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These are the user uploaded subtitles that are being translated: 1 00:00:00,000 --> 00:00:03,880 that he began to see the world through the lens of assets and yields. 2 00:00:04,960 --> 00:00:07,920 This public education gave him a different edge. 3 00:00:08,180 --> 00:00:12,600 While his peers at private East Coast schools were being groomed for 4 00:00:12,600 --> 00:00:17,680 corporate roles, Larry was developing the outsider's eye, a perspective that 5 00:00:17,680 --> 00:00:21,840 allowed him to see opportunities in the messy, unpolished corners of the bond 6 00:00:21,840 --> 00:00:22,840 market. 7 00:00:25,200 --> 00:00:31,330 He graduated in 1976, not with a silver spoon, but with a California -bred 8 00:00:31,330 --> 00:00:33,610 ambition to take on the giants of Manhattan. 9 00:00:34,550 --> 00:00:39,970 He was a Bruin headed for Wall Street, and the financial world had no idea what 10 00:00:39,970 --> 00:00:40,970 was coming. 11 00:00:45,030 --> 00:00:46,850 The year is 1976. 12 00:00:47,590 --> 00:00:52,250 New York City is a grit -covered battlefield, and Larry Fink has just 13 00:00:52,250 --> 00:00:53,710 handed the keys to the kingdom. 14 00:00:54,630 --> 00:00:59,110 Goldman Sachs, the most prestigious name in finance back then, had practically 15 00:00:59,110 --> 00:01:00,110 hired him. 16 00:01:00,770 --> 00:01:02,890 He had passed the technical test. 17 00:01:03,350 --> 00:01:04,890 He had charmed the partners. 18 00:01:05,129 --> 00:01:08,750 All that remained was a rubber stamp interview with Human Resources. 19 00:01:09,710 --> 00:01:10,710 But Larry? 20 00:01:11,230 --> 00:01:14,170 Larry wasn't just confident, he was impatient. 21 00:01:14,730 --> 00:01:19,190 When the recruiter asked for his thoughts on the firm, Larry didn't give 22 00:01:19,190 --> 00:01:20,730 you, he gave a consultation. 23 00:01:21,410 --> 00:01:23,730 He pointed out the flaws in their system. 24 00:01:24,280 --> 00:01:26,080 At Goldman, they wanted a soldier. 25 00:01:26,500 --> 00:01:29,220 Larry was already acting like a general. 26 00:01:33,020 --> 00:01:37,980 In that room, the rigid Goldman way clashed with the unfiltered Fink way. 27 00:01:38,460 --> 00:01:42,900 Before he could even hail a cab back to his hotel, the offer was dead. 28 00:01:43,540 --> 00:01:48,700 The most coveted job in Wall Street history had vanished. All because Larry 29 00:01:48,700 --> 00:01:53,140 couldn't stop himself from trying to fix a system he hadn't even joined yet. 30 00:01:53,770 --> 00:01:55,170 It was a crushing blow. 31 00:01:55,830 --> 00:02:00,770 But in the shadow of that rejection, the door opened at a scrappy second -tier 32 00:02:00,770 --> 00:02:02,230 firm called First Boston. 33 00:02:02,570 --> 00:02:06,370 It was a place with less prestige, but more white space. 34 00:02:07,090 --> 00:02:10,770 At Goldman, he would have been a cog in a perfect machine. 35 00:02:11,250 --> 00:02:13,670 At First Boston, he was the architect. 36 00:02:14,030 --> 00:02:18,870 He was given a desk, a telephone, and the freedom to build something entirely 37 00:02:18,870 --> 00:02:21,490 new. The mortgage -backed security. 38 00:02:22,430 --> 00:02:26,990 He didn't know it yet, but that recruiters know was the foundation upon 39 00:02:26,990 --> 00:02:30,890 the $14 trillion empire of Black Rock would be built. 40 00:02:38,250 --> 00:02:42,590 It's 1976 when Larry Fink arrives at First Boston. 41 00:02:42,910 --> 00:02:47,190 At the time, the firm was the scrappy underdog of investment banking. 42 00:02:47,550 --> 00:02:49,850 It wasn't as stiff as Morgan Stanley. 43 00:02:50,410 --> 00:02:52,050 or as elitist as Goldman. 44 00:02:52,490 --> 00:02:56,350 It was the perfect laboratory for a man who didn't fit the mold. 45 00:02:57,170 --> 00:02:59,410 Larry was assigned to the bond department. 46 00:03:00,070 --> 00:03:03,830 Back then, bonds were considered the boring corner of finance. 47 00:03:04,350 --> 00:03:06,290 It was where you went to retire. 48 00:03:07,070 --> 00:03:08,150 Stocks were sexy. 49 00:03:08,430 --> 00:03:10,050 Bonds were for grandmothers. 50 00:03:10,270 --> 00:03:13,850 But Larry saw something everyone else missed. 51 00:03:14,710 --> 00:03:20,350 He looked at the American dream, the suburban house, the white picket fence, 52 00:03:20,350 --> 00:03:25,950 30 -year mortgage and he saw a math problem he realized that if you took 53 00:03:25,950 --> 00:03:30,290 thousands of individual home mortgages bundled them together like a deck of 54 00:03:30,290 --> 00:03:37,010 cards and sold slices of that deck to investors you created a money machine 55 00:03:37,010 --> 00:03:43,350 was the birth of the securitization market what larry fink helped create was 56 00:03:43,350 --> 00:03:47,070 more than a financial product it was a structural shift 57 00:03:50,200 --> 00:03:52,860 Securitization didn't just bundle mortgages. 58 00:03:53,100 --> 00:03:55,480 It separated risk from reality. 59 00:03:56,100 --> 00:04:00,740 For the first time, financial value could travel faster than the underlying 60 00:04:00,740 --> 00:04:02,380 economy that supported it. 61 00:04:02,780 --> 00:04:07,920 A house in California became a line in a spreadsheet in New York, which became a 62 00:04:07,920 --> 00:04:10,160 yield sold to an investor in Tokyo. 63 00:04:10,960 --> 00:04:13,860 Risk no longer lived where decisions were made. 64 00:04:14,320 --> 00:04:19,310 It was abstracted, sliced, repackaged, and distributed across the system. 65 00:04:19,810 --> 00:04:24,390 This was the moment when finance stopped reflecting the real economy, and began 66 00:04:24,390 --> 00:04:26,030 building a parallel one. 67 00:04:26,490 --> 00:04:31,210 A system that could grow without limits, as long as everyone believed the models 68 00:04:31,210 --> 00:04:32,109 were right. 69 00:04:32,110 --> 00:04:34,170 And for a while, they were. 70 00:04:35,490 --> 00:04:38,570 By the early 80s, Larry was the golden ball. 71 00:04:38,790 --> 00:04:41,890 He wasn't just hitting targets, he was shattering them. 72 00:04:42,380 --> 00:04:46,600 In one year, his department was responsible for nearly one -third of 73 00:04:46,600 --> 00:04:48,060 Boston's total profits. 74 00:04:48,500 --> 00:04:54,260 At age 31, he became the youngest managing director the firm had ever 75 00:04:54,260 --> 00:04:55,260 was earning millions. 76 00:04:55,400 --> 00:04:59,600 He was the successor, the prodigy, the man who could do no wrong. 77 00:05:00,100 --> 00:05:02,960 He had moved his family to a sprawling estate. 78 00:05:03,180 --> 00:05:04,740 He was flying private. 79 00:05:05,080 --> 00:05:08,300 He had conquered the grit -covered battlefields of Manhattan. 80 00:05:11,270 --> 00:05:15,870 But in the world of high finance, the higher you fly, the thinner the air 81 00:05:15,870 --> 00:05:16,870 becomes. 82 00:05:20,230 --> 00:05:24,870 Larry was making hundreds of millions for the bank, but there was a ghost in 83 00:05:24,870 --> 00:05:28,310 machine, a variable he hadn't accounted for. 84 00:05:28,790 --> 00:05:30,510 The year was 1986. 85 00:05:31,210 --> 00:05:34,150 Larry had made a massive bet on interest rates. 86 00:05:34,530 --> 00:05:36,950 He believed they would stay stable. 87 00:05:37,720 --> 00:05:42,440 He was so sure of his math, so confident in his track record, that he didn't 88 00:05:42,440 --> 00:05:45,060 realize the ground was shifting beneath his feet. 89 00:05:46,100 --> 00:05:50,580 In just three months, the Golden Boys department went from profit to a 90 00:05:50,580 --> 00:05:53,060 catastrophic $100 million loss. 91 00:05:53,700 --> 00:05:58,640 In the 80s, $100 million wasn't just a loss, it was a national scandal. 92 00:05:59,740 --> 00:06:04,300 Overnight, the man who was supposed to run the bank was a pariah. The phones 93 00:06:04,300 --> 00:06:05,300 stopped ringing. 94 00:06:05,440 --> 00:06:08,560 The friends on the trading floor looked away when he walked by. 95 00:06:08,900 --> 00:06:12,780 He had been the smartest man in the room until he wasn't. 96 00:06:13,320 --> 00:06:17,820 He would later describe this moment as the most painful experience of my life. 97 00:06:18,460 --> 00:06:23,480 But as he sat in the ruins of his reputation, Larry Fink wasn't just 98 00:06:23,480 --> 00:06:26,500 his career, he was obsessed with one question. 99 00:06:27,240 --> 00:06:29,260 How did I not see the risk? 100 00:06:30,340 --> 00:06:35,350 That obsession, the fear of the unknown variable, would become the cornerstone 101 00:06:35,350 --> 00:06:36,370 of BlackRock. 102 00:06:41,830 --> 00:06:47,530 By 1983, Larry wasn't just selling bonds, he was a pioneer of the CMO, 103 00:06:47,890 --> 00:06:50,550 Collateralized Mortgage Obligation. 104 00:06:52,790 --> 00:06:54,750 Think of it like a water pool. 105 00:06:54,990 --> 00:06:58,850 Larry took thousands of mortgages and sliced them into tranches. 106 00:06:59,270 --> 00:07:03,310 Some investors took the top slice, low risk, low reward. 107 00:07:03,720 --> 00:07:06,680 Others at the bottom, high risk, high yield. 108 00:07:06,980 --> 00:07:09,520 It was a masterpiece of financial engineering. 109 00:07:09,860 --> 00:07:12,080 It made the illiquid liquid. 110 00:07:12,500 --> 00:07:16,040 It made First Boston the center of the universe. 111 00:07:17,560 --> 00:07:22,100 But there was a flaw, a tiny mathematical ghost in his models. 112 00:07:22,880 --> 00:07:27,440 Larry's team had predicted that interest rates would rise, and they hedged their 113 00:07:27,440 --> 00:07:28,440 bets accordingly. 114 00:07:28,640 --> 00:07:31,060 But in the second quarter of 1986, 115 00:07:31,790 --> 00:07:34,230 Wraiths did something the models said was impossible. 116 00:07:34,650 --> 00:07:35,910 They plummeted. 117 00:07:36,590 --> 00:07:41,150 Because they didn't have a system to track their real -time exposure, Larry 118 00:07:41,150 --> 00:07:42,150 climbed blind. 119 00:07:42,190 --> 00:07:47,990 He was the pilot of a Boeing 747, trying to land in a storm using nothing but a 120 00:07:47,990 --> 00:07:49,210 compass and a prayer. 121 00:07:49,670 --> 00:07:54,170 By the time he realized the engines were on fire, the plane had already hit the 122 00:07:54,170 --> 00:07:56,250 mountain. $100 million. 123 00:07:57,110 --> 00:07:58,190 All gone. 124 00:08:02,960 --> 00:08:05,140 He wasn't just fired, he was erased. 125 00:08:05,920 --> 00:08:10,540 After the dust settled, Larry found himself in a peculiar kind of exile. 126 00:08:10,920 --> 00:08:13,740 He wasn't just unemployed, he was haunted. 127 00:08:14,220 --> 00:08:19,440 He realized that the $100 million loss wasn't a failure of talent, it was a 128 00:08:19,440 --> 00:08:20,500 failure of vision. 129 00:08:20,880 --> 00:08:26,840 What happened in 1986 wasn't a personal miscalculation, it was a systemic 130 00:08:26,840 --> 00:08:27,840 blindness. 131 00:08:28,340 --> 00:08:33,570 At the time, every major financial institution operated the same way. 132 00:08:33,950 --> 00:08:35,390 Positions were fragmented. 133 00:08:36,150 --> 00:08:38,490 Exposure was estimated, not measured. 134 00:08:38,870 --> 00:08:41,250 Risk was inferred after the fact. 135 00:08:41,830 --> 00:08:46,170 Banks knew what they bought yesterday, but not what it was worth right now. 136 00:08:46,630 --> 00:08:51,310 The system rewarded speed, volume and confidence, not understanding. 137 00:08:51,830 --> 00:08:55,170 And as long as markets moved slowly, the illusion held. 138 00:08:55,710 --> 00:09:00,250 But once volatility entered the market, no one truly knew where the danger was. 139 00:09:00,730 --> 00:09:02,680 Or... how large it had become. 140 00:09:03,680 --> 00:09:08,560 Larry didn't just lose money. He realized the entire financial system was 141 00:09:08,560 --> 00:09:09,560 without instruments. 142 00:09:10,340 --> 00:09:13,880 Wall Street was essentially a collection of blind giants. 143 00:09:14,360 --> 00:09:20,580 Every major firm, Goldman, Lehman, Merrill Lynch, was standing just one 144 00:09:20,580 --> 00:09:23,600 away from total collapse at any given second. 145 00:09:24,200 --> 00:09:28,060 Why? Because they didn't actually know what they owned. 146 00:09:29,480 --> 00:09:30,800 with information blindness. 147 00:09:32,780 --> 00:09:37,980 In the 1980s, you knew what you bought yesterday, but you had no idea what it 148 00:09:37,980 --> 00:09:39,120 was worth right now. 149 00:09:39,600 --> 00:09:45,120 A sudden shift in interest rates or a political coup across the ocean could 150 00:09:45,120 --> 00:09:48,860 vaporize a billion dollars before the morning coffee was poured. 151 00:09:50,440 --> 00:09:53,080 Larry understood a terrifying truth. 152 00:09:53,440 --> 00:09:57,560 The entire global financial system was built on a foundation. 153 00:09:58,140 --> 00:09:59,140 of guesswork. 154 00:09:59,800 --> 00:10:02,580 It hit him with the force of an epiphany. 155 00:10:03,120 --> 00:10:07,820 If he could build a brain, a machine that could see the risk that humans were 156 00:10:07,820 --> 00:10:10,920 too slow to calculate, he wouldn't just be a banker. 157 00:10:11,360 --> 00:10:15,940 He would be the only man in the world with a flashlight in a dark room. 158 00:10:16,540 --> 00:10:20,460 This realization changed his entire philosophy of investing. 159 00:10:21,140 --> 00:10:25,520 He stopped looking for the big score and started looking for the safe passage. 160 00:10:26,140 --> 00:10:28,180 He didn't want to beat the market anymore. 161 00:10:28,380 --> 00:10:30,440 He wanted to measure it. 162 00:10:32,280 --> 00:10:36,780 He would later tell his partners, we are never going to be blind again. 163 00:10:37,760 --> 00:10:43,820 That vow, born from the humiliation of 1986, became the blueprint for a new 164 00:10:43,820 --> 00:10:49,740 of firm, a firm that didn't rely on the ego of a star trader, but on the cold, 165 00:10:49,880 --> 00:10:51,400 unblinking eye of technology. 166 00:10:58,730 --> 00:11:04,010 Larry Fink was a man with a vision, but he was also a man with a tainted resume. 167 00:11:04,550 --> 00:11:08,250 To the rest of Wall Street, he was the guy who lost $100 million. 168 00:11:08,750 --> 00:11:14,090 But to a small circle of insiders at First Boston, he was the only one who 169 00:11:14,090 --> 00:11:16,030 understood why it happened. 170 00:11:16,670 --> 00:11:18,370 He began making calls. 171 00:11:18,770 --> 00:11:21,930 He wasn't offering high salaries or flashy offices. 172 00:11:22,230 --> 00:11:25,610 He was offering a chance to build a holy grail. 173 00:11:25,880 --> 00:11:30,580 a financial firm where technology governed the ego, not the other way 174 00:11:30,980 --> 00:11:35,820 And he eventually found the right people to help him build that holy grail. 175 00:11:38,740 --> 00:11:41,640 Rob Capito, the enforcer. 176 00:11:41,880 --> 00:11:46,620 A powerhouse trader who knew the plumbing of the bond market better than 177 00:11:46,620 --> 00:11:50,920 else. He provided the muscle Larry needed to execute the vision. 178 00:11:51,740 --> 00:11:54,040 Ben Golub, the oracle. 179 00:11:54,600 --> 00:11:57,180 a PhD with a mind like a supercomputer. 180 00:11:57,700 --> 00:12:02,720 While other bankers were focused on lunch reservations, Golub was thinking 181 00:12:02,720 --> 00:12:05,360 value at risk and Monte Carlo simulations. 182 00:12:07,020 --> 00:12:09,960 Susan Wagner, the mastermind. 183 00:12:10,640 --> 00:12:15,200 Brilliant, calculating, and capable of seeing structural flaws in a multi 184 00:12:15,200 --> 00:12:18,300 -billion dollar merger before a single paper was signed. 185 00:12:18,580 --> 00:12:23,100 Along with Barbara Novick, Ralph Schlossstein, Hugh Freighter, and Keith 186 00:12:23,100 --> 00:12:25,880 Anderson, They became the original eight. 187 00:12:26,460 --> 00:12:30,740 Fink wasn't looking for bankers who would run after the money. He wanted 188 00:12:30,740 --> 00:12:34,240 architects, people who were tired of being blind. 189 00:12:35,280 --> 00:12:38,740 When he found them, they met in living rooms and coffee shops. 190 00:12:39,320 --> 00:12:44,980 They had the blueprints for a system they called Aladdin, an acronym for 191 00:12:44,980 --> 00:12:48,820 Liability, Debt and Derivative Investment Network. 192 00:12:49,820 --> 00:12:54,460 It was designed to be the unblinking eye Larry had dreamed of in his exile. 193 00:12:55,280 --> 00:12:57,900 But a brain without a body is just a dream. 194 00:12:58,440 --> 00:13:00,920 To build Aladdin, they needed hardware. 195 00:13:01,140 --> 00:13:02,500 They needed offices. 196 00:13:03,060 --> 00:13:07,640 And most importantly, they needed the one thing Larry's reputation has cost 197 00:13:08,040 --> 00:13:13,000 Capital. Aladdin was not designed to beat the market. It was designed to 198 00:13:13,000 --> 00:13:14,000 understand it. 199 00:13:14,100 --> 00:13:17,700 But its real power emerged when others started using it. 200 00:13:18,200 --> 00:13:23,750 Banks. insurance companies, pension funds, sovereign institutions. 201 00:13:24,230 --> 00:13:27,130 As Aladdin spread, something subtle happened. 202 00:13:27,770 --> 00:13:29,590 Risk stopped being subjective. 203 00:13:30,110 --> 00:13:31,550 It became standardized. 204 00:13:32,170 --> 00:13:37,590 When Aladdin flagged an asset as dangerous, entire markets adjusted 205 00:13:39,690 --> 00:13:44,570 Not because Larry Fink said so, but because the system trusted the models. 206 00:13:44,930 --> 00:13:48,510 At that point, BlackRock was no longer just managing money. 207 00:13:49,080 --> 00:13:52,040 it was helping define how risk itself was understood. 208 00:13:52,540 --> 00:13:56,800 And whoever defines risk defines the boundaries of decision -making. 209 00:14:07,180 --> 00:14:09,100 Enter Stephen Schwarzman. 210 00:14:09,320 --> 00:14:13,680 In 1988, Schwarzman was the rising king of private equity. 211 00:14:14,240 --> 00:14:17,880 His firm, Blackstone, was aggressive, wealthy, and hungry. 212 00:14:19,720 --> 00:14:20,820 The meeting was tense. 213 00:14:21,480 --> 00:14:25,860 Schwarzman knew Larry's history. He knew about the 1986 disaster. 214 00:14:26,720 --> 00:14:31,580 But Larry didn't hide from it. He used it as his primary selling point. 215 00:14:32,520 --> 00:14:37,160 Because Larry had seen the end of the world already, he knew exactly how the 216 00:14:37,160 --> 00:14:41,440 lights went out. And because of that, he was the only one who knew how to keep 217 00:14:41,440 --> 00:14:42,440 them on. 218 00:14:43,560 --> 00:14:45,300 Larry's pitch was revolutionary. 219 00:14:45,780 --> 00:14:47,880 He didn't want to start a hedge fund. 220 00:14:48,190 --> 00:14:53,010 he wanted to create a fiduciary company, a firm that managed other people's 221 00:14:53,010 --> 00:14:56,850 money with the same technological rigor usually reserved for NASA. 222 00:14:57,710 --> 00:15:01,590 He asked for a $5 million credit line and a partnership. 223 00:15:01,950 --> 00:15:06,030 In exchange, Schwarzman would own 50 % of the new venture. 224 00:15:06,410 --> 00:15:10,590 He knew he was buying cheap because he was buying on a distressed asset. 225 00:15:10,970 --> 00:15:12,550 Fink's damaged reputation. 226 00:15:13,670 --> 00:15:17,910 But he did so betting on the idea that the experience had turned Larry Fink, 227 00:15:18,110 --> 00:15:19,950 into some sort of financial genius. 228 00:15:22,290 --> 00:15:23,630 The deal was done. 229 00:15:24,090 --> 00:15:29,590 On a Friday in March 1988, the team moved into a single cramped room within 230 00:15:29,590 --> 00:15:30,630 Blackstone's offices. 231 00:15:31,630 --> 00:15:36,590 They were five computers, a few folding chairs, and a mountain of cables on the 232 00:15:36,590 --> 00:15:41,690 floor. They were under the Blackstone umbrella, but Larry knew that this was 233 00:15:41,690 --> 00:15:42,890 just a temporary shelter. 234 00:15:43,230 --> 00:15:44,990 He didn't just want a department. 235 00:15:45,230 --> 00:15:46,890 He wanted an empire. 236 00:15:47,560 --> 00:15:52,720 he had the money he had the team and in the corner of that small room the first 237 00:15:52,720 --> 00:15:59,480 lines of code for aladdin were being written the information blindness was 238 00:15:59,480 --> 00:16:04,120 the era of black rock though it didn't have that name yet had begun 239 00:16:04,120 --> 00:16:11,160 the 240 00:16:11,160 --> 00:16:16,240 first office of blackstone financial management wasn't a glass tower It was a 241 00:16:16,240 --> 00:16:17,260 glorified closet. 242 00:16:17,680 --> 00:16:23,000 Because of the heat generated by the early Sun Microsystems workstations, the 243 00:16:23,000 --> 00:16:28,040 temperature in the room rarely dropped below 80 degrees, 27 degrees Celsius. 244 00:16:28,860 --> 00:16:33,400 While the rest of the Blackstone group went out to expensive lunches, closing 245 00:16:33,400 --> 00:16:38,560 leveraged buyouts, Larry's original eight were building a digital fortress. 246 00:16:39,940 --> 00:16:42,240 They were the weirdos in the basement. 247 00:16:42,700 --> 00:16:45,900 It was here that the name Aladdin became a living thing. 248 00:16:46,460 --> 00:16:49,940 Every day, Ben Golub and his team fed it data. 249 00:16:50,280 --> 00:16:53,580 Interest rates, housing prices, historical crashes. 250 00:16:53,960 --> 00:16:58,560 They were teaching the machine to be afraid of everything Larry hadn't seen 251 00:16:58,560 --> 00:16:59,560 1986. 252 00:17:04,839 --> 00:17:10,740 By 1992, the department in Ty Blackstone was no longer a start -up. It was a 253 00:17:10,740 --> 00:17:14,730 powerhouse. Larry's team was managing $17 billion. 254 00:17:16,130 --> 00:17:18,470 They weren't just a side project anymore. 255 00:17:18,710 --> 00:17:21,670 They were a significant engine of Blackstone's growth. 256 00:17:21,950 --> 00:17:24,930 But with success came a toxic byproduct. 257 00:17:25,730 --> 00:17:26,829 Identity confusion. 258 00:17:27,890 --> 00:17:29,550 Clients were getting confused. 259 00:17:30,130 --> 00:17:34,730 They would call Blackstone looking for Larry's bond expertise or call Larry 260 00:17:34,730 --> 00:17:36,490 looking for Schwarzman's buyout. 261 00:17:36,770 --> 00:17:41,330 But the friction went deeper than a name. It was a war of philosophies. 262 00:17:41,850 --> 00:17:43,290 Schwartzman was a dealmaker. 263 00:17:43,590 --> 00:17:45,450 He wanted to own companies. 264 00:17:45,910 --> 00:17:50,070 Fink was a producer. He wanted to manage risk for others. 265 00:17:51,270 --> 00:17:56,530 The tension was similar to having two predators in a cage too small to fit 266 00:17:56,790 --> 00:17:58,910 The breaking point came over equity. 267 00:17:59,730 --> 00:18:04,190 Larry wanted to use stocks to attract and keep the original eight and new 268 00:18:04,190 --> 00:18:05,190 talent. 269 00:18:05,310 --> 00:18:09,590 Schwartzman, holding 50 % of the firm, didn't want to dilute his stake. 270 00:18:10,440 --> 00:18:14,360 The partnership that saved Larry's career was now suffocating his vision. 271 00:18:14,780 --> 00:18:17,380 In 1994, they reached a deal. 272 00:18:20,020 --> 00:18:23,780 Schwarzman agreed to sell Blackstone Stokes for $240 million. 273 00:18:24,560 --> 00:18:29,420 At the time, it seemed like a win for Schwarzman, a massive return on his $5 274 00:18:29,420 --> 00:18:30,540 million investment. 275 00:18:31,320 --> 00:18:34,180 It wasn't just about money, it was about the spotlight. 276 00:18:34,840 --> 00:18:36,860 Schwarzman was the king of wall street. 277 00:18:37,420 --> 00:18:41,560 But his sub -tenant, Larry Fink, was the one the New York Times wanted to 278 00:18:41,560 --> 00:18:45,260 interview. But for Larry, it was a price for freedom. 279 00:18:46,380 --> 00:18:51,000 Schwarzman would later call selling Black Rock the worst mistake of my 280 00:18:51,600 --> 00:18:55,220 For Larry, the divorce was the moment the training wheels came off. 281 00:18:55,560 --> 00:18:57,960 He was no longer under anyone's umbrella. 282 00:18:58,200 --> 00:19:00,860 He was the CEO of an independent firm. 283 00:19:01,260 --> 00:19:05,740 Now, he just had to prove he could survive the coming storm of the late 284 00:19:15,820 --> 00:19:16,860 It is 2008. 285 00:19:17,420 --> 00:19:20,560 The financial world was experiencing a heart attack. 286 00:19:21,040 --> 00:19:25,760 The financial smoothies that mortgage -backed securities Larry had helped 287 00:19:25,760 --> 00:19:28,920 30 years earlier had turned into a global poison. 288 00:19:29,580 --> 00:19:34,140 Banks didn't know what they owned. And more importantly, they didn't know what 289 00:19:34,140 --> 00:19:35,140 their neighbors owned. 290 00:19:35,300 --> 00:19:37,180 Trust had evaporated. 291 00:19:37,980 --> 00:19:41,940 When the U .S. government realized the economy was on the brink of a total 292 00:19:41,940 --> 00:19:44,420 blackout, they didn't call Goldman first. 293 00:19:45,020 --> 00:19:46,760 They didn't call JP Morgan. 294 00:19:47,420 --> 00:19:52,340 While the CEOs of Lehman and Merrill were begging for government checks, 295 00:19:52,340 --> 00:19:55,380 Fink was the one the government called to write the checks. 296 00:19:56,380 --> 00:20:00,160 He was the only titan left standing with a clean balance sheet. 297 00:20:01,040 --> 00:20:05,580 The United States government didn't just seek advice, it delegated 298 00:20:05,580 --> 00:20:06,580 responsibility. 299 00:20:07,370 --> 00:20:12,590 BlackRock was tasked with valuing assets no one understood, managing risks no 300 00:20:12,590 --> 00:20:16,730 one could measure, and stabilizing markets that were collapsing in real 301 00:20:18,550 --> 00:20:20,350 This wasn't a bailout. 302 00:20:20,590 --> 00:20:23,630 It was an outsourcing of core sovereign functions. 303 00:20:24,030 --> 00:20:28,610 For the first time, a private firm played a central role in maintaining 304 00:20:28,610 --> 00:20:33,710 financial stability, not through political authority, but through 305 00:20:33,710 --> 00:20:34,710 capability. 306 00:20:35,170 --> 00:20:39,860 From that moment on, Power was no longer just about laws and institutions. 307 00:20:40,440 --> 00:20:43,840 It was about who had the tools to see the system clearly. 308 00:20:45,360 --> 00:20:48,800 BlackRock was hired to manage the toxic waste of the crisis. 309 00:20:49,440 --> 00:20:54,680 They became the official cleaner for the U .S. government, managing $130 billion 310 00:20:54,680 --> 00:20:56,200 of troubled assets. 311 00:20:58,800 --> 00:21:04,040 Suddenly, Larry Fink was the most powerful man in the room, acting as an 312 00:21:04,040 --> 00:21:05,740 to the President and the Treasury. 313 00:21:06,800 --> 00:21:11,340 But while he was saving the system, he saw a once -in -a -lifetime opportunity 314 00:21:11,340 --> 00:21:12,720 to dominate it. 315 00:21:13,220 --> 00:21:17,920 In the middle of the carnage, Barclays Bank in the UK was desperate for cash. 316 00:21:18,440 --> 00:21:20,520 They needed to sell their crowns off. 317 00:21:20,720 --> 00:21:25,120 A division called Barclays Global Investors, which included a 318 00:21:25,120 --> 00:21:27,100 product called iShares. 319 00:21:28,120 --> 00:21:33,540 iShares represented passive investing, ETFs that tracked the whole market 320 00:21:33,540 --> 00:21:34,680 than trying to beat it. 321 00:21:35,530 --> 00:21:38,230 It was the ultimate expression of Larry's philosophy. 322 00:21:38,570 --> 00:21:41,670 Stop betting on stars and start owning the system. 323 00:21:42,250 --> 00:21:46,230 It was a massive $13 .5 billion gamble. 324 00:21:47,070 --> 00:21:50,890 If the markets continued to fall, the deal could sink BlackRock. 325 00:21:51,310 --> 00:21:56,010 But Larry knew something the others didn't. He had looked into the eye of 326 00:21:56,010 --> 00:21:59,350 Aladdin, and Aladdin told him that the bottom was near. 327 00:22:00,190 --> 00:22:05,250 With the acquisition of iShares in 2009, BlackRock doubled its size overnight. 328 00:22:06,010 --> 00:22:07,850 They weren't just a bond shop anymore. 329 00:22:08,170 --> 00:22:11,650 They were now the largest money manager on the planet. 330 00:22:12,130 --> 00:22:15,430 They had gone into the crisis as a respective firm. 331 00:22:15,650 --> 00:22:19,170 They came out of it as the shadow government of finance. 332 00:22:26,090 --> 00:22:29,350 By 2012, Larry Fink had built the machine. 333 00:22:30,010 --> 00:22:32,650 He had the assets, the data, and the influence. 334 00:22:33,090 --> 00:22:36,730 But he realized that being king of Wall Street wasn't enough. 335 00:22:37,410 --> 00:22:40,250 He wanted to change the way the world did business. 336 00:22:40,890 --> 00:22:45,590 Every January, a ritual began that would send tremors through boardrooms from 337 00:22:45,590 --> 00:22:46,850 Detroit to Frankfurt. 338 00:22:47,610 --> 00:22:49,330 Larry started writing letters. 339 00:22:49,610 --> 00:22:51,450 They weren't just annual reports. 340 00:22:51,850 --> 00:22:54,210 They were the Black Rock Manifesto. 341 00:22:57,120 --> 00:22:59,800 In 2018, he dropped a bomb. 342 00:23:00,080 --> 00:23:04,640 He told the world's CEOs that if they wanted BlackRock's money, they had to 343 00:23:04,640 --> 00:23:06,660 prove they served a social purpose. 344 00:23:07,320 --> 00:23:11,520 He wasn't just asking for profits, he was asking for a soul. 345 00:23:12,020 --> 00:23:18,920 He was mainstreaming ESG, Environmental, Social and Governance, and he was doing 346 00:23:18,920 --> 00:23:21,500 it with a $10 trillion hammer. 347 00:23:22,060 --> 00:23:25,500 But Larry's new gospel didn't sit well with everyone. 348 00:23:26,200 --> 00:23:31,140 By 2021, the golden boy was finding himself in the middle of a two -front 349 00:23:32,880 --> 00:23:35,660 The ESG debate was never cultural. 350 00:23:35,900 --> 00:23:37,100 It was economic. 351 00:23:37,720 --> 00:23:43,740 At its core, ESG was about risk management anticipating regulation, 352 00:23:43,740 --> 00:23:45,720 disruption, and social instability. 353 00:23:46,720 --> 00:23:51,320 For BlackRock, ignoring those factors wasn't neutral. It was dangerous. 354 00:23:51,640 --> 00:23:56,390 But when capital begins to price the future, it also begins to shape it. 355 00:23:56,610 --> 00:23:59,010 That's why the backlash was so intense. 356 00:23:59,890 --> 00:24:04,710 To the left, Larry was a hypocrite. They called him a greenwasher because 357 00:24:04,710 --> 00:24:07,770 BlackRock still held billions in oil and gas stocks. 358 00:24:08,210 --> 00:24:12,790 To the right, he was a globalist villain who was using other people's money to 359 00:24:12,790 --> 00:24:14,890 push a radical environmental agenda. 360 00:24:15,450 --> 00:24:19,050 The backlash turned into a full -scale political assault. 361 00:24:21,640 --> 00:24:26,580 State treasurers in Florida, Texas, and Mississippi began pulling billions out 362 00:24:26,580 --> 00:24:27,519 of BlackRock. 363 00:24:27,520 --> 00:24:32,600 They accused Larry of boycotting energy and violating his duty to investors. 364 00:24:33,600 --> 00:24:38,620 For the first time, the man who had mastered risk found himself in a risk he 365 00:24:38,620 --> 00:24:41,100 couldn't calculate, the culture war. 366 00:24:44,980 --> 00:24:49,460 He told a crowd in Aspen that he was ashamed to be a part of the debate. 367 00:24:50,060 --> 00:24:54,720 He even stopped using the term ESG altogether, calling it weaponized. 368 00:24:55,180 --> 00:24:57,760 He had tried to become the conscience of capitalism. 369 00:24:58,220 --> 00:25:01,300 Instead, it became its most controversial target. 370 00:25:01,700 --> 00:25:06,800 But even as the politicians shouted and the protesters marched, the assets kept 371 00:25:06,800 --> 00:25:07,800 growing. 372 00:25:09,620 --> 00:25:13,960 Because in the end, whether you loved him or hated him, you couldn't escape 373 00:25:13,960 --> 00:25:14,960 machine he built. 374 00:25:25,720 --> 00:25:27,160 January 2026. 375 00:25:27,520 --> 00:25:32,180 The number flashes on a terminal in BlackRock's Hudson Yards headquarters. 376 00:25:33,280 --> 00:25:34,400 $14 trillion. 377 00:25:35,400 --> 00:25:39,520 It is a number so vast it defies human comprehension. 378 00:25:40,240 --> 00:25:45,560 If Larry Fink's assets under management were a country's GDP, it would be the 379 00:25:45,560 --> 00:25:50,480 third largest economy on Earth, surpassed only by the United States and 380 00:25:51,240 --> 00:25:55,710 But as Larry looks out from his office, He isn't looking at stock tickets. 381 00:25:55,970 --> 00:25:58,990 He is looking at the very bones of civilization. 382 00:26:02,710 --> 00:26:07,590 In 2024, Larry made his final, most aggressive pivot. 383 00:26:08,050 --> 00:26:13,050 He realized that the next decade won't be one with bits on a screen, but with 384 00:26:13,050 --> 00:26:14,110 atoms in the ground. 385 00:26:14,510 --> 00:26:20,450 With the $12 .5 billion acquisition of global infrastructure partners, Larry 386 00:26:20,450 --> 00:26:22,970 signaled the end of the old Wall Street era. 387 00:26:23,550 --> 00:26:27,870 Larry saw the AI revolution coming, but he didn't buy the chip makers. 388 00:26:28,190 --> 00:26:31,290 He bought the power plants that feed the chips. 389 00:26:36,390 --> 00:26:39,990 But every empire faces the same inevitable question. 390 00:26:40,930 --> 00:26:41,930 Succession. 391 00:26:44,770 --> 00:26:49,450 For years, Wall Street has whispered about who could possibly replace the man 392 00:26:49,450 --> 00:26:50,930 who is Blackrock. 393 00:26:51,610 --> 00:26:56,550 Names like Rob Capito, Mark Weirman, and Jennifer Johnson swirl in the press. 394 00:26:56,810 --> 00:26:58,850 But the truth is more complex. 395 00:26:59,470 --> 00:27:02,650 Larry hasn't just built a company, he's built an organism. 396 00:27:02,970 --> 00:27:08,690 A system where Aladdin, now a very sophisticated AI entity, handles the 397 00:27:08,690 --> 00:27:12,510 while a legion of 20 ,000 employees executes the vision. 398 00:27:13,030 --> 00:27:15,410 Aladdin is no longer just a calculator. 399 00:27:15,810 --> 00:27:20,110 It is a predictive engine that runs millions of simulations every second. 400 00:27:20,560 --> 00:27:24,740 anticipating everything from a war in the Middle East to a crop failure in 401 00:27:24,740 --> 00:27:25,740 Brazil. 402 00:27:26,780 --> 00:27:28,980 Some call him the king of the world. 403 00:27:29,300 --> 00:27:31,680 Others call him the shadow architect. 404 00:27:32,380 --> 00:27:37,240 But if you ask Larry, he'll tell you he's still that kid from the Van Nuys 405 00:27:37,240 --> 00:27:40,560 store, just trying to make sure that the math sat up. 406 00:27:43,380 --> 00:27:47,940 He took the greatest humiliation of his life and turned it into a shield to the 407 00:27:47,940 --> 00:27:48,940 global economy. 408 00:27:49,870 --> 00:27:54,710 He taught the world that profit without a plan is just a gamble, and that in the 409 00:27:54,710 --> 00:27:57,250 dark, the man with the flashlight is king. 410 00:27:59,390 --> 00:28:03,010 There is one financial question the system cannot answer. 411 00:28:03,370 --> 00:28:08,550 What happens when everyone measures risk the same way? When models converge? 412 00:28:08,890 --> 00:28:10,110 When assumptions align? 413 00:28:10,490 --> 00:28:12,530 When diversity of judgment disappears? 414 00:28:13,490 --> 00:28:16,890 A system optimized for stability can become fragile. 415 00:28:17,370 --> 00:28:21,620 Not because it is wrong, but because it leaves no room for the unexpected. 416 00:28:22,400 --> 00:28:26,860 When the supervisor becomes invisible and the rules are embedded in code, 417 00:28:27,100 --> 00:28:29,480 accountability becomes harder to locate. 418 00:28:30,120 --> 00:28:33,060 The system works until it doesn't. 419 00:28:33,280 --> 00:28:37,160 And that's why BlackRock isn't just a shareholder in your company. 420 00:28:37,440 --> 00:28:42,840 They are the landlord of your power plant, the owner of your airport, the 421 00:28:42,840 --> 00:28:44,400 architect of your retirement. 422 00:28:45,050 --> 00:28:49,370 It is a level of centralized influence the world has never seen in a private 423 00:28:49,370 --> 00:28:50,370 individual. 424 00:28:50,750 --> 00:28:56,210 Lawrence D. Fink didn't just build a bank, he built the unblinking eye of 425 00:28:56,210 --> 00:28:57,210 capitalism. 426 00:28:57,550 --> 00:29:02,190 And as the world moves into the era of AI, climate shift, and global 427 00:29:02,190 --> 00:29:07,670 restructuring, one thing is certain, BlackRock will be there, watching, 428 00:29:07,950 --> 00:29:10,370 calculating, and growing. 429 00:30:33,160 --> 00:30:35,400 It's just a small plastic brick. 430 00:30:36,540 --> 00:30:38,480 Lightweight. Simple. 431 00:30:39,680 --> 00:30:41,420 Unchanged since 1958. 432 00:30:42,860 --> 00:30:46,980 And yet, it has built entire universes. 433 00:30:47,620 --> 00:30:50,100 Lego constructions truly take us back to childhood. 434 00:30:51,640 --> 00:30:54,660 But they stay with us throughout our entire lives. 435 00:30:54,920 --> 00:30:57,020 From bedrooms to boardrooms. 436 00:30:57,280 --> 00:30:59,220 From playgrounds to Hollywood. 437 00:30:59,960 --> 00:31:01,840 Lego has shaped generations. 438 00:31:02,990 --> 00:31:07,350 When I design something from scratch, I start with an idea that occurs to me at 439 00:31:07,350 --> 00:31:08,350 any time of day. 440 00:31:09,450 --> 00:31:12,250 I try to build it with Lego and see what I come up with. 441 00:31:12,730 --> 00:31:19,250 In a global toy market worth more than $120 billion, Lego stands alone. 442 00:31:19,670 --> 00:31:25,810 A single company controlling nearly one in every $10 spent on toys worldwide. 443 00:31:26,510 --> 00:31:30,490 Lego holds a leading position worldwide, recognized above all for its 444 00:31:30,490 --> 00:31:31,490 playability. 445 00:31:31,950 --> 00:31:36,150 What if the most beloved toy in the world almost didn't exist? 446 00:31:38,010 --> 00:31:43,810 Discover the incredible journey of a small, struggling carpentry shop that 447 00:31:43,810 --> 00:31:46,250 to dream bigger than anyone thought possible. 448 00:31:46,750 --> 00:31:53,450 This is the untold story of the visionary who built Lego, transforming 449 00:31:53,450 --> 00:31:59,530 simple wooden bricks into a multi -billion dollar empire and forever 450 00:31:59,530 --> 00:32:00,530 how we play. 451 00:32:02,030 --> 00:32:06,350 But none of this began with billion -dollar charts or cinematic universes. 452 00:32:07,350 --> 00:32:10,250 It began with a carpenter with a vision. 453 00:32:11,170 --> 00:32:17,930 In a tiny Danish village, one man had a dream, building toys out of scraps of 454 00:32:17,930 --> 00:32:18,930 wood. 455 00:32:27,370 --> 00:32:33,910 Olleke Christensen was born in 1891 in Western Denmark, a place defined by 456 00:32:33,910 --> 00:32:36,650 silence, soil, and hard work. 457 00:32:37,570 --> 00:32:41,610 He grew up poor, like most children in the Jutland countryside. 458 00:32:42,450 --> 00:32:45,270 But he learned the value of craftsmanship early. 459 00:32:45,790 --> 00:32:48,770 When you made something, it had to last. 460 00:32:50,070 --> 00:32:51,970 He apprenticed as a carpenter. 461 00:32:52,370 --> 00:32:55,950 It was not a really glamorous work, but meticulous. 462 00:32:56,410 --> 00:33:00,590 Honest. A craft that matched Arla's character and manners. 463 00:33:01,910 --> 00:33:05,270 Arla travelled through Denmark, Germany and Norway. 464 00:33:05,930 --> 00:33:08,830 Everywhere he went, he left a reputation. 465 00:33:09,630 --> 00:33:11,050 Precise. Patient. 466 00:33:11,470 --> 00:33:12,470 Relentless. 467 00:33:13,170 --> 00:33:19,150 In 1916, Arla returned home and bought a workshop in a place that barely existed 468 00:33:19,150 --> 00:33:20,150 on the map. 469 00:33:20,370 --> 00:33:23,850 Billund. No shop. No train station. 470 00:33:24,600 --> 00:33:27,840 Just a handful of families trying to survive the Danish winds. 471 00:33:28,140 --> 00:33:32,500 Don't worry, I'm fine. I'm fine. But eight years later, disaster struck. 472 00:33:32,900 --> 00:33:34,660 Oh, oh, oh no. 473 00:33:34,980 --> 00:33:38,600 In 1924, a fire tore through his workshop. 474 00:33:38,920 --> 00:33:40,320 Oh God, no, please no. 475 00:33:40,540 --> 00:33:42,580 Oh my God. Everything burned. 476 00:33:43,100 --> 00:33:45,680 Tools, wood, orders. 477 00:33:46,320 --> 00:33:48,040 And a lifetime of savings. 478 00:33:48,660 --> 00:33:49,660 All gone. 479 00:33:50,740 --> 00:33:52,280 But Oller didn't quit. 480 00:33:53,050 --> 00:33:54,050 He rebuilt. 481 00:33:54,610 --> 00:33:56,450 And rebuilt bigger than before. 482 00:33:56,950 --> 00:34:02,070 Not because it was safe, but because he refused to let villains disappear into 483 00:34:02,070 --> 00:34:03,070 the wind. 484 00:34:03,950 --> 00:34:05,590 Then came the Great Depression. 485 00:34:06,490 --> 00:34:08,090 Houses weren't being built. 486 00:34:08,610 --> 00:34:10,070 Doors weren't being ordered. 487 00:34:10,550 --> 00:34:12,310 Bills weren't being paid. 488 00:34:13,469 --> 00:34:15,850 Oller had workers depending on him. 489 00:34:16,230 --> 00:34:17,929 Families depending on him. 490 00:34:18,449 --> 00:34:20,070 So he did something unexpected. 491 00:34:20,969 --> 00:34:23,449 He began crafting more wooden toys. 492 00:34:24,290 --> 00:34:28,070 They were simple, durable, and beautiful. 493 00:34:29,710 --> 00:34:33,730 Locals mocked him. A grown man making toys for children? 494 00:34:33,949 --> 00:34:35,150 You'll never survive. 495 00:34:36,090 --> 00:34:40,489 But Zoller believed that play, and fun, was a serious business. 496 00:34:41,409 --> 00:34:45,710 In 1934, he held a contest to name the new toy company. 497 00:34:46,290 --> 00:34:47,850 He chose a short word, 498 00:34:48,570 --> 00:34:49,570 Lego. 499 00:34:49,900 --> 00:34:54,719 It was not only a simple idea, but a philosophy and a promise. 500 00:34:55,580 --> 00:34:57,480 He hung a sign in the workshop. 501 00:34:57,860 --> 00:34:59,800 Only the best is good enough. 502 00:35:00,400 --> 00:35:01,820 It wasn't marketing. 503 00:35:02,080 --> 00:35:03,780 It was his identity. 504 00:35:07,860 --> 00:35:13,120 Oh, God, not again. In 1942, Oller faced another fire. 505 00:35:13,820 --> 00:35:16,420 This time it was bigger, more devastating. 506 00:35:16,940 --> 00:35:18,000 Every blueprint. 507 00:35:18,570 --> 00:35:22,130 Every toy, every dream he had turned into smoke. 508 00:35:23,390 --> 00:35:25,510 But he had built himself the hardship. 509 00:35:26,250 --> 00:35:32,130 And once more, he rebuilt the factory, stronger than the two previous ones. 510 00:35:32,950 --> 00:35:36,610 In 1947, at the worst economic moment, 511 00:35:37,410 --> 00:35:39,610 Oller made the riskiest choice of his life. 512 00:35:40,350 --> 00:35:45,110 He spent more than twice the company's annual profits on a strange new machine, 513 00:35:45,470 --> 00:35:48,810 one that worked not with wood, but with plastic. 514 00:35:50,350 --> 00:35:51,710 Retailers hated plastic. 515 00:35:52,330 --> 00:35:56,210 Parents distrusted it. But Ola saw something they didn't. 516 00:35:56,750 --> 00:35:59,930 Precision, repeatability, and possibilities. 517 00:36:00,710 --> 00:36:02,030 Endless possibilities. 518 00:36:03,550 --> 00:36:09,690 Only two years later, in 1949, Lego released the first plastic bricks of its 519 00:36:09,690 --> 00:36:11,710 history. They didn't click. 520 00:36:12,010 --> 00:36:13,310 They weren't perfect. 521 00:36:13,810 --> 00:36:15,650 But they were the beginning. 522 00:36:22,640 --> 00:36:27,360 The idea was good, but Olen had seen faith setbacks while designing the brick 523 00:36:27,360 --> 00:36:30,140 that had cemented Lego's identity through the years. 524 00:36:30,660 --> 00:36:33,220 The plastic brick didn't grip. 525 00:36:33,960 --> 00:36:38,140 This was a major problem for a building set because buildings collapsed. 526 00:36:38,860 --> 00:36:40,900 Towers fell in front of their eyes. 527 00:36:41,460 --> 00:36:44,340 Apparently Lego wasn't created to build. 528 00:36:44,880 --> 00:36:49,360 And then, in 1958, everything changed. 529 00:36:50,570 --> 00:36:55,350 Unlike 20 years ago, LEGO today allows us to build many more things because 530 00:36:55,350 --> 00:36:58,030 have released more realistic colors and shapes. 531 00:37:00,670 --> 00:37:03,450 In the past, the pieces were mostly square. 532 00:37:03,750 --> 00:37:08,730 Today, there is a much wider variety of shapes, including more rounded elements, 533 00:37:08,930 --> 00:37:13,970 which allow us to create more ergonomic forms, ones that more closely resemble 534 00:37:13,970 --> 00:37:17,630 the kinds of buildings and structures we see in everyday life. 535 00:37:18,900 --> 00:37:22,960 Engineers at LEGO perfected a simple but ingenious solution. 536 00:37:23,620 --> 00:37:25,780 Hollow tubes inside the brick. 537 00:37:27,120 --> 00:37:32,380 Paired with the studs on top, the geometry created what LEGO calls clutch 538 00:37:32,800 --> 00:37:36,800 Not too tight, not too loose, just perfect. 539 00:37:37,980 --> 00:37:40,560 This was not just an adjustment or improvement. 540 00:37:41,020 --> 00:37:44,660 It was the birth of what we know today as a LEGO brick. 541 00:37:45,340 --> 00:37:49,140 The brick that, today, can still be used with the modern ones. 542 00:37:50,280 --> 00:37:54,700 The brick that was the foundation of a company that still makes history today. 543 00:37:55,860 --> 00:37:58,660 That same year, Lego filed the patent. 544 00:37:59,320 --> 00:38:03,940 They had something worth protecting, and Ollie knew that sooner or later, it 545 00:38:03,940 --> 00:38:04,940 would be replicated. 546 00:38:06,720 --> 00:38:11,580 It was January the 28th, 1958, when the patent was filed. 547 00:38:12,260 --> 00:38:15,750 Later that year, Oliver Christensen passed away. 548 00:38:16,730 --> 00:38:21,430 And sadly, he never lived to see how far his brick would travel. 549 00:38:31,270 --> 00:38:35,390 After his father died, Gottfried Kirk Christensen stepped in. 550 00:38:36,150 --> 00:38:38,310 He wasn't inheriting the company. 551 00:38:38,630 --> 00:38:40,570 He was inheriting a philosophy. 552 00:38:41,250 --> 00:38:42,970 One he had been raised with. 553 00:38:43,550 --> 00:38:48,490 His father wasn't around anymore, but the original spirit of Lego lived on in 554 00:38:48,490 --> 00:38:49,950 the second Christensen generation. 555 00:38:51,190 --> 00:38:53,170 But he also had something to add. 556 00:38:53,830 --> 00:38:58,370 Godfrey believed Lego should be more than toys. It should be a system. 557 00:38:58,770 --> 00:39:04,430 A system where every piece connected with every other piece, across every 558 00:39:05,270 --> 00:39:08,550 This created a language of creativity and possibilities. 559 00:39:09,190 --> 00:39:11,590 And a single idea changed everything. 560 00:39:12,680 --> 00:39:17,600 Suddenly, LEGO wasn't a collection of toys, but an entire universe. 561 00:39:18,800 --> 00:39:22,760 The company began to grow far beyond its original frontiers. 562 00:39:23,360 --> 00:39:30,020 During the 1960s and 70s, LEGO expanded across Europe, Germany, Sweden, 563 00:39:30,240 --> 00:39:31,240 the UK. 564 00:39:31,980 --> 00:39:36,160 Finland, once a small village, became a global hub of play. 565 00:39:36,780 --> 00:39:41,480 LEGO then built its own airports, factories, and distribution centers. 566 00:39:41,960 --> 00:39:46,280 In the world of construction toys, we know that LEGO isn't the only brand 567 00:39:46,280 --> 00:39:47,280 around. 568 00:39:48,400 --> 00:39:50,780 What LEGO provides is a quality product. 569 00:39:52,980 --> 00:39:58,440 Maybe one part is wrong for every 10 ,000 or 100 ,000 items, and if you are 570 00:39:58,440 --> 00:40:02,920 missing an item from a box, or if it is faulty, the company's after -sales 571 00:40:02,920 --> 00:40:05,820 service will not question the fact that you are missing a part. 572 00:40:09,080 --> 00:40:10,080 And then? 573 00:40:10,570 --> 00:40:11,690 The magic happened. 574 00:40:12,590 --> 00:40:16,470 Lego introduced something no toy company had done at scale. 575 00:40:17,030 --> 00:40:18,830 Fully themed worlds. 576 00:40:19,430 --> 00:40:22,410 Base, town, castles. 577 00:40:23,270 --> 00:40:25,750 Children weren't just building structures anymore. 578 00:40:26,010 --> 00:40:27,710 They were building stories. 579 00:40:28,830 --> 00:40:34,850 In 1978, Lego released its most iconic invention since the brick. The 580 00:40:34,850 --> 00:40:37,530 minifigure. It had a simple face. 581 00:40:38,030 --> 00:40:39,770 Hands shaped like a C. 582 00:40:40,410 --> 00:40:42,330 and feet made to stand on studs. 583 00:40:42,610 --> 00:40:47,830 A tiny character that let kids project themselves into entire universes. 584 00:40:48,770 --> 00:40:52,290 Dory's now had heroes, and Lego had a heartbeat. 585 00:40:52,990 --> 00:40:58,270 In the late 1970s, Lego was already run by the third Christensen generation. 586 00:40:59,090 --> 00:41:05,070 Ole's grandson, Kjeld, began shaping the company into the global powerhouse we 587 00:41:05,070 --> 00:41:06,070 know today. 588 00:41:06,310 --> 00:41:09,510 He did so by creating more sophisticated lines. 589 00:41:10,140 --> 00:41:11,540 bringing in new universes. 590 00:41:12,240 --> 00:41:17,500 Technic brought mechanics, pirates brought adventure, and trains brought 591 00:41:18,140 --> 00:41:22,920 By the late 20th century, the global toy market was becoming massive. 592 00:41:23,560 --> 00:41:26,180 Tens of billions of dollars a year worth. 593 00:41:26,780 --> 00:41:32,340 The United States spent more on toys than any country on Earth, and China 594 00:41:32,340 --> 00:41:35,880 produced most of them, nearly three quarters of the world total. 595 00:41:36,900 --> 00:41:38,640 In this booming landscape, 596 00:41:39,370 --> 00:41:41,290 Lego wasn't just another toy. 597 00:41:41,670 --> 00:41:43,450 It was the toy. 598 00:41:50,370 --> 00:41:53,990 By the late 1990s, Lego was flying high. 599 00:41:54,270 --> 00:41:59,410 It had become one of the most admired companies in Europe. A creative 600 00:41:59,410 --> 00:42:02,270 built on the philosophy of imagination and creation. 601 00:42:02,890 --> 00:42:06,830 We're not focused only on childhood, but on something that has quite literally 602 00:42:06,830 --> 00:42:11,650 built us, pun intended, shaping our personalities through Lego from an early 603 00:42:11,650 --> 00:42:16,150 age. Those memories became a foundation we've kept building on over time. 604 00:42:18,470 --> 00:42:21,810 That's why exhibitions like this bring us straight back to childhood. 605 00:42:22,010 --> 00:42:27,430 The audience here is very diverse, but once people walk in, they all become the 606 00:42:27,430 --> 00:42:28,950 boy or girl they once were. 607 00:42:29,470 --> 00:42:31,870 But it's not all gold that glitters. 608 00:42:32,590 --> 00:42:35,890 Under the surface, something dangerous was creeping in. 609 00:42:36,330 --> 00:42:38,710 The toy market was changing fast. 610 00:42:39,090 --> 00:42:43,010 Children were spending more and more time with video games and early computer 611 00:42:43,010 --> 00:42:44,010 entertainment. 612 00:42:44,390 --> 00:42:49,030 Sony's PlayStation, Nintendo and Hasbro's electronic toys were capturing 613 00:42:49,030 --> 00:42:55,570 attention. And Lego, determined not to fall behind, expanded too far, too fast. 614 00:42:56,470 --> 00:43:01,870 Throughout the 1990s, Lego began introducing thousands of completely new 615 00:43:02,520 --> 00:43:05,360 specialized parts that not only worked in one set. 616 00:43:05,860 --> 00:43:12,280 A single year could bring more than 350 new designs, each of them costing tens 617 00:43:12,280 --> 00:43:16,020 of thousands of dollars in steel, machining, and precision engineering. 618 00:43:17,480 --> 00:43:22,420 In 2002, LEGO had more than 12 ,000 active elements. 619 00:43:22,900 --> 00:43:28,420 The system of play, once simple and universal, was becoming chaotic and 620 00:43:28,420 --> 00:43:29,420 difficult to follow. 621 00:43:30,060 --> 00:43:32,860 Lego also tried becoming a lifestyle brand. 622 00:43:33,340 --> 00:43:35,220 New ventures appeared everywhere. 623 00:43:35,460 --> 00:43:41,260 Clothing lines, theme parks, home goods, cartoon series, even watches and 624 00:43:41,260 --> 00:43:42,260 sneakers. 625 00:43:42,380 --> 00:43:47,820 But these projects drained resources without reinforcing the core product, 626 00:43:47,820 --> 00:43:54,180 brick. And between 1999 and 2003, Lego sales collapsed. 627 00:43:54,900 --> 00:43:59,640 During these years, The company went from double -digit growth to struggling, 628 00:43:59,860 --> 00:44:05,460 and by 2003, the company was losing the equivalent of $1 million a day. 629 00:44:06,160 --> 00:44:12,940 In a global toy market, still worth more than $70 billion at the time, Lego, 630 00:44:13,200 --> 00:44:17,080 once the king of the toy box, was only a few steps away from bankruptcy. 631 00:44:18,140 --> 00:44:21,760 Times were dark, but the spark of genius appeared. 632 00:44:22,440 --> 00:44:23,640 In 1999, 633 00:44:24,490 --> 00:44:28,770 Lego signed its first ever licensing deal with no other than Lucasfilm. 634 00:44:29,590 --> 00:44:31,210 The timing was perfect. 635 00:44:32,030 --> 00:44:35,410 Star Wars Episode I was about to hit theaters. 636 00:44:36,050 --> 00:44:40,650 Hype was global, and the first Lego Star Wars sets were instant hits. 637 00:44:41,330 --> 00:44:43,850 Not just with children, with adults. 638 00:44:44,630 --> 00:44:49,490 Collectors lined up to buy the X -Wing, the Snowspeeder, or the first Millennium 639 00:44:49,490 --> 00:44:53,110 Falcon. For the first time in Lego's history, 640 00:44:54,050 --> 00:44:58,650 Adults, including those in their 30s and 40s, were buying sets for themselves. 641 00:44:59,190 --> 00:45:01,830 The adult fan of LEGO community is getting bigger. 642 00:45:02,110 --> 00:45:06,450 This is because LEGO is not the same as it was 20 or 30 years ago. 643 00:45:08,350 --> 00:45:12,730 Before, LEGO was only seen as a toy to play with when it was cold and you were 644 00:45:12,730 --> 00:45:13,730 indoors. 645 00:45:15,900 --> 00:45:20,800 Today, LEGO is much more than a toy. It's used to create logos, to design 646 00:45:20,800 --> 00:45:25,240 dynamic group activities, and it also represents a shift in how we see it. 647 00:45:26,020 --> 00:45:30,860 Years ago, if you said you played with LEGO or built LEGO, you almost had to 648 00:45:30,860 --> 00:45:35,080 explain yourself that you were at home, playing with little figures, making up 649 00:45:35,080 --> 00:45:39,780 battles. What we do today is different. We come together as a community of 650 00:45:39,780 --> 00:45:42,060 adults, and LEGO has recognized that. 651 00:45:43,040 --> 00:45:47,840 That's why more and more products are now designed specifically for adults, 652 00:45:47,840 --> 00:45:50,760 complex to build, and also more expensive. 653 00:45:53,920 --> 00:45:58,620 This kid -old demographic would later become one of LEGO's most profitable 654 00:45:58,620 --> 00:46:01,400 segments. More licenses followed. 655 00:46:01,640 --> 00:46:07,540 Harry Potter, Spider -Man, Batman, Indiana Jones, and later the newest 656 00:46:07,540 --> 00:46:08,580 Cinematic Universe. 657 00:46:09,680 --> 00:46:15,300 Even though Lego learned that storytelling sells, in 2004 losses were 658 00:46:15,300 --> 00:46:17,060 and survival was uncertain. 659 00:46:17,760 --> 00:46:20,960 And then the company made a radical decision. 660 00:46:21,780 --> 00:46:27,080 For the first time in its history, the company appointed a CEO from outside the 661 00:46:27,080 --> 00:46:28,080 Christensen family, 662 00:46:28,640 --> 00:46:33,460 JĂ¼rgen B. Knudstorp, a 35 -year -old former McKinsey consultant. 663 00:46:34,100 --> 00:46:38,920 He was calm, precise, analytical, and... 664 00:46:39,130 --> 00:46:40,130 brutally honest. 665 00:46:40,510 --> 00:46:42,410 His diagnosis was simple. 666 00:46:42,930 --> 00:46:46,230 Lego had forgotten what made it Lego. 667 00:46:47,450 --> 00:46:53,130 Knut Storp cut the number of unique elements by nearly 50%. He sold off the 668 00:46:53,130 --> 00:46:56,930 theme parks. He shut down unprofitable production facilities. 669 00:46:57,450 --> 00:47:02,610 He centralized supply chains, standardized materials, and brought back 670 00:47:02,610 --> 00:47:03,750 discipline to the system. 671 00:47:04,090 --> 00:47:07,190 But more important, he put the brakes back. 672 00:47:07,520 --> 00:47:08,620 at the center of the company. 673 00:47:12,560 --> 00:47:15,240 This turnaround didn't happen in isolation. 674 00:47:15,700 --> 00:47:19,500 The global toy industry was undergoing a seismic change. 675 00:47:20,280 --> 00:47:25,560 China was producing nearly 75 % of the world's toys, being the largest 676 00:47:25,560 --> 00:47:28,080 manufacturing consolidation in toy history. 677 00:47:29,140 --> 00:47:33,960 Meanwhile, the United States had become the single largest consumer, responsible 678 00:47:33,960 --> 00:47:36,680 for nearly one -third of the global toy spending. 679 00:47:39,470 --> 00:47:44,810 By 2005, the toy market was worth close to 80 billion US dollars. 680 00:47:45,250 --> 00:47:47,910 But it was brutally competitive as well. 681 00:47:49,130 --> 00:47:50,470 Seasonality was extreme. 682 00:47:50,750 --> 00:47:55,890 Nearly half of the annual toy sales occurred in just three months, from 683 00:47:55,890 --> 00:47:56,890 to December. 684 00:47:57,850 --> 00:48:00,330 Companies lived or died by Christmas. 685 00:48:01,130 --> 00:48:03,510 Mattel was battling declining Barbie sales. 686 00:48:03,990 --> 00:48:08,130 Hasbro was betting its future on Transformers and board game 687 00:48:08,990 --> 00:48:12,410 electronics were eating market share across every age group. 688 00:48:12,890 --> 00:48:19,590 In this scenario, LEGO rebuilt and refocused, and then began 689 00:48:19,590 --> 00:48:21,470 rising above all of them. 690 00:48:26,870 --> 00:48:33,830 Between 2008 and 2015, LEGO entered a new era, a renaissance driven 691 00:48:33,830 --> 00:48:40,760 by design, storytelling, digital engagement, and adult passion the 692 00:48:40,760 --> 00:48:45,680 launched the ultimate collective series producing the largest most detailed 693 00:48:45,680 --> 00:48:51,280 models in toy history lego architecture brought landmarks to coffee tables 694 00:48:51,280 --> 00:48:57,240 modular buildings turned living rooms into miniature cities and adults were no 695 00:48:57,240 --> 00:49:02,720 longer hiding their lego hobby but embracing it my story with lego began in 696 00:49:02,720 --> 00:49:04,740 early 90s when i was a small child 697 00:49:06,400 --> 00:49:09,100 I started playing, but then I stopped for a while. 698 00:49:10,140 --> 00:49:14,220 This is what most of us want to do when we are teenagers, to do other hobbies 699 00:49:14,220 --> 00:49:16,020 and spend less time playing with LEGO. 700 00:49:18,860 --> 00:49:22,860 After that, when I was in my early 20s, I started collecting LEGO. 701 00:49:23,780 --> 00:49:27,340 I met people from the Valencian community and founded Valbrek. 702 00:49:29,080 --> 00:49:32,880 That eventually led me to a television show where I took part and won. 703 00:49:33,470 --> 00:49:36,850 From there, companies began approaching me to develop projects. 704 00:49:39,950 --> 00:49:42,890 At first, this hadn't even occurred to me. 705 00:49:44,090 --> 00:49:48,690 But I started to see a growing demand, whether it was building a corporate kit 706 00:49:48,690 --> 00:49:53,090 like a transport company's truck or even a company's logistics headquarters. 707 00:49:54,010 --> 00:49:57,030 This market opened up a professional path for me. 708 00:49:57,950 --> 00:50:02,350 It supports me financially, but more importantly, it's deeply rewarding. 709 00:50:03,490 --> 00:50:07,370 Many of these projects challenge me to build things I would never choose on my 710 00:50:07,370 --> 00:50:08,370 own. 711 00:50:08,690 --> 00:50:13,330 But once the challenge is set, build this, my mind immediately starts 712 00:50:13,330 --> 00:50:18,510 ideas, figuring out how to shape them and bring the project to life in the 713 00:50:18,510 --> 00:50:19,510 possible way. 714 00:50:23,350 --> 00:50:26,230 Seattle fans of LEGO skyrocketed. 715 00:50:26,650 --> 00:50:30,590 Forums, conventions, fan events, engineering cups. 716 00:50:31,040 --> 00:50:32,640 a global movement emerged. 717 00:50:33,400 --> 00:50:38,440 By 2014, Adolf accounted for nearly one -third of Lego sales. 718 00:50:39,220 --> 00:50:44,160 To anyone who thinks Lego is only for children, I'd say, come and see the 719 00:50:44,160 --> 00:50:48,940 exhibition. See what we're capable of creating with Lego pieces and how 720 00:50:48,940 --> 00:50:51,840 imagination develops in both children and adults. 721 00:50:54,000 --> 00:50:58,900 Children work within certain limits and see things differently, but adults... 722 00:50:59,360 --> 00:51:04,340 with a wider range of colors, shapes, and ways to use the pieces, can explore 723 00:51:04,340 --> 00:51:05,700 just how much is possible. 724 00:51:07,500 --> 00:51:12,620 It was a radical shift in the economics of play, and then came the cultural 725 00:51:12,620 --> 00:51:13,620 explosion. 726 00:51:14,160 --> 00:51:21,060 In 2014, the Lego movie shattered expectations, earning nearly 500 million 727 00:51:21,060 --> 00:51:22,820 US dollars at the box office. 728 00:51:23,680 --> 00:51:27,380 What started as a toy was now pop culture. 729 00:51:28,040 --> 00:51:33,900 By the mid -2010s, Lego was the world's most valuable toy company, even 730 00:51:33,900 --> 00:51:37,040 surpassing Mattel, Hasbro, and every other competitor. 731 00:51:38,040 --> 00:51:42,020 The brick that started it all was no longer just a product. 732 00:51:42,320 --> 00:51:44,620 It was a global icon. 733 00:51:48,920 --> 00:51:53,580 The Lego Group stands today as one of the most efficient, profitable, and 734 00:51:53,580 --> 00:51:55,860 culturally influential toy companies on Earth. 735 00:51:56,380 --> 00:51:58,880 Its factories run with near -perfect precision. 736 00:51:59,940 --> 00:52:03,900 Its design teams develop thousands of prototypes each year. 737 00:52:04,320 --> 00:52:08,740 Its supply chain delivers billions of bricks that must all fit together 738 00:52:08,740 --> 00:52:10,900 flawlessly across decades. 739 00:52:11,980 --> 00:52:18,960 In a global toy market worth roughly $120 billion a year, LEGO commands 740 00:52:18,960 --> 00:52:22,060 nearly 9 % of all worldwide toy sales. 741 00:52:22,920 --> 00:52:28,420 No other toy brand, not Barbie, not Marvel figures, not Nintendo 742 00:52:28,860 --> 00:52:33,700 maintains such consistency across continents, genders, and generations. 743 00:52:34,560 --> 00:52:40,120 And unlike most toy companies that outsource manufacturing, LEGO controls a 744 00:52:40,120 --> 00:52:45,040 significant portion of its own production, with major hubs in Denmark, 745 00:52:45,260 --> 00:52:47,520 Mexico, China, and Czech Republic. 746 00:52:48,760 --> 00:52:54,670 This vertical integration reduces risk, stabilizes quality, and protects one of 747 00:52:54,670 --> 00:52:58,450 the most important values in the company's DNA, precision. 748 00:52:59,470 --> 00:53:04,470 Every LEGO brick must be manufactured with tolerances thinner than a strand of 749 00:53:04,470 --> 00:53:08,110 hair. If the clutch is too tight, the model breaks. 750 00:53:08,530 --> 00:53:11,310 If it's too loose, towers collapse. 751 00:53:12,090 --> 00:53:16,050 Across billions of pieces, perfection is not an ambition. 752 00:53:16,410 --> 00:53:19,310 It is an engineering reality for LEGO. 753 00:53:20,840 --> 00:53:25,500 This level of detail gives the company one of the highest brand trust ratings 754 00:53:25,500 --> 00:53:26,500 the world. 755 00:53:26,540 --> 00:53:28,460 Parents know the bricks will last. 756 00:53:29,000 --> 00:53:30,780 Adults know the sets will impress. 757 00:53:31,640 --> 00:53:34,240 Collectors know the investment will hold value. 758 00:53:35,260 --> 00:53:40,640 The modern toy market is a machine of impulse, tradition, celebration and 759 00:53:40,640 --> 00:53:41,640 nostalgia. 760 00:53:41,940 --> 00:53:48,080 In 2025, global spending on toys approaches $120 billion. 761 00:53:49,020 --> 00:53:51,540 nearly double what it was two decades earlier. 762 00:53:52,140 --> 00:53:57,000 The United States remains the world's largest consumer, accounting for roughly 763 00:53:57,000 --> 00:53:58,520 one -third of global sales. 764 00:53:59,240 --> 00:54:05,440 A typical American household with children may spend $300 to $400 per 765 00:54:05,440 --> 00:54:06,440 year on toys. 766 00:54:06,820 --> 00:54:09,700 This is more than five times the global average. 767 00:54:11,040 --> 00:54:15,820 Europe forms the second largest bloc, with strong purchasing power in Germany, 768 00:54:15,940 --> 00:54:17,660 the United Kingdom and France. 769 00:54:18,730 --> 00:54:24,050 Asia -Pacific is rapidly growing, especially in China, South Korea, and 770 00:54:24,370 --> 00:54:28,050 driven by rising middle classes and urban lifestyles. 771 00:54:28,870 --> 00:54:33,510 But the most important shift of the last decade is not geographic. 772 00:54:33,770 --> 00:54:35,490 It is demographic. 773 00:54:41,910 --> 00:54:47,230 Adults, once considered irrelevant to the toy industry, are now one of the 774 00:54:47,230 --> 00:54:48,440 most... powerful forces. 775 00:54:49,020 --> 00:54:53,880 This growing segment, commonly called the kid -old market, now represents 776 00:54:53,880 --> 00:54:57,920 between 25 and 30 % of all toy purchases worldwide. 777 00:54:59,300 --> 00:55:05,340 Adults buy toys for nostalgia, for stress relief, for display, for 778 00:55:06,300 --> 00:55:09,220 Lego is the undisputed champion of this movement. 779 00:55:09,700 --> 00:55:13,020 Unlike other hobbies, Lego gives me a sense of calm. 780 00:55:16,610 --> 00:55:21,730 It lets me take ideas from my mind, bring them to life, think them through, 781 00:55:21,730 --> 00:55:23,090 simply enjoy the process. 782 00:55:23,870 --> 00:55:29,450 Right now, I'm trying to instill that in my son, to enjoy himself, to learn, to 783 00:55:29,450 --> 00:55:33,530 see colors and shapes, and to understand that with imagination anything is 784 00:55:33,530 --> 00:55:34,530 possible. 785 00:55:42,880 --> 00:55:47,460 Regularly exceed prices of $300, $500, even $800. 786 00:55:48,220 --> 00:55:50,240 They sell within hours. 787 00:55:50,500 --> 00:55:53,920 They hold aftermarket values like fine collectibles. 788 00:55:54,280 --> 00:55:59,080 This adult segment has reshaped the entire financial landscape of the 789 00:55:59,640 --> 00:56:03,060 It provides stability when children's trends shift. 790 00:56:03,340 --> 00:56:06,440 It creates recurring revenue from loyal fans. 791 00:56:06,840 --> 00:56:11,220 And it strengthens LEGO's position as a cross -generational brand. 792 00:56:12,110 --> 00:56:14,590 something few toy companies have ever achieved. 793 00:56:15,850 --> 00:56:19,110 Seasonality still dictates much of the global toy market. 794 00:56:19,470 --> 00:56:24,530 Every year, nearly half of all toy sales occur between October and December. 795 00:56:25,270 --> 00:56:31,010 Companies live or die by holiday forecasting, inventory strategy, and 796 00:56:31,010 --> 00:56:34,170 timing. But LEGO has become the exception. 797 00:56:34,930 --> 00:56:37,150 Adult collectors buy year -round. 798 00:56:37,840 --> 00:56:41,600 Digital experiences drive sales outside the holiday season. 799 00:56:42,240 --> 00:56:46,120 Licensed launches create anticipation even in slow quarters. 800 00:56:47,080 --> 00:56:51,920 Lego has effectively freed itself, or at least partially, from the seasonal 801 00:56:51,920 --> 00:56:55,560 dependency that has defined the toy industry for over a century. 802 00:56:56,260 --> 00:56:59,960 The brick is physical, tangible, mechanical. 803 00:57:00,520 --> 00:57:05,600 But Lego's success in the 21st century extends into the digital world. 804 00:57:06,000 --> 00:57:07,040 Star Wars. 805 00:57:07,530 --> 00:57:08,870 Batman, Marvel. 806 00:57:09,310 --> 00:57:13,630 These games defined an entire generation of family -friendly titles. 807 00:57:14,050 --> 00:57:16,630 They sold tens of millions of copies. 808 00:57:16,910 --> 00:57:22,790 They introduced humor, storytelling, and simplicity to a medium often dominated 809 00:57:22,790 --> 00:57:23,790 by complexity. 810 00:57:24,550 --> 00:57:30,010 For many children born after the year 2000, Lego was not discovered in a toy 811 00:57:30,010 --> 00:57:31,670 box, but on a screen. 812 00:57:32,230 --> 00:57:35,070 The cinematic leap came in 2014. 813 00:57:35,920 --> 00:57:40,920 when the Lego movie premiered to global acclaim. It earned nearly half a billion 814 00:57:40,920 --> 00:57:47,060 dollars. Most importantly, it reframed Lego as a cultural idea, not a product. 815 00:57:47,560 --> 00:57:52,920 The film taught a global audience that creativity matters, that imperfection is 816 00:57:52,920 --> 00:57:58,200 beautiful, that building and rebuilding are not failures, they are the process 817 00:57:58,200 --> 00:57:59,200 of play. 818 00:57:59,460 --> 00:58:01,820 Lego Batman expanded the concept. 819 00:58:02,410 --> 00:58:08,350 Lego Ninjago created an entirely new generation of fans, and Lego Masters on 820 00:58:08,350 --> 00:58:11,550 television turned building into a competitive art form. 821 00:58:12,170 --> 00:58:17,170 The brand had moved beyond toys, beyond stories, beyond bricks. 822 00:58:17,490 --> 00:58:21,770 It had become part of the cultural grammar of the 21st century. 823 00:58:27,450 --> 00:58:32,760 Long before STEM became a global movement, Lego was already teaching 824 00:58:32,760 --> 00:58:34,300 how to think like engineers. 825 00:58:34,880 --> 00:58:41,080 In the 1990s, Lego Mindstorms introduced programmable robotics to students 826 00:58:41,080 --> 00:58:42,080 around the world. 827 00:58:42,740 --> 00:58:49,220 Later sets, WeDo, Spike Prime, Boost, brought coding, sensors, and motors into 828 00:58:49,220 --> 00:58:50,260 classrooms and homes. 829 00:58:50,840 --> 00:58:56,880 Today, Lego Education works with governments, schools, and universities 830 00:58:56,880 --> 00:58:58,940 hands -on learning to millions of students. 831 00:58:59,950 --> 00:59:01,270 The philosophy is simple. 832 00:59:01,670 --> 00:59:03,490 Children learn best through play. 833 00:59:03,990 --> 00:59:08,850 This approach shapes future engineers, designers, and problem solvers. 834 00:59:09,330 --> 00:59:12,750 It helps children experiment in ways that textbooks cannot. 835 00:59:13,350 --> 00:59:18,350 And it continues Oleg Kirk's belief that play is not a distraction from 836 00:59:18,350 --> 00:59:20,610 learning, but the foundation of it. 837 00:59:22,320 --> 00:59:26,520 In a world increasingly focused on sustainability... From my experience, 838 00:59:26,520 --> 00:59:30,820 makes LEGO different from other construction toys is its growing 839 00:59:30,820 --> 00:59:35,760 inclusion. In recent years, LEGO has actively embraced people with different 840 00:59:35,760 --> 00:59:40,220 abilities, for example, by including figures in wheelchairs and releasing 841 00:59:40,220 --> 00:59:41,220 in Braille. 842 00:59:41,520 --> 00:59:45,080 These are things most other brands simply don't offer, but LEGO does. 843 00:59:46,320 --> 00:59:49,520 In addition, LEGO is strongly committed to the environment. 844 00:59:50,420 --> 00:59:54,420 They're producing more and more pieces using recycled plastic and replacing 845 00:59:54,420 --> 00:59:58,800 plastic packaging with paper to reduce weight, something other brands simply 846 00:59:58,800 --> 00:59:59,880 don't do. 847 01:00:01,640 --> 01:00:03,800 LEGO faces a unique challenge. 848 01:00:04,440 --> 01:00:06,500 Its bricks are made to last forever. 849 01:00:07,200 --> 01:00:11,460 A blessing for creativity, but a concern in an era of plastic waste. 850 01:00:11,980 --> 01:00:17,140 In response, Lego has invested hundreds of millions of dollars into developing 851 01:00:17,140 --> 01:00:18,520 more sustainable materials. 852 01:00:19,420 --> 01:00:23,460 Plant -based polyethylene is already used for leaves and trees. 853 01:00:24,440 --> 01:00:27,460 Recycled PET prototypes continue to advance. 854 01:00:28,660 --> 01:00:31,440 Recycled PET prototypes continue to advance. 855 01:00:32,330 --> 01:00:38,490 New polymer engineering aims to create bricks as durable as ABS, without the 856 01:00:38,490 --> 01:00:39,490 environmental cost. 857 01:00:40,330 --> 01:00:42,810 This transition is not simple. 858 01:00:43,370 --> 01:00:46,630 The Lego brick must interlock with perfect precision. 859 01:00:47,050 --> 01:00:51,290 A fraction of a millimeter can make the difference between wonder and 860 01:00:51,290 --> 01:00:53,950 frustration. But the mission is clear. 861 01:00:54,550 --> 01:00:59,170 A toy that lasts forever should also protect the world it is played in. 862 01:00:59,890 --> 01:01:01,470 Play is not a luxury. 863 01:01:02,160 --> 01:01:03,160 Play is exploration. 864 01:01:03,660 --> 01:01:05,160 Play is curiosity. 865 01:01:06,020 --> 01:01:09,140 Play is the earliest form of human creativity. 866 01:01:10,120 --> 01:01:15,420 From wooden ducks in a small Danish workshop, to interlocking bricks that 867 01:01:15,420 --> 01:01:21,800 generation, to movies, video games, robotics, and global fan community, 868 01:01:22,480 --> 01:01:25,160 LEGO has remained loyal to a simple truth. 869 01:01:25,440 --> 01:01:27,620 When we build, we grow. 870 01:01:27,860 --> 01:01:30,300 When we imagine, we expand. 871 01:01:31,080 --> 01:01:34,000 When we play, we become more human. 872 01:01:40,160 --> 01:01:45,300 More than a century ago, a carpenter rebuilt his workshop after a fire. 873 01:01:45,680 --> 01:01:47,880 He rebuilt it again after another. 874 01:01:48,700 --> 01:01:53,660 Not because it was easy, but because he believed in the power of making things. 875 01:01:54,080 --> 01:01:55,660 And in the power of play. 876 01:01:56,560 --> 01:02:00,360 Today, billions of creations have risen from that belief. 877 01:02:00,990 --> 01:02:02,850 Cities. Castles. 878 01:02:03,310 --> 01:02:04,310 Bayships. 879 01:02:04,950 --> 01:02:09,050 Dreams that exist nowhere else but in the minds of the people who build them. 880 01:02:10,110 --> 01:02:12,110 Lego is not perfect. 881 01:02:12,450 --> 01:02:16,730 It has faced crises, challenges, and impossible decisions. 882 01:02:17,250 --> 01:02:23,390 But it endures. Through war, through technological revolutions, through 883 01:02:23,390 --> 01:02:27,690 storms. The car's imagination always endures. 884 01:02:28,490 --> 01:02:33,130 And as long as there are hands reaching the brick, as long as there are minds 885 01:02:33,130 --> 01:02:37,890 ready to create, the legacy of Ola Kirk -Christensen will continue. 886 01:02:39,070 --> 01:02:42,370 Every dream starts with a single piece. 887 01:04:11,180 --> 01:04:14,320 Jensen Huang, the software moat. 888 01:04:15,140 --> 01:04:17,460 June 18th, 2024. 889 01:04:18,460 --> 01:04:23,220 For a brief historic moment, the world had a new king. 890 01:04:24,440 --> 01:04:31,240 Jensen Huang, the co -founder and CEO of NVIDIA, stood at the peak of a $3 .4 891 01:04:31,240 --> 01:04:32,500 trillion mountain. 892 01:04:34,600 --> 01:04:37,860 Analysts whispered that he wasn't just leading a company. 893 01:04:38,640 --> 01:04:43,860 He was leading the first entity destined for a $4 trillion valuation. 894 01:04:46,140 --> 01:04:51,180 But to understand the man in the leather jacket, you cannot look at the triumph. 895 01:04:51,460 --> 01:04:53,700 You must look at the fear. 896 01:04:54,600 --> 01:05:01,300 Behind the 250 % revenue jumps and the sold -out H100 backlogs 897 01:05:01,300 --> 01:05:04,620 lies a leader obsessed with the cyclical trap. 898 01:05:05,930 --> 01:05:11,770 In a 60 -year history of semiconductors, giants like Texas Instruments, Intel, 899 01:05:12,050 --> 01:05:17,370 and Samsung have all held the crown only to see it slip away. 900 01:05:19,030 --> 01:05:20,850 Jensen's mission is simple. 901 01:05:21,350 --> 01:05:24,610 Break the cycle before it breaks him. 902 01:05:26,910 --> 01:05:29,050 Flashback to September 1996. 903 01:05:29,550 --> 01:05:34,290 The golden era of the Internet is dawning for everyone else. 904 01:05:34,640 --> 01:05:37,300 But for NVIDIA, it is a death knell. 905 01:05:38,660 --> 01:05:45,200 Their first chip, the NV1, is a technical ghost, rejected by Microsoft's 906 01:05:45,200 --> 01:05:46,200 DirectX. 907 01:05:47,240 --> 01:05:53,020 Jensen stands before a dwindling team and delivers the most famous mantra in 908 01:05:53,020 --> 01:05:54,160 Silicon Valley history. 909 01:05:55,100 --> 01:05:58,680 We have exactly 30 days of oxygen left. 910 01:05:59,020 --> 01:06:01,580 We are 30 days from bankruptcy. 911 01:06:02,990 --> 01:06:07,910 How does a man go from cleaning toilets in a Kentucky reform school to 912 01:06:07,910 --> 01:06:11,450 controlling the foundational layer of the global AI economy? 913 01:06:12,730 --> 01:06:18,110 From a red leather booth at a Denny's to a legal showdown in the U .S. Supreme 914 01:06:18,110 --> 01:06:21,970 Court over the very intellectual honesty of his empire. 915 01:06:22,750 --> 01:06:26,130 This is not just a story of silicon and software. 916 01:06:27,180 --> 01:06:32,140 This is the chronicle of the man who decided to manufacture intelligence 917 01:06:32,880 --> 01:06:37,920 This is Jensen Huang, the architect of the digital brain. 918 01:06:39,840 --> 01:06:46,800 Chapter 1 Forged in the Chaos Nvidia was not 919 01:06:46,800 --> 01:06:48,060 born from abundance. 920 01:06:48,520 --> 01:06:52,140 Its DNA was forged in the raw fires of survival. 921 01:06:53,540 --> 01:06:59,420 Jensen Huang arrived in the United States as a young migrant, but his 922 01:06:59,420 --> 01:07:01,920 destination wasn't an elite prep school. 923 01:07:02,540 --> 01:07:08,120 Due to a clerical misunderstanding by his parents, he was sent to Oneida 924 01:07:08,120 --> 01:07:14,460 Institute in rural Kentucky, a place that, at the time, functioned more as a 925 01:07:14,460 --> 01:07:17,840 reformed school for troubled youth than a traditional academy. 926 01:07:18,740 --> 01:07:24,060 At nine years old, The future CEO of one of the world's most valuable companies 927 01:07:24,060 --> 01:07:25,100 wasn't coding. 928 01:07:25,520 --> 01:07:30,680 He was cleaning the toilets of 150 teenagers every single afternoon. 929 01:07:31,920 --> 01:07:37,040 In his personal transcript, Jensen reflects on this with a chilling 930 01:07:37,480 --> 01:07:38,800 I didn't complain. 931 01:07:39,060 --> 01:07:41,160 I just learned to work hard. 932 01:07:41,940 --> 01:07:47,020 That boy learned the first law of accelerated computing decades before it 933 01:07:47,020 --> 01:07:53,060 existed. For a system to be efficient, it must be able to process chaos under 934 01:07:53,060 --> 01:07:54,120 extreme pressure. 935 01:07:56,020 --> 01:08:01,820 By 15, Jensen was the most efficient dishwasher and waiter at a Denny's in 936 01:08:01,820 --> 01:08:02,819 Portland. 937 01:08:02,820 --> 01:08:08,380 I was incredibly shy, he admits, but the chaos of the kitchen forced me out of 938 01:08:08,380 --> 01:08:09,380 my shell. 939 01:08:10,020 --> 01:08:16,880 It is no coincidence that NVIDIA was founded in 1993 inside a booth at that 940 01:08:16,880 --> 01:08:18,120 same restaurant chain. 941 01:08:19,020 --> 01:08:23,600 While the world saw the dawn of the PC as an office tool for spreadsheets, 942 01:08:23,840 --> 01:08:29,260 Jensen, Chris Malachowski, and Curtis Priam saw a fatal weakness. 943 01:08:31,319 --> 01:08:37,399 In 1993, Intel's general -purpose CPU was hitting a physical wall. 944 01:08:38,020 --> 01:08:43,300 If the future of computing was visual and immersive, the traditional serial 945 01:08:43,300 --> 01:08:46,600 architecture would become the bottleneck of human progress. 946 01:08:47,819 --> 01:08:54,000 With only $40 ,000 in startup capital, they founded NVIDIA to chase a ghost, 947 01:08:54,260 --> 01:08:55,620 accelerated computing. 948 01:08:56,680 --> 01:09:01,340 They bet on a market the rest of the industry dismissed as a niche for toys, 949 01:09:01,660 --> 01:09:02,700 video games. 950 01:09:03,300 --> 01:09:08,120 But Thor Jensen, video games were the ultimate technological flywheel. 951 01:09:08,740 --> 01:09:13,500 He knew that if you could master the massive, real -time rendering of pixels, 952 01:09:13,779 --> 01:09:16,600 you could eventually simulate reality itself. 953 01:09:18,250 --> 01:09:23,090 But before they could reach that glory, they had to survive their first massive 954 01:09:23,090 --> 01:09:25,430 technical abyss, the NV1. 955 01:09:34,550 --> 01:09:41,529 By 1995, NVIDIA's first massive bet, the NV1 chip, was ready 956 01:09:41,529 --> 01:09:42,550 to conquer the market. 957 01:09:42,950 --> 01:09:46,529 But Jensen Huang had made a catastrophic technical gamble. 958 01:09:47,850 --> 01:09:52,710 At the time when the industry was undecided, he bet on quadratic texture 959 01:09:52,710 --> 01:09:57,030 mapping, a method that used curved surfaces to create 3D images. 960 01:09:58,070 --> 01:10:02,490 It was mathematically intelligent, but it was a lonely path. 961 01:10:03,370 --> 01:10:08,090 The industry hammer dropped when Microsoft released its first DirectX 962 01:10:08,450 --> 01:10:14,210 Microsoft chose triangles, not quads, as the universal language for PC gaming. 963 01:10:15,400 --> 01:10:19,580 This decision rendered NVIDIA's technology instantly obsolete. 964 01:10:20,440 --> 01:10:24,620 The NV1 wasn't just a failure, it was a dead end. 965 01:10:25,040 --> 01:10:30,940 The company was bleeding cash, and as Jensen famously put it, they were 966 01:10:30,940 --> 01:10:33,420 at exactly 30 days of oxygen. 967 01:10:36,420 --> 01:10:41,480 NVIDIA's only lifeline was a strategic contract with the Japanese giant Sega to 968 01:10:41,480 --> 01:10:43,800 build the graphics engine for the Sega Saturn. 969 01:10:44,750 --> 01:10:47,890 but Jensen was trapped in a moral and business dilemma. 970 01:10:48,890 --> 01:10:53,830 He knew that if they continued building the chip for Sega using NVIDIA's flawed 971 01:10:53,830 --> 01:10:59,890 quad technology, Sega would lose the console war to Sony's PlayStation, and 972 01:10:59,890 --> 01:11:02,050 NVIDIA would eventually perish anyway. 973 01:11:02,750 --> 01:11:07,690 In an act of intellectual honesty, or as many at the time called corporate 974 01:11:07,690 --> 01:11:08,690 suicide, 975 01:11:09,130 --> 01:11:10,290 Jensen flew to Japan. 976 01:11:10,970 --> 01:11:17,600 He sat across from Shoichiro Irimajiri, the CEO of Sega, and told him the brutal 977 01:11:17,600 --> 01:11:21,120 truth. Our technology is on the wrong path. 978 01:11:21,420 --> 01:11:25,480 If we finish this project, you will produce an inferior product. 979 01:11:27,100 --> 01:11:29,080 Jensen asked for the impossible. 980 01:11:29,620 --> 01:11:34,600 He asked Sega to terminate the contract, but to pay the remaining $5 million 981 01:11:34,600 --> 01:11:40,520 anyway. If you don't pay us, Jensen pleaded, NVIDIA will cease to exist 982 01:11:40,520 --> 01:11:41,520 tomorrow. 983 01:11:42,470 --> 01:11:46,490 To the astonishment of the tech world, Irimajiri -san agreed. 984 01:11:47,070 --> 01:11:49,070 He didn't pay for a working chip. 985 01:11:49,330 --> 01:11:51,310 He paid for Jensen's integrity. 986 01:11:53,090 --> 01:11:57,530 That $5 million was the most expensive oxygen in history. 987 01:11:58,490 --> 01:12:02,370 To make it last, Jensen had to fire half of his workforce. 988 01:12:03,030 --> 01:12:06,730 These weren't just employees. They were friends who had shared the Denny's 989 01:12:06,730 --> 01:12:07,730 dream. 990 01:12:07,920 --> 01:12:12,120 This trauma institutionalized a permanent state of emergency at NVIDIA. 991 01:12:13,520 --> 01:12:18,980 With the remaining team, Jensen funneled every cent into the Revo 128. 992 01:12:20,040 --> 01:12:24,740 They abandoned quarks and embraced Microsoft's triangles with a vengeance. 993 01:12:25,240 --> 01:12:31,920 When it launched in 1997, the Revo 128 was 400 % faster 994 01:12:31,920 --> 01:12:33,660 than anything else on the market. 995 01:12:34,730 --> 01:12:37,130 It was a dive catch of epic proportions. 996 01:12:37,990 --> 01:12:40,090 NVIDIA was no longer just a survivor. 997 01:12:40,410 --> 01:12:42,470 It had become a hunter. 998 01:12:43,650 --> 01:12:49,290 But as Jensen looked at the horizon, he saw 70 rivals waiting to kill him. 999 01:12:49,590 --> 01:12:51,810 The war was only beginning. 1000 01:12:59,310 --> 01:13:03,190 The success of the Reaver 128 was a dive catch. 1001 01:13:03,800 --> 01:13:06,780 but it placed NVIDIA in the middle of a slaughterhouse. 1002 01:13:07,600 --> 01:13:13,480 By 1997, there were over 70 companies fighting for the soul of the 3D graphics 1003 01:13:13,480 --> 01:13:14,480 market. 1004 01:13:14,920 --> 01:13:19,080 It was a commodity war where price -cutting was the only weapon for most. 1005 01:13:20,240 --> 01:13:25,180 Jensen Huang realized that if NVIDIA played by the industry's rules, they 1006 01:13:25,180 --> 01:13:26,600 eventually be ground in dust. 1007 01:13:28,220 --> 01:13:30,700 He decided to break the laws of time. 1008 01:13:31,790 --> 01:13:37,250 The industry standard for developing a new chip was 18 to 24 months, following 1009 01:13:37,250 --> 01:13:38,790 the steady beat of Moore's Law. 1010 01:13:39,790 --> 01:13:43,710 Jensen gathered his engineers and imposed a suicidal mandate. 1011 01:13:44,350 --> 01:13:49,850 NVIDIA would release a brand new, groundbreaking architecture every six 1012 01:13:51,730 --> 01:13:54,510 It was a strategy of relentless execution. 1013 01:13:55,230 --> 01:14:02,170 By the time a competitor like 3DFX or S3 could react to one NVIDIA chip, Jensen 1014 01:14:02,170 --> 01:14:03,870 had already launched two more. 1015 01:14:04,910 --> 01:14:08,650 This forced the competition into a permanent state of obsolescence. 1016 01:14:09,330 --> 01:14:15,070 To achieve this, NVIDIA had to reinvent its internal engineering, running 1017 01:14:15,070 --> 01:14:19,730 multiple design teams in parallel, a massive financial risk that pushed the 1018 01:14:19,730 --> 01:14:21,970 company to the edge of its operational capacity. 1019 01:14:22,530 --> 01:14:26,590 In 1999, the war reached its climax. 1020 01:14:27,330 --> 01:14:30,110 NVIDIA released the GeForce 256. 1021 01:14:32,200 --> 01:14:35,240 Jensen didn't just market it as a faster card. 1022 01:14:35,500 --> 01:14:38,640 He coined a term that would redefine computing history. 1023 01:14:39,140 --> 01:14:40,240 The GPU. 1024 01:14:41,080 --> 01:14:42,500 Graphics Processing Unit. 1025 01:14:43,140 --> 01:14:44,760 This wasn't just branding. 1026 01:14:45,520 --> 01:14:52,520 Technically, the G4 -256 moved the transform and writing calculations, the 1027 01:14:52,520 --> 01:14:57,400 heavy mathematical lifting of 3D, off the CPU and onto the chip itself. 1028 01:14:57,960 --> 01:15:00,240 It was the birth of a new era. 1029 01:15:01,390 --> 01:15:06,390 This performance leap was so massive that NVIDIA secured the prestigious 1030 01:15:06,390 --> 01:15:12,090 to the original Microsoft Xbox, receiving a crucial $200 million 1031 01:15:13,910 --> 01:15:15,910 The six -month cycle worked. 1032 01:15:16,270 --> 01:15:22,670 By the early 2000s, the 70 competitors had been reduced to just two, NVIDIA and 1033 01:15:22,670 --> 01:15:23,670 ATI. 1034 01:15:24,010 --> 01:15:29,830 In a final act of dominance, NVIDIA acquired the assets of its former idol 1035 01:15:29,830 --> 01:15:32,600 arch -rival, 3DFX in 2000. 1036 01:15:33,860 --> 01:15:35,860 Jensen had cleared the board. 1037 01:15:36,080 --> 01:15:39,140 He was the undisputed king of gaming. 1038 01:15:39,680 --> 01:15:44,720 But at the very moment of his greatest triumph, he began to look at the high 1039 01:15:44,720 --> 01:15:46,100 -performance computing market. 1040 01:15:46,640 --> 01:15:51,540 He realized that the GPU's massive parallel map could do more than just 1041 01:15:51,540 --> 01:15:55,400 pixels. It could solve the world's most complex problems. 1042 01:15:56,000 --> 01:16:00,200 The Thieves of Cuda and the $10 billion gamble. 1043 01:16:00,730 --> 01:16:01,730 were being planted. 1044 01:16:09,070 --> 01:16:14,330 By 2006, NVIDIA was the undisputed king of the gaming world. 1045 01:16:14,810 --> 01:16:16,950 But Jensen Huang was restless. 1046 01:16:17,270 --> 01:16:21,770 He realized that the same parallel processing power that rendered pixels 1047 01:16:21,770 --> 01:16:25,990 World of Warcraft could be used to solve the world's most complex mathematical 1048 01:16:25,990 --> 01:16:26,990 problems. 1049 01:16:27,730 --> 01:16:29,450 He launched CUDA. 1050 01:16:30,080 --> 01:16:32,180 Compute Unified Device Architecture. 1051 01:16:32,720 --> 01:16:36,580 It was a declaration of war against the CPU -centric world. 1052 01:16:37,440 --> 01:16:39,840 The goal was simple, yet insane. 1053 01:16:40,420 --> 01:16:44,840 Transform every NVIDIA GPU into a general -purpose supercomputer. 1054 01:16:46,000 --> 01:16:48,880 But this decision came with a staggering cost. 1055 01:16:49,680 --> 01:16:55,400 Jensen mandated that every single GPU NVIDIA manufactured, from the high -end 1056 01:16:55,400 --> 01:17:00,010 workstation cards to the cheapest laptop chips, must include the extra 1057 01:17:00,010 --> 01:17:02,950 transistors and hardware logic to support CUDA. 1058 01:17:04,130 --> 01:17:06,310 Wall Street was horrified. 1059 01:17:07,710 --> 01:17:14,470 For nearly a decade, NVIDIA spent billions, estimated at over $10 billion 1060 01:17:14,470 --> 01:17:19,150 cumulative R &D, on a software platform that almost no one was using. 1061 01:17:20,130 --> 01:17:25,450 Profit margins, which once sat comfortably high, were sacrificed at the 1062 01:17:25,450 --> 01:17:26,450 this vision. 1063 01:17:27,080 --> 01:17:31,320 analysts mocked the strategy, calling it the bridge to nowhere. 1064 01:17:32,040 --> 01:17:38,060 During the 2008 financial crisis, NVIDIA's market cap plummeted, and the 1065 01:17:38,060 --> 01:17:40,520 was once again staring into the abyss. 1066 01:17:41,880 --> 01:17:44,340 But Jensen wasn't just building hardware. 1067 01:17:44,580 --> 01:17:47,200 He was building a software moat. 1068 01:17:47,540 --> 01:17:52,840 He sent NVIDIA engineers to universities around the world, helping professors 1069 01:17:52,840 --> 01:17:55,440 teach parallel programming using CUDA. 1070 01:17:56,560 --> 01:17:57,980 He was ceding the ground. 1071 01:17:58,580 --> 01:18:04,860 While competitors like Intel and AMD focused on making faster chips, Jensen 1072 01:18:04,860 --> 01:18:06,280 building an entire language. 1073 01:18:07,120 --> 01:18:10,720 By the time a developer learned CUDA, they were locked in. 1074 01:18:11,400 --> 01:18:14,860 Switching to a competitor wouldn't just mean buying a new chip. 1075 01:18:15,120 --> 01:18:18,340 It would mean rewriting millions of lines of code. 1076 01:18:19,820 --> 01:18:24,820 Year after year, Jensen defended CUDA in boardrooms and earning calls. 1077 01:18:25,610 --> 01:18:30,730 He practiced what he calls long -term commitment to a vision, even when the 1078 01:18:30,730 --> 01:18:31,830 didn't yet support it. 1079 01:18:32,590 --> 01:18:35,870 He was waiting for a killer app for accelerated computing. 1080 01:18:36,830 --> 01:18:41,230 He didn't know what it would be, but he knew that if data grew exponentially, 1081 01:18:41,770 --> 01:18:45,170 the serial processing of the CPU would eventually fail. 1082 01:18:46,190 --> 01:18:49,510 The silence of the cuda winter was about to be broken. 1083 01:18:50,470 --> 01:18:56,700 In a lab at the University of Toronto, A PhD student named Alex Krusevsky was 1084 01:18:56,700 --> 01:19:01,200 about to feed a neural network called AlexNet into those NVIDIA GPUs. 1085 01:19:02,020 --> 01:19:07,800 The big bang of artificial intelligence was seconds away, and Jensen Huang was 1086 01:19:07,800 --> 01:19:12,020 the only person on Earth who had already built the engine to power it. 1087 01:19:19,840 --> 01:19:21,520 The year was 2012. 1088 01:19:22,440 --> 01:19:27,300 While the world saw just another academic competition, Jensen Huang saw 1089 01:19:27,300 --> 01:19:29,720 spark that would ignite a global revolution. 1090 01:19:30,420 --> 01:19:37,400 A neural network called AlexNet, powered by NVIDIA GPUs, crushed the competition 1091 01:19:37,400 --> 01:19:38,640 in image recognition. 1092 01:19:39,120 --> 01:19:42,100 It was the big bang of deep learning. 1093 01:19:43,000 --> 01:19:47,260 Jensen didn't just celebrate, he pivoted the entire company. 1094 01:19:47,720 --> 01:19:53,180 He realized that the $10 billion gamble on CUDA but finally found its soul, 1095 01:19:53,440 --> 01:19:54,960 artificial intelligence. 1096 01:19:56,180 --> 01:20:01,520 This pivot transformed NVIDIA from a graphics card company into the 1097 01:20:01,520 --> 01:20:04,540 engine of the world's most powerful data center. 1098 01:20:06,160 --> 01:20:08,880 Jensen's vision was no longer about drawing pixels. 1099 01:20:09,120 --> 01:20:11,580 It was about generative AI. 1100 01:20:12,340 --> 01:20:19,080 By the time ChatGPT launched in late 2022, NVIDIA didn't just have a head 1101 01:20:19,740 --> 01:20:21,900 They were the only ones at the starting line. 1102 01:20:24,380 --> 01:20:27,560 Jensen acted with a speed that terrified his competitors. 1103 01:20:27,960 --> 01:20:32,940 He didn't just wait for orders. He re -engineered NVIDIA's entire roadmap. 1104 01:20:33,780 --> 01:20:40,540 In 2016, he personally delivered the first NVIDIA DGX -1, the world's 1105 01:20:40,540 --> 01:20:46,040 first AI supercomputer in a box, to a then -small non -profit called OpenAI. 1106 01:20:46,520 --> 01:20:47,900 He was very clear. 1107 01:20:48,570 --> 01:20:50,270 This will change the world. 1108 01:20:53,510 --> 01:20:56,210 Technically, this period was about specialization. 1109 01:20:56,970 --> 01:20:59,910 NVIDIA began adding tensor cores to its chips. 1110 01:21:00,410 --> 01:21:03,990 These weren't for graphics. They were designed specifically for the deep 1111 01:21:03,990 --> 01:21:06,330 learning math that powers neural networks. 1112 01:21:07,510 --> 01:21:12,130 NVIDIA was no longer just making a faster graphics card. It was building a 1113 01:21:12,130 --> 01:21:13,130 specialized brain. 1114 01:21:13,970 --> 01:21:17,170 By 2017, the momentum was unstoppable. 1115 01:21:18,090 --> 01:21:22,810 Every major tech giant was building AI labs, and they all had one thing in 1116 01:21:22,810 --> 01:21:25,370 common. They were built on NVIDIA's stack. 1117 01:21:26,390 --> 01:21:29,930 This was the era when the software moat became a fortress. 1118 01:21:30,810 --> 01:21:34,810 Thousands of researchers were now writing their doctoral thesis on CUDA. 1119 01:21:36,070 --> 01:21:40,630 If a competitor wanted to challenge NVIDIA, they wouldn't just need a better 1120 01:21:40,630 --> 01:21:45,470 chip. They would have to convince the world's brightest minds to forget 1121 01:21:45,470 --> 01:21:46,970 everything they had learned. 1122 01:21:48,430 --> 01:21:52,730 But as the AI revolution took hold, an unexpected shadow emerged. 1123 01:21:53,210 --> 01:21:58,370 A new craze called Bitcoin and Ethereum began to consume NVIDIA's supply. 1124 01:21:59,330 --> 01:22:04,910 To the world, NVIDIA looked invincible, but internally, Jensen was wary. 1125 01:22:05,530 --> 01:22:08,390 Jensen knew that every bubble eventually burst. 1126 01:22:09,190 --> 01:22:14,350 This period of explosive, accidental growth from crypto miners was creating a 1127 01:22:14,350 --> 01:22:16,270 shadow over the company's true mission. 1128 01:22:17,320 --> 01:22:21,560 setting the stage for a high -stakes legal battle over corporate transparency 1129 01:22:21,560 --> 01:22:25,820 and a financial storm that would test the very foundations of its leadership. 1130 01:22:31,820 --> 01:22:38,220 In 2018, NVIDIA was riding a wave that looked like a miracle, but felt like a 1131 01:22:38,220 --> 01:22:43,380 mirage. The explosion of cryptocurrency mining had created an insatiable hunger 1132 01:22:43,380 --> 01:22:44,560 for G4 cards. 1133 01:22:45,960 --> 01:22:50,140 To the outside world, NVIDIA's revenue was reaching historic heights. 1134 01:22:50,540 --> 01:22:54,920 However, beneath the surface, a dangerous ambiguity was growing. 1135 01:22:55,920 --> 01:23:00,580 Jensen Huang insisted that the growth was driven by a gaining renaissance, but 1136 01:23:00,580 --> 01:23:02,100 the reality was more volatile. 1137 01:23:02,680 --> 01:23:06,260 The mirage evaporated in late 2018. 1138 01:23:07,000 --> 01:23:12,240 The crypto winter arrived, and the demand for mining chips vanished 1139 01:23:13,660 --> 01:23:17,860 NVIDIA was left with a massive surplus of inventory, and the market's reaction 1140 01:23:17,860 --> 01:23:18,860 was brutal. 1141 01:23:18,980 --> 01:23:23,420 The company's stock price plummeted by 28 % in a single day. 1142 01:23:24,560 --> 01:23:29,340 The invincible architect of AI was suddenly facing a crisis of credibility. 1143 01:23:31,140 --> 01:23:34,940 This financial collapse ignited a high -stakes legal battle that would 1144 01:23:34,940 --> 01:23:37,560 eventually reach the steps of the US Supreme Court. 1145 01:23:38,560 --> 01:23:42,240 A group of institutional investors filed a class -action lawsuit. 1146 01:23:42,920 --> 01:23:46,340 alleging that Jensen Huang had deliberately misled the market. 1147 01:23:46,840 --> 01:23:50,560 The core of the case rested on a single, devastating word. 1148 01:23:51,700 --> 01:23:54,300 Cienta. The intent to deceive. 1149 01:23:55,340 --> 01:23:57,140 The accusation was sharp. 1150 01:23:57,520 --> 01:24:01,780 Investors claimed that internal Nvidia reports clearly showed over a billion 1151 01:24:01,780 --> 01:24:06,480 dollars in revenue attributed to gamers was actually coming from crypto miners. 1152 01:24:07,380 --> 01:24:10,900 Jensen fought back, defending his intellectual honesty. 1153 01:24:11,520 --> 01:24:15,260 and arguing that the expert opinions used against him were nothing more than 1154 01:24:15,260 --> 01:24:16,260 speculation. 1155 01:24:17,000 --> 01:24:19,360 This battle, known as Petition No. 1156 01:24:19,580 --> 01:24:26,480 23 -970, became a landmark moment for Silicon Valley, questioning how much a 1157 01:24:26,480 --> 01:24:30,600 must disclose when their technology accidentally conquered the market they 1158 01:24:30,600 --> 01:24:31,840 didn't intend to lead. 1159 01:24:33,560 --> 01:24:38,220 While lawyers argued in Washington, Jensen was already looking past the 1160 01:24:38,220 --> 01:24:43,100 wreckage. He didn't let the legal storm or the inventory crisis slow down his 1161 01:24:43,100 --> 01:24:44,100 ultimate plan. 1162 01:24:44,500 --> 01:24:49,720 He doubled down on the data center, acquiring Mellanox for $7 billion to 1163 01:24:49,720 --> 01:24:51,660 the highways between his chips. 1164 01:24:52,520 --> 01:24:57,420 He was preparing for a world where AI wouldn't just be a research project, but 1165 01:24:57,420 --> 01:24:59,700 the operating system of the entire planet. 1166 01:25:00,720 --> 01:25:06,260 The storm of 2018 had been a warning. The era of generative AI was about to 1167 01:25:06,260 --> 01:25:07,260 provide the answer. 1168 01:25:13,680 --> 01:25:16,900 By 2022, the world had changed. 1169 01:25:17,560 --> 01:25:23,260 The launch of ChatGPT signaled the arrival of the generative AI era, and 1170 01:25:23,260 --> 01:25:25,640 was the only company prepared to power it. 1171 01:25:26,640 --> 01:25:32,240 But as Jensen Huang stood on the brink of total market dominance, a new wall 1172 01:25:32,240 --> 01:25:36,000 built, not by a competitor, but by the U .S. government. 1173 01:25:36,980 --> 01:25:40,760 Washington imposed strict export controls on high -end AI chips. 1174 01:25:41,200 --> 01:25:43,990 For NVIDIA, the stakes were astronomical. 1175 01:25:45,470 --> 01:25:50,930 According to the geographical revenue data, China accounted for approximately 1176 01:25:50,930 --> 01:25:54,270 % to 25 % of the company's total business. 1177 01:25:55,690 --> 01:26:01,110 Overnight, Jensen had to navigate a geopolitical minefield, redesigning 1178 01:26:01,110 --> 01:26:05,410 specifically to comply with regulations while trying to keep his most important 1179 01:26:05,410 --> 01:26:06,790 market from slipping away. 1180 01:26:08,650 --> 01:26:12,950 Jensen's answer to the geopolitical and technical pressure was the Blackwell 1181 01:26:12,950 --> 01:26:13,950 architecture. 1182 01:26:14,110 --> 01:26:18,370 If the H100 was a spark, Blackwell was a sun. 1183 01:26:19,230 --> 01:26:25,150 Packing an incredible 208 billion transistors, it delivered up to 30 times 1184 01:26:25,150 --> 01:26:27,790 performance of its predecessor for certain AI tasks. 1185 01:26:28,850 --> 01:26:32,030 But Blackwell represented a deeper strategic shift. 1186 01:26:32,470 --> 01:26:34,870 NVIDIA was no longer just a chipmaker. 1187 01:26:36,550 --> 01:26:40,170 Jensen was now building entire AI factories. 1188 01:26:41,230 --> 01:26:46,170 By integrating Mellanox networking technology, he controlled the highways 1189 01:26:46,170 --> 01:26:50,210 allowed thousands of chips to talk to each other as if they were a single 1190 01:26:50,210 --> 01:26:51,210 brain. 1191 01:26:52,090 --> 01:26:56,710 This system -on -a -cluster approach meant that even if a competitor produced 1192 01:26:56,710 --> 01:27:00,890 faster individual chip, they couldn't compete with the sheer efficiency of the 1193 01:27:00,890 --> 01:27:01,890 NVIDIA ecosystem. 1194 01:27:03,390 --> 01:27:05,810 The financial results were staggering. 1195 01:27:06,090 --> 01:27:07,670 By early 2024, 1196 01:27:08,520 --> 01:27:15,140 NVIDIA's data center revenue had surged to over $47 billion, a 217 % 1197 01:27:15,140 --> 01:27:16,920 increase in a single year. 1198 01:27:17,600 --> 01:27:23,680 The company was operating with 78 .4 % gross margins, profit levels usually 1199 01:27:23,680 --> 01:27:27,120 reserved for software giants, not hardware manufacturers. 1200 01:27:28,300 --> 01:27:34,340 On June 18, 2024, NVIDIA became the most valuable company on the planet. 1201 01:27:35,440 --> 01:27:40,120 Yet... Even as he stood at the summit, Jensen refused to relax. 1202 01:27:40,820 --> 01:27:46,020 He looked at the 60 -year history of semiconductors, the rise and fall of 1203 01:27:46,260 --> 01:27:51,260 the cycles of Samsung and TI, and he knew that being on top was the most 1204 01:27:51,260 --> 01:27:52,340 dangerous place to be. 1205 01:27:52,880 --> 01:27:56,260 His next challenge wouldn't just be about chips. 1206 01:27:56,700 --> 01:27:59,880 It would be about giving AI a physical body. 1207 01:28:06,220 --> 01:28:11,980 In 2024, Jensen Huang had already conquered the digital world, but his 1208 01:28:11,980 --> 01:28:14,500 fixed on a new frontier, the physical one. 1209 01:28:15,080 --> 01:28:20,240 He declared that the next wave of AI would be physical AI, intelligence that 1210 01:28:20,240 --> 01:28:24,800 doesn't just process text or images, but understands the laws of physics. 1211 01:28:25,840 --> 01:28:31,360 Everything that moved, from autonomous cars to humanoid robots, would 1212 01:28:31,360 --> 01:28:33,160 be powered by an NVIDIA brain. 1213 01:28:34,350 --> 01:28:38,050 This identifies it as the third pillar of NVIDIA's future. 1214 01:28:38,690 --> 01:28:44,770 To win this race, Jensen isn't just building chips, he's building the 1215 01:28:45,370 --> 01:28:49,990 This is a digital world where robots are trained millions of times in a virtual 1216 01:28:49,990 --> 01:28:53,510 simulation before they ever step into a real factory. 1217 01:28:54,670 --> 01:29:00,070 By the time a robot starts its job, it has already lived a thousand lifetimes 1218 01:29:00,070 --> 01:29:01,070 experience. 1219 01:29:01,200 --> 01:29:04,400 Jensen's strategy is a total vertical integration. 1220 01:29:04,840 --> 01:29:08,820 He is transforming NVIDIA into a provider of AI factories. 1221 01:29:09,540 --> 01:29:14,900 He believes that in the future, every company will have two factories, one 1222 01:29:14,900 --> 01:29:18,700 produces physical goods and a digital one that produces intelligence. 1223 01:29:19,560 --> 01:29:23,980 With the Mellanox networking high -speed highways and the CUDA software 1224 01:29:23,980 --> 01:29:28,440 fortress, Jensen has ensured that the entire infrastructure of this new 1225 01:29:28,440 --> 01:29:31,260 industrial revolution runs on NVIDIA. 1226 01:29:31,520 --> 01:29:37,140 When asked about his legacy, Jensen doesn't talk about stock prices or 1227 01:29:37,140 --> 01:29:37,999 of dollars. 1228 01:29:38,000 --> 01:29:42,220 He talks about material sciences and scientific discovery. 1229 01:29:43,040 --> 01:29:48,480 He believes AI will give humans superpowers, helping us solve climate 1230 01:29:48,700 --> 01:29:53,740 cure diseases, and handle the dangerous and mundane tasks so we can focus on 1231 01:29:53,740 --> 01:29:56,500 what truly makes us human, curiosity. 1232 01:30:01,610 --> 01:30:02,630 By 2025, 1233 01:30:03,390 --> 01:30:07,050 the world had entered a state of compute geopolitics. 1234 01:30:07,690 --> 01:30:13,550 NVIDIA was no longer just a company. It had become a strategic resource, similar 1235 01:30:13,550 --> 01:30:14,950 to oil or grain. 1236 01:30:15,710 --> 01:30:21,570 The launch of the Bacwell B200 hadn't just met demand. It had ignited a global 1237 01:30:21,570 --> 01:30:22,570 scramble. 1238 01:30:22,890 --> 01:30:28,670 Nations like Japan, France, and the UAE began building sovereign AI clouds. 1239 01:30:29,400 --> 01:30:33,900 Realizing that depending on a few Silicon Valley giants for intelligence 1240 01:30:33,900 --> 01:30:35,240 national security risk. 1241 01:30:36,100 --> 01:30:41,280 But as 2025 progressed, a new whisper began to haunt the industry. 1242 01:30:42,020 --> 01:30:43,020 The wall. 1243 01:30:43,140 --> 01:30:46,740 For years, AI progress relied on scaling laws. 1244 01:30:47,080 --> 01:30:51,640 The idea that more data and more GPUs would inevitably lead to more 1245 01:30:51,640 --> 01:30:57,040 intelligence. However, in 2026, the returns are starting to diminish. 1246 01:30:57,840 --> 01:31:02,700 Data centers are becoming so massive, they require their own dedicated nuclear 1247 01:31:02,700 --> 01:31:07,300 power plants, and the low -hanging fruit of Internet data has been exhausted. 1248 01:31:08,780 --> 01:31:12,100 Jensen's response to the wall is typically defiant. 1249 01:31:12,500 --> 01:31:16,600 He pivoted the industry towards synthetic data and reasoning models. 1250 01:31:17,100 --> 01:31:24,020 In 2026, NVIDIA's focus has shifted from simply training AI to inference 1251 01:31:24,020 --> 01:31:25,020 of scale. 1252 01:31:25,640 --> 01:31:30,620 The goal is no longer just to build a model that knows everything, but to 1253 01:31:30,620 --> 01:31:35,180 a system that thinks through a problem for days if necessary, using massive 1254 01:31:35,180 --> 01:31:37,640 clusters of GPUs to reach a breakthrough. 1255 01:31:39,260 --> 01:31:43,320 The competition in 2026 has never been fiercer. 1256 01:31:44,060 --> 01:31:49,200 NVIDIA's biggest customers, Amazon, Google, and Microsoft, have become its 1257 01:31:49,200 --> 01:31:53,360 dangerous rivals, pouring billions into their own custom AI chips. 1258 01:31:53,870 --> 01:31:55,370 to escape the NVIDIA tax. 1259 01:31:56,210 --> 01:31:59,370 Yet, the software moat remains unbreached. 1260 01:31:59,670 --> 01:32:04,730 While others build chips, Jensen is building the entire ecosystem, the 1261 01:32:04,730 --> 01:32:09,330 networking, the libraries, and the pre -trained models that make a competitor's 1262 01:32:09,330 --> 01:32:13,530 hardware feel like a relic before it even leaves the factory. 1263 01:32:14,550 --> 01:32:19,050 In this era, Jensen Huang has become one of the world's most influential 1264 01:32:19,050 --> 01:32:24,280 diplomats. He navigates a world where the power grid is the new bottleneck and 1265 01:32:24,280 --> 01:32:28,460 where a single shipment of chips can determine the economic future of a 1266 01:32:29,620 --> 01:32:35,380 The trillion -dollar question of 2026 is no longer if AI will change the world, 1267 01:32:35,580 --> 01:32:38,580 but who will own the infrastructure of that change. 1268 01:32:44,260 --> 01:32:48,800 The story of NVIDIA is often told as a series of lucky breaks or inevitable 1269 01:32:48,800 --> 01:32:55,010 triumphs. But as we look at the empire Jensen Huang has built, the reality is 1270 01:32:55,010 --> 01:32:58,090 far more deliberate and far more precarious. 1271 01:32:58,930 --> 01:33:04,390 In 2026, the company stands at the center of the greatest industrial shift 1272 01:33:04,390 --> 01:33:05,390 human history. 1273 01:33:05,950 --> 01:33:12,150 Yet for Jensen, the valuation of $3, $4 or $5 trillion is a lagging indicator. 1274 01:33:12,650 --> 01:33:15,110 The true metric is the oxygen. 1275 01:33:16,070 --> 01:33:20,470 Throughout his journey, From the dishpits of Denny's to the halls of the 1276 01:33:20,470 --> 01:33:24,910 Court, Jensen has maintained a philosophy of intellectual honesty. 1277 01:33:25,930 --> 01:33:31,670 He admits when the technology is wrong, he pivots when the market shifts, and he 1278 01:33:31,670 --> 01:33:34,110 invests billions when the world calls him a fool. 1279 01:33:34,970 --> 01:33:40,410 He has turned a semiconductor company into a geopolitical superpower, a 1280 01:33:40,410 --> 01:33:44,710 fortress, and the primary architect of a new form of life. 1281 01:33:45,820 --> 01:33:50,940 Critics ask if NVIDIA is a bubble waiting to burst, or if the scaling laws 1282 01:33:50,940 --> 01:33:52,520 will eventually hit a dead end. 1283 01:33:53,180 --> 01:33:56,800 But Jensen doesn't operate on the timeline of a stock market cycle. 1284 01:33:57,180 --> 01:34:00,540 He operates on the timeline of human evolution. 1285 01:34:01,380 --> 01:34:03,460 He isn't just selling chips. 1286 01:34:03,740 --> 01:34:08,520 He is selling the marginal cost of intelligence, making the most valuable 1287 01:34:08,520 --> 01:34:14,580 resource in the universe so abundant that it changes the very definition of 1288 01:34:14,580 --> 01:34:15,580 is possible. 1289 01:34:16,720 --> 01:34:20,880 Jensen often says that he wakes up every morning with the same feeling he had in 1290 01:34:20,880 --> 01:34:25,000 1993, the feeling that the company is going out of business. 1291 01:34:25,840 --> 01:34:30,980 It is this productive paranoia that prevents the cyclical trap that claimed 1292 01:34:30,980 --> 01:34:31,980 giants of the past. 1293 01:34:32,880 --> 01:34:35,140 He doesn't want to be the king of a legacy. 1294 01:34:35,680 --> 01:34:40,980 He wants to be the architect of a future that hasn't even been imagined yet. 1295 01:34:43,500 --> 01:34:45,300 Run, don't walk. 1296 01:34:45,980 --> 01:34:49,820 Either you are running for food, or you are running from being food. 1297 01:34:50,400 --> 01:34:55,740 In the era of the digital brain, the race has only just begun. 1298 01:36:20,840 --> 01:36:24,500 The financial world is in constant transformation. But in this decade, 1299 01:36:24,680 --> 01:36:28,040 digitalization has accelerated that change faster than anyone imagined. 1300 01:36:29,840 --> 01:36:33,300 Today, money, investments, and assets flow through code. 1301 01:36:34,240 --> 01:36:36,660 Silent, transparent, and borderless. 1302 01:36:37,620 --> 01:36:42,300 Cryptocurrencies, led by Bitcoin, mark the beginning of a new era. They shook 1303 01:36:42,300 --> 01:36:46,100 the foundations of the global financial system, sparking both excitement and 1304 01:36:46,100 --> 01:36:50,100 skepticism. Yet behind that phenomenon emerged something even deeper. 1305 01:36:51,389 --> 01:36:55,110 Tokenization. A technology redefining ownership, exchange, and value. 1306 01:36:55,710 --> 01:36:59,350 Decentralized, programmable, and capable of operating 24 hours a day without 1307 01:36:59,350 --> 01:37:02,430 intermediaries. What once seemed like a promise has become a reality. 1308 01:37:02,810 --> 01:37:07,350 A token is basically a database entry, and it says which address, which is 1309 01:37:07,350 --> 01:37:11,690 basically the digital place where a token is stored, how many pieces, how 1310 01:37:11,690 --> 01:37:15,250 tokens it has, and is implemented by its local program code. 1311 01:37:15,590 --> 01:37:18,370 The idea is simple. The impact, enormous. 1312 01:37:18,910 --> 01:37:23,350 Each token represents a fraction of an asset, a share, a bond, a property, or 1313 01:37:23,350 --> 01:37:27,590 even a work of art, all recorded on a blockchain, a global tamper -proof 1314 01:37:27,790 --> 01:37:30,150 You know, you can look at the Genesis block as a picket sign. 1315 01:37:30,630 --> 01:37:36,590 It was a protest, really, against what many people viewed as financial 1316 01:37:36,590 --> 01:37:40,650 injustices. What began as an alternative to financial power has become the 1317 01:37:40,650 --> 01:37:42,710 infrastructure of a new economic system. 1318 01:37:43,030 --> 01:37:46,870 We believe the next step going forward will be the tokenization of financial 1319 01:37:46,870 --> 01:37:47,870 assets. 1320 01:37:48,060 --> 01:37:54,220 And that means every stock, every bond will have its own basically USIF. It'll 1321 01:37:54,220 --> 01:37:58,820 be on one general ledger. By 2025, that step is already underway. 1322 01:37:59,120 --> 01:38:04,420 The tokenized assets market has surpassed $1 trillion in regulation. 1323 01:38:04,420 --> 01:38:08,540 Europe's MISI framework to the ESSI's latest guidelines, it's shaping a global 1324 01:38:08,540 --> 01:38:14,460 ecosystem. Basically aim to target some specific assets in the crypto industry 1325 01:38:14,460 --> 01:38:17,860 and certain services linked to those crypto assets. 1326 01:38:18,160 --> 01:38:21,800 Meanwhile, in the United States, companies like Securitize are bridging 1327 01:38:21,800 --> 01:38:23,980 traditional finance with the digital world. 1328 01:38:24,560 --> 01:38:28,020 Blockchain technology and tokenization brings the most suitable, most modern 1329 01:38:28,020 --> 01:38:31,120 ledger technology, ideal for modernizing the market. 1330 01:38:31,820 --> 01:38:36,000 Tokenization promises more than efficiency. It points toward a financial 1331 01:38:36,000 --> 01:38:38,840 that is faster, more transparent, and more inclusive. 1332 01:38:39,290 --> 01:38:41,070 where value moves at the speed of information. 1333 01:38:42,370 --> 01:38:44,490 The future of money has already begun. 1334 01:38:46,570 --> 01:38:49,690 This is the journey toward the economic system of the future. 1335 01:38:52,610 --> 01:38:57,110 As early as about 5 ,000 years ago, people traded by exchanging goods or 1336 01:38:57,110 --> 01:38:58,110 services. 1337 01:39:00,170 --> 01:39:05,170 Over time, opportunities developed to also trade shares in goods or services 1338 01:39:05,170 --> 01:39:07,830 even sell them to the public in order to raise capital. 1339 01:39:10,920 --> 01:39:15,040 This is how the stock markets came into being, where companies offer individual 1340 01:39:15,040 --> 01:39:19,380 small company shares to a variety of investors to invest in the future of the 1341 01:39:19,380 --> 01:39:20,380 company. 1342 01:39:22,840 --> 01:39:26,980 This need for shareholding has increased more and more and ultimately developed 1343 01:39:26,980 --> 01:39:28,640 into the global financial market. 1344 01:39:32,460 --> 01:39:35,840 Tokenization meets this need in an even more extreme way. 1345 01:39:36,300 --> 01:39:40,920 This is because tokenization is a further segmentation of a unit or 1346 01:39:40,920 --> 01:39:42,940 into other individual components. 1347 01:39:44,560 --> 01:39:46,440 A kind of fractionalization. 1348 01:39:46,800 --> 01:39:51,680 For example, pairs can also be further fractioned and the resulting units can 1349 01:39:51,680 --> 01:39:52,680 turn be traded. 1350 01:39:53,900 --> 01:39:59,340 However, the special and new thing about tokenization is not the segmentation, 1351 01:39:59,420 --> 01:40:04,080 but it's linking with another process that makes tokenization interesting in 1352 01:40:04,080 --> 01:40:05,080 first place. 1353 01:40:05,550 --> 01:40:09,450 the digital and decentralized storage of the fractions in the blockchain. 1354 01:40:11,770 --> 01:40:16,070 Individual sectors of the market for tokenized assets are currently still in 1355 01:40:16,070 --> 01:40:18,410 kind of discovery or experimentation phase. 1356 01:40:20,310 --> 01:40:23,850 Its value is estimated at less than $20 billion. 1357 01:40:24,570 --> 01:40:29,450 The value of the total market for digital assets is about $350 billion. 1358 01:40:32,140 --> 01:40:35,260 This is where the enormous growth potential becomes clear. 1359 01:40:36,320 --> 01:40:41,320 Tokenization and blockchain technology could fundamentally change the financial 1360 01:40:41,320 --> 01:40:42,320 and banking sector. 1361 01:40:42,840 --> 01:40:49,700 By 2027, this growth will increase dramatically to an estimated $6 .89 1362 01:40:52,010 --> 01:40:57,270 Major institutions such as BlackRock, JP Morgan, and HSBC are already using 1363 01:40:57,270 --> 01:41:01,490 tokenized platforms to issue real -world assets on networks like Ethereum and 1364 01:41:01,490 --> 01:41:06,110 Polygon. Digital funds and tokenized bonds are no longer a promise. They are 1365 01:41:06,110 --> 01:41:07,850 part of the global financial system. 1366 01:41:08,090 --> 01:41:12,030 We believe the next step going forward will be the tokenization of financial 1367 01:41:12,030 --> 01:41:13,030 assets. 1368 01:41:13,440 --> 01:41:19,380 And that means every stock, every bond will have its own basically QSIP. It'll 1369 01:41:19,380 --> 01:41:24,320 be on one general ledger. Every investor, you and I, will have our own 1370 01:41:24,460 --> 01:41:25,580 our own identification. 1371 01:41:26,380 --> 01:41:30,980 We could rid ourselves of all issues around illicit activities about bonds 1372 01:41:30,980 --> 01:41:35,840 stocks and digital by having a tokenization. 1373 01:41:36,140 --> 01:41:40,660 But the most important thing, we can customize strategies through 1374 01:41:40,660 --> 01:41:42,460 that fits every individual. 1375 01:41:43,230 --> 01:41:47,110 We would have instantaneous settlement. Think about all the costs of settling 1376 01:41:47,110 --> 01:41:48,110 bonds and stocks. 1377 01:41:48,290 --> 01:41:52,790 But if you had a tokenization, everything would be immediate because 1378 01:41:52,790 --> 01:41:53,790 line item. 1379 01:41:53,930 --> 01:41:58,350 And so we believe this is a technological transformation for 1380 01:41:58,730 --> 01:42:03,470 Think's words capture a turning point. The very institutions that define 20th 1381 01:42:03,470 --> 01:42:08,770 century finance are now building the digital infrastructure of the 21st. 1382 01:42:08,770 --> 01:42:12,050 is one of the biggest players that will shake up the digital token game. 1383 01:42:13,200 --> 01:42:16,960 In 2022, the United States held the largest market share. 1384 01:42:18,120 --> 01:42:19,620 But what is tokenization? 1385 01:42:20,020 --> 01:42:24,040 How do all these new token -based players operate in the fintech market? 1386 01:42:24,300 --> 01:42:27,100 What is their agenda and what are their products? 1387 01:42:30,420 --> 01:42:35,300 In Europe, Luxembourg -based Tokeny Solutions is one of the market leaders 1388 01:42:35,300 --> 01:42:38,640 providing an institutional and modular end -to -end platform. 1389 01:42:39,340 --> 01:42:43,760 That enables the issuance, transfer, and management of tradable digital assets 1390 01:42:43,760 --> 01:42:44,860 and security tokens. 1391 01:42:46,780 --> 01:42:51,080 Such as tokenized loans, structured debt securities, stock and funds. 1392 01:42:53,720 --> 01:42:58,140 This private B2B company provides an end -to -end platform for the unified 1393 01:42:58,140 --> 01:43:01,760 issuance, management, and trading of service and security tokens. 1394 01:43:05,560 --> 01:43:07,820 The company valuation for token solutions. 1395 01:43:08,590 --> 01:43:14,330 range from $22 million to $33 million, with a revenue estimate of $6 .5 million 1396 01:43:14,330 --> 01:43:17,110 for the year and a fund of $11 million. 1397 01:43:20,650 --> 01:43:25,730 The company uses Ethereum and Polygon's blockchain technology and works with the 1398 01:43:25,730 --> 01:43:28,230 ERC3643 token standard. 1399 01:43:32,470 --> 01:43:36,770 Another interesting player in the European market is the Berlin -based 1400 01:43:36,770 --> 01:43:41,200 Bitbon. They have launched the first security token offering in Europe. 1401 01:43:42,200 --> 01:43:46,840 This was approved by the German financial regular BaFin in 2019. 1402 01:43:48,620 --> 01:43:52,940 Bitbon is a technology provider for the tokenization infrastructure of digital 1403 01:43:52,940 --> 01:43:53,940 assets. 1404 01:43:54,180 --> 01:43:59,320 Their Web3 product, TokenTool, allows their customers to create, manage, and 1405 01:43:59,320 --> 01:44:02,180 distribute tokens and NFTs through EVM chains. 1406 01:44:03,980 --> 01:44:09,560 The Bitbon token, or BB1, is a security bond token that can be purchased with 1407 01:44:09,560 --> 01:44:12,980 BTC, ETH, XLM, or Euros. 1408 01:44:13,460 --> 01:44:16,160 The value per token is equal to 1 Euro. 1409 01:44:18,560 --> 01:44:23,820 Their global market share is currently less than 0 .1%, but with a team size of 1410 01:44:23,820 --> 01:44:29,220 less than 50 people, it is valued at around 7 to 11 million US dollars as a 1411 01:44:29,220 --> 01:44:30,220 company. 1412 01:44:31,980 --> 01:44:35,980 Fitbon is a private company with a capital of $13 .2 million. 1413 01:44:36,780 --> 01:44:40,540 Its turnover will be around $1 million in 2023. 1414 01:44:42,560 --> 01:44:44,240 But how does it work exactly? 1415 01:44:45,340 --> 01:44:48,100 Fitbon uses the ERC -20 token standard. 1416 01:44:48,620 --> 01:44:52,400 This is the most commonly used security token in the fintech industry. 1417 01:44:53,980 --> 01:44:58,800 The token stands for tokenized assets that company with current regulations 1418 01:44:58,800 --> 01:44:59,800 securities. 1419 01:44:59,850 --> 01:45:04,030 There are securities in the form of a token, and through a company such as 1420 01:45:04,030 --> 01:45:09,030 Bitbon or Tokeny Solutions, the buyer can buy and trade such a security as a 1421 01:45:09,030 --> 01:45:10,030 token. 1422 01:45:11,010 --> 01:45:13,790 The acquired token is implemented on a blockchain. 1423 01:45:14,050 --> 01:45:16,770 The blockchains are called Ethereum or Polygon. 1424 01:45:19,560 --> 01:45:24,920 I'm Radoslav Albrecht, a founder and CEO of Bitbon. A token is a term that has 1425 01:45:24,920 --> 01:45:28,840 been around for a long time, and it basically stands for the fact that an 1426 01:45:28,840 --> 01:45:30,960 or digital good stands for something else. 1427 01:45:31,280 --> 01:45:36,020 For example, if you go to a fun fair and pay admission, you often get a token, a 1428 01:45:36,020 --> 01:45:39,200 plastic chip, which you then hand in in a carousel, for example. 1429 01:45:39,560 --> 01:45:43,260 And that's where the term originally comes from. My name is Markus Kluge. 1430 01:45:46,240 --> 01:45:48,440 I'm one of the co -founders of Tokenforge. 1431 01:45:48,800 --> 01:45:53,480 The best known is the standard, is this ERC -20 standard, which is basically 1432 01:45:53,480 --> 01:45:58,040 just a small register in which anyone who has received a token there is 1433 01:45:58,040 --> 01:46:01,420 access as the only one who can move it into a private key. 1434 01:46:01,660 --> 01:46:04,540 This is what is meant by tokenization in blockchain. 1435 01:46:04,920 --> 01:46:09,240 And that's what happens without regulations and without access from any 1436 01:46:09,240 --> 01:46:11,640 administrator or from any regulated party. 1437 01:46:12,000 --> 01:46:16,040 with a high risk that if you lose your private key, you won't be able to access 1438 01:46:16,040 --> 01:46:20,020 that token, and you won't be able to move it, you won't be able to sell it. 1439 01:46:22,760 --> 01:46:28,760 From a technical point of view, a token is basically a database entry, and it 1440 01:46:28,760 --> 01:46:32,580 says which address, which is basically the digital place where a token is 1441 01:46:32,580 --> 01:46:37,240 stored, how many pieces, how many tokens it has, and is implemented by so 1442 01:46:37,240 --> 01:46:38,240 -called program code. 1443 01:46:40,250 --> 01:46:44,050 which in a context of blockchains is also called smart contracts. 1444 01:46:46,510 --> 01:46:50,510 But basically, this is a program code that describes what are the technical 1445 01:46:50,510 --> 01:46:54,550 properties of the token and who owns the token and who holds these tokens. 1446 01:47:00,070 --> 01:47:04,470 It is therefore important in tokenization, i .e. in the creation of 1447 01:47:04,470 --> 01:47:07,690 entries, with which certain rights of the token owners are linked. 1448 01:47:08,120 --> 01:47:12,380 that there is a register, a database where the entries are readable and 1449 01:47:12,380 --> 01:47:17,460 securely. This register is granted by the ERC -20 standard just mentioned. 1450 01:47:17,720 --> 01:47:20,040 It sits on a blockchain, so it's secure. 1451 01:47:20,340 --> 01:47:25,220 In other words, a token isn't just an asset. It's a digital entry in a new 1452 01:47:25,220 --> 01:47:28,100 of ledger that is rewriting how capital markets keep their books. 1453 01:47:28,600 --> 01:47:31,620 Financial services industry, for the most part, a lot of the capital market 1454 01:47:31,620 --> 01:47:36,320 infrastructure and products are still running in technology from the 70s. So I 1455 01:47:36,320 --> 01:47:41,020 don't think anybody questions that you need to modernize that infrastructure to 1456 01:47:41,020 --> 01:47:46,280 be able to move products and settle trades and access investors, et cetera, 1457 01:47:46,280 --> 01:47:47,280 much more efficient way. 1458 01:47:48,090 --> 01:47:51,050 At the end of the day, capital markets boil down to like updating ledgers and 1459 01:47:51,050 --> 01:47:55,090 how people, you know, move the ownership of assets in a ledger. And that's what 1460 01:47:55,090 --> 01:47:58,190 a blockchain technology and tokenization brings. So it's the most suitable, most 1461 01:47:58,190 --> 01:48:01,890 modern ledger technology ideal for modernizing capital markets. 1462 01:48:05,050 --> 01:48:08,390 The token stands for a value, for a service. 1463 01:48:08,920 --> 01:48:12,500 Tokens, as we understand them today in the field, have been around since around 1464 01:48:12,500 --> 01:48:13,740 2014, 2015. 1465 01:48:14,640 --> 01:48:18,340 That's when the so -called Ethereum blockchain came into being, and the 1466 01:48:18,340 --> 01:48:21,900 blockchain was the first blockchain on which tokens, namely digital values, 1467 01:48:22,060 --> 01:48:23,060 could be created. 1468 01:48:23,720 --> 01:48:28,180 And that's how the whole development began, that there were digital tokens, 1469 01:48:28,180 --> 01:48:31,240 since then this term has existed in the context of fintech. 1470 01:48:36,299 --> 01:48:40,280 And now we have the blockchain technology with the one with the 1471 01:48:40,280 --> 01:48:44,360 the signature, which just makes a lot more personal responsibility possible, 1472 01:48:44,720 --> 01:48:49,340 because everyone in the game can just see, hey, that's really the one who owns 1473 01:48:49,340 --> 01:48:54,000 the asset, who transfers it, and that's what this private key takes care of, 1474 01:48:54,040 --> 01:48:55,040 public pair. 1475 01:48:55,060 --> 01:48:57,140 That then just makes this thing safe. 1476 01:48:59,140 --> 01:49:00,740 Cryptocurrencies are also tokens. 1477 01:49:00,980 --> 01:49:04,100 They are produced and managed by companies instead of institutions. 1478 01:49:05,100 --> 01:49:08,060 Strictly speaking, cryptocurrencies are not currencies. 1479 01:49:08,380 --> 01:49:11,880 They are digital assets that can be exchanged and traded. 1480 01:49:12,240 --> 01:49:17,600 Their creation is carried out by so -called ICOs, the abbreviation for 1481 01:49:17,600 --> 01:49:18,600 Coin Offering. 1482 01:49:22,640 --> 01:49:27,860 So the first so -called initial coin offering was that of Ethereum itself. 1483 01:49:28,430 --> 01:49:32,190 And they basically invented the technical concept of the token and 1484 01:49:32,190 --> 01:49:33,270 commercializing it. 1485 01:49:33,630 --> 01:49:37,230 And then many, many more companies came along that took advantage of these 1486 01:49:37,230 --> 01:49:39,710 technical possibilities and issued more tokens. 1487 01:49:41,510 --> 01:49:45,530 My name is Erwin Vollader. I am the head of policy for the European Blockchain 1488 01:49:45,530 --> 01:49:46,530 Association. 1489 01:49:47,720 --> 01:49:50,840 If you want to buy the argument that crypto is political, I think it is. 1490 01:49:51,340 --> 01:49:53,640 And I think it's been political since the Genesis block. 1491 01:49:53,980 --> 01:49:57,580 So if you look at actually what's inscribed in the Genesis block, the 1492 01:49:57,580 --> 01:49:58,580 block is the Bitcoin blockchain. 1493 01:49:58,680 --> 01:50:02,040 It's Chancellor on the brink, second bailout to banks, right? And this is 1494 01:50:02,040 --> 01:50:04,060 the height of the 2008 financial crisis. 1495 01:50:04,700 --> 01:50:09,140 And specifically, you know, you can look at the Genesis block as a picket sign. 1496 01:50:09,700 --> 01:50:12,440 It was a protest, really, against. 1497 01:50:13,269 --> 01:50:19,010 what many people viewed as financial injustices that were incurred at the 1498 01:50:19,010 --> 01:50:22,450 of the people for the benefit, at the cost of the majority for the benefit of 1499 01:50:22,450 --> 01:50:23,450 minority. 1500 01:50:24,330 --> 01:50:28,690 With tokenization and cryptocurrencies, a new chapter in the history of capital 1501 01:50:28,690 --> 01:50:30,010 investment is being written. 1502 01:50:30,590 --> 01:50:35,110 The new way of investing is influencing society, politics, and markets. 1503 01:50:35,370 --> 01:50:40,030 The revolutionary concept makes it possible to divide assets into 1504 01:50:40,030 --> 01:50:41,030 small parts. 1505 01:50:43,120 --> 01:50:44,340 The idea is not new. 1506 01:50:44,720 --> 01:50:48,960 Fractional ownership is a consistent trend among financial instruments. 1507 01:50:49,340 --> 01:50:53,980 For centuries, companies have been broken down into small parties by shares 1508 01:50:53,980 --> 01:50:58,660 funds. What is completely new, however, is to register these fractions as 1509 01:50:58,660 --> 01:51:00,240 digital tokens on a blockchain. 1510 01:51:03,280 --> 01:51:07,540 From a technical point of view, there are about three dominant technological 1511 01:51:07,540 --> 01:51:08,540 standards. 1512 01:51:09,120 --> 01:51:13,540 There are many more, but these three technical standards that can be used to 1513 01:51:13,540 --> 01:51:14,540 all use cases. 1514 01:51:14,940 --> 01:51:18,820 The tokens that are then issued by companies that take advantage of the 1515 01:51:18,820 --> 01:51:20,560 technology, there are thousands. 1516 01:51:20,820 --> 01:51:24,680 There are probably around 5 million different tokens at the moment, but they 1517 01:51:24,680 --> 01:51:26,800 all based on the same technical standards. 1518 01:51:27,790 --> 01:51:30,490 but where other values are represented with it. 1519 01:51:30,970 --> 01:51:35,650 For example, there are so -called stablecoins, which represent fiat 1520 01:51:35,670 --> 01:51:37,350 such as the euro, the dollar. 1521 01:51:37,670 --> 01:51:41,910 Then there are tokens that represent, for example, securities, such as bonds 1522 01:51:41,910 --> 01:51:42,910 stocks. 1523 01:51:44,230 --> 01:51:50,790 Tokenization allows you to transfer value with a technical substrate 1524 01:51:50,790 --> 01:51:55,290 that enables the removal of a lot of different frictions. 1525 01:51:56,240 --> 01:51:58,720 And these frictions also lead to cost reductions. 1526 01:51:58,980 --> 01:52:03,660 So instantaneous settlement, fractionalization, it opens up the door 1527 01:52:03,660 --> 01:52:09,800 cases like paper use models, streaming money, and generally the ability to take 1528 01:52:09,800 --> 01:52:15,480 real world assets and represent them in a digitalized form and then offer them 1529 01:52:15,480 --> 01:52:16,480 to investors. 1530 01:52:16,990 --> 01:52:22,130 new ways to package financial products, the ability to ease frictions and cross 1531 01:52:22,130 --> 01:52:24,910 -border payments as well from an institutional perspective. 1532 01:52:25,310 --> 01:52:31,310 And I think also what's very important is tokenization, and tokenization within 1533 01:52:31,310 --> 01:52:38,250 blockchain has the ability to produce a higher level of financial agency and 1534 01:52:38,250 --> 01:52:42,390 financial inclusion, which I think is ultimately really important. Otherwise, 1535 01:52:42,510 --> 01:52:44,210 why are we doing all of this? 1536 01:52:46,090 --> 01:52:48,970 All assets can thus be digitalized and standardized. 1537 01:52:49,290 --> 01:52:51,810 This increases liquidity and transparency. 1538 01:52:52,450 --> 01:52:54,710 Process can be automated like never before. 1539 01:52:57,370 --> 01:53:00,970 Software developers have been thinking about how to standardize tokens. 1540 01:53:01,670 --> 01:53:03,830 This has a very, very important background. 1541 01:53:04,070 --> 01:53:08,430 Namely, the tokens are held in so -called wallets. These are basically 1542 01:53:08,430 --> 01:53:11,730 wallets, and not every wallet can hold every type of token. 1543 01:53:13,259 --> 01:53:17,300 Software developers have been considering ways to standardize tokens, 1544 01:53:17,300 --> 01:53:21,340 importance of doing so lies in the fact that tokens are held in digital wallets, 1545 01:53:21,340 --> 01:53:23,860 and not every wallet can store every type of token. 1546 01:53:24,490 --> 01:53:28,650 Therefore, it has been suggested that a standard should be established to enable 1547 01:53:28,650 --> 01:53:31,630 wallets to support as many types of tokens as possible. 1548 01:53:32,410 --> 01:53:36,190 Developers propose open -source software, and the market adapted 1549 01:53:36,190 --> 01:53:38,610 technical standards based on their effectiveness. 1550 01:53:39,370 --> 01:53:43,790 These standards have become prevalent with two dominant token variations, ERC 1551 01:53:43,790 --> 01:53:49,190 -20 standard for the fungible tokens and the ERC -721 standard for non -fungible 1552 01:53:49,190 --> 01:53:53,620 tokens. These ideas, initially suggested by developers, have since become 1553 01:53:53,620 --> 01:53:56,540 indispensable and are widely used throughout the world. 1554 01:53:58,080 --> 01:54:02,220 But the true highlight of tokenization lies in affordable entry prices for 1555 01:54:02,220 --> 01:54:04,840 investors that are associated with smaller stakes. 1556 01:54:05,620 --> 01:54:12,460 The one challenge that blockchain, crypto, or I should say that crypto 1557 01:54:12,740 --> 01:54:17,520 and you see this in decentralized finance, is the end user or the user 1558 01:54:17,520 --> 01:54:18,520 experience, right? 1559 01:54:18,990 --> 01:54:22,610 Using these financial products and services is oftentimes tricky and 1560 01:54:22,610 --> 01:54:26,150 or requires a certain level of technical literacy that not everyone has. 1561 01:54:26,430 --> 01:54:29,530 And also at the end of the day, it's generally driven by interest. 1562 01:54:29,810 --> 01:54:33,790 I don't think, you know, you can make the argument and say that everyone will 1563 01:54:33,790 --> 01:54:37,550 use this all the time, everywhere, because that isn't the case with 1564 01:54:37,550 --> 01:54:41,150 now. So why would it be any different? You know, human nature is a fickle 1565 01:54:41,250 --> 01:54:46,150 So I think that the point should be to make it as easy to use as possible, as 1566 01:54:46,150 --> 01:54:47,150 frictionless, as seamless. 1567 01:54:47,630 --> 01:54:51,150 The real challenge today isn't the idea of tokenization itself, but the 1568 01:54:51,150 --> 01:54:54,530 integration between new blockchain networks and decades -old finance. 1569 01:54:55,250 --> 01:54:58,850 Most of the adoption for tokenization today is still within the crypto 1570 01:54:58,850 --> 01:55:00,330 ecosystem. 1571 01:55:01,190 --> 01:55:04,150 That's where the majority of the people that are kind of using the technology 1572 01:55:04,150 --> 01:55:07,730 and adopting tokenized assets are. It is to some extent true that it hasn't 1573 01:55:07,730 --> 01:55:09,990 trickled down into like mainstream Wall Street. 1574 01:55:10,710 --> 01:55:14,470 That doesn't necessarily mean it's not going to happen. I think it's a much 1575 01:55:14,470 --> 01:55:16,570 complicated problem because you need to get... 1576 01:55:17,389 --> 01:55:21,750 wallet infrastructure and blockchains, etc., integrated with existing legacy 1577 01:55:21,750 --> 01:55:25,090 infrastructure, and that usually takes longer than creating new markets, which 1578 01:55:25,090 --> 01:55:26,090 is what's happening today. 1579 01:55:26,170 --> 01:55:27,330 But it will definitely happen. 1580 01:55:27,690 --> 01:55:32,330 As I mentioned at the beginning, digitization is an unavoidable fact for 1581 01:55:32,330 --> 01:55:33,330 industries. 1582 01:55:34,690 --> 01:55:38,610 Issuers can save money through tokenization, which enables them to 1583 01:55:38,610 --> 01:55:41,450 directly without the need for an intermediary. 1584 01:55:41,840 --> 01:55:45,800 thus eliminating the high fees associated with working with investment 1585 01:55:45,800 --> 01:55:46,800 other institutions. 1586 01:55:50,840 --> 01:55:51,560 The 1587 01:55:51,560 --> 01:56:02,420 MICA 1588 01:56:02,420 --> 01:56:09,420 is an EU legal framework for cryptocurrencies and tokens that 1589 01:56:09,420 --> 01:56:10,780 are traded on digital platforms. 1590 01:56:11,260 --> 01:56:14,460 It replaces the individual regulations on the individual countries. 1591 01:56:15,920 --> 01:56:22,100 Mika basically aims to target some specific assets in the crypto industry 1592 01:56:22,100 --> 01:56:24,800 certain services linked to those crypto assets. 1593 01:56:25,100 --> 01:56:30,040 So if we take the parallelism to the traditional financial sector, we have 1594 01:56:30,040 --> 01:56:35,000 Mifid, which covers financial instruments. Now we have Mika that 1595 01:56:35,000 --> 01:56:39,960 type of crypto assets, which are in three big categories, which are the 1596 01:56:39,960 --> 01:56:44,620 coins and the other crypto assets, including... 1597 01:56:47,039 --> 01:56:51,960 With the implementation of the markets and crypto assets regulation called 1598 01:56:52,080 --> 01:56:55,320 a consistent EU -wide framework has been established. 1599 01:56:55,900 --> 01:57:00,620 So it will change a lot of things in the regulatory landscape and also in the 1600 01:57:00,620 --> 01:57:03,020 crypto industry itself because as we know... 1601 01:57:03,260 --> 01:57:06,680 All the continents have their own approach, but sometimes they don't have 1602 01:57:06,680 --> 01:57:10,860 approach at all. So I think it will change a lot of things, and also within 1603 01:57:10,860 --> 01:57:12,020 financial sector as well. 1604 01:57:12,320 --> 01:57:16,620 Why? Because the traditional financial sector so far, if you go to a bank and 1605 01:57:16,620 --> 01:57:21,400 you want to buy some Bitcoin, your banker will most likely refuse this 1606 01:57:21,640 --> 01:57:26,700 Some of them, they jump on board with it, but 99 % will say, no, we don't do 1607 01:57:27,000 --> 01:57:31,100 While Europe advances under the MyCA framework, the United States is also 1608 01:57:31,100 --> 01:57:35,290 forward. providing new clarity for issuers, custodians, and stablecoins. 1609 01:57:35,570 --> 01:57:39,030 I think it's going to get accelerated because now we have stablecoins that 1610 01:57:39,030 --> 01:57:44,850 become legal with the Genius Act. We've had the recent administration and the 1611 01:57:44,850 --> 01:57:45,850 recent SEC. 1612 01:57:47,180 --> 01:57:50,940 basically clarifying a lot of the perhaps more gray areas with respect to 1613 01:57:50,940 --> 01:57:55,160 tokenization about how transfer agents use a blockchain technology for their 1614 01:57:55,160 --> 01:57:59,080 ledger or how the broker dealers can do custody of tokenized assets. 1615 01:57:59,320 --> 01:58:02,340 And I think this is going to significantly accelerate. So I see that 1616 01:58:02,340 --> 01:58:04,660 within the next three to five years for sure. 1617 01:58:05,100 --> 01:58:09,540 After Mika comes into force right now, what they can do is actually they can 1618 01:58:09,540 --> 01:58:13,980 offer those services without even having the Mika license, which can be quite a 1619 01:58:13,980 --> 01:58:17,460 bit of polemic because it's not because you're a bank or financial institution 1620 01:58:17,460 --> 01:58:21,100 that you can actually understand and you have the experience and the knowledge 1621 01:58:21,100 --> 01:58:22,100 to provide those services. 1622 01:58:24,800 --> 01:58:26,800 Cryptocurrencies are traded through crypto exchanges. 1623 01:58:27,440 --> 01:58:32,060 Utility tokens represent a specific utility or functionality on a platform. 1624 01:58:32,680 --> 01:58:36,040 There are different types of tokens that can serve as financial instruments. 1625 01:58:36,660 --> 01:58:39,220 Security tokens act as digital securities. 1626 01:58:39,740 --> 01:58:42,620 They can have the characteristics of stocks or bonds. 1627 01:58:45,300 --> 01:58:52,180 A security token usually certifies as a security. 1628 01:58:52,860 --> 01:58:57,700 It is technically referred to as the ERC -20 token and is similar to a fungible 1629 01:58:57,700 --> 01:58:59,700 token with some additional features. 1630 01:59:00,040 --> 01:59:03,900 It is crucial to identify the token holders for securities and specific 1631 01:59:03,900 --> 01:59:07,720 technical settings can be implemented to restrict the transaction of these 1632 01:59:07,720 --> 01:59:09,900 tokens to a particular whitelist of recipients. 1633 01:59:11,320 --> 01:59:15,160 By approving which recipients can hold the token, you're indicating their 1634 01:59:15,160 --> 01:59:16,160 authorization. 1635 01:59:16,360 --> 01:59:20,920 Security tokens are commonly designed this way as issuers usually need to know 1636 01:59:20,920 --> 01:59:23,880 and sometimes may be legally mandated to know. 145833

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