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How Jensen Huang Actually Built NVIDIA

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How Jensen Huang Actually Built NVIDIA

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421 segments

0:00

This dishwasher boy built a $5 empire

0:03

from the table of a Denny's diner.

0:05

He pitched the business plan over cheap

0:06

coffee in 1992, and 34 years later, his

0:10

company makes $20

0:11

every single hour.

0:13

Not from the safe bet, but from a gamble

0:15

nobody believed in that crushed entire

0:17

industries and took over the AI space,

0:20

the gaming industry, and even all of

0:22

your app algorithms.

0:23

And just as he started winning, the

0:25

government moved to [music] bring him

0:27

down.

0:29

Jensen Huang was born in Taiwan in 1963.

0:33

When he was nine, [music] his parents

0:35

sent him and his brother to America for

0:36

a better education.

0:38

The plan was simple. Live with relatives

0:40

in Kentucky, study hard, build a future.

0:45

This doesn't look like a school. It

0:47

looks more like somewhere people get

0:48

sent after they've done something very,

0:50

very wrong. That's because

0:52

>> [music]

0:52

>> it kind of is. Welcome to Oneida Baptist

0:54

Institute. You'll learn English,

0:56

discipline, and how not to complain

0:58

while cleaning bathrooms.

1:00

This is not how most tech CEO origin

1:03

stories start, but it didn't break him.

1:05

It taught him something no lecture hall

1:07

could.

1:08

When the situation is terrible, you

1:10

adapt [music]

1:10

or you disappear.

1:12

He eventually made it to Oregon State,

1:14

then Stanford, spent years at chip

1:16

companies,

1:17

AMD, then LSI Logic, studying

1:21

semiconductors with a level of obsession

1:22

that was, frankly, a little alarming.

1:25

By 1992, Jensen had an idea.

1:28

Graphics are going to change computing.

1:31

Games are getting bigger. 3D is getting

1:33

harder. CPUs can't carry this forever.

1:37

Someone is going to build a chip for

1:38

this new world.

1:40

I think it should be us.

1:41

Jensen, I have a mortgage, a stable job,

1:44

and a family that currently believes I

1:46

make responsible decisions.

1:48

Good.

1:49

Then this will be exciting. So, the plan

1:51

is, quit our jobs, start from zero, and

1:54

build a chip for a market that barely

1:56

exists?

1:57

Correct. I hate that this sounds insane

2:00

and also kind of logical.

2:02

They called the company Nvidia.

2:04

The idea was ambitious. Build one

2:06

powerful [music] graphics chip that

2:07

could handle everything. A clean

2:10

universal chip for the future of gaming

2:12

hardware.

2:13

For 2 years they worked. They spent

2:15

every dollar they had. And in 1995,

2:18

Nvidia launched its first product, the

2:20

NV1.

2:22

Jensen, we have a problem. Microsoft

2:25

just [music] published the Direct X

2:26

spec, full triangle based rendering

2:28

pipeline. Holy crap, the NV1 runs

2:31

quadratic mapping?

2:33

Yes.

2:34

We are the only ones going in the

2:35

opposite direction. Games are about to

2:37

be built from tiny flat triangles?

2:40

Our chip is built for curved surfaces.

2:42

We built the wrong chip with tremendous

2:44

confidence. 2 years, every dollar. A

2:47

chip built for a world that no longer

2:48

existed. The NV1 [music] flopped.

2:51

But Nvidia still had a lifeline. Sega

2:54

had contracted them to build the

2:55

graphics processor for the company's

2:57

next generation console,

2:59

the Dreamcast.

3:01

Real money, real chance to start over.

3:04

There was only one problem.

3:06

Sega's chip used the same dead-end

3:08

technology. [music] You're doing the

3:09

Sega math again, aren't you?

3:11

We'll spend the next year building

3:12

something we already know is dead. And

3:14

if we cancel, we lose the only customer

3:17

still paying us.

3:18

Uh, Pretty much.

3:21

I miss normal employment.

3:23

If we're going to die, let's die

3:25

building the right chip.

3:26

>> [music]

3:26

>> So Jensen flew to Japan.

3:29

The chip is a dead end. You should

3:31

cancel our contract and find someone

3:32

else.

3:33

We shouldn't finish the contract. It

3:35

would be a waste of your money.

3:36

>> [music]

3:38

>> There's one more thing. I still need the

3:40

money, the $5 million remaining on our

3:42

contract. Please put it into Nvidia as

3:44

an investment instead. Otherwise, we'll

3:46

vaporize overnight.

3:47

>> [music]

3:48

>> I have nothing to offer you. This money

3:50

will most likely be lost, but I'm asking

3:52

anyway.

3:55

I'll need a few days.

3:56

Jensen [music] bowed, walked out, and

3:58

got on a plane. Nothing to do now but

4:01

sit, and wait, and watch the Pacific

4:03

stretch out beneath him.

4:05

Jensen, you might want to see this.

4:08

He opens [music] it, eyes wide. It's a

4:10

massive 10% offer on the value of

4:13

BetterHelp.

4:15

Just kidding.

4:16

Let's be real for a second. When the

4:18

outcome is completely out of your hands,

4:20

the anxiety Did I make the right call?

4:23

That noise won't switch off. It doesn't

4:25

go away on its own.

4:27

The hardest part for me was noticing the

4:29

pattern.

4:31

I was pushing through instead of

4:33

actually dealing with anything.

4:35

My therapist asked me one question.

4:37

Are you solving something, or are you

4:39

rehearsing a disaster?

4:41

I didn't have an answer. Just having a

4:43

name for what I was doing,

4:45

that single reframe broke the loop.

4:48

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4:49

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4:52

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5:01

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5:16

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5:19

Every great ship [music] needs

5:20

maintenance. So do you.

5:25

Hello.

5:26

The money is coming.

5:28

The reason the Sega CEO said yes had

5:31

nothing to do with business logic. He

5:33

just liked Jensen.

5:35

That $5 million bought Nvidia 6 months.

5:38

And now they had one last shot to build

5:40

the right chip, or

5:41

>> [music]

5:41

>> go bankrupt.

5:44

They called it the Riva 128,

5:46

triangle-based, [music]

5:47

DirectX compatible, built from scratch.

5:51

Weeks of late nights, bad coffee, and

5:53

absolutely zero plan B. They had exactly

5:56

1 month of payroll [music] left in the

5:58

bank to find out if it worked.

6:01

The chip launched in 1997, and this time

6:04

Nvidia did not miss. Game developers

6:06

could actually use it. Customers

6:08

actually bought it. From the brink of

6:09

bankruptcy to a million units sold in 4

6:13

months.

6:14

Most CEOs would have taken a long

6:16

vacation and slow down a bit.

6:18

He walked back into the office and wrote

6:20

one word on the whiteboard.

6:22

More.

6:24

So, by 1999, Nvidia launched the GeForce

6:27

256 and gave the world a term it didn't

6:29

really have yet, GPU.

6:32

Graphics processing unit.

6:34

It was a genuine leap. A chip that

6:36

handled complex 3D calculations that

6:38

previously required an entirely separate

6:40

processor. For gamers,

6:42

>> [music]

6:43

>> this meant smoother worlds, better

6:45

lighting, and monsters that looked

6:46

slightly less like wet cardboard. Gamers

6:49

loved it. Developers wept [music] with

6:51

joy.

6:52

Revenue exploded. And by the early

6:54

2000s, Nvidia had become the king of PC

6:57

graphics. Every serious gamer, every

7:00

visual effects studio, every game

7:02

developer on the planet. The obvious

7:04

move was simple. Keep making better

7:06

gaming chips, sell them to gamers,

7:08

become rich, buy a very large leather

7:10

jacket museum.

7:11

But Jensen started looking at something

7:13

other people missed.

7:15

A CPU is like one very smart employee

7:18

doing tasks one by one extremely fast.

7:21

Meanwhile, a GPU is like 10,000 interns

7:24

doing [music] tiny calculations at once.

7:26

Are the interns smart?

7:28

No.

7:29

But there are a lot of them, and if your

7:31

problem can be broken into thousands of

7:32

small calculations, physics, chemistry,

7:35

weather, biology, artificial

7:37

intelligence,

7:39

suddenly, the chip built for video games

7:41

[music] starts looking like something

7:42

else, a cheap supercomputer.

7:45

Jensen looked at this and thought, "What

7:47

if the same chip that rendered

7:48

explosions in video games could help

7:50

simulate molecules, predict weather,

7:53

model fluids, and maybe one day train

7:55

machines to think?"

7:57

So, in 2006, Nvidia launched CUDA,

8:00

Compute Unified Device Architecture, a

8:03

platform that let scientists,

8:04

researchers, and engineers use Nvidia

8:07

GPUs [music] for general-purpose

8:08

computing.

8:10

And then, he committed roughly $500

8:12

million to build it.

8:14

Jensen,

8:16

the gaming business is printing money.

8:18

Walk me through who CUDA is actually

8:20

for.

8:21

Researchers, scientists, people running

8:23

fluid dynamics simulations, climate

8:26

models, drug discovery?

8:28

So, not our customers.

8:30

Not yet.

8:32

I'm starting to hate that phrase. This

8:34

is our CUDA revenue after 2 years. Do

8:36

you see a number?

8:37

Not today.

8:39

Jensen, this is not a business. We are

8:42

subsidizing a hobby for PhD students.

8:45

PhD students are where the future

8:47

starts. For the first time, they can use

8:49

a gaming chip like a supercomputer.

8:51

We don't know what they'll build with

8:53

it. But when they build [music]

8:54

something important, it will run on us.

8:56

If they build nothing,

8:58

we still have the best gaming cards in

9:00

the world and a $500 million science

9:03

project. We've survived worse.

9:06

>> [music]

9:06

>> Six years passed. The gaming business

9:08

kept printing money. CUDA kept printing

9:11

almost nothing.

9:12

And Jensen kept waiting for the problem

9:14

big enough to prove him right.

9:16

Then, in Toronto, someone found it.

9:20

It's 2012. Every year, the world's top

9:23

AI researchers compete in a challenge

9:24

[music] called ImageNet. Tens of

9:27

millions of images, and your software

9:29

has to identify what's in them.

9:31

You see the Toronto submission? Some PhD

9:34

student [music] who running a a network

9:35

on gaming cards. We've been hand-coding

9:37

classifiers for a decade. Gaming cards

9:40

aren't going to crack this.

9:41

Ladies and gentlemen, thank you for

9:43

waiting.

9:44

The ImageNet [music] 2012 results are

9:46

final. Second place, University of Tokyo

9:50

with a 26.2% error rate. And this year's

9:53

winner,

9:54

University of Toronto, AlexNet, 15.3%.

9:59

I'm sorry, 15?

10:00

That's not a win. That's a murder scene.

10:03

For years, researchers have been trying

10:05

to teach computers how to see by

10:07

manually designing the features they

10:09

should look for.

10:10

Edges, textures, shapes, patterns.

10:14

AlexNet took a different path. Give the

10:16

neural network enough data, enough

10:18

layers, and enough computing power,

10:21

and let it learn the features itself.

10:24

Training a neural network requires

10:26

millions of small calculations happening

10:28

at the same time.

10:29

Exactly the kind of work that Nvidia had

10:32

been quietly perfecting for 6 years.

10:35

The $500 million bet

10:36

>> [music]

10:36

>> had finally found its customer.

10:38

Suddenly, every major AI lab started

10:40

paying attention. Stanford, MIT, Google,

10:45

Meta, Microsoft.

10:47

They weren't just buying graphics cards

10:49

[music] anymore.

10:50

They were buying computing power for

10:51

intelligence itself.

10:53

And Nvidia had the hardware, the

10:55

software, and the scale to deliver it.

10:58

Great news for Nvidia, until in 2022,

11:00

[music]

11:01

Washington made a phone call.

11:05

Before Washington called, Jensen had

11:07

already tried to fix Nvidia's biggest

11:08

weakness. Because Nvidia designed the

11:10

chips,

11:12

but it didn't make them.

11:13

That job belonged mostly to TSMC in

11:16

Taiwan.

11:17

And he didn't own the underlying

11:19

architecture, the fundamental

11:20

instruction set that tells processors

11:22

how to think.

11:24

That belonged to a British company

11:25

called ARM.

11:27

A company whose technology sat inside

11:29

virtually every smartphone on Earth.

11:31

Apple, Samsung, Qualcomm, your pocket.

11:35

Their DNA, not Jensen's.

11:38

So, for all of Nvidia's power, [music]

11:39

Jensen was still renting the building.

11:42

He owned the furniture.

11:43

So, in 2020,

11:44

>> [music]

11:44

>> Jensen made his move. Nvidia offered $40

11:47

to buy ARM.

11:49

Own the GPU, own the software, own the

11:52

architecture. Simple.

11:54

Unless you were literally everyone else

11:55

in tech.

11:57

Nvidia cannot own ARM. Agreed. Agreed.

11:59

Also agreed.

12:01

Wow, I hate how united we are. If Jensen

12:04

owns ARM, then every chip we build runs

12:06

through our most dangerous competitor.

12:08

Phones,

12:09

>> [music]

12:09

>> servers, AI chips, everything. So, what

12:12

do we do?

12:13

We complain to every regulator with an

12:15

email address.

12:17

And they did. The FTC sued. The European

12:20

Commission investigated. The UK blocked

12:22

it on national security grounds.

12:24

18 months later, Nvidia walked away.

12:27

Then Washington called. Mr. Huang,

12:30

effective immediately, advanced AI

12:32

chips, the H100,

12:34

>> [music]

12:34

>> can no longer be exported to China.

12:37

How much revenue are we talking about?

12:39

That sounds like a you problem.

12:41

Just like that, some of Nvidia's biggest

12:43

customers were cut off.

12:45

Alibaba, Baidu, ByteDance, China's AI

12:49

companies,

12:50

gone.

12:51

So, Nvidia did what Nvidia always did.

12:53

It engineered around the problem.

12:56

They built a weaker version, the H800,

12:58

designed to fit inside the rules.

13:01

Legal enough to ship. Powerful enough

13:03

[music] to sell.

13:04

For about 5 minutes, because by late

13:06

2023, Washington tightened the rules

13:08

again.

13:09

The H800 was restricted to

13:11

>> [music]

13:12

>> The message was clear. Nvidia was now a

13:14

strategic weapon in America's technology

13:16

war with China.

13:18

Jensen wasn't just a CEO anymore. He was

13:21

a piece on someone else's chessboard,

13:23

moved by people he couldn't negotiate

13:24

with.

13:25

But while politics got messier, demand

13:27

got insane. OpenAI, Google, [music]

13:30

Anthropic, xAI, Microsoft. Everyone

13:34

building large AI models needed the same

13:36

thing, more Nvidia chips, more data

13:39

centers, more power, more cooling, more

13:42

everything.

13:44

Blackwell, Nvidia's next [music]

13:45

generation chip, was being ordered

13:47

before factories could even finish

13:48

making it.

13:50

By October 2025, Nvidia [music] crossed

13:52

$5 trillion in market value.

13:54

The most valuable company on Earth,

13:56

ahead of Google, ahead of Apple.

13:59

Not bad for a company that once had 30

14:01

days of cash left and one very wrong

14:03

chip.

14:04

None of it was supposed to work.

14:06

Every single [music] bet looked insane

14:08

from the outside, and every single one

14:10

paid off.

14:11

As what he himself [music] said,

14:13

"My will to survive exceeds everybody

14:15

else's will to kill me."

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