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These are the user uploaded subtitles that are being translated: 1 00:00:00,000 --> 00:00:04,960 delivers billions of bricks that must all fit together flawlessly across 2 00:00:04,960 --> 00:00:05,960 decades. 3 00:00:06,540 --> 00:00:13,100 In a global toy market worth roughly $120 billion a year, LEGO 4 00:00:13,100 --> 00:00:16,760 commands nearly 9 % of all worldwide toy chaos. 5 00:00:17,220 --> 00:00:23,020 No other toy brand, not Barbie, not Marvel figures, not Nintendo 6 00:00:23,500 --> 00:00:28,320 maintains such consistency across continents, genders, and generations. 7 00:00:29,610 --> 00:00:34,750 And unlike most toy companies with outsourced manufacturing, LEGO controls 8 00:00:34,750 --> 00:00:39,710 significant portion of its own production, with major hubs in Denmark, 9 00:00:39,950 --> 00:00:42,210 Mexico, China and the Czech Republic. 10 00:00:43,510 --> 00:00:49,350 This vertical integration reduces risk, stabilizes quality and protects one of 11 00:00:49,350 --> 00:00:53,070 the most important values in the company's DNA, precision. 12 00:00:54,190 --> 00:00:59,110 Every Lego brick must be manufactured with tolerances thinner than a strand of 13 00:00:59,110 --> 00:01:02,710 hair. If the clutch is too tight, the model breaks. 14 00:01:03,190 --> 00:01:05,930 If it's too loose, towers collapse. 15 00:01:06,750 --> 00:01:10,710 Across billions of pieces, perfection is not an ambition. 16 00:01:11,110 --> 00:01:13,970 It is an engineering reality for Lego. 17 00:01:15,270 --> 00:01:20,150 This level of detail gives the company one of the highest brand trust ratings 18 00:01:20,150 --> 00:01:21,150 the world. 19 00:01:21,190 --> 00:01:23,110 Parents know the bricks will last. 20 00:01:23,770 --> 00:01:25,430 Adults know the sets will impress. 21 00:01:26,210 --> 00:01:28,890 Collectors know the investment will hold value. 22 00:01:29,830 --> 00:01:35,310 The modern toy market is a machine of impulse, tradition, celebration, and 23 00:01:35,310 --> 00:01:36,310 nostalgia. 24 00:01:36,530 --> 00:01:42,750 In 2025, global spending on toys approaches $120 billion, 25 00:01:43,130 --> 00:01:46,190 nearly double what it was two decades earlier. 26 00:01:46,750 --> 00:01:50,010 The United States remains the world's largest consumer. 27 00:01:50,650 --> 00:01:53,190 accounting for roughly one -third of global sales. 28 00:01:53,990 --> 00:02:00,090 A typical American household with children may spend $300 to $400 per 29 00:02:00,090 --> 00:02:01,090 year on toys. 30 00:02:01,470 --> 00:02:04,350 This is more than five times the global average. 31 00:02:05,650 --> 00:02:10,449 Europe forms the second largest bloc, with strong purchasing power in Germany, 32 00:02:10,590 --> 00:02:12,290 the United Kingdom, and France. 33 00:02:13,250 --> 00:02:18,690 Asia -Pacific is rapidly growing, especially in China, South Korea, and 34 00:02:19,420 --> 00:02:22,700 driven by rising middle classes and urban lifestyles. 35 00:02:23,540 --> 00:02:28,100 But the most important shift of the last decade is not geographic. 36 00:02:28,540 --> 00:02:30,140 It is demographic. 37 00:02:36,520 --> 00:02:42,080 Adults, once considered irrelevant to the toy industry, are now one of the 38 00:02:42,080 --> 00:02:43,100 powerful forces. 39 00:02:43,680 --> 00:02:48,560 This growing segment, commonly called the kid -old market, now represents 40 00:02:48,560 --> 00:02:52,580 between 25 and 30 % of all toy purchases worldwide. 41 00:02:53,960 --> 00:03:00,020 Adults buy toys for nostalgia, for stress relief, for display, for 42 00:03:00,940 --> 00:03:03,860 LEGO is the undisputed champion of this movement. 43 00:03:04,340 --> 00:03:07,680 Unlike other hobbies, LEGO gives me a sense of calm. 44 00:03:11,240 --> 00:03:16,360 It lets me take ideas from my mind, bring them to life, think them through, 45 00:03:16,360 --> 00:03:17,740 simply enjoy the process. 46 00:03:18,520 --> 00:03:24,040 Right now, I'm trying to instill that in my son, to enjoy himself, to learn, to 47 00:03:24,040 --> 00:03:28,180 see colors and shapes, and to understand that with imagination anything is 48 00:03:28,180 --> 00:03:29,180 possible. 49 00:03:37,500 --> 00:03:42,100 Regularly exceed prices of $300, $500, even $800. 50 00:03:42,880 --> 00:03:44,840 They sell within hours. 51 00:03:45,160 --> 00:03:48,560 They hold aftermarket values like fine collectibles. 52 00:03:48,960 --> 00:03:53,720 This adult segment has reshaped the entire financial landscape of the 53 00:03:54,240 --> 00:03:57,680 It provides stability when children's trends shift. 54 00:03:57,960 --> 00:04:01,080 It creates recurring revenue from loyal fans. 55 00:04:01,520 --> 00:04:05,860 And it strengthens LEGO's position as a cross -generational brand. 56 00:04:06,810 --> 00:04:09,250 something few toy companies have ever achieved. 57 00:04:10,470 --> 00:04:13,750 Seasonality still dictates much of the global toy market. 58 00:04:14,090 --> 00:04:19,170 Every year, nearly half of all toy sales occur between October and December. 59 00:04:19,910 --> 00:04:25,650 Companies live or die by holiday forecasting, inventory strategy, and 60 00:04:25,650 --> 00:04:28,830 timing. But Lego has become the exception. 61 00:04:29,550 --> 00:04:31,850 Adult collectors buy year -round. 62 00:04:32,510 --> 00:04:36,210 Digital experiences drive sales outside the holiday season. 63 00:04:36,850 --> 00:04:40,770 Licensed launches create anticipation even in slow quarters. 64 00:04:41,710 --> 00:04:46,570 LEGO has effectively freed itself, or at least partially, from the seasonal 65 00:04:46,570 --> 00:04:50,190 dependency that has defined the toy industry for over a century. 66 00:04:51,070 --> 00:04:54,630 The brick is physical, tangible, mechanical. 67 00:04:55,130 --> 00:05:00,330 But LEGO's success in the 21st century extends into digital worlds. 68 00:05:02,170 --> 00:05:03,530 Batman, Marvel. 69 00:05:03,970 --> 00:05:08,310 These games defined an entire generation of family -friendly titles. 70 00:05:08,710 --> 00:05:11,270 They sold tens of millions of copies. 71 00:05:11,550 --> 00:05:17,450 They introduced humor, storytelling, and simplicity to a medium often dominated 72 00:05:17,450 --> 00:05:18,450 by complexity. 73 00:05:19,190 --> 00:05:24,650 For many children born after the year 2000, Lego was not discovered in a toy 74 00:05:24,650 --> 00:05:26,330 box, but on a screen. 75 00:05:26,890 --> 00:05:29,670 The cinematic leap came in 2014. 76 00:05:30,540 --> 00:05:35,560 When the Lego movie premiered to global acclaim, it earned nearly half a billion 77 00:05:35,560 --> 00:05:41,700 dollars. Most importantly, it reframed Lego as a cultural idea, not a product. 78 00:05:42,120 --> 00:05:47,560 The film taught a global audience that creativity matters, that imperfection is 79 00:05:47,560 --> 00:05:52,840 beautiful, that building and rebuilding are not failures, they are the process 80 00:05:52,840 --> 00:05:53,840 of play. 81 00:05:54,100 --> 00:05:56,460 Lego Batman expanded the concept. 82 00:05:57,070 --> 00:06:02,990 Lego Ninjago created an entirely new generation of fans, and Lego Masters on 83 00:06:02,990 --> 00:06:06,190 television turned building into a competitive art form. 84 00:06:06,830 --> 00:06:11,810 The brand had moved beyond toys, beyond stories, beyond brick. 85 00:06:12,090 --> 00:06:16,430 It had become part of the cultural grammar of the 21st century. 86 00:06:22,110 --> 00:06:27,410 Long before STEM became a global movement, Lego was already teaching 87 00:06:27,410 --> 00:06:28,950 how to think like engineers. 88 00:06:29,530 --> 00:06:35,710 In the 1990s, Lego Mindstorms introduced programmable robotics to students 89 00:06:35,710 --> 00:06:36,730 around the world. 90 00:06:37,390 --> 00:06:43,870 Later sets, WeDo, Fight Prime, Boost, brought coding, sensors, and motors into 91 00:06:43,870 --> 00:06:44,930 classrooms and homes. 92 00:06:45,490 --> 00:06:51,530 Today, Lego Education works with governments, schools, and universities 93 00:06:51,530 --> 00:06:53,590 hands -on learning to millions of students. 94 00:06:54,600 --> 00:06:55,940 The philosophy is simple. 95 00:06:56,300 --> 00:06:58,160 Children learn best through play. 96 00:06:58,600 --> 00:07:03,500 This approach saves future engineers, designers, and problem solvers. 97 00:07:03,960 --> 00:07:07,360 It helps children experiment in ways that textbooks cannot. 98 00:07:08,000 --> 00:07:13,000 And it continues Oleg Kirk's belief that play is not a distraction from 99 00:07:13,000 --> 00:07:15,260 learning, but the foundation of it. 100 00:07:16,970 --> 00:07:21,150 In a world increasingly focused on sustainability... From my experience, 101 00:07:21,150 --> 00:07:25,450 makes LEGO different from other construction toys is its growing 102 00:07:25,450 --> 00:07:30,390 inclusion. In recent years, LEGO has actively embraced people with different 103 00:07:30,390 --> 00:07:34,830 abilities, for example, by including figures in wheelchairs and releasing 104 00:07:34,830 --> 00:07:35,830 in Braille. 105 00:07:35,990 --> 00:07:39,730 These are things most other brands simply don't offer, but LEGO does. 106 00:07:40,950 --> 00:07:44,110 In addition, LEGO is strongly committed to the environment. 107 00:07:45,320 --> 00:07:49,060 They're producing more and more pieces using recycled plastic and replacing 108 00:07:49,060 --> 00:07:51,380 plastic packaging with paper to reduce waste. 109 00:07:51,760 --> 00:07:54,500 Something other brands simply don't do. 110 00:07:56,180 --> 00:07:58,400 LEGO faces a unique challenge. 111 00:07:59,240 --> 00:08:01,140 Its bricks are made to last forever. 112 00:08:01,380 --> 00:08:06,100 A blessing for creativity, but a concern in an era of plastic waste. 113 00:08:06,700 --> 00:08:11,780 In response, LEGO has invested hundreds of millions of dollars into developing 114 00:08:11,780 --> 00:08:13,140 more sustainable materials. 115 00:08:14,480 --> 00:08:18,100 Plant -based polyethylene is already used for leaves and trees. 116 00:08:18,940 --> 00:08:22,160 Recycled PET prototypes continue to advance. 117 00:08:23,160 --> 00:08:26,080 Recycled PET prototypes continue to advance. 118 00:08:26,720 --> 00:08:33,140 New polymer engineering aims to create bricks as durable as ABS, without the 119 00:08:33,140 --> 00:08:34,140 environmental cost. 120 00:08:34,919 --> 00:08:37,440 This transition is not simple. 121 00:08:37,980 --> 00:08:41,240 The Lego brick must interlock with perfect precision. 122 00:08:42,030 --> 00:08:45,870 A fraction of a millimeter can make the difference between wonder and 123 00:08:45,870 --> 00:08:46,870 frustration. 124 00:08:47,190 --> 00:08:48,610 But the mission is clear. 125 00:08:49,070 --> 00:08:53,830 A toy that lasts forever should also protect the world it is played in. 126 00:08:54,470 --> 00:08:56,150 Play is not a luxury. 127 00:08:56,550 --> 00:08:57,750 Play is exploration. 128 00:08:58,530 --> 00:08:59,850 Play is curiosity. 129 00:09:00,670 --> 00:09:03,790 Play is the earliest form of human creativity. 130 00:09:04,850 --> 00:09:10,050 From wooden ducks in a small Danish workshop to interlocking bricks that 131 00:09:10,050 --> 00:09:11,050 generations, 132 00:09:11,850 --> 00:09:16,550 to movies, video games, robotics, and global fan communities. 133 00:09:17,110 --> 00:09:19,810 LEGO has remained loyal to a simple truth. 134 00:09:20,230 --> 00:09:22,270 When we build, we grow. 135 00:09:22,510 --> 00:09:24,910 When we imagine, we expand. 136 00:09:25,330 --> 00:09:28,650 When we play, we become more human. 137 00:09:34,750 --> 00:09:39,950 More than a century ago, a carpenter rebuilt his workshop after a fire. 138 00:09:40,590 --> 00:09:42,570 He rebuilt it again after another. 139 00:09:43,430 --> 00:09:48,310 Not because it was easy, but because he believed in the power of making things. 140 00:09:48,790 --> 00:09:50,290 And in the power of play. 141 00:09:51,270 --> 00:09:55,050 Today, billions of creations have risen from that belief. 142 00:09:55,710 --> 00:09:58,770 Cities, castles, spaceships. 143 00:09:59,810 --> 00:10:03,710 Dreams that exist nowhere else but in the minds of the people who build them. 144 00:10:04,910 --> 00:10:06,750 Lego is not perfect. 145 00:10:07,170 --> 00:10:11,360 It has faced crises, challenges, and impossible decisions. 146 00:10:11,800 --> 00:10:18,080 But it endures. Through war, through technological revolutions, through 147 00:10:18,080 --> 00:10:22,320 storms. Because imagination always endures. 148 00:10:22,800 --> 00:10:27,760 And as long as there are hands reaching the bricks, as long as there are minds 149 00:10:27,760 --> 00:10:32,540 ready to create, the legacy of Oleg Kirk -Christensen will continue. 150 00:10:33,600 --> 00:10:37,020 Every dream starts with a single piece. 151 00:12:05,800 --> 00:12:08,940 Jensen Huang, the software moat. 152 00:12:09,780 --> 00:12:12,100 June 18th, 2024. 153 00:12:13,100 --> 00:12:17,840 For a brief historic moment, the world had a new king. 154 00:12:19,060 --> 00:12:25,860 Jensen Huang, the co -founder and CEO of NVIDIA, stood at the peak of a $3 .4 155 00:12:25,860 --> 00:12:27,160 trillion mountain. 156 00:12:29,220 --> 00:12:32,500 Analysts whispered that he wasn't just leading a company. 157 00:12:33,260 --> 00:12:38,500 He was leading the first entity destined for a $4 trillion valuation. 158 00:12:40,720 --> 00:12:45,780 But to understand the man in the leather jacket, you cannot look at the triumph. 159 00:12:46,040 --> 00:12:48,320 You must look at the fear. 160 00:12:49,260 --> 00:12:55,520 Behind the 250 % revenue jump and the sold -out H100 backlog 161 00:12:55,520 --> 00:12:59,220 lies a leader obsessed with the cyclical trap. 162 00:13:00,560 --> 00:13:06,400 In a 60 -year history of semiconductors, giants like Texas Instruments, Intel, 163 00:13:06,680 --> 00:13:12,000 and Samsung have all held the crown only to see it slip away. 164 00:13:13,680 --> 00:13:15,480 Jensen's mission is simple. 165 00:13:15,980 --> 00:13:19,260 Break the cycle before it breaks him. 166 00:13:21,560 --> 00:13:23,680 Flashback to September 1996. 167 00:13:24,220 --> 00:13:28,920 The golden era of the Internet is dawning for everyone else. 168 00:13:29,290 --> 00:13:31,930 But for NVIDIA, it is a death knell. 169 00:13:33,290 --> 00:13:39,830 Their first chip, the NV1, is a technical ghost, rejected by Microsoft's 170 00:13:39,830 --> 00:13:40,830 DirectX. 171 00:13:41,890 --> 00:13:47,630 Jensen stands before a dwindling team and delivers the most famous mantra in 172 00:13:47,630 --> 00:13:48,790 Silicon Valley history. 173 00:13:49,750 --> 00:13:53,290 We have exactly 30 days of oxygen left. 174 00:13:53,650 --> 00:13:56,210 We are 30 days from bankruptcy. 175 00:13:57,610 --> 00:14:02,530 How does a man go from cleaning toilets in a Kentucky reform school to 176 00:14:02,530 --> 00:14:06,090 controlling the foundational layer of the global AI economy? 177 00:14:07,230 --> 00:14:12,730 From a red leather booth at a Denny's to a legal showdown in the U .S. Supreme 178 00:14:12,730 --> 00:14:16,590 Court over the very intellectual honesty of his empire. 179 00:14:17,390 --> 00:14:20,750 This is not just a story of silicon and software. 180 00:14:21,800 --> 00:14:26,760 This is the chronicle of the man who decided to manufacture intelligence 181 00:14:27,540 --> 00:14:32,540 This is Jensen Huang, the architect of the digital brain. 182 00:14:40,100 --> 00:14:42,680 Invidia was not born from abundance. 183 00:14:43,160 --> 00:14:46,760 Its DNA was forged in the raw fires of survival. 184 00:14:48,180 --> 00:14:54,040 Jensen Huang arrived in the United States as a young migrant, but his 185 00:14:54,040 --> 00:14:56,560 destination wasn't an elite prep school. 186 00:14:57,180 --> 00:15:02,740 Due to a clerical misunderstanding by his parents, he was sent to Oneida 187 00:15:02,740 --> 00:15:09,080 Institute in rural Kentucky, a place that, at the time, functioned more as a 188 00:15:09,080 --> 00:15:12,460 reform school for troubled youth than a traditional academy. 189 00:15:13,400 --> 00:15:18,680 At nine years old, the future CEO of one of the world's most valuable companies, 190 00:15:19,040 --> 00:15:20,040 wasn't coding. 191 00:15:20,200 --> 00:15:25,300 He was cleaning the toilets of 150 teenagers every single afternoon. 192 00:15:26,600 --> 00:15:31,680 In his personal transcript, Jensen reflects on this with a chilling 193 00:15:32,160 --> 00:15:33,440 I didn't complain. 194 00:15:33,760 --> 00:15:35,780 I just learned to want a cart. 195 00:15:36,600 --> 00:15:41,640 That boy learned the first law of accelerated computing decades before it 196 00:15:41,640 --> 00:15:47,140 existed. For a system to be efficient, it must be able to process chaos. 197 00:15:47,520 --> 00:15:48,760 under extreme pressure. 198 00:15:50,600 --> 00:15:56,420 By 15, Jensen was the most efficient dishwasher and waiter at a Denny's in 199 00:15:56,420 --> 00:16:02,400 Portland. I was incredibly shy, he admits, but the chaos of the kitchen 200 00:16:02,400 --> 00:16:03,400 me out of my shell. 201 00:16:04,620 --> 00:16:11,480 It is no coincidence that NVIDIA was founded in 1993 inside a booth at that 202 00:16:11,480 --> 00:16:12,740 same restaurant chain. 203 00:16:13,640 --> 00:16:18,260 While the world saw the dawn of the PC as an office tool for spreadsheets, 204 00:16:18,560 --> 00:16:23,880 Jensen, Chris Malachowski, and Curtis Prim saw a fatal weakness. 205 00:16:25,920 --> 00:16:32,040 In 1993, Intel's general -purpose CPU was hitting a physical wall. 206 00:16:32,800 --> 00:16:37,940 If the future of computing was visual and immersive, the traditional serial 207 00:16:37,940 --> 00:16:41,220 architecture would become the bottleneck of human progress. 208 00:16:42,480 --> 00:16:48,680 With only $40 ,000 in startup capital, they founded NVIDIA to chase a ghost, 209 00:16:48,900 --> 00:16:50,240 accelerated computing. 210 00:16:51,280 --> 00:16:55,960 They bet on a market the rest of the industry dismissed as a niche for toys, 211 00:16:56,420 --> 00:16:57,420 video games. 212 00:16:57,980 --> 00:17:02,760 Before Jensen, video games were the ultimate technological flywheel. 213 00:17:03,320 --> 00:17:08,119 He knew that if you could master the massive, real -time rendering of pixels, 214 00:17:08,420 --> 00:17:11,240 you could eventually simulate reality itself. 215 00:17:12,880 --> 00:17:17,720 But before they could reach that glory, they had to survive their first massive 216 00:17:17,720 --> 00:17:20,079 technical abyss, the NV1. 217 00:17:29,220 --> 00:17:36,180 By 1995, NVIDIA's first massive bet, the NV1 chip, was ready 218 00:17:36,180 --> 00:17:37,180 to conquer the market. 219 00:17:37,600 --> 00:17:41,180 But Jensen Huang had made a catastrophic technical gamble. 220 00:17:42,480 --> 00:17:47,680 At a time when the industry was undecided, he bet on quadratic texture 221 00:17:48,000 --> 00:17:51,680 a method that used curved surfaces to create 3D images. 222 00:17:52,640 --> 00:17:57,140 It was mathematically intelligent, but it was a lonely path. 223 00:17:57,960 --> 00:18:02,720 The industry hammer dropped when Microsoft released its first DirectX 224 00:18:03,080 --> 00:18:08,840 Microsoft chose triangles, not quads, as the universal language for PC gaming. 225 00:18:10,060 --> 00:18:14,220 This decision rendered NVIDIA's technology instantly obsolete. 226 00:18:15,080 --> 00:18:19,220 The NV1 wasn't just a failure, it was a dead end. 227 00:18:19,680 --> 00:18:25,580 The company was bleeding cash, and as Jensen famously put it, they were 228 00:18:25,580 --> 00:18:28,060 at exactly 30 days of oxygen. 229 00:18:31,060 --> 00:18:36,200 NVIDIA's only lifeline was a strategic contract with the Japanese giant Sega to 230 00:18:36,200 --> 00:18:38,420 build the graphics engine for the Sega Saturn. 231 00:18:39,370 --> 00:18:42,510 but Jensen was trapped in a moral and business dilemma. 232 00:18:43,530 --> 00:18:48,430 He knew that if they continued building the chip for Sega using NVIDIA's flawed 233 00:18:48,430 --> 00:18:54,510 quad technology, Sega would lose the console war to Sony's PlayStation, and 234 00:18:54,510 --> 00:18:56,670 NVIDIA would eventually perish anyway. 235 00:18:57,410 --> 00:19:02,330 In an act of intellectual honesty, or as many at the time called corporate 236 00:19:02,330 --> 00:19:03,330 suicide, 237 00:19:03,550 --> 00:19:04,930 Jensen flew to Japan. 238 00:19:05,630 --> 00:19:12,240 He sat across from Shoichiro Irimajiri, the CEO of Sega, and told him the brutal 239 00:19:12,240 --> 00:19:15,740 truth. Our technology is on the wrong path. 240 00:19:16,060 --> 00:19:20,100 If we finish this project, you will produce an inferior product. 241 00:19:21,680 --> 00:19:23,660 Jensen asked for the impossible. 242 00:19:24,220 --> 00:19:29,220 He asked Sega to terminate the contract, but to pay the remaining $5 million 243 00:19:29,220 --> 00:19:35,140 anyway. If you don't pay us, Jensen pleaded, NVIDIA will cease to exist 244 00:19:35,140 --> 00:19:36,140 tomorrow. 245 00:19:37,100 --> 00:19:41,060 Through the astonishment of the tech world, Irimajiri -san agreed. 246 00:19:41,680 --> 00:19:43,700 He didn't pay for a working chip. 247 00:19:43,940 --> 00:19:46,000 He paid for Jensen's integrity. 248 00:19:47,700 --> 00:19:52,180 That $5 million was the most expensive oxygen in history. 249 00:19:53,100 --> 00:19:56,980 To make it last, Jensen had to fire half of his workforce. 250 00:19:57,640 --> 00:20:01,360 These weren't just employees. They were friends who had shared the Denny's 251 00:20:01,360 --> 00:20:02,360 dream. 252 00:20:02,510 --> 00:20:06,750 This trauma institutionalized a permanent state of emergency at NVIDIA. 253 00:20:08,210 --> 00:20:13,610 With the remaining team, Jensen funneled every cent into the Revo 128. 254 00:20:14,730 --> 00:20:19,390 They abandoned quads and embraced Microsoft's triangles with a vengeance. 255 00:20:19,930 --> 00:20:26,930 When it launched in 1997, the Revo 128 was 400 % faster than 256 00:20:26,930 --> 00:20:28,290 anything else on the market. 257 00:20:29,350 --> 00:20:31,730 It was a dive catch of epic proportions. 258 00:20:32,610 --> 00:20:34,710 NVIDIA was no longer just a survivor. 259 00:20:35,010 --> 00:20:37,090 It had become a hunter. 260 00:20:38,230 --> 00:20:43,950 But as Jensen looked out the horizon, he saw 70 rivals waiting to kill him. 261 00:20:44,210 --> 00:20:46,450 The war was only beginning. 262 00:20:53,910 --> 00:20:57,790 The success of the Reaver 128 was a dive catch. 263 00:20:58,430 --> 00:21:01,430 but it placed NVIDIA in the middle of a slaughterhouse. 264 00:21:02,230 --> 00:21:08,170 By 1997, there were over 70 companies fighting for the soul of the 3D graphics 265 00:21:08,170 --> 00:21:09,170 market. 266 00:21:09,550 --> 00:21:13,750 It was a commodity war where price -cutting was the only weapon for most. 267 00:21:14,890 --> 00:21:19,810 Jensen Huang realized that if NVIDIA played by the industry's rules, they 268 00:21:19,810 --> 00:21:21,210 eventually be ground in dust. 269 00:21:22,850 --> 00:21:25,310 He decided to break the laws of time. 270 00:21:26,410 --> 00:21:31,870 The industry standard for developing a new chip was 18 to 24 months, following 271 00:21:31,870 --> 00:21:33,430 the steady beat of Moore's Law. 272 00:21:34,290 --> 00:21:38,350 Jensen gathered his engineers and imposed a suicidal mandate. 273 00:21:39,090 --> 00:21:44,470 NVIDIA would release a brand new, groundbreaking architecture every six 274 00:21:46,370 --> 00:21:49,130 It was a strategy of relentless execution. 275 00:21:49,850 --> 00:21:56,810 By the time a competitor like 3DFX or S3 could react to one NVIDIA chip, Jensen 276 00:21:56,810 --> 00:21:58,510 had already launched two more. 277 00:21:59,430 --> 00:22:03,310 This forced the competition into a permanent state of obsolescence. 278 00:22:03,910 --> 00:22:09,730 To achieve this, NVIDIA had to reinvent its internal engineering, running 279 00:22:09,730 --> 00:22:14,350 multiple design teams in parallel, a massive financial risk that pushed the 280 00:22:14,350 --> 00:22:16,590 company to the edge of its operational capacity. 281 00:22:17,250 --> 00:22:21,230 In 1999, the war reached its climax. 282 00:22:21,910 --> 00:22:24,750 NVIDIA released the GeForce 256. 283 00:22:26,830 --> 00:22:29,870 Jensen didn't just market it as a faster card. 284 00:22:30,150 --> 00:22:33,270 He coined a term that would redefine computing history. 285 00:22:33,790 --> 00:22:34,850 The GPU. 286 00:22:35,670 --> 00:22:37,130 Graphics Processing Unit. 287 00:22:37,770 --> 00:22:39,410 This wasn't just branding. 288 00:22:40,170 --> 00:22:47,170 Technically, the G4 -256 moved the transformer writing calculation, the 289 00:22:47,170 --> 00:22:52,030 heavy mathematical lifting of 3D, off the CPU and onto the chip itself. 290 00:22:52,630 --> 00:22:54,870 It was the birth of a new era. 291 00:22:56,010 --> 00:23:00,430 This performance leap was so massive that NVIDIA secured the prestigious 292 00:23:00,430 --> 00:23:06,050 contract to the original Microsoft Xbox, receiving a crucial $200 million 293 00:23:06,050 --> 00:23:07,050 advance. 294 00:23:08,570 --> 00:23:10,530 The six -month cycle worked. 295 00:23:10,930 --> 00:23:17,310 By the early 2000s, the 70 competitors had been reduced to just two, NVIDIA and 296 00:23:17,310 --> 00:23:18,310 KPI. 297 00:23:18,650 --> 00:23:24,450 In a final act of dominance, NVIDIA acquired the assets of its former idol 298 00:23:24,450 --> 00:23:27,210 arch -rival, 3DFX in 2000. 299 00:23:28,510 --> 00:23:30,490 Jensen had cleared the board. 300 00:23:30,710 --> 00:23:33,770 He was the undisputed king of gaming. 301 00:23:34,310 --> 00:23:39,350 But at the very moment of his greatest triumph, he began to look at the high 302 00:23:39,350 --> 00:23:40,750 -performance computing market. 303 00:23:41,310 --> 00:23:46,130 He realized that the GPU's massive parallel math could do more than just 304 00:23:46,130 --> 00:23:50,030 pixels. It could solve the world's most complex problems. 305 00:23:50,650 --> 00:23:54,830 The seeds of CUDA and the $10 billion gamble. 306 00:23:55,370 --> 00:23:56,370 were being planted. 307 00:24:03,710 --> 00:24:08,970 By 2006, NVIDIA was the undisputed king of the gaming world. 308 00:24:09,470 --> 00:24:11,610 But Jensen Huang was restless. 309 00:24:11,910 --> 00:24:16,410 He realized that the same parallel processing power that rendered pixels 310 00:24:16,410 --> 00:24:20,630 World of Warcraft could be used to solve the world's most complex mathematical 311 00:24:20,630 --> 00:24:21,630 problems. 312 00:24:22,390 --> 00:24:24,070 He launched CUDA. 313 00:24:24,700 --> 00:24:26,840 Compute Unified Device Architecture. 314 00:24:27,340 --> 00:24:31,220 It was a declaration of war against the CPU -centric world. 315 00:24:32,060 --> 00:24:34,460 The goal was simple, yet insane. 316 00:24:35,040 --> 00:24:39,440 Transform every NVIDIA GPU into a general -purpose supercomputer. 317 00:24:40,620 --> 00:24:43,520 But this decision came with a staggering cost. 318 00:24:44,240 --> 00:24:50,020 Jensen mandated that every single GPU NVIDIA manufactured, from the high -end 319 00:24:50,020 --> 00:24:54,620 workstation cards to the cheapest laptop chips, must include the extra 320 00:24:54,620 --> 00:24:57,580 transistors and hardware logic to support CUDA. 321 00:24:58,720 --> 00:25:00,940 Wall Street was horrified. 322 00:25:02,340 --> 00:25:09,120 For nearly a decade, NVIDIA spent billions, estimated at over $10 billion 323 00:25:09,120 --> 00:25:13,760 cumulative R &D, on a software platform that almost no one was using. 324 00:25:14,760 --> 00:25:20,060 Profit margins, which once sat comfortably high, were sacrificed at the 325 00:25:20,060 --> 00:25:21,060 this vision. 326 00:25:21,850 --> 00:25:25,970 Analysts mocked the strategy, calling it the bridge to nowhere. 327 00:25:26,730 --> 00:25:32,670 During the 2008 financial crisis, NVIDIA's market cap plummeted and the 328 00:25:32,670 --> 00:25:35,150 was once again staring into the abyss. 329 00:25:36,550 --> 00:25:38,930 But Jensen wasn't just building hardware. 330 00:25:39,170 --> 00:25:41,830 He was building a software moat. 331 00:25:42,230 --> 00:25:47,510 He sent NVIDIA engineers to universities around the world, helping professors 332 00:25:47,510 --> 00:25:50,070 teach parallel programming using CUDA. 333 00:25:51,210 --> 00:25:52,630 He was ceding the ground. 334 00:25:53,210 --> 00:25:59,470 While competitors like Intel and AMD focused on making faster chips, Jensen 335 00:25:59,470 --> 00:26:00,910 building an entire language. 336 00:26:01,750 --> 00:26:05,350 By the time a developer learned CUDA, they were locked in. 337 00:26:06,010 --> 00:26:09,470 Switching to a competitor wouldn't just mean buying a new chip. 338 00:26:09,750 --> 00:26:12,970 It would mean rewriting millions of lines of code. 339 00:26:14,430 --> 00:26:19,430 Year after year, Jensen defended CUDA in boardrooms and earning calls. 340 00:26:20,240 --> 00:26:25,120 He practiced what he called long -term commitment to a vision, even when the 341 00:26:25,120 --> 00:26:26,480 data didn't yet support it. 342 00:26:27,200 --> 00:26:30,520 He was waiting for a killer app for accelerated computing. 343 00:26:31,480 --> 00:26:35,880 He didn't know what it would be, but he knew that if data grew exponentially, 344 00:26:36,380 --> 00:26:39,800 the serial processing of the CPU would eventually fail. 345 00:26:40,840 --> 00:26:44,160 The silence of the cuda winter was about to be broken. 346 00:26:45,100 --> 00:26:51,320 In a lab at the University of Toronto, A PhD student named Alex Krzyzewski was 347 00:26:51,320 --> 00:26:55,820 about to feed a neural network called AlexNet into those NVIDIA GPUs. 348 00:26:56,620 --> 00:27:02,480 The big bang of artificial intelligence was seconds away, and Jensen Huang was 349 00:27:02,480 --> 00:27:06,660 the only person on Earth who had already built the engine to power it. 350 00:27:14,440 --> 00:27:16,120 The year was 2012. 351 00:27:17,070 --> 00:27:21,930 While the world saw just another academic competition, Jensen Huang saw 352 00:27:21,930 --> 00:27:24,350 spark that would ignite a global revolution. 353 00:27:25,210 --> 00:27:32,030 A neural network called AlexNet, powered by NVIDIA GPUs, crushed the competition 354 00:27:32,030 --> 00:27:33,270 in image recognition. 355 00:27:33,770 --> 00:27:36,750 It was the big bang of deep learning. 356 00:27:37,650 --> 00:27:41,890 Jensen didn't just celebrate, he pivoted the entire company. 357 00:27:42,370 --> 00:27:47,830 He realized that the $10 billion gamble on CUDA had finally found its soul, 358 00:27:48,090 --> 00:27:49,610 artificial intelligence. 359 00:27:50,850 --> 00:27:56,150 This pivot transformed NVIDIA from a graphics card company into the 360 00:27:56,150 --> 00:27:59,250 engine of the world's most powerful data centers. 361 00:28:00,830 --> 00:28:03,550 Jensen's vision was no longer about drawing pixels. 362 00:28:03,750 --> 00:28:06,230 It was about generative AI. 363 00:28:06,970 --> 00:28:13,710 By the time ChatGPT launched in late 2022, NVIDIA didn't just have a head 364 00:28:14,440 --> 00:28:16,540 They were the only ones at the starting line. 365 00:28:19,000 --> 00:28:22,180 Jensen acted with a speed that terrified his competitors. 366 00:28:22,560 --> 00:28:27,560 He didn't just wait for orders. He re -engineered NVIDIA's entire roadmap. 367 00:28:28,400 --> 00:28:35,160 In 2016, he personally delivered the first NVIDIA DGX -1, the world's 368 00:28:35,160 --> 00:28:40,660 first AI supercomputer in a box, to a then -small non -profit called OpenAI. 369 00:28:41,160 --> 00:28:42,540 He was very clear. 370 00:28:43,200 --> 00:28:44,920 This will change the world. 371 00:28:48,140 --> 00:28:50,840 Technically, this period was about specialization. 372 00:28:51,620 --> 00:28:54,500 NVIDIA began adding tensor cores to its chip. 373 00:28:54,840 --> 00:28:58,620 These weren't for graphics. They were designed specifically for the deep 374 00:28:58,620 --> 00:29:01,000 learning math that powers neural networks. 375 00:29:02,160 --> 00:29:06,760 NVIDIA was no longer just making a faster graphics card. It was building a 376 00:29:06,760 --> 00:29:07,760 specialized brain. 377 00:29:08,600 --> 00:29:11,820 By 2017, the momentum was unstoppable. 378 00:29:12,720 --> 00:29:17,420 Every major tech giant was building AI labs, and they all had one thing in 379 00:29:17,420 --> 00:29:20,020 common. They were built on NVIDIA's stack. 380 00:29:21,040 --> 00:29:24,560 This was the era when the software moat became a fortress. 381 00:29:25,460 --> 00:29:29,440 Thousands of researchers were now writing their doctoral thesis on CUDA. 382 00:29:30,700 --> 00:29:35,260 If a competitor wanted to challenge NVIDIA, they wouldn't just need a better 383 00:29:35,260 --> 00:29:40,120 chip. They would have to convince the world's brightest minds to forget 384 00:29:40,120 --> 00:29:41,600 everything they had learned. 385 00:29:43,080 --> 00:29:47,340 But as the AI revolution took hold, an unexpected shadow emerged. 386 00:29:47,860 --> 00:29:52,980 A new craze called Bitcoin and Ethereum began to consume NVIDIA's supply. 387 00:29:53,760 --> 00:29:59,540 To the world, NVIDIA looked invincible, but internally, Jensen was wary. 388 00:30:00,160 --> 00:30:03,000 Jensen knew that every bubble eventually burst. 389 00:30:03,860 --> 00:30:08,980 This period of explosive, accidental growth from crypto miners was creating a 390 00:30:08,980 --> 00:30:10,940 shadow over the company's true mission. 391 00:30:11,950 --> 00:30:16,170 setting the stage for a high -stakes legal battle over corporate transparency 392 00:30:16,170 --> 00:30:20,470 and a financial storm that would test the very foundations of its leadership. 393 00:30:26,490 --> 00:30:32,850 In 2018, NVIDIA was riding a wave that looked like a miracle, but felt like a 394 00:30:32,850 --> 00:30:38,010 mirage. The explosion of cryptocurrency mining had created an insatiable hunger 395 00:30:38,010 --> 00:30:39,110 for G -Force cars. 396 00:30:40,590 --> 00:30:44,770 To the outside world, NVIDIA's revenue was reaching historic heights. 397 00:30:45,170 --> 00:30:49,570 However, beneath the surface, a dangerous ambiguity was growing. 398 00:30:50,570 --> 00:30:55,210 Jensen Huang insisted that the growth was driven by a gaming renaissance, but 399 00:30:55,210 --> 00:30:56,730 the reality was more volatile. 400 00:30:57,310 --> 00:31:00,730 The mirage evaporated in May 2018. 401 00:31:01,630 --> 00:31:06,870 The crypto winter arrived, and the demand for mining chips vanished 402 00:31:08,260 --> 00:31:12,480 NVIDIA was left with a massive surplus of inventory, and the market's reaction 403 00:31:12,480 --> 00:31:13,480 was brutal. 404 00:31:13,580 --> 00:31:18,040 The company's stock price plummeted by 28 % in a single day. 405 00:31:19,160 --> 00:31:23,980 The invincible architect of AI was suddenly facing a crisis of credibility. 406 00:31:25,720 --> 00:31:29,560 This financial collapse ignited a high -stakes legal battle that would 407 00:31:29,560 --> 00:31:32,240 eventually reach the steps of the US Supreme Court. 408 00:31:33,140 --> 00:31:36,860 A group of institutional investors filed a class -action lawsuit. 409 00:31:37,550 --> 00:31:40,990 alleging that Jensen Huang had deliberately misled the market. 410 00:31:41,470 --> 00:31:45,190 The core of the case rested on a single, devastating word. 411 00:31:46,330 --> 00:31:48,910 Cienta. The intent to deceive. 412 00:31:49,970 --> 00:31:51,750 The accusation was sharp. 413 00:31:52,170 --> 00:31:56,410 Investors claimed that internal NVIDIA reports clearly showed over a billion 414 00:31:56,410 --> 00:32:01,110 dollars in revenue attributed to gamers was actually coming from crypto miners. 415 00:32:02,010 --> 00:32:05,550 Jensen fought back, defending his intellectual honesty. 416 00:32:06,140 --> 00:32:09,880 and arguing that the expert opinions used against him were nothing more than 417 00:32:09,880 --> 00:32:10,880 speculation. 418 00:32:11,620 --> 00:32:13,960 This battle, known as Petition No. 419 00:32:14,200 --> 00:32:21,100 23 -970, became a landmark moment for Silicon Valley, questioning how much a 420 00:32:21,100 --> 00:32:25,240 must disclose when their technology accidentally conquered the market they 421 00:32:25,240 --> 00:32:26,460 didn't intend to lead. 422 00:32:28,180 --> 00:32:32,840 While lawyers argued in Washington, Jensen was already looking past the 423 00:32:32,840 --> 00:32:37,720 wreckage. He didn't let the legal storm or the inventory crisis blow down his 424 00:32:37,720 --> 00:32:38,720 ultimate plan. 425 00:32:39,120 --> 00:32:44,340 He doubled down on the data center, acquiring Mellanox for $7 billion to 426 00:32:44,340 --> 00:32:46,300 the highways between his chips. 427 00:32:47,140 --> 00:32:52,040 He was preparing for a world where AI wouldn't just be a research project, but 428 00:32:52,040 --> 00:32:54,280 the operating system of the entire planet. 429 00:32:55,340 --> 00:33:00,880 The storm of 2018 had been a warning. The era of generative AI was about to 430 00:33:00,880 --> 00:33:01,880 provide the answer. 431 00:33:08,300 --> 00:33:11,500 By 2022, the world had changed. 432 00:33:12,180 --> 00:33:17,880 The launch of ChatGPT signaled the arrival of the generative AI era, and 433 00:33:17,880 --> 00:33:20,260 was the only company prepared to power it. 434 00:33:21,240 --> 00:33:26,840 But as Jensen Huang stood on the brink of total market dominance, a new wall 435 00:33:26,840 --> 00:33:30,660 built, not by a competitor, but by the US government. 436 00:33:31,620 --> 00:33:35,400 Washington imposed strict export controls on high -end AI chips. 437 00:33:35,800 --> 00:33:38,650 For NVIDIA, The stakes were astronomical. 438 00:33:40,110 --> 00:33:45,550 According to the geographical revenue data, China accounted for approximately 439 00:33:45,550 --> 00:33:48,890 % to 25 % of the company's total business. 440 00:33:50,370 --> 00:33:55,730 Overnight, Jensen had to navigate a geopolitical minefield, redesigning 441 00:33:55,730 --> 00:34:00,010 specifically to comply with regulations while trying to keep his most important 442 00:34:00,010 --> 00:34:01,410 market from slipping away. 443 00:34:03,270 --> 00:34:07,590 Jensen's answer to the geopolitical and technical pressure was the Blackwell 444 00:34:07,590 --> 00:34:08,590 architecture. 445 00:34:08,830 --> 00:34:13,010 If the H100 was a spark, Blackwell was the sun. 446 00:34:13,870 --> 00:34:19,770 Packing an incredible 208 billion transistors, it delivered up to 30 times 447 00:34:19,770 --> 00:34:22,429 performance of its predecessor for certain AI tasks. 448 00:34:23,489 --> 00:34:26,650 But Blackwell represented a deeper strategic shift. 449 00:34:27,090 --> 00:34:29,510 NVIDIA was no longer just a chipmaker. 450 00:34:31,170 --> 00:34:34,810 Jensen was now building entire AI factories. 451 00:34:35,850 --> 00:34:40,790 By integrating Mellanox networking technology, he controlled the highways 452 00:34:40,790 --> 00:34:44,810 allowed thousands of chips to talk to each other as if they were a single 453 00:34:44,810 --> 00:34:45,810 brain. 454 00:34:46,750 --> 00:34:51,330 This system -on -a -cluster approach meant that even if a competitor produced 455 00:34:51,330 --> 00:34:55,510 faster individual chip, they couldn't compete with the sheer efficiency of the 456 00:34:55,510 --> 00:34:56,510 NVIDIA ecosystem. 457 00:34:58,070 --> 00:35:00,430 The financial results were staggering. 458 00:35:00,750 --> 00:35:02,290 By early 2024, 459 00:35:03,150 --> 00:35:09,790 NVIDIA's data center revenue had surged to over $47 billion, a 217 % 460 00:35:09,790 --> 00:35:11,590 increase in a single year. 461 00:35:12,250 --> 00:35:18,330 The company was operating with 78 .4 % growth margins, profit levels usually 462 00:35:18,330 --> 00:35:21,770 reserved for software giants, not hardware manufacturers. 463 00:35:22,930 --> 00:35:28,970 On June 18, 2024, NVIDIA became the most valuable company on the planet. 464 00:35:29,930 --> 00:35:34,770 Yet, even as it stood at the summit, Jensen refused to relax. 465 00:35:35,370 --> 00:35:40,650 He looked at the 60 -year history of semiconductors, the rise and fall of 466 00:35:40,910 --> 00:35:45,890 the cycles of Samsung and TI, and he knew that being on top was the most 467 00:35:45,890 --> 00:35:46,990 dangerous place to be. 468 00:35:47,430 --> 00:35:50,890 His next challenge wouldn't just be about chips. 469 00:35:51,230 --> 00:35:54,450 It would be about giving AI a physical body. 470 00:36:00,570 --> 00:36:01,810 In 2024, 471 00:36:02,650 --> 00:36:07,070 Jensen Huang had already conquered the digital world, but his eyes were fixed 472 00:36:07,070 --> 00:36:09,130 a new frontier, the physical one. 473 00:36:09,710 --> 00:36:14,870 He declared that the next wave of AI would be physical AI, intelligence that 474 00:36:14,870 --> 00:36:19,430 doesn't just process text or images, but understands the laws of physics. 475 00:36:20,490 --> 00:36:25,990 Everything that moves, from autonomous cars to humanoid robots, would 476 00:36:25,990 --> 00:36:27,790 be powered by an NVIDIA brain. 477 00:36:29,000 --> 00:36:32,680 This identifies it as the third pillar of NVIDIA's future. 478 00:36:33,360 --> 00:36:39,360 To win this race, Jensen isn't just building chips, he's building the 479 00:36:40,040 --> 00:36:44,600 This is a digital world where robots are trained millions of times in a virtual 480 00:36:44,600 --> 00:36:48,180 simulation before they ever step into a real factory. 481 00:36:49,300 --> 00:36:54,700 By the time a robot starts its job, it has already lived a thousand lifetimes 482 00:36:54,700 --> 00:36:55,700 experience. 483 00:36:55,840 --> 00:36:58,980 Jensen's strategy is a total vertical integration. 484 00:36:59,520 --> 00:37:03,440 He is transforming NVIDIA into a provider of AI factories. 485 00:37:04,440 --> 00:37:09,520 He believes that in the future, every company will have two factories, one 486 00:37:09,520 --> 00:37:13,340 produces physical goods and a digital one that produces intelligence. 487 00:37:14,240 --> 00:37:19,100 With the Monox networking high -speed highways and the CUDA software fortress, 488 00:37:19,540 --> 00:37:23,580 Jensen has ensured that the entire infrastructure of this new industrial 489 00:37:23,580 --> 00:37:24,880 revolution runs. 490 00:37:25,320 --> 00:37:26,158 On NVIDIA. 491 00:37:26,160 --> 00:37:31,760 When asked about his legacy, Jensen doesn't talk about stock prices or 492 00:37:31,760 --> 00:37:32,658 of dollars. 493 00:37:32,660 --> 00:37:36,840 He talks about material sciences and scientific discovery. 494 00:37:37,740 --> 00:37:43,160 He believes AI will give humans superpowers, helping us solve climate 495 00:37:43,320 --> 00:37:48,380 cure diseases, and handle the dangerous and mundane tasks so we can focus on 496 00:37:48,380 --> 00:37:50,140 what truly makes us human. 497 00:37:50,460 --> 00:37:51,460 Curiosity. 498 00:37:56,270 --> 00:37:57,270 By 2025, 499 00:37:58,010 --> 00:38:01,670 the world had entered a state of compute geopolitics. 500 00:38:02,310 --> 00:38:08,230 NVIDIA was no longer just a company. It had become a strategic resource, similar 501 00:38:08,230 --> 00:38:09,590 to oil or grain. 502 00:38:10,350 --> 00:38:16,210 The launch of the Bacwell B200 hadn't just met demand, it had ignited a global 503 00:38:16,210 --> 00:38:17,210 scramble. 504 00:38:17,530 --> 00:38:23,370 Nations like Japan, France, and the UAE began building sovereign AI clouds. 505 00:38:23,960 --> 00:38:28,540 realizing that depending on a few Silicon Valley giants for intelligence 506 00:38:28,540 --> 00:38:29,880 national security risk. 507 00:38:30,720 --> 00:38:35,900 But as 2025 progressed, a new whisper began to haunt the industry. 508 00:38:36,600 --> 00:38:37,600 The wall. 509 00:38:37,760 --> 00:38:43,980 For years, AI progress relied on scaling laws, the idea that more data and more 510 00:38:43,980 --> 00:38:46,800 GPUs would inevitably lead to more intelligence. 511 00:38:47,320 --> 00:38:51,660 However, in 2026, the returns are starting to diminish. 512 00:38:52,440 --> 00:38:57,320 Data centers are becoming so massive, they require their own dedicated nuclear 513 00:38:57,320 --> 00:39:01,900 power plants, and the low -hanging fruit of Internet data has been exhausted. 514 00:39:03,400 --> 00:39:06,720 Jensen's response to the wall is typically defiant. 515 00:39:07,120 --> 00:39:11,220 He pivoted the industry towards synthetic data and reasoning models. 516 00:39:11,700 --> 00:39:18,600 In 2026, NVIDIA's focus has shifted from simply training AI to inference 517 00:39:18,600 --> 00:39:19,600 at scale. 518 00:39:20,270 --> 00:39:25,230 The goal is no longer just to build a model that knows everything, but to 519 00:39:25,230 --> 00:39:29,830 a system that thinks through a problem for days if necessary, using massive 520 00:39:29,830 --> 00:39:32,270 clusters of GPUs to reach a breakthrough. 521 00:39:33,910 --> 00:39:37,950 The competition in 2026 has never been fiercer. 522 00:39:38,690 --> 00:39:43,830 NVIDIA's biggest customers, Amazon, Google, and Microsoft, have become its 523 00:39:43,830 --> 00:39:47,950 dangerous rivals, pouring billions into their own custom AI chip. 524 00:39:48,480 --> 00:39:49,980 to escape the NVIDIA attack. 525 00:39:50,840 --> 00:39:54,000 Yet, the software mode remains unbreached. 526 00:39:54,280 --> 00:39:59,340 While others build chips, Jensen is building the entire ecosystem, the 527 00:39:59,340 --> 00:40:03,380 networking, the libraries, and the pre -trained models that make the 528 00:40:03,380 --> 00:40:08,160 competitor's hardware feel like a relic before it even leaves the factory. 529 00:40:09,180 --> 00:40:13,700 In this era, Jensen Huang has become one of the world's most influential 530 00:40:13,700 --> 00:40:19,220 diplomat. He navigates a world where the power grid is the new bottleneck, and 531 00:40:19,220 --> 00:40:23,080 where a single shipment of chips can determine the economic future of a 532 00:40:24,280 --> 00:40:29,980 The trillion -dollar question of 2026 is no longer if AI will change the world, 533 00:40:30,220 --> 00:40:33,200 but who will own the infrastructure of that change. 534 00:40:38,920 --> 00:40:43,440 The story of NVIDIA is often told as a series of lucky breaks or inevitable 535 00:40:43,440 --> 00:40:49,660 triumphs. But as we look at the empire Jensen Huang has built, the reality is 536 00:40:49,660 --> 00:40:52,760 far more deliberate and far more precarious. 537 00:40:53,580 --> 00:40:59,020 In 2026, the company stands at the center of the greatest industrial shift 538 00:40:59,020 --> 00:41:00,020 human history. 539 00:41:00,640 --> 00:41:06,820 Yet for Jensen, the valuation of $3, $4 or $5 trillion is a lagging indicator. 540 00:41:07,300 --> 00:41:09,740 The true metric is the oxygen. 541 00:41:10,720 --> 00:41:15,090 Throughout his journey, From the dishpits of Denny's to the halls of the 542 00:41:15,090 --> 00:41:19,530 Court, Jensen has maintained a philosophy of intellectual honesty. 543 00:41:20,610 --> 00:41:26,290 He admits when the technology is wrong, he pivots when the market shifts, and he 544 00:41:26,290 --> 00:41:28,750 invests billions when the world calls him a fool. 545 00:41:29,650 --> 00:41:35,030 He has turned a semiconductor company into a geopolitical superpower, a 546 00:41:35,030 --> 00:41:39,330 fortress, and the primary architect of a new form of life. 547 00:41:40,460 --> 00:41:45,580 Critics ask if NVIDIA is a bubble waiting to burst, or if the scaling laws 548 00:41:45,580 --> 00:41:47,180 will eventually hit a dead end. 549 00:41:47,720 --> 00:41:51,500 But Jensen doesn't operate on the timeline of its stock market cycle. 550 00:41:51,800 --> 00:41:55,160 He operates on the timeline of human evolution. 551 00:41:56,020 --> 00:41:58,080 He isn't just selling chips. 552 00:41:58,360 --> 00:42:03,180 He is selling the marginal cost of intelligence, making the most valuable 553 00:42:03,180 --> 00:42:09,200 resource in the universe so abundant that it changes the very definition of 554 00:42:09,200 --> 00:42:10,200 is possible. 555 00:42:11,370 --> 00:42:15,510 Jensen often says that he wakes up every morning with the same feeling he had in 556 00:42:15,510 --> 00:42:19,610 1993, the feeling that the company is going out of business. 557 00:42:20,450 --> 00:42:25,610 It is this productive paranoia that prevents the cyclical trap that claimed 558 00:42:25,610 --> 00:42:26,610 giants of the past. 559 00:42:27,470 --> 00:42:29,770 He doesn't want to be the king of a legacy. 560 00:42:30,310 --> 00:42:35,610 He wants to be the architect of a future that hasn't even been imagined yet. 561 00:42:38,110 --> 00:42:39,930 Run, don't walk. 562 00:42:40,600 --> 00:42:44,460 Either you are running for food, or you are running from being food. 563 00:42:45,080 --> 00:42:50,360 In the era of the digital brain, the race has only just begun. 564 00:44:19,440 --> 00:44:24,220 At the edge of the world, in a country with more sheep than people, one of the 565 00:44:24,220 --> 00:44:28,060 most powerful men in Silicon Valley built an escape hatch. 566 00:44:28,460 --> 00:44:34,280 Not a vacation home, not a tax shelter, a contingency plan. 567 00:44:36,280 --> 00:44:42,920 In 2011, a billionaire quietly secured citizenship in New Zealand after 568 00:44:42,920 --> 00:44:44,440 just days in the country. 569 00:44:44,780 --> 00:44:48,740 A legal backdoor, a geopolitical lifeboat, 570 00:44:49,640 --> 00:44:54,940 Deep in the rugged terrain of New Zealand's South Island, Peter Thiel owns 571 00:44:54,940 --> 00:45:00,640 vast private estate, remote, secluded, and far from the centres of power. 572 00:45:01,760 --> 00:45:07,260 While most billionaires buy yachts or private islands, Thiel secures something 573 00:45:07,260 --> 00:45:14,180 more strategic, New Zealand citizenship, and a vast estate in one of the most 574 00:45:14,180 --> 00:45:16,040 remote democracies on Earth. 575 00:45:17,100 --> 00:45:20,660 The purchase price for this geopolitical insurance policy? 576 00:45:21,360 --> 00:45:28,300 In 2011, Thiel obtained New Zealand citizenship after spending just 12 days 577 00:45:28,300 --> 00:45:33,620 the country over the previous two years, a process that normally requires years 578 00:45:33,620 --> 00:45:34,620 of residency. 579 00:45:36,640 --> 00:45:40,260 The investment that secured this exceptional pathway? 580 00:45:40,840 --> 00:45:45,560 Approximately $7 million in local assets and business investments. 581 00:45:47,280 --> 00:45:54,220 The centrepiece, a 477 -acre estate near Lake Wanaka, purchased 582 00:45:54,220 --> 00:45:59,860 for 13 .5 million New Zealand dollars, about 10 million US dollars. 583 00:46:00,740 --> 00:46:07,480 When New Zealand media exposed the deal in 2017, it sparked a national scandal. 584 00:46:08,090 --> 00:46:09,049 Hi, Benedict. 585 00:46:09,050 --> 00:46:12,250 Nice to talk to you again. So when we last spoke, you told us that Peter Thiel 586 00:46:12,250 --> 00:46:17,770 was granted citizenship after having only visited New Zealand four times for 587 00:46:17,770 --> 00:46:22,930 unknown number of days because the documents had that information redacted, 588 00:46:22,930 --> 00:46:26,130 right? Politicians called it citizenship for sale. 589 00:46:26,770 --> 00:46:29,130 Opposition leaders demanded investigations. 590 00:46:30,190 --> 00:46:33,130 But Thiel had already achieved his objective. 591 00:46:34,010 --> 00:46:39,770 a legal escape hatch in the world's most politically stable democracy, a 592 00:46:39,770 --> 00:46:43,530 geopolitical insurance policy that money can buy. 593 00:46:45,610 --> 00:46:50,970 Why would a man who helped build the digital future prepare for the collapse 594 00:46:50,970 --> 00:46:51,970 the physical one? 595 00:46:52,390 --> 00:46:55,630 What does he see that others don't? 596 00:47:00,600 --> 00:47:06,940 The slogan of the Antichrist is peace and safety, which is nothing wrong with 597 00:47:06,940 --> 00:47:10,840 peace and safety, but you have to sort of imagine that it resonates very 598 00:47:10,840 --> 00:47:15,000 differently in a world where the stakes are so absolute, where the stakes are so 599 00:47:15,000 --> 00:47:21,960 extreme, where the alternative to peace and safety is Armageddon 600 00:47:21,960 --> 00:47:23,480 and the destruction of all things. 601 00:47:24,400 --> 00:47:28,140 He is one of the most polarizing figures in Silicon Valley. 602 00:47:28,880 --> 00:47:34,620 To some, a visionary genius who saw the future early. To others, the shadow 603 00:47:34,620 --> 00:47:39,940 financier of movements and candidates who challenge liberal democratic norms. 604 00:47:40,880 --> 00:47:43,940 This is not fear. This is strategy. 605 00:47:44,640 --> 00:47:49,860 For decades, Peter Thiel has made the same bet over and over again. 606 00:47:50,300 --> 00:47:52,520 Bets against consensus. 607 00:47:53,120 --> 00:47:54,640 Bets against the crowd. 608 00:47:54,920 --> 00:47:56,780 Bets against the system itself. 609 00:47:58,890 --> 00:48:03,370 To understand why he built a fortress at the end of the earth, we have to go 610 00:48:03,370 --> 00:48:09,090 back to a childhood of constant displacement, to a chessboard where 611 00:48:09,090 --> 00:48:14,550 meant nothing, to a company that tried to replace money, and another that 612 00:48:14,550 --> 00:48:15,850 learned to see everything. 613 00:48:18,330 --> 00:48:21,550 But the estate is more than a luxury retreat. 614 00:48:21,830 --> 00:48:25,590 It is a fortress designed for civilizational uncertainty. 615 00:48:27,180 --> 00:48:33,060 Off -grid power systems, advanced security infrastructure, multiple 616 00:48:33,060 --> 00:48:34,720 routes through the mountains. 617 00:48:35,040 --> 00:48:38,420 Not built for comfort, built for continuity. 618 00:48:39,300 --> 00:48:44,400 While the world debates progress, Peter Thiel is preparing for a different 619 00:48:44,400 --> 00:48:49,700 possibility. Not how to build the future, how to survive it. 620 00:48:53,000 --> 00:48:55,500 The Architect of Dissidence 621 00:48:57,040 --> 00:49:03,320 Total estimated value of SEAL's contingency infrastructure, $20 to $30 622 00:49:04,400 --> 00:49:10,320 Not for lifestyle, not for prestige, but for the day the system he helped build 623 00:49:10,320 --> 00:49:11,460 no longer holds. 624 00:49:12,280 --> 00:49:15,140 He didn't build this because he panics easily. 625 00:49:15,440 --> 00:49:20,660 He built it because he has always believed that the crowd is wrong, and 626 00:49:20,660 --> 00:49:24,260 future belongs to those willing to stand apart from it. 627 00:49:25,000 --> 00:49:30,700 Every fortress begins as an idea, and Peter Thiel has been building 628 00:49:30,700 --> 00:49:33,060 fortresses since he was a child. 629 00:49:39,320 --> 00:49:44,980 Before he was a billionaire, before he funded political outsiders, before he 630 00:49:44,980 --> 00:49:50,320 built machines that could see everything, he was a boy who never 631 00:49:50,320 --> 00:49:52,940 place long enough to believe the world made sense. 632 00:49:54,060 --> 00:49:57,220 So he searched for a world where the rules didn't change. 633 00:49:57,840 --> 00:50:00,180 He found it on a chessboard. 634 00:50:01,060 --> 00:50:06,280 To understand Peter Thiel, you must understand what it means to be a 635 00:50:06,280 --> 00:50:07,280 outsider. 636 00:50:08,100 --> 00:50:13,580 Born in Frankfurt, West Germany, Peter Thiel spent part of his early childhood 637 00:50:13,580 --> 00:50:19,320 in Southwest Africa, now Namibia, before growing up mainly in the United States 638 00:50:19,320 --> 00:50:21,320 between Ohio and California. 639 00:50:22,860 --> 00:50:27,100 Before he was a teenager, he had already experienced life on multiple 640 00:50:27,100 --> 00:50:31,460 continents, never staying long enough to feel fully at home. 641 00:50:32,440 --> 00:50:34,280 He didn't have a hometown. 642 00:50:34,620 --> 00:50:41,480 He didn't have a tribe. He only had his own mind, and in that isolation, he 643 00:50:41,480 --> 00:50:44,100 found a language that didn't require a passport. 644 00:50:48,620 --> 00:50:53,040 For a child who changed continents before he could even make friends, the 645 00:50:53,040 --> 00:50:55,400 outside world was unpredictable noise. 646 00:50:55,900 --> 00:50:57,140 But the board? 647 00:50:57,360 --> 00:51:02,140 The board was the only place where the rules didn't change depending on the 648 00:51:02,140 --> 00:51:03,140 country. 649 00:51:06,660 --> 00:51:11,680 His father, an engineer trained in a culture of precision and system 650 00:51:12,120 --> 00:51:16,160 passed on a belief that reality could be understood and optimized. 651 00:51:17,960 --> 00:51:22,140 While other children sought to fit in, Peter sought the edge. 652 00:51:22,580 --> 00:51:26,840 He learned that the consensus of the crowd is usually a distraction. 653 00:51:27,880 --> 00:51:33,320 If everyone is running toward the ball, you run toward where the ball is going 654 00:51:33,320 --> 00:51:34,320 to be. 655 00:51:34,820 --> 00:51:37,580 Chess is the ultimate antidote to consensus. 656 00:51:38,720 --> 00:51:41,740 In a crowd, you can hide behind a popular opinion. 657 00:51:42,100 --> 00:51:45,740 In chess, you are either right or you are dead. 658 00:51:46,460 --> 00:51:50,300 There is no middle ground, there is no social construction of the board. 659 00:51:51,320 --> 00:51:56,360 He became a serious tournament chess player, drawn to a world where rules 660 00:51:56,360 --> 00:52:00,500 fixed, outcomes were earned, and consensus meant nothing. 661 00:52:02,520 --> 00:52:05,480 Mid -1980s, Stanford University. 662 00:52:06,740 --> 00:52:10,820 To the world, this was the peak of American meritocracy. 663 00:52:11,420 --> 00:52:15,140 To Thiel, it was a factory of conformity. 664 00:52:15,980 --> 00:52:19,960 While his classmates were debating how to change the world through activism, 665 00:52:20,580 --> 00:52:23,820 Thiel was wondering why they all sounded exactly the same. 666 00:52:24,480 --> 00:52:29,720 He saw the multiculturalism movement not as progress, but as a new form of 667 00:52:29,720 --> 00:52:30,720 fundamentalism. 668 00:52:31,560 --> 00:52:37,440 Stanford in the late 1980s was ground zero for America's culture wars, battles 669 00:52:37,440 --> 00:52:41,860 over multiculturalism, speech, and the purpose of higher education. 670 00:52:43,020 --> 00:52:44,820 Thiel believed the university 671 00:52:45,530 --> 00:52:50,610 was drifting toward ideological conformity, that certain views were 672 00:52:50,610 --> 00:52:53,430 socially, if not formally, off -limits. 673 00:52:53,830 --> 00:52:57,210 Here his investment methodology was born. 674 00:52:57,850 --> 00:53:02,050 Identify what the crowd considered sacred and question it. 675 00:53:03,590 --> 00:53:10,530 If everyone says identity diversity is the most important thing, you argue that 676 00:53:10,530 --> 00:53:14,270 intellectual diversity is the only thing that matters. 677 00:53:15,470 --> 00:53:20,630 He wasn't looking for friends. He was looking to recruit others who, like him, 678 00:53:20,770 --> 00:53:22,710 did not fear being hated. 679 00:53:23,390 --> 00:53:25,850 He founded the Stanford Review. 680 00:53:26,510 --> 00:53:32,010 The paper quickly became one of the most controversial publications on campus, 681 00:53:32,330 --> 00:53:38,410 attacking what Fields saw as intellectual monoculture and political 682 00:53:39,050 --> 00:53:44,040 He saw that the smartest people in the country were all competing for the same 683 00:53:44,040 --> 00:53:47,660 narrow prizes, thinking the same narrow thoughts. 684 00:53:48,580 --> 00:53:51,440 He did what every top student does. 685 00:53:51,740 --> 00:53:53,240 He followed the track. 686 00:53:53,980 --> 00:54:00,080 After Stanford Law, he secured a prestigious federal appellate clerkship, 687 00:54:00,080 --> 00:54:03,440 kind of credential that opens every elite door in America. 688 00:54:04,280 --> 00:54:09,300 After his clerkship, he joined Sullivan and Cromwell in New York, one of the 689 00:54:09,300 --> 00:54:11,500 most elite law firms in the world. 690 00:54:12,300 --> 00:54:14,360 On paper, he had reached the summit. 691 00:54:14,720 --> 00:54:18,060 Wall Street was his great negative epiphany. 692 00:54:19,620 --> 00:54:24,380 But from his perspective, the brightest graduates in America were locked in 693 00:54:24,380 --> 00:54:27,920 brutal competition for careers they didn't even seem to want. 694 00:54:29,060 --> 00:54:34,840 It looked like Rene Girard's theory made flesh, a system where everyone desired 695 00:54:34,840 --> 00:54:37,960 the same prize simply because everyone else did. 696 00:54:38,720 --> 00:54:43,140 Wall Street looked to Theo like a laboratory of mimetic rivalry. 697 00:54:43,820 --> 00:54:49,000 He realized that if he won that race, his prize would be becoming the man in 698 00:54:49,000 --> 00:54:52,020 office next door, a copy of a copy. 699 00:54:52,620 --> 00:54:57,760 The day he lost the opportunity to clerk for the U .S. Supreme Court wasn't a 700 00:54:57,760 --> 00:54:59,960 defeat. It was his liberation. 701 00:55:00,880 --> 00:55:02,920 He lasted less than a year. 702 00:55:03,800 --> 00:55:09,680 But Thiel's first venture after leaving law was a humbling lesson in failure, a 703 00:55:09,680 --> 00:55:12,380 lesson that would save everything that came after. 704 00:55:14,280 --> 00:55:21,120 In 1996, he launched Thiel Capital Management, a 705 00:55:21,120 --> 00:55:25,740 hedge fund focused on currency trading and macroeconomic derivatives. 706 00:55:26,420 --> 00:55:32,220 The strategy was to make big directional bets on interest rates, inflation 707 00:55:32,220 --> 00:55:33,220 expectations, 708 00:55:33,800 --> 00:55:35,320 and foreign exchange movements. 709 00:55:36,140 --> 00:55:42,460 Initial capital raised $1 million, mostly from Stanford Connections, who 710 00:55:42,460 --> 00:55:45,980 believed in the chess prodigy turned lawyer turned financier. 711 00:55:48,460 --> 00:55:51,120 The result was spectacular failure. 712 00:55:51,700 --> 00:55:55,520 Within the first year, the fund had lost significant capital. 713 00:55:56,040 --> 00:56:01,520 Industry estimates suggest losses between 30 % and 40 % of the initial 714 00:56:01,520 --> 00:56:02,520 investment pool. 715 00:56:03,100 --> 00:56:04,320 Investors fled. 716 00:56:04,660 --> 00:56:08,000 Some demanded their remaining money back immediately. 717 00:56:09,320 --> 00:56:14,300 Steele's reputation among finance professionals, the people he had walked 718 00:56:14,300 --> 00:56:17,500 from at Sullivan and Cromwell, took a serious hit. 719 00:56:18,560 --> 00:56:21,100 He was no longer the Stanford genius. 720 00:56:21,580 --> 00:56:24,220 He was just another failed trader. 721 00:56:25,060 --> 00:56:29,760 But this failure taught him the most important lesson of his career. 722 00:56:30,520 --> 00:56:36,970 Competition. is for losers do not compete in crowded markets where 723 00:56:36,970 --> 00:56:42,930 making the same trades with the same information and the same tools wall 724 00:56:42,930 --> 00:56:48,830 was full of extremely smart people doing the same macro trades reading the same 725 00:56:48,830 --> 00:56:55,070 economic reports betting on the same currency movements it was a zero -sum 726 00:56:55,070 --> 00:56:58,110 played by thousands of nearly identical players 727 00:57:00,490 --> 00:57:06,110 He needed to find a space where the rules were still being written, where 728 00:57:06,110 --> 00:57:11,830 first mattered more than being best, where a monopoly position was still 729 00:57:11,830 --> 00:57:14,610 available. He needed technology. 730 00:57:15,370 --> 00:57:20,910 And from the ashes of field capital management, a new philosophy was born. 731 00:57:21,490 --> 00:57:25,630 If you want to create lasting value, you have to build a monopoly. 732 00:57:26,310 --> 00:57:29,090 This became his investing mantra. 733 00:57:29,740 --> 00:57:31,660 and it would make him billions. 734 00:57:35,580 --> 00:57:40,740 Thiel walked away from the firm and went back to California, not to start a tech 735 00:57:40,740 --> 00:57:44,400 empire, but to try trading, then to launch a hedge fund. 736 00:57:44,640 --> 00:57:45,640 It failed. 737 00:57:46,000 --> 00:57:51,560 The system he had rejected did not welcome him back as a prodigy. It 738 00:57:51,560 --> 00:57:52,560 like a nobody. 739 00:57:53,200 --> 00:57:57,880 That failure would become the last lesson before his real beginning. 740 00:57:58,860 --> 00:58:00,160 But he'd learned something. 741 00:58:00,740 --> 00:58:05,220 If you play the system game as everyone else, you've already lost. 742 00:58:06,260 --> 00:58:08,720 The chess master was done with the board. 743 00:58:08,980 --> 00:58:11,440 He was ready to build his own. 744 00:58:18,820 --> 00:58:20,180 So this is an ATM. 745 00:58:20,500 --> 00:58:23,360 All we're going to do is transform the traditional banking industry. 746 00:58:24,540 --> 00:58:26,580 I do not fit the picture of a banker. 747 00:58:28,410 --> 00:58:29,570 X .com, this is Julie. 748 00:58:29,910 --> 00:58:34,950 Raising $50 million is a matter of making a series of phone calls, and the 749 00:58:34,950 --> 00:58:35,950 is there. 750 00:58:36,690 --> 00:58:41,350 I've sunk the great majority of my net worth into X .com, which is the new 751 00:58:41,350 --> 00:58:44,410 banking and mutual funds company on the Internet that I've started. 752 00:58:45,510 --> 00:58:46,690 December 1998. 753 00:58:47,910 --> 00:58:54,090 Peter Thiel co -founds a company called Confinity with Max Levchin, a brilliant 754 00:58:54,090 --> 00:58:57,010 Ukrainian -born programmer, and Luke Nosek. 755 00:58:57,400 --> 00:58:59,520 a fellow Stanford reviewer luminous. 756 00:59:00,660 --> 00:59:06,300 Initial funding, $300 ,000, scraped together from friends, family, and 757 00:59:06,300 --> 00:59:09,100 libertarian true believers from the Stanford days. 758 00:59:09,860 --> 00:59:15,440 The original product idea, digital wallet on Palm Pilot handheld devices. 759 00:59:16,160 --> 00:59:18,020 The vision was that people... 67402

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