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