meant that even if a competitor produced 1163 01:25:44,640 --> 01:25:48,820 faster individual chip, they couldn't compete with the sheer efficiency of the 1164 01:25:48,820 --> 01:25:49,820 NVIDIA ecosystem. 1165 01:25:51,380 --> 01:25:53,740 The financial results were staggering. 1166 01:25:54,060 --> 01:25:55,600 By early 2024, 1167 01:25:56,470 --> 01:26:03,090 NVIDIA's data center revenue had surged to over $47 billion, a 217 % 1168 01:26:03,090 --> 01:26:04,870 increase in a single year. 1169 01:26:05,510 --> 01:26:11,650 The company was operating with 78 .4 % growth margins, profit levels usually 1170 01:26:11,650 --> 01:26:15,070 reserved for software giants, not hardware manufacturers. 1171 01:26:16,190 --> 01:26:22,290 On June 18, 2024, NVIDIA became the most valuable company on the planet. 1172 01:26:23,350 --> 01:26:28,050 Yet... Even if he stood at the summit, Jensen refused to relax. 1173 01:26:28,730 --> 01:26:33,950 He looked at the 60 -year history of semiconductors, the rise and fall of 1174 01:26:34,190 --> 01:26:39,190 the cycles of Samsung and TI, and he knew that being on top was the most 1175 01:26:39,190 --> 01:26:40,290 dangerous place to be. 1176 01:26:40,810 --> 01:26:44,190 His next challenge wouldn't just be about chips. 1177 01:26:44,610 --> 01:26:47,810 It would be about giving AI a physical body. 1178 01:26:54,160 --> 01:26:55,160 In 2024, 1179 01:26:55,860 --> 01:27:00,400 Jensen Huang had already conquered the digital world, but his eyes were fixed 1180 01:27:00,400 --> 01:27:02,440 a new frontier, the physical one. 1181 01:27:03,020 --> 01:27:08,200 He declared that the next wave of AI would be physical AI, intelligence that 1182 01:27:08,200 --> 01:27:12,740 doesn't just process text or images, but understands the laws of physics. 1183 01:27:13,780 --> 01:27:19,300 Everything that moves, from autonomous cars to humanoid robots, would 1184 01:27:19,300 --> 01:27:21,100 be powered by an NVIDIA brain. 1185 01:27:22,320 --> 01:27:26,000 This identifies it as the third pillar of NVIDIA's future. 1186 01:27:26,620 --> 01:27:32,660 To win this race, Jensen isn't just building chips, he's building the 1187 01:27:33,320 --> 01:27:37,920 This is a digital world where robots are trained millions of times in a virtual 1188 01:27:37,920 --> 01:27:41,480 simulation before they ever step into a real factory. 1189 01:27:42,600 --> 01:27:48,020 By the time a robot starts its job, it has already lived a thousand lifetimes 1190 01:27:48,020 --> 01:27:49,020 experience. 1191 01:27:49,150 --> 01:27:52,350 Jensen's strategy is a total vertical integration. 1192 01:27:52,830 --> 01:27:56,750 He is transforming NVIDIA into a provider of AI factories. 1193 01:27:57,510 --> 01:28:02,830 He believes that in the future, every company will have two factories, one 1194 01:28:02,830 --> 01:28:06,650 produces physical goods and a digital one that produces intelligence. 1195 01:28:07,550 --> 01:28:12,450 With the Monox networking high -speed highways and the CUDA software fortress, 1196 01:28:13,130 --> 01:28:16,830 Jensen has ensured that the entire infrastructure of this new industrial 1197 01:28:16,830 --> 01:28:23,210 revolution runs on NVIDIA. When asked about his legacy, Jensen doesn't talk 1198 01:28:23,210 --> 01:28:25,610 about stock prices or trillions of dollars. 1199 01:28:25,850 --> 01:28:30,170 He talks about material sciences and scientific discovery. 1200 01:28:30,870 --> 01:28:36,450 He believes AI will give humans superpowers, helping us solve climate 1201 01:28:36,610 --> 01:28:41,690 cure diseases, and handle the dangerous and mundane tasks so we can focus on 1202 01:28:41,690 --> 01:28:44,450 what truly makes us human, curiosity. 1203 01:28:49,270 --> 01:28:55,010 By 2025, the world had entered a state of compute geopolitics. 1204 01:28:55,670 --> 01:29:01,510 NVIDIA was no longer just a company. It had become a strategic resource, similar 1205 01:29:01,510 --> 01:29:02,890 to oil or grain. 1206 01:29:03,690 --> 01:29:09,480 The launch of the Bacwell B200 hadn't just met demand, it had ignited a global 1207 01:29:09,480 --> 01:29:16,220 scramble. Nations like Japan, France, and the UAE began building sovereign AI 1208 01:29:16,220 --> 01:29:21,040 clouds, realizing that depending on a few Silicon Valley giants for 1209 01:29:21,040 --> 01:29:23,220 was a national security risk. 1210 01:29:24,020 --> 01:29:29,200 But as 2025 progressed, a new whisper began to haunt the industry. 1211 01:29:29,680 --> 01:29:30,740 The wall. 1212 01:29:31,060 --> 01:29:34,680 For years, AI progress relied on scaling laws. 1213 01:29:35,400 --> 01:29:39,600 The idea that more data and more GPUs would inevitably lead to more 1214 01:29:39,600 --> 01:29:44,980 intelligence. However, in 2026, the returns are starting to diminish. 1215 01:29:45,680 --> 01:29:50,640 Data centers are becoming so massive, they require their own dedicated nuclear 1216 01:29:50,640 --> 01:29:55,240 power plants, and the low -hanging fruit of Internet data has been exhausted. 1217 01:29:56,780 --> 01:30:00,080 Jensen's response to the wall is typically defiant. 1218 01:30:00,500 --> 01:30:04,520 He pivoted the industry towards synthetic data and reasoning models. 1219 01:30:05,360 --> 01:30:12,320 In 2026, NVIDIA's focus has shifted from simply training AI to inference at 1220 01:30:12,320 --> 01:30:18,340 scale. The goal is no longer just to build a model that knows everything, but 1221 01:30:18,340 --> 01:30:22,700 build a system that thinks through a problem for days if necessary, using 1222 01:30:22,700 --> 01:30:25,580 massive clusters of GPUs to reach a breakthrough. 1223 01:30:27,180 --> 01:30:31,280 The competition in 2026 has never been fiercer. 1224 01:30:34,040 --> 01:30:39,020 Amazon, Google, and Microsoft have become its most dangerous rivals, 1225 01:30:39,020 --> 01:30:43,300 billions into their own custom AI chips to escape the NVIDIA attack. 1226 01:30:44,120 --> 01:30:47,320 Yet, the software moat remains unbreached. 1227 01:30:47,560 --> 01:30:52,660 While others build chips, Jensen is building the entire ecosystem, the 1228 01:30:52,660 --> 01:30:57,280 networking, the libraries, and the pre -trained models that make a competitor's 1229 01:30:57,280 --> 01:31:01,460 hardware feel like a relic before it even leaves the factory. 1230 01:31:02,700 --> 01:31:07,040 In this era, Jensen Huang has become one of the world's most influential 1231 01:31:07,040 --> 01:31:12,520 diplomat. He navigates a world where the power grid is the new bottleneck, and 1232 01:31:12,520 --> 01:31:16,400 where a single shipment of chips can determine the economic future of a 1233 01:31:17,560 --> 01:31:23,320 The trillion -dollar question of 2026 is no longer if AI will change the world, 1234 01:31:23,520 --> 01:31:26,500 but who will own the infrastructure of that change. 1235 01:31:32,460 --> 01:31:36,760 The story of NVIDIA is often told as a series of lucky breaks or inevitable 1236 01:31:36,760 --> 01:31:42,960 triumphs. But as we look at the empire Jensen Huang has built, the reality is 1237 01:31:42,960 --> 01:31:46,040 far more deliberate and far more precarious. 1238 01:31:46,900 --> 01:31:52,340 In 2026, the company stands at the center of the greatest industrial shift 1239 01:31:52,340 --> 01:31:53,340 human history. 1240 01:31:53,940 --> 01:32:00,140 Yet for Jensen, the valuation of $3, $4, or $5 trillion is a lagging indicator. 1241 01:32:00,660 --> 01:32:03,030 The true metric, is the oxygen. 1242 01:32:04,070 --> 01:32:08,230 Throughout his journey, from the dish pits of Denny's to the halls of the 1243 01:32:08,230 --> 01:32:12,830 Supreme Court, Jensen has maintained a philosophy of intellectual honesty. 1244 01:32:13,910 --> 01:32:19,610 He admits when the technology is wrong, he pivots when the markets shift, and he 1245 01:32:19,610 --> 01:32:22,070 invests billions when the world calls them a fool. 1246 01:32:22,950 --> 01:32:28,350 He has turned a semiconductor company into a geopolitical superpower, a 1247 01:32:28,350 --> 01:32:32,640 fortress, and the primary architect of a new form of life. 1248 01:32:33,800 --> 01:32:38,720 Critics ask if NVIDIA is a bubble waiting to burst, or if the stealing 1249 01:32:38,720 --> 01:32:40,500 AI will eventually hit a dead end. 1250 01:32:40,980 --> 01:32:44,760 But Jensen doesn't operate on the timeline of a stock market cycle. 1251 01:32:45,140 --> 01:32:48,500 He operates on the timeline of human evolution. 1252 01:32:49,400 --> 01:32:51,400 He isn't just selling chips. 1253 01:32:51,720 --> 01:32:56,480 He is selling the marginal cost of intelligence, making the most valuable 1254 01:32:56,480 --> 01:32:58,780 resource in the universe so abundant. 1255 01:32:59,420 --> 01:33:03,040 that it changes the very definition of what is possible. 1256 01:33:04,580 --> 01:33:08,820 Jensen often says that he wakes up every morning with the same feeling he had in 1257 01:33:08,820 --> 01:33:12,940 1993, the feeling that the company is going out of business. 1258 01:33:13,800 --> 01:33:18,920 It is this productive paranoia that prevents the cyclical trap that claimed 1259 01:33:18,920 --> 01:33:19,920 giants of the past. 1260 01:33:20,800 --> 01:33:23,100 He doesn't want to be the king of a legacy. 1261 01:33:23,620 --> 01:33:26,140 He wants to be the architect of a future. 1262 01:33:26,650 --> 01:33:28,950 that hasn't even been imagined yet. 1263 01:33:31,210 --> 01:33:33,270 Run, don't walk. 1264 01:33:33,790 --> 01:33:37,770 Either you are running for food, or you are running from being food. 1265 01:33:38,310 --> 01:33:43,670 In the era of the digital brain, the race has only just begun. 1266 01:35:09,070 --> 01:35:12,570 The financial world is in constant transformation. But in this decade, 1267 01:35:12,770 --> 01:35:16,130 digitalization has accelerated that change faster than anyone imagined. 1268 01:35:17,930 --> 01:35:21,390 Today, money, investments, and assets flow through code. 1269 01:35:22,310 --> 01:35:24,730 Silent, transparent, and borderless. 1270 01:35:25,670 --> 01:35:30,370 Cryptocurrencies, led by Bitcoin, marked the beginning of a new era. They shook 1271 01:35:30,370 --> 01:35:34,170 the foundations of the global financial system, sparking both excitement and 1272 01:35:34,170 --> 01:35:38,190 skepticism. Yet behind that phenomenon emerged something even deeper. 1273 01:35:38,990 --> 01:35:43,190 Tokenization. A technology redefining ownership, exchange, and value. 1274 01:35:43,730 --> 01:35:47,430 Decentralized, programmable, and capable of operating 24 hours a day without 1275 01:35:47,430 --> 01:35:50,510 intermediaries. What once seemed like a promise has become a reality. 1276 01:35:50,850 --> 01:35:55,410 A token is basically a database entry, and it says which address, which is 1277 01:35:55,410 --> 01:35:59,750 basically the digital place where a token is stored, how many pieces, how 1278 01:35:59,750 --> 01:36:03,330 tokens it has, and is implemented by its local program code. 1279 01:36:03,630 --> 01:36:06,430 The idea is simple. The impact, enormous. 1280 01:36:06,970 --> 01:36:11,410 Each token represents a fraction of an asset, a share, a bond, a property, or 1281 01:36:11,410 --> 01:36:15,670 even a work of art, all recorded on a blockchain, a global tamper -proof 1282 01:36:15,870 --> 01:36:18,230 You know, you can look at the Genesis block as a picket sign. 1283 01:36:18,650 --> 01:36:24,650 It was a protest, really, against what many people viewed as financial 1284 01:36:24,650 --> 01:36:28,710 injustices. What began as an alternative to financial power has become the 1285 01:36:28,710 --> 01:36:30,730 infrastructure of a new economic system. 1286 01:36:31,050 --> 01:36:34,950 We believe the next step going forward will be the tokenization of financial 1287 01:36:34,950 --> 01:36:35,950 assets. 1288 01:36:36,320 --> 01:36:42,280 And that means every stock, every bond will have its own basically QSIP. It'll 1289 01:36:42,280 --> 01:36:46,900 be on one general ledger. By 2025, that step is already underway. 1290 01:36:47,200 --> 01:36:52,500 The tokenized assets market has surpassed $1 trillion in regulation. 1291 01:36:52,500 --> 01:36:56,620 Europe's MISI framework to the ESSI's latest guidelines, it's shaping a global 1292 01:36:56,620 --> 01:37:02,530 ecosystem. Basically aim to target some specific assets in the crypto industry 1293 01:37:02,530 --> 01:37:05,930 and certain services linked to those crypto assets. 1294 01:37:06,230 --> 01:37:09,870 Meanwhile, in the United States, companies like Securitize are bridging 1295 01:37:09,870 --> 01:37:12,070 traditional finance with the digital world. 1296 01:37:12,630 --> 01:37:16,090 Blockchain technology and tokenization brings the most suitable, most modern 1297 01:37:16,090 --> 01:37:19,250 ledger technology, ideal for modernizing the market. 1298 01:37:19,890 --> 01:37:24,090 Tokenization promises more than efficiency. It points toward a financial 1299 01:37:24,090 --> 01:37:26,910 that is faster, more transparent, and more inclusive. 1300 01:37:27,370 --> 01:37:29,130 where value moves at the speed of information. 1301 01:37:30,450 --> 01:37:32,550 The future of money has already begun. 1302 01:37:34,630 --> 01:37:37,770 This is the journey toward the economic system of the future. 1303 01:37:40,690 --> 01:37:45,170 As early as about 5 ,000 years ago, people traded by exchanging goods or 1304 01:37:45,170 --> 01:37:46,170 services. 1305 01:37:48,250 --> 01:37:53,230 Over time, opportunities developed to also trade shares in goods or services 1306 01:37:53,230 --> 01:37:55,890 even sell them to the public in order to raise capital. 1307 01:37:58,990 --> 01:38:03,130 This is how the stock markets came into being, where companies offer individual 1308 01:38:03,130 --> 01:38:07,430 small company shares to a variety of investors to invest in the future of the 1309 01:38:07,430 --> 01:38:08,430 company. 1310 01:38:10,890 --> 01:38:15,050 This need for shareholding has increased more and more and ultimately developed 1311 01:38:15,050 --> 01:38:16,730 into the global financial market. 1312 01:38:20,530 --> 01:38:23,910 Tokenization meets this need in an even more extreme way. 1313 01:38:24,380 --> 01:38:28,980 This is because tokenization is a further segmentation of a unit or 1314 01:38:28,980 --> 01:38:30,980 into other individual components. 1315 01:38:32,640 --> 01:38:34,500 A kind of fractionalization. 1316 01:38:34,840 --> 01:38:39,560 For example, shares can also be further fractioned and the resulting units can 1317 01:38:39,560 --> 01:38:40,640 in turn be traded. 1318 01:38:41,980 --> 01:38:47,400 However, the special and new thing about tokenization is not the segmentation, 1319 01:38:47,480 --> 01:38:52,140 but it's linking with another process that makes tokenization interesting in 1320 01:38:52,140 --> 01:38:53,140 first place. 1321 01:38:53,610 --> 01:38:57,510 the digital and decentralized storage of the fractions in the blockchain. 1322 01:38:59,850 --> 01:39:04,150 Individual sectors of the market for tokenized assets are currently still in 1323 01:39:04,150 --> 01:39:06,490 kind of discovery or experimentation phase. 1324 01:39:08,390 --> 01:39:11,910 Its value is estimated at less than $20 billion. 1325 01:39:12,650 --> 01:39:17,530 The value of the total market for digital assets is about $350 billion. 1326 01:39:20,200 --> 01:39:23,320 This is where the enormous growth potential becomes clear. 1327 01:39:24,400 --> 01:39:29,380 Tokenization and blockchain technology could fundamentally change the financial 1328 01:39:29,380 --> 01:39:30,380 and banking sector. 1329 01:39:30,940 --> 01:39:37,780 By 2027, this growth will increase dramatically to an estimated $6 .89 1330 01:39:40,110 --> 01:39:45,350 Major institutions such as BlackRock, JPMorgan, and HSBC are already using 1331 01:39:45,350 --> 01:39:49,570 tokenized platforms to issue real -world assets on networks like Ethereum and 1332 01:39:49,570 --> 01:39:53,370 Polygon. Digital funds and tokenized bonds are no longer a promise. 1333 01:39:53,590 --> 01:39:55,910 They are now part of the global financial system. 1334 01:39:56,190 --> 01:40:00,090 We believe the next step going forward will be the tokenization of financial 1335 01:40:00,090 --> 01:40:03,730 assets. And that means every stock... 1336 01:40:03,950 --> 01:40:08,810 Every bond will have its own basically QSIP. It'll be on one general ledger. 1337 01:40:08,850 --> 01:40:13,650 Every investor, you and I, will have our own number, our own identification. 1338 01:40:14,450 --> 01:40:19,050 We could rid ourselves of all issues around illicit activities about bonds 1339 01:40:19,050 --> 01:40:23,910 stocks and digital by having a tokenization. 1340 01:40:24,210 --> 01:40:28,750 But the most important thing, we can customize strategies through 1341 01:40:28,750 --> 01:40:30,530 that fits every individual. 1342 01:40:31,280 --> 01:40:35,200 We would have instantaneous settlement. Think about all the costs of settling 1343 01:40:35,200 --> 01:40:36,200 bonds and stocks. 1344 01:40:36,360 --> 01:40:40,860 But if you had a tokenization, everything would be immediate because 1345 01:40:40,860 --> 01:40:41,860 line item. 1346 01:40:42,000 --> 01:40:46,420 And so we believe this is a technological transformation for 1347 01:40:46,800 --> 01:40:51,540 Fink's words capture a turning point. The very institutions that define 20th 1348 01:40:51,540 --> 01:40:56,880 century finance are now building the digital infrastructure of the 21st. 1349 01:40:56,880 --> 01:41:00,120 is one of the biggest players that will shake up the digital token game. 1350 01:41:01,290 --> 01:41:05,010 In 2022, the United States held the largest market share. 1351 01:41:06,230 --> 01:41:07,710 But what is tokenization? 1352 01:41:08,130 --> 01:41:12,110 How do all these new token -based players operate in the fintech market? 1353 01:41:12,350 --> 01:41:15,170 What is their agenda and what are their products? 1354 01:41:18,530 --> 01:41:23,330 In Europe, Luxembourg -based Tokeny Solutions is one of the market leaders 1355 01:41:23,330 --> 01:41:26,690 providing an institutional and modular end -to -end platform. 1356 01:41:27,420 --> 01:41:31,860 That enables the issuance, transfer, and management of tradable digital assets 1357 01:41:31,860 --> 01:41:32,940 and security tokens. 1358 01:41:34,880 --> 01:41:39,140 Such as tokenized loans, structured debt securities, stock and funds. 1359 01:41:41,800 --> 01:41:46,200 This private B2B company provides an end -to -end platform for the unified 1360 01:41:46,200 --> 01:41:49,820 issuance, management, and trading of service and security tokens. 1361 01:41:53,680 --> 01:41:55,920 The company valuation for token solutions. 1362 01:41:56,670 --> 01:42:02,410 range from $22 million to $33 million, with a revenue estimate of $6 .5 million 1363 01:42:02,410 --> 01:42:05,190 for the year and a fund of $11 million. 1364 01:42:08,710 --> 01:42:13,790 The company uses Ethereum and Polygon's blockchain technology and works with the 1365 01:42:13,790 --> 01:42:16,230 ERC3643 token standard. 1366 01:42:20,550 --> 01:42:24,850 Another interesting player in the European market is the Berlin -based 1367 01:42:24,850 --> 01:42:29,270 Bitbon. They have launched the first security token offering in Europe. 1368 01:42:30,330 --> 01:42:34,910 This was approved by the German financial regular BaFin in 2019. 1369 01:42:36,770 --> 01:42:41,030 Bitbon is a technology provider for the tokenization infrastructure of digital 1370 01:42:41,030 --> 01:42:42,030 assets. 1371 01:42:42,210 --> 01:42:47,410 Their Web3 product, TokenTool, allows their customers to create, manage, and 1372 01:42:47,410 --> 01:42:50,250 distribute tokens and NFTs through EVM chains. 1373 01:42:52,360 --> 01:42:57,640 The Bitbon Token, or BB1, is a security bond token that can be purchased with 1374 01:42:57,640 --> 01:43:01,040 BTC, ETH, XLM, or Euros. 1375 01:43:01,540 --> 01:43:04,240 The value per token is equal to 1 Euro. 1376 01:43:06,640 --> 01:43:11,900 Their global market share is currently less than 0 .1%, but with a team size of 1377 01:43:11,900 --> 01:43:17,280 less than 50 people, it is valued at around 7 to 11 million US dollars as a 1378 01:43:17,280 --> 01:43:18,280 company. 1379 01:43:20,040 --> 01:43:24,040 Bitbon is a private company with a capital of $13 .2 million. 1380 01:43:24,900 --> 01:43:28,600 Its turnover will be around $1 million in 2023. 1381 01:43:30,660 --> 01:43:32,320 But how does it work exactly? 1382 01:43:33,460 --> 01:43:36,180 Bitbon uses the ERC -20 token standard. 1383 01:43:36,740 --> 01:43:40,460 This is the most commonly used security token in the fintech industry. 1384 01:43:42,080 --> 01:43:46,400 The token stands for tokenized assets that accompany with current regulations 1385 01:43:46,400 --> 01:43:47,400 for securities. 1386 01:43:47,920 --> 01:43:52,120 There are securities in the form of a token, and through a company such as 1387 01:43:52,120 --> 01:43:57,120 Bitbon or Tokeny Solutions, the buyer can buy and trade such a security as a 1388 01:43:57,120 --> 01:43:58,120 token. 1389 01:43:59,100 --> 01:44:01,860 The acquired token is implemented on a blockchain. 1390 01:44:02,120 --> 01:44:04,860 The blockchains are called Ethereum or Polygon. 1391 01:44:07,640 --> 01:44:13,000 I'm Radoslav Albrecht, founder and CEO of Bitbon. A token is a term that has 1392 01:44:13,000 --> 01:44:16,900 been around for a long time, and it basically stands for the fact that an 1393 01:44:16,900 --> 01:44:19,040 or digital good stands for something else. 1394 01:44:19,340 --> 01:44:24,100 For example, if you go to a fun fair and pay admission, you often get a token, a 1395 01:44:24,100 --> 01:44:27,260 plastic chip, which you then hand in in a carousel, for example. 1396 01:44:27,960 --> 01:44:29,920 And that's where the term originally comes from. 1397 01:44:32,420 --> 01:44:36,500 My name is Markus Kluge. I'm one of the co -founders of Tokenforge. 1398 01:44:36,800 --> 01:44:41,860 The best known is the standard, is this ERC20 standard, which is basically just 1399 01:44:41,860 --> 01:44:46,100 a small register in which anyone who has received a token there is granted 1400 01:44:46,100 --> 01:44:49,480 access and is the only one who can move it into a private key. 1401 01:44:49,760 --> 01:44:52,620 This is what is meant by tokenization in blockchain. 1402 01:44:53,260 --> 01:44:57,300 And that's what happens without regulations and without access from any 1403 01:44:57,300 --> 01:45:01,860 administrator or from any regulated party, with a high risk that if you lose 1404 01:45:01,860 --> 01:45:06,020 your private key, you won't be able to access that token, and you won't be able 1405 01:45:06,020 --> 01:45:08,100 to move it, you won't be able to sell it. 1406 01:45:10,880 --> 01:45:16,840 From a technical point of view, a token is basically a database entry, and it 1407 01:45:16,840 --> 01:45:20,640 says which address, which is basically the digital place where a token is 1408 01:45:20,640 --> 01:45:25,560 stored. how many pieces, how many tokens have and is implemented by a so -called 1409 01:45:25,560 --> 01:45:31,520 program code, which in the context of blockchains is also called smart 1410 01:45:31,520 --> 01:45:32,520 contracts. 1411 01:45:34,580 --> 01:45:38,580 But basically, this is a program code that describes what are the technical 1412 01:45:38,580 --> 01:45:42,600 properties of the token and who owns the token and who holds these tokens. 1413 01:45:48,300 --> 01:45:52,560 It is therefore important in tokenization, i .e. in the creation of 1414 01:45:52,560 --> 01:45:56,920 entries, with which certain rights of the token owners are linked, that there 1415 01:45:56,920 --> 01:46:00,800 a register, a database where the entries are readable and stored securely. 1416 01:46:01,180 --> 01:46:05,560 This register is granted by the ERC -20 standard just mentioned. 1417 01:46:05,840 --> 01:46:08,120 It sits on a blockchain, so it's secure. 1418 01:46:08,400 --> 01:46:13,320 In other words, a token isn't just an asset. It's a digital entry in a new 1419 01:46:13,320 --> 01:46:16,180 of ledger that is rewriting how capital markets keep their books. 1420 01:46:16,650 --> 01:46:19,710 Financial services industries, for the most part, a lot of the capital markets 1421 01:46:19,710 --> 01:46:23,930 infrastructure and products, they're still running in technology from the 1422 01:46:23,930 --> 01:46:27,110 So I don't think anybody questions that you need to modernize that 1423 01:46:27,110 --> 01:46:33,390 infrastructure to be able to move products and settle trades and access 1424 01:46:33,390 --> 01:46:36,830 investors, et cetera, in a much more efficient way. And at the end of the 1425 01:46:36,870 --> 01:46:39,890 capital markets boil down to like updating ledgers and how people... 1426 01:46:40,270 --> 01:46:43,530 you know move the ownership of assets in a ledger and that's what a blockchain 1427 01:46:43,530 --> 01:46:46,990 technology and tokenization brings so it's the most suitable most modern 1428 01:46:46,990 --> 01:46:49,930 technology ideal for modernizing capital markets 1429 01:46:53,160 --> 01:46:56,480 The token stands for a value, for a service. 1430 01:46:56,920 --> 01:47:00,560 Tokens, as we understand them today in the field, have been around since around 1431 01:47:00,560 --> 01:47:01,960 2014 -2015. 1432 01:47:02,700 --> 01:47:06,420 That's when the so -called Ethereum blockchain came into being, and the 1433 01:47:06,420 --> 01:47:09,960 blockchain was the first blockchain on which tokens, namely digital values, 1434 01:47:10,120 --> 01:47:11,120 could be created. 1435 01:47:11,820 --> 01:47:16,260 And that's how the whole development began, that there were digital tokens, 1436 01:47:16,260 --> 01:47:19,320 since then this term has existed in the context of fintech. 1437 01:47:24,430 --> 01:47:28,350 And now we have the blockchain technology with the one with the 1438 01:47:28,350 --> 01:47:32,410 the signature, which just makes a lot more personal responsibility possible, 1439 01:47:32,770 --> 01:47:37,410 because everyone in the game can just see, hey, that's really the one who owns 1440 01:47:37,410 --> 01:47:42,070 the asset, who transfers it, and that's what this private key takes care of, 1441 01:47:42,110 --> 01:47:43,110 public pair. 1442 01:47:43,170 --> 01:47:45,330 That then just makes this thing safe. 1443 01:47:47,270 --> 01:47:48,750 Cryptocurrencies are also tokens. 1444 01:47:49,320 --> 01:47:53,580 they are produced and managed by companies instead of institutions 1445 01:47:53,580 --> 01:47:58,520 speaking cryptocurrencies are not currencies there are digital assets that 1446 01:47:58,520 --> 01:48:04,140 be exchanged and traded their creation is carried out by so -called icos the 1447 01:48:04,140 --> 01:48:06,340 abbreviation for initial crane offering 1448 01:48:06,340 --> 01:48:13,240 so the first the first so -called initial 1449 01:48:13,240 --> 01:48:18,040 coin offering was that of ethereum itself And they basically invented the 1450 01:48:18,040 --> 01:48:21,340 technical concept of the token and started commercializing it. 1451 01:48:21,800 --> 01:48:25,320 And then many, many more companies came along that took advantage of these 1452 01:48:25,320 --> 01:48:27,800 technical possibilities and issued more tokens. 1453 01:48:29,540 --> 01:48:33,600 My name is Erwin Wallader. I am the head of policy for the European Blockchain 1454 01:48:33,600 --> 01:48:34,600 Association. 1455 01:48:35,920 --> 01:48:38,920 If you want to buy the argument that crypto is political, I think it is. 1456 01:48:39,380 --> 01:48:41,720 And I think it's been political since the Genesis block. 1457 01:48:42,040 --> 01:48:45,680 So if you look at actually what's inscribed in the Genesis block, the 1458 01:48:45,680 --> 01:48:46,680 block is the Bitcoin blockchain. 1459 01:48:46,780 --> 01:48:49,900 It's the chancellor on the brink of second bailout to banks, right? And this 1460 01:48:49,900 --> 01:48:52,160 during the height of the 2008 financial crisis. 1461 01:48:52,740 --> 01:48:57,220 And specifically, you know, you can look at the Genesis block as a picket sign. 1462 01:48:57,760 --> 01:48:59,100 It was a protest. 1463 01:48:59,820 --> 01:49:04,560 really against what many people viewed as financial injustices that were 1464 01:49:04,560 --> 01:49:09,660 incurred at the cost of the people for the benefit, at the cost of the majority 1465 01:49:09,660 --> 01:49:10,740 for the benefit of a minority. 1466 01:49:12,400 --> 01:49:16,780 With tokenization and cryptocurrencies, a new chapter in the history of capital 1467 01:49:16,780 --> 01:49:18,080 investment is being written. 1468 01:49:18,680 --> 01:49:23,940 The new way of investing is influencing society, politics and markets. The 1469 01:49:23,940 --> 01:49:28,420 revolutionary concept makes it possible to divide assets into arbitrarily small 1470 01:49:28,420 --> 01:49:29,420 parts. 1471 01:49:31,150 --> 01:49:32,410 The idea is not new. 1472 01:49:32,790 --> 01:49:37,010 Fractional ownership is a consistent trend among financial instruments. 1473 01:49:37,350 --> 01:49:42,050 For centuries, companies have been broken down into small parties by shares 1474 01:49:42,050 --> 01:49:46,730 funds. What is completely new, however, is to register these fractions as 1475 01:49:46,730 --> 01:49:48,310 digital tokens on a blockchain. 1476 01:49:51,350 --> 01:49:55,610 From a technical point of view, there are about three dominant technological 1477 01:49:55,610 --> 01:49:56,610 standards. 1478 01:49:57,200 --> 01:50:01,620 There are many more, but these three technical standards that can be used to 1479 01:50:01,620 --> 01:50:02,620 all use cases. 1480 01:50:03,020 --> 01:50:06,900 The tokens that are then issued by companies that take advantage of the 1481 01:50:06,900 --> 01:50:08,620 technology, there are thousands. 1482 01:50:08,900 --> 01:50:12,760 There are probably around 5 million different tokens at the moment, but they 1483 01:50:12,760 --> 01:50:14,860 all based on the same technical standards. 1484 01:50:15,830 --> 01:50:18,590 but where other values are represented with it. 1485 01:50:19,030 --> 01:50:23,730 For example, there are so -called stablecoins, which represent fiat 1486 01:50:23,770 --> 01:50:25,410 such as the euro, the dollar. 1487 01:50:25,750 --> 01:50:29,990 Then there are tokens that represent, for example, securities, such as bonds 1488 01:50:29,990 --> 01:50:30,990 stocks. 1489 01:50:32,250 --> 01:50:38,850 Tokenization allows you to transfer value with a technical substrate 1490 01:50:38,850 --> 01:50:43,370 that enables the removal of a lot of different frictions. 1491 01:50:44,320 --> 01:50:46,760 And these frictions also lead to cost reductions. 1492 01:50:47,040 --> 01:50:51,720 So instantaneous settlement, fractionalization, it opens up the door 1493 01:50:51,720 --> 01:50:57,600 cases like pay -per -use models, streaming money, and generally the 1494 01:50:57,600 --> 01:51:03,280 take real -world assets and represent them in a digitalized form and then 1495 01:51:03,280 --> 01:51:04,280 them to investors. 1496 01:51:05,120 --> 01:51:10,200 new ways to package financial products, the ability to ease frictions and cross 1497 01:51:10,200 --> 01:51:13,000 -border payments as well from an institutional perspective. 1498 01:51:13,440 --> 01:51:19,040 And I think also what's very important is that tokenization and tokenization 1499 01:51:19,040 --> 01:51:25,760 within blockchain has the ability to produce a higher level of financial 1500 01:51:25,760 --> 01:51:29,940 and financial inclusion, which I think is ultimately really important. 1501 01:51:30,060 --> 01:51:32,280 Otherwise, why are we doing all of this? 1502 01:51:34,160 --> 01:51:37,040 All assets can thus be digitalized and standardized. 1503 01:51:37,340 --> 01:51:39,900 This increases liquidity and transparency. 1504 01:51:40,500 --> 01:51:42,800 Process can be automated like never before. 1505 01:51:45,200 --> 01:51:49,020 Software developers have been thinking about how to standardize tokens. 1506 01:51:49,520 --> 01:51:51,920 This has a very, very important background. 1507 01:51:52,140 --> 01:51:56,560 Namely, the tokens are held in so -called wallets. These are basically 1508 01:51:56,560 --> 01:51:59,820 wallets, and not every wallet can hold every type of token. 1509 01:52:01,320 --> 01:52:05,360 Software developers have been considering ways to standardize tokens, 1510 01:52:05,360 --> 01:52:09,400 importance of doing so lies in the fact that tokens are held in digital wallets, 1511 01:52:09,400 --> 01:52:11,920 and not every wallet can store every type of token. 1512 01:52:12,570 --> 01:52:16,730 Therefore, it has been suggested that a standard should be established to enable 1513 01:52:16,730 --> 01:52:19,690 wallets to support as many types of token as possible. 1514 01:52:20,510 --> 01:52:24,350 Developers propose open -source software, and the market adapted 1515 01:52:24,350 --> 01:52:26,690 technical standards based on their effectiveness. 1516 01:52:27,370 --> 01:52:31,890 These standards have become prevalent with two dominant token variations, ERC 1517 01:52:31,890 --> 01:52:37,270 -20 standard for the fungible tokens and the ERC -721 standard for non -fungible 1518 01:52:37,270 --> 01:52:38,270 tokens. 1519 01:52:38,280 --> 01:52:42,240 These ideas, initially suggested by developers, have since become 1520 01:52:42,240 --> 01:52:44,620 and are widely used throughout the world. 1521 01:52:46,060 --> 01:52:50,300 But the true highlight of tokenization lies in affordable entry prices for 1522 01:52:50,300 --> 01:52:52,920 investors that are associated with smaller stakes. 1523 01:52:53,600 --> 01:52:58,920 The one challenge that blockchain, crypto, or... 1524 01:52:59,280 --> 01:53:03,440 I should say that crypto faces, and you see this in decentralized finance, is 1525 01:53:03,440 --> 01:53:06,500 the end user or the user experience, right? 1526 01:53:06,940 --> 01:53:10,660 Using these financial products and services is oftentimes tricky and 1527 01:53:10,660 --> 01:53:14,200 or requires a certain level of technical literacy that not everyone has. 1528 01:53:14,480 --> 01:53:18,380 And also, at the end of the day, it's generally driven by interest. I don't 1529 01:53:18,380 --> 01:53:22,680 think you can make the argument and say that everyone will use this all the 1530 01:53:22,680 --> 01:53:27,020 time. everywhere because that isn't the case with anything now so why why would 1531 01:53:27,020 --> 01:53:30,540 it be any different you know human nature is a fickle thing so i think that 1532 01:53:30,540 --> 01:53:34,880 point should be to make it as easy to use as possible as frictionless as 1533 01:53:34,880 --> 01:53:38,300 seamless as possible the real challenge today isn't the idea of tokenization 1534 01:53:38,300 --> 01:53:42,260 itself but the integration between new blockchain networks and decades -old 1535 01:53:42,260 --> 01:53:46,520 financials most of the adoption for tokenization today is still within the 1536 01:53:46,520 --> 01:53:47,520 crypto 1537 01:53:47,610 --> 01:53:51,650 uh ecosystem um that's where the majority of the people that are kind of 1538 01:53:51,650 --> 01:53:55,410 the technology and adopting tokenized assets are it is to some extent true 1539 01:53:55,410 --> 01:53:59,980 it hasn't trickle down into mainstream Wall Street, that doesn't necessarily 1540 01:53:59,980 --> 01:54:03,300 mean it's not going to happen. I think it's a much more complicated problem 1541 01:54:03,300 --> 01:54:08,200 because you need to get wallet infrastructure and blockchains, etc., 1542 01:54:08,200 --> 01:54:12,300 with existing legacy infrastructure, and that usually takes longer than creating 1543 01:54:12,300 --> 01:54:13,980 new markets, which is what's happening today. 1544 01:54:14,200 --> 01:54:15,380 But it will definitely happen. 1545 01:54:15,780 --> 01:54:20,400 As I mentioned at the beginning, digitization is an unavoidable fact for 1546 01:54:20,400 --> 01:54:21,400 industries. 1547 01:54:25,160 --> 01:54:28,600 which enables them to access funds directly without the need for an 1548 01:54:28,600 --> 01:54:32,920 intermediary, thus eliminating the high fees associated with working with 1549 01:54:32,920 --> 01:54:34,500 investment banks or other institutions. 1550 01:54:35,820 --> 01:54:38,720 I'm Elisabetta Palaznik. I'm an economist in the background. 1551 01:54:38,960 --> 01:54:43,220 And to this day, I help basically crypto asset service providers, law firms, 1552 01:54:43,380 --> 01:54:48,180 consulting firms, navigate through this new European regulatory regime that we 1553 01:54:48,180 --> 01:54:52,200 have in crypto assets, which we call MICA, Market in Crypto Assets. 1554 01:54:53,420 --> 01:54:57,640 The MICA is an EU legal framework for cryptocurrencies and tokens that are 1555 01:54:57,640 --> 01:55:01,680 traded on digital platforms. It replaces the individual regulations on the 1556 01:55:01,680 --> 01:55:02,680 individual countries. 1557 01:55:03,950 --> 01:55:10,170 Mika basically aims to target some specific assets in the crypto industry 1558 01:55:10,170 --> 01:55:12,870 certain services linked to those crypto assets. 1559 01:55:13,170 --> 01:55:18,110 So if we take the parallelism to the traditional financial sector, we have 1560 01:55:18,110 --> 01:55:23,070 Mifid, which covers financial instruments. Now we have Mika that 1561 01:55:23,070 --> 01:55:28,030 type of crypto assets, which are in three big categories, which are the 1562 01:55:28,030 --> 01:55:32,690 coins and the other crypto assets, including... 1563 01:55:35,200 --> 01:55:40,040 With the implementation of the markets and crypto assets regulation called 1564 01:55:40,140 --> 01:55:43,400 a consistent EU -wide framework has been established. 1565 01:55:44,000 --> 01:55:48,700 So it will change a lot of things in the regulatory landscape and also in the 1566 01:55:48,700 --> 01:55:51,080 crypto industry itself, because as we know... 1567 01:55:51,340 --> 01:55:54,720 All the continents have their own approach, but sometimes they don't have 1568 01:55:54,720 --> 01:55:58,940 approach at all. So I think it will change a lot of things, and also within 1569 01:55:58,940 --> 01:56:00,080 financial sector as well. 1570 01:56:00,440 --> 01:56:04,680 Why? Because the traditional financial sector so far, if you go to a bank and 1571 01:56:04,680 --> 01:56:09,460 you want to buy some Bitcoin, your banker will most likely refuse this 1572 01:56:09,620 --> 01:56:14,780 Some of them, they jump on board with it, but 99 % will say, no, we don't do 1573 01:56:15,080 --> 01:56:19,180 While Europe advances under the MyCA framework, the United States is also 1574 01:56:19,180 --> 01:56:23,410 forward. Providing new clarity for issuers, custodians, and stable coins. 1575 01:56:23,760 --> 01:56:27,140 I think it's going to get accelerated because now we have stable coins that 1576 01:56:27,140 --> 01:56:30,420 become legal with the Genius Act. 1577 01:56:30,680 --> 01:56:36,300 We've had the recent administration and the recent SEC basically clarifying a 1578 01:56:36,300 --> 01:56:40,080 lot of the perhaps more gray areas with respect to tokenization about how 1579 01:56:40,080 --> 01:56:45,480 transfer agents use a blockchain technology for their ledger or how the 1580 01:56:45,480 --> 01:56:48,340 dealers can do custody of tokenized assets. And I think this is going to 1581 01:56:48,340 --> 01:56:49,340 significantly accelerate. 1582 01:56:49,480 --> 01:56:51,140 So I see that happening within the next... 1583 01:56:51,500 --> 01:56:52,760 you know, two to five years for sure. 1584 01:56:52,980 --> 01:56:57,600 After Mika comes into force right now, what they can do is actually they can 1585 01:56:57,600 --> 01:57:02,040 offer those services without even having the Mika license, which can be quite a 1586 01:57:02,040 --> 01:57:05,560 bit of polemic because it's not because you're a bank or financial institution 1587 01:57:05,560 --> 01:57:09,160 that you can actually understand and you have the experience and the knowledge 1588 01:57:09,160 --> 01:57:10,160 to provide those services. 1589 01:57:12,900 --> 01:57:14,880 Cryptocurrencies are traded through crypto exchanges. 1590 01:57:15,560 --> 01:57:20,140 Utility tokens represent a specific utility or functionality on a platform. 1591 01:57:20,750 --> 01:57:24,130 There are different types of tokens that can serve as financial instruments. 1592 01:57:24,750 --> 01:57:27,250 Security tokens act as digital securities. 1593 01:57:27,810 --> 01:57:30,710 They can have the characteristics of stocks or bonds. 1594 01:57:33,390 --> 01:57:40,250 A security token usually certifies as a security. 1595 01:57:40,960 --> 01:57:45,760 It is technically referred to as the ERC -20 token and is similar to a fungible 1596 01:57:45,760 --> 01:57:47,780 token with some additional features. 1597 01:57:48,060 --> 01:57:51,980 It is crucial to identify the token holders for securities and specific 1598 01:57:51,980 --> 01:57:55,800 technical settings can be implemented to restrict the transaction of these 1599 01:57:55,800 --> 01:57:57,980 tokens to a particular whitelist of recipients. 1600 01:57:59,340 --> 01:58:03,240 By approving which recipients can hold the token, you're indicating their 1601 01:58:03,240 --> 01:58:04,240 authorization. 1602 01:58:04,410 --> 01:58:08,990 Security tokens are commonly designed this way as issuers usually need to know 1603 01:58:08,990 --> 01:58:13,050 and sometimes may be legally mandated to know the owner of the tokens. 1604 01:58:22,050 --> 01:58:26,430 Utility tokens, on the other hand, refer to tokens that operate as platforms or 1605 01:58:26,430 --> 01:58:27,430 specific currencies. 1606 01:58:27,810 --> 01:58:31,910 Imagine that, for instance, you do not utilize standard currency on social 1607 01:58:31,910 --> 01:58:36,300 media. but a token that has been developed particularly for these 1608 01:58:36,300 --> 01:58:40,260 subsequently you can exchange this token for certain features on the platform. 1609 01:58:44,400 --> 01:58:48,480 The process of tokenization begins with a collection of information about the 1610 01:58:48,480 --> 01:58:53,480 asset. This can be, for example, a detailed description of a property, or a 1611 01:58:53,480 --> 01:58:57,060 of works of art in a collection with all their individual characteristics. 1612 01:59:01,390 --> 01:59:04,990 This information is then converted into a digital form and stored. 1613 01:59:05,510 --> 01:59:09,570 Subsequently, a token is generated that represents the ownership rights to the 1614 01:59:09,570 --> 01:59:10,750 described tangible asset. 1615 01:59:11,310 --> 01:59:15,650 The token is also stored on the blockchain and contains a unique digital 1616 01:59:15,650 --> 01:59:18,690 fingerprint of the asset thanks to individual information. 1617 01:59:24,790 --> 01:59:29,170 There is a considerable opposition because it represents a new technology 1618 01:59:29,170 --> 01:59:30,370 paradigm shift in the approach. 1619 01:59:31,349 --> 01:59:36,010 Previously, when moving a security from A to B, physical transfer was necessary, 1620 01:59:36,250 --> 01:59:37,790 hence the creation of securities. 1621 01:59:38,570 --> 01:59:43,590 Now, however, there is only a register, this sufficient to modify access rights 1622 01:59:43,590 --> 01:59:45,330 to a token and transfer it. 1623 01:59:47,540 --> 01:59:51,900 In essence, the security is now linked to the asset and no longer a freely 1624 01:59:51,900 --> 01:59:53,000 transferable security. 1625 01:59:53,400 --> 01:59:56,640 This change has various consequences for the process involved. 1626 01:59:57,080 --> 02:00:01,440 Our current objective is to integrate all the available technologies, such as 1627 02:00:01,440 --> 02:00:05,680 digital identities, digital currencies, and tokenization in a manner that 1628 02:00:05,680 --> 02:00:07,760 achieves genuine democratized access. 1629 02:00:11,920 --> 02:00:16,050 Once a token has been created and stored on a blockchain, It can be managed 1630 02:00:16,050 --> 02:00:17,270 through smart contracts. 146718

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