Nvidia Part I: The GPU Company (1993-2006)｜Acquired

Who got the truth?

Is it you, is it, you?

Is it you?

Who got the truth now?

Is it you, is it, you is it you?

Sit me down, say it straight.

Another story on the way who got?

Welcome to Season 10, Episode 5 of Acquired, the podcast about great technology companies and the stories and playbooks behind them.

I'm Ben Gilbert and I'm the co-founder and managing director of Seattle-based Pioneer Square Labs and our venture fund, PSL Ventures.

And I'm David Rosenthal, and I am an angel investor based in San Francisco.

And we are your hosts.

It is the eighth largest company in the world by market cap.

Dang!

When NVIDIA began in 1993, it made computer graphics chips in a brutally competitive and low-margin market.

They have an 83% market share of standalone GPUs, that's graphics processing units for those of you starting with us from Square One, that are supplied for desktop and laptop computers.

Ben, you're telling like the whole story here.

Sorry, sorry.

I'll just, I'll tease a few things here.

So not only that, but of course followers of NVIDIA know that they recently pioneered a completely new market called the hardware and software development tools to power machine learning, neural networks, deep learning, all of this in the cloud and the data center which obviously is proving to define this whole decade of computing.

And as David and I began our research, we realized This really could be a book and like a thriller of a book, since the co-founder and CEO, Jensen Huang, really has bet the company like the whole company three separate times, nearly going bankrupt each time.

But obviously, as we reflect back here today, that certainly did not happen.

All right.

So here's everything you need to know about Jensen.

The CliffsNotes before we talk for like six hours about him.

The dude used to drive a Toyota Supra like a Fast and the Furious style, like a death machine.

And he almost died.

He got in like a huge accident.

Just one more way.

He is like Elon Musk.

Oh, man.

Crazy.

Well, because we have way too much here for one episode, we'll save the stories on machine learning for next time.

Today we are going to tell the wild story of NVIDIA's founding to its rise in prominence, powering the computer graphics and gaming revolution.

This really is a story of true invention and innovation.

It reminds you that engineering breakthroughs really do push our world forward.

And in saying that just kind of set some context.

This is a story that takes place from about 1993 to kind of the mid to late 2000s.

And as hyped as NVIDIA has been, you know, over the last five years obviously, with the stock run up and everyone's excitement around the company, I think Jensen is still an underrated CEO, even rated 100 where the NVIDIA bulls have put him.

I think Jensen is one of those people where like, if you know about him, you know what we're talking about and you have unbelievable reverence.

But I think not enough people really know.

Just one more Jensen quote before we get into the episode.

This is the best.

My will to survive exceeds almost everybody else's will to kill me.

Amazing.

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They also have a screener that lets you filter across thousands of stocks, so you can quickly surface investment ideas.

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And David, take us in.

So we start in February of 1963.

What was going on in Silicon Valley in 1963?

Let's see.

Fairchild had already started, I think.

And Silicon Valley was like underway, but it was early days.

But we start not in Silicon Valley, but in Taiwan.

Yes.

The southern part of the island of Taiwan, with the birth of Jen Soon-Hwang, later Americanized to Jensen Jensen Huang.

So his dad was an engineer for the air conditioning company Carrier.

Oh, yeah.

Yeah, you see those big industrial air conditioning units on buildings and stuff.

And when Jensen is four, his dad goes on a company training to America, to New York City.

And he was like, wow, this is amazing.

I want my kids to grow up here and to have all the opportunities that are available.

So he comes home.

Jensen's four.

Jensen has an older brother who's a couple years older.

You know, like nobody speaks English.

So his mom gets an English dictionary and picks 10 words every day, grills the two kids and like, quizzes them and teaches them English out of the dictionary.

Now, if you listen to Jensen, where does that accent come from?

Because it's not what you would think.

The family ends up moving to Thailand a few years later.

And then, when they're living in Thailand and Jensen is nine, They finally decide that this is the right time to send the kids to America.

Now, the parents can't move to America yet.

They don't have enough money.

But they found a boarding school in America that is cheap enough that they can afford.

It is called Oneida Baptist Institute.

And it is in eastern Kentucky, the sticks of Kentucky.

Jensen would later say that he and his brother were the first foreigners to attend this school and they're pretty sure they were the first Chinese people ever in the town of Oneida.

Whoa.

Well, it turns out that the reason that this school, OBI Oneida Baptist Institute, was so cheap was it's actually not a prep school.

It's a reform school.

Yeah.

So this is a school for troubled kids.

It's a reform school.

So Jensen's roommate, when he shows up as a nine year old, is a 17 year old kid who had just gotten out of prison and was recovering from seven stab wounds that he got in a knife fight.

Classic American journey right here.

And amazingly this is so, Jensen like they become great friends, even though this kid is eight years older than him, like twice his age, basically from a way different background.

Jensen helps him with math and he gets Jensen into weightlifting.

So you see Jensen today and you're like, that dude is jacked.

He is jacked.

He's been weightlifting since he was nine years old.

He says about his time in Anita, you know, now I don't get scared very often.

I don't worry about going places I haven't gone before.

I can tolerate a lot of discomfort.

Boy, does that play out in his life as we will see.

So it's pretty awesome.

Actually, now he and his wife, Lori, have given a few million dollars to the school.

And it's like a amazing institution.

Now you can see Jensen gave the commencement address in 2020.

We're going to link to this in the sources.

It's pretty awesome.

So after a couple years at OBI, his parents are finally able to save up enough money to afford to come to the US themselves.

So they move first to Tacoma Washington, the great state of Washington, and then they move a little farther south down to the suburbs of Portland Oregon.

Jensen and his brother go home.

They live with them.

They go to public school there.

Jensen continues his American upbringing.

He gets really into table tennis.

He places third in the junior nationals in table tennis and he gets his picture in Sports Illustrated.

Oh, no way.

Pretty amazing.

But his parents continue their sort of like academic discipline.

And Jensen's super smart, obviously.

He ends up skipping two grades and then going to college.

He goes to in-state college.

He goes to Oregon State University, just down the road a little bit.

And he got there when he was like 16, right?

He got there when he was 16 because he had skipped a couple of grades.

And he loves math.

So he decides he's going to major in electrical engineering at OSU.

And he totally falls in love in more ways than one.

The first way that he falls in love is he just thinks electrical engineering is the coolest thing in the world.

Becomes one of the top students in the school.

He talks about how he gets mad at the professors because they don't use enough precision when talking about exact numbers.

Which he later comes to say that he respects the opposite position.

I think some of the NVIDIA employees call it CEO math, when he sort of rounds all the numbers and he's like reflecting back.

I do understand.

What the professors were trying to show is like the details only matter if you understand the big picture first.

That's so Jensen.

He understands.

Yeah, my employees get mad at me when I round the numbers and use CEO math.

I get it.

I appreciate precision too, but the big picture is what matters here.

The second way he falls in love is with his lab partner.

In electrical engineering fundamentals, his lab partner, Lori, who goes on to become his wife.

Such a cool story.

So he graduates in 1984.

She graduates in 1985.

They move down to Silicon Valley and Jensen joins AMD as a sort of equivalent of like a chip design PM.

It's very like engineering heavy, but he's kind of like a PM.

He's sort of like helping as a junior manager of a process for developing a chip.

He's working on a then blazing fast one megahertz CPU chip.

Yeah, he talks about this and he says you know he's talking about how slow one megahertz is.

And he refers to it and says you could even see it coming.

It's about how fast it was.

You could see it coming from a long way away and still coming and still coming.

Amazing.

And of course, now he makes literally the fastest chips in the entire world.

So he starts at AMD.

He starts at night working on a master's degree in electrical engineering at Stanford.

It ultimately takes him eight years to finish this master's.

He works all the time that he's at AMD and then at LSI Logic, where he goes to we're going to talk about in a sec.

He ultimately does graduate right before they start NVIDIA.

This is like a super cool bit of trivia.

Did you go back and watch the Don Valentine, uh, view from the top?

No, I didn't lecture at GSP.

Oh, I watched that like once a year, every year, every time there's an excuse.

Is that the one where he holds up, uh, Alfred's resume?

It's yeah.

He holds up Alfred Linton's resume.

So also Easter egg in that talk.

That was the day that the Jensen and Laurie Huang engineering center at Stanford was dedicated.

And as Don says, Jensen did a building, uh, Pretty awesome.

I did watch.

He gives a talk where he walks in and gives a talk at Stanford.

I think it's the first time that Jensen has given a talk since the building opened.

And he says, I've donated.

We have this nice building now, so I have no more money.

I'm penniless.

Right, right, Jensen.

So great.

Just to set context for people, if you look at his Nvidia shares, he's worth about 20 billion right now.

I think he owns what, like three and a half percent of NVIDIA, something like that.

Yeah, he's not penniless.

OK, so he works at AMD for a couple of years.

And while he's working there probably from working on this chip that you can so fast, you can really see it coming.

He realizes that designing chips is really freaking hard.

Intel can do it.

AMD can do it.

But, you know, there's not many companies.

It's all like full stack at this time.

You know, TSMC doesn't start till 1987, right?

Not only are you manufacturing in-house, but for the most part, the process of designing a chip is a manual one.

And so these companies sort of each have their own institutionalized, internal way of working that you design and lay out the elements of a chip.

And Jensen talks about, like when he was in school, the reason he wanted to go to AMD was he thought this was so cool that, like you could do it all.

And then once he's actually at AMD, he realizes like it's actually not cool.

Like it would be cooler if you could be really good at like a certain part of the stack and have tools and platforms and other companies to allow you, to allow anybody to make chips.

Yeah.

If there were, like design tools to help you make chips.

So after a couple years his office me at amd leaves and goes to join a startup called lsi logic which had just gone public and we've talked about it on the show made Don Valentine and Sequoia, the then largest venture, return in an IPO in history.

Maybe the largest venture return ever in history when they went public of $153 million on day one.

Boy, has venture changed as an asset class.

But I'm trying to think that fund that probably would have been I don't know Sequoia Fund, two or three maybe.

I mean I bet the fund was like I don't know 10, 15 million like so, probably roughly 10x the fund in one day.

Right.

Pretty awesome.

So what was LSI?

It was one of the first and was sort of the premier ASICs company.

A-S-I-C application specific integrated circuit companies.

And so what they did and what that meant was they basically made custom design chips for other companies.

It's what Jensen's kind of thinking about.

And the custom design chips that they would make these ASICs would be like for a very, very specific function that would be integrated into other systems.

So, like defense companies lockheed martin and the like but lots of other companies now too are coming to lsa, logic and the other asics companies and saying hey, we want to create these systems of chips.

You help us design the chips to go into these systems.

And yeah, we'll use processors from, you know, Intel too.

But like, it really helps democratize making end product systems.

Right.

And the idea with ASICs is really, if you're not saying hey, there's going to be a general purpose computer that this needs to power, that can, you know, be super flexible and people might have all kinds of applications that run on it but, you know, more inefficient in order to get that flexibility chip hey, I know the exact thing that this chip will do and it will only ever do this.

And so we can actually literally hard code that right on the chip.

I mean, the actual design of the physical chip can be for this one specific thing.

So it's super efficient at this one low level thing.

Yep.

And the legacy of ASICs today still around, still used by ASICs, but the legacy is FPGAs field programmable array chips that are.

You know.

Some might say is sort of a bear case for NVIDIA these days.

But we will get to that far, far, far down the road.

Sun Microsystems was one of their biggest customers.

And that was how Sun got started and made the chips for their workstations.

And in fact...

Jensen, when he shows up at LSI, Sun is like just starting and coming to LSI.

And so he gets put on the project.

He basically embeds with Sun, like in the early days, of Sun Microsystems to help them build out the chips for what would ultimately become the Spark Station 1, Sun's first big workstation product.

Over the next few years, he pretty much exclusively works with Sun while he's at LSI Logic.

He works directly with Andy Bechtelstein, the founder of Sun, and with Vinod Khosla.

He becomes super well-known and develops quite a reputation there as somebody who can really take these visions for chips and these customer requirements from Sun and turn it into reality and production.

So...

One day, right around Thanksgiving 1992, Jensen has finally, after eight years, finished his master's degree at Stanford.

And Stanford is quite, quite glad that he finished before this happens.

Two of Jensen's buddies who he's become close with at Sun, Chris Malachowski and Curtis Prem who, in Jensen's own words, he describes them as really, really fantastic engineers.

And when Jensen says that, he means it.

They come to Jensen and they're like, we're not like super happy at Sun, the two of us.

We have an idea that we want to talk to you about.

And Jensen's like, well, sure.

Let's go meet at my favorite spot, Denny's.

Really?

Yeah.

Like the man loves Denny's.

He worked at Denny's in high school.

Like he's always going to Denny's.

He orders the Superbird, I think is like his go-to dish.

Nice.

He's so folksy.

I love him.

So they go all have dinner at Denny's and Chris and Curtis pitch him on their idea.

Which their idea is, it's pretty good.

It's pretty good.

Tell me as a venture capitalist if you would fund this idea back then in late 1992.

So they see...

3D graphics are really becoming a thing.

And, you know, remember, this is the era of Sun, Alice in Logic, all this stuff.

It's also the era of Silicon Graphics right down the street, right there in Silicon Valley SGI so many great things that come out of there.

You know, Jim Clark, Netscape, like all this great stuff.

Jurassic Park.

Jurassic Park is about to come out.

It comes out in 1993.

So there's this huge demand for 3D graphics.

The way 3D graphics are done, you need SGI workstations.

You need like super custom, you know, very high end, very expensive stuff.

Only something with the budget of like either the military or like a Jurassic Park can afford to do this.

But people love it.

Like the consumers love 3D graphics.

Not to mention, where are we in the evolution of video game consoles at this point?

Well, we're still in the Super Nintendo days, so we're not at 3D console graphics yet.

That's coming very shortly.

But what is happening is the PC wave is like really cresting right now.

Like we're like a year and a half from Windows 95 coming out.

Mm hmm.

And I remember doing this.

I bet you do, too.

Or kids in 1992, 1993 doing on their PCs.

They're playing.

Wolfenstein 3D and Doom.

Doom comes out in 1993.

These are taking the world by storm and they're made by id software in Texas and John Carmack and John Romero.

But Carmack is like doing incredible feats of engineering to get 3D graphics to run on consumer PCs.

It took somebody of Carmack's caliber to make this happen.

And the market loved it.

So the idea that Chris and Curtis has, they're like, we're really great chip engineers.

Jensen, you're a really great chip PM, essentially.

Let's make a graphics card.

Let's make a chip that can accelerate the graphics of a normal PC to enable 3D graphics, like SGI is doing with professional workstations to enable them for consumer hardware, PCs.

We know that people love games.

This will help the entire industry, you know, take off.

And you're not even saying sounds pretty good, right?

That they're going to try and make it so you can develop games on a PC.

You're saying like just so you can play games on a PC, right?

Well, both.

I mean mostly that you can play games on the PC.

But then you're also going to have to create, you know, all the APIs and SDKs and developer ecosystem for developers to access this new hardware on PCs.

But they'll just develop on PCs.

It's really about getting the like the hardware, into consumers hands that they can actually play this stuff.

All right.

So what do you think?

Is this like a good pitch?

I mean.

So what you're basically asking me to believe 1992 me is that video games on PCs are going to be a thing, that there's going to be a big economic wave around that lots of consumers are going to want to do this.

They're going to want to do it on PCs instead of on Super Nintendo and dedicated systems.

Maybe.

Well, I have this proof point of id Software and Wolfenstein and Doom right there.

I have millions of people doing this.

But still maybe because it's not clear that like video games are going to be a giant market.

It could be like a kid market, you know, and it could be the case that like, do you really need to totally change the development environment?

Or can like there be like five or six different dooms out there?

There's five or six CarMax who are all independently geniuses and can figure out how to do all the graphics on their own.

Yeah, maybe.

But there's a leap of faith.

Yeah, definitely a leap of faith.

So OK, not totally obvious, but still I think this was pretty fundable, I think, at this moment in time.

And the other thing that was going on was in Silicon Valley.

These peripheral companies like people building chips and cards that plug into consumers PCs.

This was full swing.

There are companies making sound cards.

There are companies making networking cards.

There are companies making serial port cards like God knows what.

Okay.

So there's already like sort of an accelerated computing wave here where people are saying, like there's some reason to do something specialized off the CPU that needs its own integrated circuit that vendors are making custom and there's a market to make custom stuff as a vendor for PCs that takes a workload off the CPU.

Yeah, and so the pitch is we're going to make a custom graphics card, take a graphics workload off the CPU, specifically for gaming.

Great.

Okay.

So yeah, it was pretty much a brain dead.

Yes.

But, as you alluded to at the top of the show, the problem when something is a brain dead yes, for venture capitalists is is that it's a brain dead?

Yes, for lots of venture capitalists, and lots and lots and lots of companies get funded to do this.

But back to Denny's that night, NVIDIA is the first.

They are the first dedicated graphics card company.

They all decide the three of them that they're going to go in on this.

Jensen goes to the CEO of LSI Logic, walks into his office, and tells him that he's going to resign.

He's going to go start this company with two engineers from Sun, and this is what the business plan is going to be.

Now, do you know who the CEO of LSI Logic was?

No.

It was a man named Wilf Corrigan, who was previously... the CEO of Fairchild Semiconductor.

No way!

Damn right.

So is that how, Don?

Because Don Valentine obviously was the biggest investor in, or Sequoia was in LSI Logic.

And did he know him from Fairchild?

Yeah, they were colleagues back in the day.

Okay.

And then the biggest exit in Sequoia's history to that point in time.

So Wilf says, so let me get this straight.

And he says to Jensen, you're going to go build these graphics cards.

And kind of just like you were saying there, Ben, who's going to use these and what for?

It's like, well, you know, you're going to be in PCs.

They're for gaming.

They're for a bunch of kids.

And Wilf hones in on the critical question.

He's like well, who makes PC graphics games?

Is there a developer ecosystem for this?

So that's kind of like we think if we build it like, they'll come.

So wolf says uh, remember he was a fair child.

He said i was like he knows when to make silicon for specific applications.

And uh, wolf says, all right, you'll be back, i'm gonna hold your desk, but in the meantime, before you go, i'm gonna call up don.

I'm gonna do you've done good work for me.

I want to call up Don.

He calls up Don and he's like, Don, I got a kid.

He's going to come see you.

Stand by.

Which this is a lesson for all founders and aspiring founders out there.

Getting a reference from the CEO of a portfolio company is a really good way to come in with a venture capitalist already leaning toward investing, especially if you're referred by the top performing company of all time in their portfolio.

Yes.

It's kind of hard for Jensen to mess up this pitch with the recommendation that he's coming in with.

It's literally impossible because he goes to see Don.

You know, Don sits down and he's like, So and Jensen completely botches the pitch.

He gets like really nervous.

At this point I think he had like a partially written business plan that he had like bought a book on like how to start a business and was like three chapters into the book but decided not to finish and started writing the plan.

It didn't finish the plan.

So he comes into this meeting and just kind of like barfs all over Don.

Yes, exactly.

So Jensen's walking out the door.

He's like, you know, totally dejected.

Don stops him and says, well, that wasn't very good.

But Wilf says to give you money.

So against my best judgment, based on what you just told me, I'm going to give you money.

But if you lose my money, I'll kill you.

Classic.

Classic Don line.

So good.

So the deal happens.

Sutter Hill comes in, too.

Because, you know, again, this is all dramatizing.

At the end of the day, this is a hot deal.

This is a...

Two episodes in a row for us with Sutter Hill.

I know.

Oh, geez, they're so good.

But it was a hot deal.

They wanted it.

And this fits central casting of at this point in time.

They invested like a million each.

Is that right?

For a total of two.

So two million dollar total round.

I don't know who invested what.

I assume a million each, but two million dollar total, round at a six million dollar post money valuation.

Yeah.

Remember, everybody, this is the eighth most valuable company in the world right now.

Started at a $6 million post-money valuation.

So they're getting things ironed out.

And there's just one problem.

They don't have a name for the company yet.

Jensen and Chris and Curtis.

They've just been, you know, working on this, working on the business plan, but they don't have a name.

They need to incorporate the company.

And they were saving the files that they were working on for the chip design for the first graphics chip as nv nv being short for next version.

And so like, oh, we kind of like that.

You know, we're always working on the next version here.

They start looking around in the dictionary for words that have envy in them.

It's probably a very short list.

And they find the Latin word invidia, I-N-V-I-D-I-A, which means envy.

And they're like, great, we'll be the envy of the industry.

Invidia, we'll drop the I at the beginning.

So we start with envy.

This is awesome.

Of course, they pick green.

So later on, they can have that marketing campaign of green with envy.

Careful what you wish for here though because again, as we've been saying, literally 89 other companies get funded within a couple months to go do the same thing.

It's a very clever name.

Also the notion of like vid being in there, that it's sort of video and that that's another thing that they want to do.

Like, it's the classic Rich Barton empty vessel name.

You know, there's enough things that it could mean, and we're gonna fill it with meaning.

Because they're doing a thing here that, like well, 89 other people are also sort of simultaneously doing.

It is kind of a new frontier that they need to invent and then own like thought leadership in that area.

And they do need to, kind of like, quickly build a brand not only with consumers but with PC manufacturers.

Jensen, the way he sort of describes it is that their vision, although he doesn't like the word vision because he thinks it's exclusionary to people.

So he said our perspective is that they want to enable graphics to be a new medium to tell stories.

And here's sort of the way that he articulates at the time why video games today are 180 billion a year.

Industry bigger than Hollywood, bigger than music.

It's the biggest entertainment medium.

But at the time, he sort of has this thesis that you really can't, through computer graphics, tell stories today.

But if you could, it's really interesting because it's not pre-recorded so it can be sort of new and different every single time.

You enjoy it.

It's also the only medium of entertainment that can be networked, and so therefore, it's the only one that can really be like social and interactive.

And so our reason for being is to create...

3D graphics as a form of artistic storytelling for the future, and everything will be in service of that.

And I think that's not really what they are today, necessarily.

It's a piece of what they are today, but that kept them going for the first 20 years of their existence.

Well, and baked into that is again you know Wolf, kind of like hit on it and you did too.

To your credit, you're a very good venture capitalist.

You hit on really the key problem with this first iteration of NVIDIA, which is they have to go evangelize to developers to like yeah, there's it and there's Carmack out there, but like, not a whole lot of other pc game developers out there, not a whole lot of other 3d pc game developers at this time there are 2d pc game developers but they got to convince a whole lot of people to go, you know, learn how to do 3d game development for pcs and that's like oh, we're going to enable storytelling all them.

So to do that, they have to go write their own you know apis and sdk and development framework to develop for this new graphics chip that they come out and they have to make a whole bunch of like technical design decisions that they want the industry to standardize on.

Right.

This is a case study of what happens when you get more clever than the rest of the industry.

Exactly.

So at first, things start off really well.

Remember, this is super hot.

They're the first company.

They're.

They land a big deal with Sega to power their arcade consoles and their next generation home console to be the 3D graphics engine.

It would ultimately become the Sega Saturn.

And as we know from our Sony episode... Not quite the Sega Genesis.

Not quite the Sega Genesis.

Well, so the problem is, so NVIDIA and Sega, they're working together.

They make a bunch of these design decisions, the biggest of which is they decide that the way they're going to create People probably know.

You create 3D graphics, you use polygons.

That's why people are always talking about polygons in this industry.

They have to decide on a sort of primitive for the polygon.

They're like oh well, we'll use quadrilaterals for vertex, you know, and anybody who knows anything about video game development.

Now it's like that's not how it's done.

I'm pretty sure people talk about triangles.

Yeah, and i'm pretty sure if you look at nvidia's amazing headquarters building today it's, you know, made out of triangles in a homage to game developers, not quadrilaterals.

So this becomes a pretty big problem.

You know, things go along for a while.

It's like fine for about a year.

NVIDIA's leading.

They got this big Sega deal.

There's not a reason to need standards yet, right?

The industry isn't complex enough yet to necessitate a whole bunch of collaboration and set of tools that everyone standardizes on using.

You're like okay well, we're just going to put this chip in our game console.

Ship the game console.

We're the only people that, you know, make an SDK, we being Sega.

So everyone will have to kind of standardize on this thing anyway.

So great.

But obviously the ecosystem gets much more complex, much more quickly and it sure would be nice to have some kind of compatibility.

Well, here's what happens.

So you know, Curtis and Chris and Jensen, they weren't the only people in Silicon Valley that saw that kids want to play games on PCs with Doom.

Microsoft is like, oh, that's interesting.

We like selling PCs.

And gosh, there are all these graphics cards companies out there now that are doing this.

And, you know, what do we do as Microsoft?

We really want to encourage this in the ecosystem.

Well, we create standards.

We would love it if Windows developers could be able to easily develop for all these new machines shipping with all these advanced graphics capabilities.

Let's make that as easy as possible for those developers.

Yeah, you know, developers want to do 3D graphics directly into Windows without any of this.

You know crufty middleware from some no-name company Nvidia, out there.

Why don't we just bake these APIs right into Windows directly for 3D graphics?

We'll call it Direct 3D.

And of course, anybody who knows about the history of this, that becomes DirectX.

And DirectX made some pretty different design decisions than Nvidia had made.

Is that right?

Yeah.

So they use triangles because triangles make sense.

So now Nvidia's really up a creek like all of their come.

You know the 89 other competitors out there that started later.

Most of them are like sure i'm gonna jump on board of this microsoft ecosystem, like i would be dumb not to.

It's standardized on this completely different paradigm than nvidia.

And then sega, you know, they've got sega, they've got this one sort of customer and then in 1996 sega's like Yeah.

We're not so sure about this quadrilaterals thing either.

And just so that like this doesn't feel arbitrary, why we're talking about this and we're gonna say, at a super high level on 3D graphics here, rather than really going into the weeds.

A triangle is the fewest vertices in a shape that you can have while still creating a two-dimensional shape.

And so it serves as a basic building block where, assuming you can draw enough triangles and make the triangles small enough, you can form any other shape, any other curved surface.

It's sort of the most fundamental building block that you could use to create something that is perceived as 3D.

Yep.

So NVIDIA?

At this point they're halfway down the road of developing the next chip that they think Sega is going to adopt for what ultimately would become the Dreamcast.

Nvidia was calling the nv2.

When sega comes back and says we're switching horses, we're not gonna do this.

So, like they're screwed for so many reasons, everything we've discussed there's also in the interim.

You know, year and a half since nvidia started, the price of memory dropped because Thank you, Moore's Law.

So NVIDIA's chips were designed to be like super, super tight on memory.

And the memory cost about $200 in component parts to go into their chips.

Their competitors have more memory that's costing them like $50.

And that was just in that one iteration.

So it's interesting to note that NVIDIA, by being first and not projecting out the exponential change that would come from Moore's Law, was actually at a disadvantage.

Because A, they didn't get a chance to watch and see where the standards were adopted.

And so they, sort of like, picked their own lane and went off in their own direction, which ended up not being what everyone else picked, which put them at a disadvantage.

But second of all, everyone else's cost structure was way lower, or at least everyone else could see that the cost structure was getting way lower.

And so NVIDIA sort of designed for a constraint.

That was no longer true by the time everyone else came out with their stuff.

At this point Jensen and his co-founders kind of had to look at each other and say okay, do we scrap everything we did?

And if so, how do we not make this mistake again?

How do we make sure that in future generations we sort of premeditate the exponential curve of Moore's law and prices coming down and design for things that are, you know two three, four generations beyond what we actually have available to hardware right now?

So when all this goes down, the company has about nine months of runway left.

And like, Literally anybody else, you pull the plug.

It's over.

Everything in the deck is stacked against you. you're effed.

And I can't imagine sitting there dreaming up a way out of this.

But Jensen, God, he's such a G. He's like, no, we're not going out like this.

You know, when you hear Jensen talk today about like NVIDIA's culture and he says that intellectual honesty is like the cornerstone of NVIDIA's culture, like this is what he's freaking, talking about.

Like He sits down with Curtis and Chris and remember they're engineers and they've recruited NVIDIA 100-plus engineers into the company at this point and sold them on this technological vision of we're going to define the industry.

We set the standards.

We're not going to use some off-the-shelf stuff.

And like, it's all toast.

And so Jensen's like, guys, like this is a pipe dream.

We need to throw it all out.

If we're going to survive, the only thing we can do is standardize on on the same Microsoft.

You know, direct 3d as everyone else same architecture.

And our only shot is just to like compete on performance and try and become like the best uh chip out there in this now sea of commodity chips.

And his co-founders like don't want to do this.

This is not an exciting vision for a Silicon Valley engineer.

When your CEO comes to you and says that what they're basically saying is look, if my job was strategy and your job is execution, the strategy failed.

And so we just now need to literally out-engineer all of our competitors.

We need to be smarter at engineering decisions so we can be more performant at a lower price point, using less energy, than our competitors.

Because Microsoft, being Microsoft, had all the developer attention.

And because Microsoft set a standard, NVIDIA realized look, we have no ability to uniquely get our own developers, at least at that point in the company's history.

And so we must just, on our left, look and see all the developers are coming from Microsoft, using this API.

On our right is all the same consumers.

And we have to compete just head-to-head on raw engineering ability with everyone else.

Well, you're saying engineering ability.

But remember, this is essentially a commodity at this point.

So Really, it's not just engineering ability.

It's how fast can you ship?

Like how fast can you design the next generation of chip?

And can you ship it before everybody else?

Because everybody knows what's going to be in that ship.

And why is it what fundamentally about was it about graphics cards that made it a commodity?

Well, at this point, like all the other peripherals and we're going to get into this in a sec there was nothing that special about it.

They all did the same thing, which was take polygon-level 3D graphics processing out of the CPU and onto this other chip on the motherboard, just like sound cards were doing the same thing for sound, just like networking cards were doing the same thing for networking.

And it was just like, what's the price performance ratio of doing that?

The interfaces and the programming language, that's all standardized by Microsoft.

You're just commodity hardware.

And so what GPUs actually do, or did at least in this point in time, is say OK let's, The system is going to feed me in, basically point clouds like vertexes that make polygons that represent like a 3D world.

And my job as the GPU is to as fast as I can in the highest resolution that I can, or I suppose, a standard predetermined resolution.

As fast as I can.

That'll drive the resolution.

Output a 2D thing that goes on the screen.

So I turn 3D stuff into 2D stuff and I have to do that better than other things that I'm competing against, where basically all of us are.

When you say commodity, you mean limited by Moore's law and doing right up to the edge of what integrated circuit manufacturing techniques enable us to do.

Yep.

So everybody knows what this means is that they got to ship faster than their competitors.

They also got to ship faster than their competitors because they're about to go bankrupt.

So they drop this plan that's like they're trying to thread like the tightest needle possible here.

They have to lay off 70 percent of the company, which they do.

They go down to about 35 people.

And everybody who's staying knows.

We now have to design from scratch and ship a new chip before our runway runs out, which is nine months.

You can't do that on a normal chip design cycle.

Takes like two years, right?

Yeah, the way that you know with these Fabless chip companies, the way they would design chips is they would work on the design, they would send them over to the Fabless company.

The Fabless company would produce some prototypes, they'd send them back, they'd test them.

They'd go back and forth a few times.

You mean the foundry would produce them?

Like the TSMC or the Samsung or the global foundries or... Now, importantly...

Nvidia is not using TSMC at this point because they can't.

They can't.

TSMC only works with the best and Nvidia is not the best.

So they're using like second rate foundries.

And that process takes a long time.

And then at the end of it, when you're sure you've got the design right, then you do what's called a tape out of the chip.

I love this term, by the way.

It harkens back to literally like when you used to tape you know masks.

To like do the photolithography on the chip back in the day.

So cool.

But it just means finalizing the design.

But you actually do run it on some prototypes first, like the foundry sends back some, you know.

Hey, thanks for the designs.

Here's the chip, you know, run your tests on it, make sure everything does what you think it does.

And, you know, that process takes two years to get a full sort of iteration on.

Yep.

So they're like, we can't do this.

Like, Jensen's here.

Like, here's what we're going to do.

I've heard about.

There's a new technology, some new machines out there that enable emulation of chips.

And, in our case, we're going to use it to emulate the graphics chip that we're designing, all in software.

And, you know, it works.

They're startups, but they exist.

The problem is when you emulate it in software, you know, it's like it's really slow.

So when you play a game and you're looking at your computer or monitor or whatever, it's refreshing 30 to 60 times a second.

If you're a professional gamer you probably have a go on it like 120 times a second.

You know frames per second.

This emulator runs at one frame every 30 seconds.

So they're going to have to debug this thing in software to save this time, going at one frame every 30 seconds.

It's just insane.

That's brutal.

They're basically making this trade-off of okay, if we want to ship something in nine months, we don't have time to actually have it execute on the hardware.

So we're going to make the trade-off of our testing being mind-numbing, like running whatever our graphics tests are where we're looking for this certain specified output.

We need to plant someone in front of a screen to watch the new frame render once every 30 seconds and look against some tests to verify that the output is correct.

And if it is, and this person does that mind-numbing work and sits there just observing, and observing, and observing, then we will go right to manufacturing without ever producing a physical prototype and ship that.

And that is exactly what they do.

They had to spend a million dollars just to get the emulator.

You know hardware and software to do this.

Which I think they had generated some revenue, but it was still like a third of the cash that they had in the entire bank account.

So they go down to six months until their cash out in the company.

They get it done in a few months, and then they call up their foundry.

I don't know if they're using United or one of the other foundries in Taiwan, not TSMC.

They're like, all right, we taped this thing out.

Send it to production.

And the foundry's like, are you guys sure about that?

They're like, yep, we're sure.

Make 100,000 units.

If I'm remembering right, I think NVIDIA basically was the only customer of that emulation software.

Like that was a startup that really wasn't fully proven yet.

But NVIDIA was like, look, we literally have no options.

Yeah, they were the only customer.

And then that company went out of business after.

It's wild.

And so the chip they designed.

So now the advantage, like this is lunacy what they're doing.

Obviously, they have to do it because their back is against the wall.

The advantage of this though, is they are now designing this chip with, you know, the same set of assumptions about what technology is available as all their competitors.

But their competitors are working on those designs.

They're not going to be able to get them out for like 18 to 24 months.

Nvidia is going to get this same you know generation of design out in six months.

So this chip is called the riva 128.

That's what they call it.

It is a freaking beast and it is like a beast in every sense of the word.

It's big.

It's extremely powerful relative to anything else on the market, More powerful than any customers are telling them they want.

Yeah, way more powerful.

Way, way, way, way, way more powerful.

But it comes with some downsides.

With great power comes great responsibility.

Because they built this thing in such a manner, it barely works.

There's a lot of stuff wrong with it.

I forget the exact number of this, but like essentially, direct 3d at the time had something like let's call it like 24, 25 different ways, like different sort of techniques.

These are the like blend modes yeah, i think that's what it was blend modes and the reba only works with about two-thirds like one-third of it, just like freaking crashes, like it just doesn't work.

I thought even worse than that, but basically, like i think NVIDIA had to launch a campaign going around to all the different developers and being like come on, what do you really need more than these eight for?

Come on, what are you really going to do where you need to use that fancy stuff?

Do us a favor for this generation of the chip.

These eight work great.

You're going to love them.

They're so good.

And just use those.

Okay, so this is so, so, so great because... people do it.

And so what they learn from this, like they learn about the market.

You know the first iteration of Nvidia.

We're going to build all this technology.

We're going to drive the market.

They didn't know anything about the market.

They were just making all these assumptions about what people wanted, but now they're actually going out and Jensen's going to these developers trying to convince them to do this.

And they all do it.

Why do they do it?

Because the only thing that matters is performance.

Consumers are going to buy hardware and games based on the quality of the graphics.

This is like being discovered for the first time.

And so like people are willing to make a lot of compromises in, you know, service of performance.

Nvidia is like the first one that figured this out, because they have to go around and do this and developers all get on board.

And to be clear, it's because the consumer is making the buying decision, right?

On what graphics card they buy.

It's a completely interrelated system where the consumer is making all of the decisions.

That's where the demand is.

The consumer is deciding what hardware to buy.

That's what NVIDIA's business is.

Whether they're buying it as a fully built computer from the OEM or whether they're buying the card to put in later themselves.

They're making a decision on what graphics card goes in the computer.

Exactly.

And the game developers are making decisions on what graphics cards to support right, right and how to build their games with, like the assumption of what's my target market of consumers like who do, i think, will this game run on?

Do you need to have at least an x level performance rig in order to run my game, or run my game in its fullest form?

So the developers are premeditating what graphics cards are going to be out in the market when their games launch.

And they're saying, yes, it's going to be the most performant one at the right price point.

So whatever the mass market is, we kind of have to target that.

And if you're telling us and we're going to test it and it turns out that yours is the best performance per price or performance per watt or whatever, it's the most efficient card, then people are going to buy that one, and so we must target it.

That card, and they're going to buy my game.

I mean, I remember, like, this is a few years later.

This is a trope that happened.

There was a game called Crysis.

C-R-Y-S-I-S, remember this?

Oh, yeah.

What's the relationship between Crysis and Far Cry?

It was, oh no, Far Cry was the first game.

Yeah, the Crysis engine and then Crysis also.

It was super convoluted.

Basically, my perception of this thing was when this came out, when Far Cry came out, this was like mid-2000s, the graphics were unbelievable.

Unbelievable.

And if you had a rig powerful enough to run it, like just unbelievable.

The game itself was terrible.

Total crap.

Like, I don't think I ever played more than 10 minutes of it.

I'm pretty sure if your computer didn't support it, there was all these videos that people would record of like building a tower of like a thousand gasoline barrels and then shooting it.

And because it was too complex for their graphics card to handle, their computer would just freeze.

That was the failure mode of Far Cry with non-performance chips.

This is how the hardcore gaming industry evolves.

Like Far Cry, sold so much software and so much hardware just because people wanted to experience that, to attempt to experience that level of graphics.

And so that's what the developers are starting to figure out.

They're like, all right, well.

If you can ship this thing, we'll use only those.

You know, eight blend modes or whatever, like whatever it takes, because we want, you know, graphical performance is the most important thing.

So it works.

They sell one million units of the Riva 128 within four months.

Wow.

I should have looked what the MSRP was of it, but that is a lot of revenue.

Yeah, no kidding.

What year was this?

This was 1997.

Okay, so we're... It's an interesting era.

Like, the internet is a thing.

We still have a few more years till the dot-com bubble crashes.

PlayStation 1 is out, but PS2 is not out yet, I think.

Yep, PlayStation 1.

And with that the gaming market kind of bifurcated into sort of the know the console market, which was standardized and you knew it was all going to work, and then the hardcore pc gaming market, which just had so much revenue potential, even though it was smaller in terms of numbers, because people are willing to spend so much money on this stuff.

So at the end of this, nvidia has now figured out these dynamics of the pc gaming market And they now have a process within the company to design and ship each next generation of their hardware in a six-month timeline, while the rest of the industry is on an 18 to 24-month timeline.

Necessity is the mother of invention.

To say this is huge is like understatement of the century.

Huge.

And it's huge for this market.

But nobody even saw this at the time.

Like Jensen didn't see this.

Nobody saw this.

They're now shipping relatively, you know, doubling essentially the performance in each generation with their hardware.

And they're shipping it every six months.

And you think about Moore's law, right?

Like Moore's law, was that the number of transistors on a chip equating to the compute power available at a given price point to the market would double every 18 to 24 months.

NVIDIA is now on a cycle, starting in 1997 1998, where they are doubling the performance that they are delivering at a given price point to the market every six months.

It's fascinating.

And they're also competing on a different vector than the CPU manufacturers because...

And it's kind of amazing we've made it an hour into the episode and haven't talked about this yet.

But the magic of GPUs is that they're very, very parallel.

Like CPUs.

For anyone who's taken a low-level computing class, you sort of know that, like every time the clock ticks, an instruction can sort of run and things move through the sort of long chain of operations that can happen within the CPU.

And it's advancing things serially through the processor.

It's serial processing.

It can read from a register or it can add two things together.

But like it's all happening serially.

It's like the I Love Lucy, you know famous one where, like the chocolates are coming down the factory pipeline and you had, the CPU has to like wrap each individual chocolate one, and then the next one.

Yes, exactly.

And with graphics processing, like...

The magic of it is that it's super parallelizable.

Like there's all these things that need to get outputted to the screen, that do not depend on each other.

And so you can do them independently.

And so the vector that they're competing on is really like oh, we can, and it would be years before they would really get to this but add more and more cores or find more ways to execute more instructions simultaneously, to parallelize these tasks.

And I think at the time people thought really the only big use case for parallelization is graphics.

Let's put a pin in that for now, but it's worth knowing.

The thing that they're doing is figuring out how to process more things in parallel faster.

Yes.

So graphics cards like NVIDIA is making at this point in time are really good at in parallel lighting the pixels on a screen, you know 30 60, 120 times a second, with the images that are being fed to them from, like the game or the graphics program which is living all in the CPU land.

So, like you're a game developer, you develop in Microsoft.

Direct3D becomes DirectX or OpenGL is the open source competitor to this.

All that logic is really happening in the CPU realm.

They're all kind of the same.

They're all the same, right?

All the lighting, like the lighting, it's all like pre-done.

So like when you're a game developer, you set the scene.

You'd never see like a character running around carrying a torch, and that torch light like impacting the rest of the environment.

It's all set in advance.

Like no intelligence is happening in the GPU level with the screen.

It's just lighting up the pixels.

Basically in order to make it easy for developers.

The software development kit is written at such a high level that you don't really get enough control to make your game stylistically different.

You just get to lay out the items on screen.

It's all the same.

It's all flat.

Maybe you can program that like hard code, that like oh, time of day might change, and like that might change the way things look, but you're hard coding like what they look like no computation is happening, right?

If you're playing a game today, even the most basic, you know, mobile game or whatever you're seeing dynamic lighting and shading, which we'll get into in a sec all over the place.

So this is still like in the.

You know GPUs are like a really, really important sort of commodity, but they're a commodity.

There's not a lot of smarts happening here.

No programming, but NVIDIA has figured this out.

They can now ship on a six month time cycle. they're starting to like really take huge market share.

Now, a lot of people start paying attention to them in a good way.

TSMC that wouldn't even return Jensen's calls back in the day.

There's this amazing, amazing story.

Did you watch the TSMC 30th anniversary?

I did.

Celebration.

This is so good.

It's like three hours on YouTube.

This is worth a brief aside.

This is how much pull Morris Chang from TSMC has.

He gets the CEOs on stage of NVIDIA, ARM.

ARM, ASML, Qualcomm, and Broadcom?

Yep.

I don't think Lisa from AMD was there.

No, it's basically everyone but AMD of the sort of pillars of the TSMC ecosystem.

I mean, Morris is playing interviewer.

Like, it's very entertaining to watch him.

It's like a celebration of Morris and of TSMC.

It's amazing.

Yes.

So in the section with Jensen they tell the story of how NVIDIA, at this point it's got to be TSMC's biggest customer.

I mean, they've been like tied at the hip forever of how this all came to be.

After the Riva 128 hits and has become a big success.

Jensen writes a letter to Morris like a physical letter.

Addresses it to Morris Chang in Taiwan.

Because he can't get in touch through any of the like salespeople.

Exactly, exactly.

They've all just been ignoring him as well they should, because they were a left for dead startup in a sea of startups.

The letter gets to Morris.

He opens it.

He reads it in Taiwan.

He does the most Morris Chang thing possible.

He calls up jensen on the phone right there and the phone rings.

As they tell the story in the nvidia office, this is in the middle of their trying like mad scramble as a startup to ship these riva 128s that are coming in.

They're testing them all by hand in the office because none of this stuff was.

It's fresh off the line, it's not been tested.

It's chaos.

Jensen picked up the phone, is like yeah, who's this?

Morris is like hello, this is morris chang at tsmc.

I got your letter And Morris says that there's like a silence on the other end for a couple seconds.

And then he hears Jensen yelling, everybody shut up.

Morris Chang is on the phone.

Amazing.

And that's how TSMC became the manufacturer of NVIDIA chips.

Yep, the next year, the two companies sign a huge multi-year deal for TSMC to become the primary foundry for NVIDIA and still are today.

Jensen and Morris are super close.

It's a landmark, landmark deal for both companies.

So, with now an actually really good foundry as their partner, and this super unique chip development process and video just keeps accelerating.

So in 1999 they rebrand their products.

You know they'd use the envy one first and then this Riva one 28.

They actually run a little contest of what they should name the products.

And the winning name is geometry force.

Forces with you, which they shortened to G force, which anybody who knows who you know buys graphics cards.

The Nvidia G force, still the brand name they use for their gaming cards today.

And is probably the most, one of the most respected, you know, brands in the gaming ecosystem.

And it's because this card that they ship, the first GeForce in 1999, it's the GeForce 256.

It's so powerful.

It has 5x better graphics performance than like anything else on the market.

And they call this like the first GPU, right?

Don't they say like we're inventing the GPU?

They call it a GPU.

Before this, the term GPU didn't exist.

It was these were graphics cards, graphics chips.

I think Sony had like sort of used it about the PlayStation, but no one's marketing this idea.

So they market this as the graphical processing unit.

Now, on the one hand, that's sort of like marketing bravado.

On the other hand, that is a very loaded statement to make.

And why so?

What does Jensen and NVIDIA mean by this?

So intel, you know, you think chips, you think intel.

Right, you think silicon, you think intel.

Intel's whole strategy at this point in time was basically, they're almost like a biotech company today, like one of the big pharma companies and uh or or, put another way, it was another version of the microsoft embrace extend, extinguish thing.

They would see.

They're all these peripherals, sound cards, networking cards, all the graphics cards, all the stuff we've talked about.

They would let all these flowers bloom.

Be like, oh, yeah, yeah, yeah.

Just plug into the PCI slots on our motherboards.

No big deal.

We're an open ecosystem.

We want everybody to flourish.

And then they would see which of these, you know, peripherals got consumer traction.

And then they would just turn them into, you know, a component in the motherboard.

And thus began the wave of being able to buy a PC with an Intel motherboard and integrated graphics.

Well, and before that, you know, integrated sound, integrated networking.

Like, remember, oh, it was so fun doing this research.

Remember the company Creative and the Sound Blaster cards?

Oh, yeah.

I remember buying tons of that stuff.

And then at a certain point, you stopped buying Sound Blaster cards, right?

You're like, oh, the motherboard does 90% of what I need it to do.

And why would I spend extra money on a separate thing?

Exactly.

And so Intel, they just sit back and watch all this happening.

They'd integrate it.

Game over for the startups.

And there was reasons for specialized stuff.

I remember buying a special network card because the integrated networking capability of the motherboard on my I don't know what it was, a Mac 8500 or something wasn't as fast as if you bought a dedicated PCI card.

That could be a faster networking card.

And graphics cards would sort of become that same thing where the integrated graphics for most people was good enough, unless you were a gamer, in which case you'd go buy your own graphics card or you'd buy it directly from the OEM when they were making the computer and shipping it to you.

But wait a generation or two.

Even if you have the most demanding performance for home networking, you're not buying a separate networking card.

Like, get out of here.

These things are like dead-end businesses.

And there's no reason why graphics cards wouldn't be the same.

So Jensen and Intel coming out and being like, we're a graphical processing unit.

We're a GPU.

It's a big middle finger to Intel and this whole CPU dominant world.

And it really wasn't true yet.

It wasn't a processing unit, in the same way that a CPU is a processing unit.

Where it was, people could write software for it in a way that created a meaningfully different experience for people using the software.

Yep.

But this is where Jensen is just such a master strategist and NVIDIA was so great.

Like this whole kind of orchestration of a bunch of things all hit over the next couple of years.

So first Nvidia goes public, you know, they've now shipped the Revo 128 was a huge hit.

This new GeForce 256 flying off the shelves.

They go public in beginning of 1999 at a $600 million market cap.

So a hundred X return from the 6 million post money valuation on the Sequoia and Sutter Hill round.

That gets them, you know, some more capital.

And And then behind the scenes, they're working, they're in talks with Microsoft.

Microsoft's got a secret project that they're working on at this time the Xbox, which we talked about a lot on the Sony episode and so many times on the show.

And Microsoft comes to NVIDIA.

And like, we want you to be a key supplier of the graphics, the GPU for the Xbox.

And they do a huge, huge deal 500 million a year deal for NVIDIA to supply the graphics for the Xbox with a 200 million advance.

And the chip that they use is a modified version of this chip.

Incredible new chip that NVIDIA is working on.

I sound like Steve Jobs here.

Jetson sounds like Steve Jobs talking about this.

The GeForce 3, which introduces for the first time programmable shaders and lighting. on the GPU.

Everything we just talked about though, like the GPU massively parallel can light all these pixels, but it's essentially just taken instructions that are pre, you know hard-coded, baked in on what the lighting's gonna look like.

Now you can program for these GPUs and you can make dynamic lighting in games and 3D graphics.

That is calculated.

This is game changing.

The way to think about it is those GPUs in quotes were fixed function graphics accelerators.

So they would be able to map textures onto a set of polygons, but you couldn't do the thing that you're talking about, David custom lighting a lot of that sort of stuff to actually program at the GPU level what is happening.

And so this is like, of course it's cool because it's a wave of new consumer experiences.

That can happen because every game developer can, kind of stylistically, put their own stamp on games.

But it's a totally different metaphor for the computer architecture, where suddenly you can program a GPU.

And I guess that's why they're calling it a GPU.

And this is different than a graphics card.

And NVIDIA develops in conjunction with this.

They call it C G literally, like they extend the C programming language with graphics libraries and capabilities to directly program graphics and lighting and shaders for the GPU.

So this makes, you know, that sort of like marketing, you know, Oh, this G force two 56, it's a GPU.

Now it's real.

Like this is a graphical processing unit that is intelligent.

That is uh, Every bit is, you know, maybe not every bit as important as the CPU yet, but like this is like the stake in the ground of like this is no sound card.

This is not going to get commoditized.

Do you know if this was the GeForce FX or if the GeForce FX was a similar version of this that was available to PC?

That's a good question.

It was the GeForce 3 was the PC version of this.

Okay, this move to programmable shaders was a bet the company move.

And it was Jensen's answer to how do we get out of this commodity business and do something unique and different?

And I'm pretty sure they were like months away from cash out again by pulling this move because of how aggressively they had to staff this like very new type of product they were inventing.

Yeah.

I mean, this is the you know back to that original sort of quixotic vision for the company of we're going to create an industry.

We're going to create the APIs, the SDK to interface with it.

We're going to do all this.

Like now they're doing it, and they're doing it with Microsoft this time, instead of like against Microsoft.

So like a plus move there.

Yeah.

But yeah, like the amount of capital investment that went into this was insane. enormous.

So at this point, Intel's like, we might have a problem here.

Right.

It's going to be more difficult than we thought to just take whatever these people are doing and integrate it directly into our motherboards.

Yep.

And irony of ironies, Jensen presses this even further.

He does a big partnership with AMD.

It's worth knowing here when you're saying AMD, because people probably know AMD and NVIDIA are big competitors today in the GPU world.

Not yet.

Right.

AMD primarily made CPUs at this point.

They made processors and competed with Intel.

They hadn't yet bought ATI, which is where the Radeon business comes from.

That's all the graphics stuff that they do today.

Yeah, ATI at this point was the number two competitor to NVIDIA.

Actually an amazing story too.

It was a Canadian company, started in the 80s and pivoted into graphics cards, like very different.

I feel like there's a lesson in here, right?

We could talk about this in playbook but, like when all the VCs funded these 90 Silicon Valley startups to go make graphics cards, 3D graphics cards the only two surviving ones were NVIDIA, which went through this hellish journey, And then these Canadian guys that were like totally out of the ecosystem and like did it sort of more in a more bootstrapped way and evolved into the space.

Jensen has a great quote about this.

And he's giving this lecture at Stanford years later.

And he says when technology moves this fast, if you're not reinventing yourself, you're just slowly dying.

You're slowly dying, unfortunately at the rate of Moore's law, which is the fastest of any rate that we know.

It's so clarifying of how he thinks about why NVIDIA needed to do these like three complete transformations of the company.

Bet it all, risk it all.

Because if you're not, you're one of those 89 companies.

Exactly.

So Intel's like, holy crap.

We might have a problem on her.

This is not a problem for Intel.

It just is a thing they're going to have to deal with instead of it being part of their extinguished strategy.

Right.

Intel is used to at this point, just like Microsoft at this point.

Oh.

Sure, you know, you want to go make Word perfect?

We'll let you do that.

We'll see these great applications and then we'll go make our own.

That's what Intel's doing.

And now this is the first example of like Intel's going to have some trouble doing this on their own.

So they actually at first come out with their own dedicated intel graphics, you know gpus graphics cards competing as separate cards other than intel had ever done.

I may be speaking out of turn here but like, as far as i know, i don't.

This is not a common strategy for intel.

It's usually integrate into the motherboard in the cpu.

They come out with their own external cards right around this time, like 1999, to directly compete and like They suck.

Like these are like some of the worst reviewed graphics cards in history.

Talk about not your core competency.

Not your core competency.

And it really illustrates how different NVIDIA's approach was to what graphics cards had been before, and building programmable shaders and creating CG, which was a little bit of an early strategy and something they would later do with CUDA, but really understanding that like oh, we can differentiate our hardware not only with interesting hardware features but by building software on top that it only works with our hardware but makes it really great for developers to develop for our thing.

So Intel does make a big push and this actually ends up becoming a great strategy for them into integrated graphics.

So they do try and integrate this, but it's never good enough for the high end.

It's only good enough for if you don't care about graphical applications for laptops and the like.

And that's great.

That's a big market for them for a long time, and especially leading into mobile, although Intel and mobile is a story for another day.

But for the hardcore market, and that's making it sound too small for the market of anybody who cares about graphical performance and quality, which is not just gaming.

At this point you know, it's 3D modeling, it's architecture, it's lots and lots of graphical, high performance, graphical computing applications.

You're always going to want it's this dynamic, and it sets up just like moore's law whatever the current maximum is, it's not enough, it's never enough.

You always want more.

As good as graphics are today, it'll never be good enough 10 years from now.

Game graphics will make today's graphics look Silly and we'll all be in the metaverse or the omniverse if NVIDIA has their way.

But it still won't be good enough.

Like, it's Moore's Law.

You always want as much performance as possible.

All right, listeners.

It's time to talk about another one of our favorite companies, Statsig.

Since you last heard from us about Statsig, they have a very exciting update.

They raised their Series C, valuing them at $1.1 billion.

Yeah, huge milestone.

Congrats to the team.

And...

Timing is interesting because the experimentation space is really heating up.

Yes.

So why do investors value stat seg at over a billion dollars?

It's because experimentation has become a critical part of the product stack for the world's best product teams.

Yep.

This trend started with Web 2.0 companies like Facebook and Netflix and Airbnb.

How do you maintain a fast, decentralized product and engineering culture while also scaling up to thousands of employees?

Experimentation systems were a huge part of that answer.

These systems gave everyone at those companies access to a global set of product metrics.

From page views to watch time to performance.

And then every time a team released a new feature or product, they could measure the impact of that feature on those metrics.

So Facebook could set a company-wide goal like increasing time in app and let individual teams go and figure out how to achieve it.

Multiply this across thousands of engineers and PMs and boom, you get exponential growth.

It's no wonder that experimentation is now seen as essential infrastructure.

Yep today's best product teams like Notion OpenAI, Rippling and Figma are equally reliant on experimentation.

But instead of building it in-house, they just use Statsig.

And they don't just use Statsig for experimentation.

Over the last few years, Statsig has added all the tools that fast product teams need, like feature flags, product analytics, session replays and more.

So if you would like to help your team's engineers and PMs figure out how to build faster and make smarter decisions, go to statsigcom slash acquired or click the link in the show notes.

They have a super generous free tier, a 50000 startup program and affordable enterprise contracts for large companies.

Just tell them that Ben and David sent you.

Okay, David.

So Xbox comes out.

NVIDIA has a card in there that is the GPU of the Xbox, that has programmable shaders.

So rather than literally just spitting out triangles to put on screen, they actually are running these little programs in shaders.

It's super cool.

What happens after that?

Basically, the company goes like supernova in a good way, in a good way at this point in time.

So the fiscal year that ends January 31st 1999 this is like right before they go public or right as they go public they did 158 million in revenue.

The next year, the fiscal year ended January 31st, 2000.

So like the calendar year 1999, they do $375 million in revenue.

So more than double that year.

Wow.

The next year, they do $735 million in revenue.

The year after that, which is basically the calendar year 2001, the year the Xbox comes out, they do just about 14 billion in revenue.

Which makes them the fastest semiconductor ever to reach a billion in revenue and gets them added to the SP 500.

Indeed.

This is the company's essentially ninth year of existence.

They're already doing over a billion dollars a year in revenue now.

Throughout the company's history, they basically have these, like, six to ten year epochs.

And during those they have like meteoric rise.

When they do something contrarian, that's off the rest of the industry and then it starts to taper and they need to figure out how to reinvent themselves again.

And so we sort of saw it the first time, before the competitors come in.

And then the competitors come in, and then we see it again, with them figuring out.

We got to do the emulated version of letting our engineers design the chips and lay out the chips so we can be faster than everyone.

And then everyone sort of catches up and they have to do it again with programmable shaders, launching those to the industry, and then they have these few amazing years.

After that, there is kind of a plateau again, and you can see it in their revenue.

They did obviously close to $2 billion as we move through 2001.

They stayed reasonably flat for a few years after that.

I think they eventually did $2.8 billion in 2005, but it was kind of barely profitable.

Like they never lost money.

But net income for each of those years was only a couple hundred million or less.

So it's not like they're this like super free cashflow positive company.

They're not adding to their cash pile in a meaningful way.

You can start to see competitors figure out programmable shaders too.

Yep, ATI, of course.

And then in 2005, I think it is, AMD.

That's where they start shopping around.

06 is when the transaction actually happens.

They buy ATI.

And of course now AMD is the main competitor to NVIDIA.

So we're going to tell those stories on the next episode, but basically like a little sort of teaser what's going on here.

They kind of take their eye off the ball in the gaming market.

Now, maybe that's too harsh.

I don't know what Jensen would say about that, but yeah, right around this time, there's something that ultimately becomes pretty amazing that happens, which is they've achieved the dream at nvidia they've created a programmable gpu.

It is truly a GPU.

It rivals the CPU.

This is the model.

They have driven forth this new industry of computer graphics, enabled a whole generation of storytellers to program their GPUs and tell stories.

A whole new class of users and developers starts to tinker around with these GPUs.

And Jensen likes to tell a little story that's probably apocryphal, but you know we'll repeat it here as a little teaser for next time.

I need to thank you because I do this work in my lab on these supercomputers that we have at Stanford.

And I write these models for the molecules that I'm researching.

And it takes a couple of weeks to finish the computation on these models.

Well, my son, who's a gamer...

He told me that I might want to try going over to Fry's, the local electronics store, and buying a bunch of your GeForce cards.

So I did.

And that I should try porting my models into CG, into your graphics, computer language, and just see what happens.

Well, I did it.

And my computation finished in a couple hours.

So I waited a couple weeks for the supercomputer here at Stanford to finish.

I checked the results and they were identical.

Boom.

So I just want to thank you, Jensen, for making my life's work achievable in my lifetime.

This is for sure something that Jensen made up.

Maybe he did, maybe he didn't.

It's probably cobbled together from a few different people's experiences.

Probably.

It's a composite.

But every word of it is true in spirit.

Yes.

There is a whole industry called scientific computing, or a whole segment that NVIDIA would be able to address in the future, but they need a whole lot of tools to be built for them to be able to really use GPUs for all those purposes and more, with machine learning and everything else.

But Right now yes, you are buying off-the-shelf G-forces here in this mid-2000s era and trying your best to sort of hack them together to do your super parallel processing task.

That is not specifically building a cool video game.

What's interesting is the industry perception around this time was that NVIDIA had started to sort of focus on this high-performance computing segment and that they were starting to take their eye off the ball in gaming.

So people were starting to think like oh, maybe ATI is actually more interesting as a gaming-specific graphics card maker at this point.

And there's a little-known fact that is...

So you mentioned this AMD-ATI deal, and we all think the AMD Radeon at this point.

You don't think about the ATI Radeon, which was the... I think they retired the ATI brand in 2009.

But AMD's first choice was actually NVIDIA.

Ah.

So AMD tried to buy NVIDIA to make that their graphics line.

And it was possible because it's not like the stock was blowing up at this point in time.

It had this sort of few years of reasonable stagnation before we get into late 2006, 2007.

And certainly people didn't see the machine learning market.

People didn't really see the scientific computing market.

And it was like, hey, maybe this company needs... some guidance from a smart company like us, AMD.

And so they make the offer and there's the cover story on Forbes.

We'll put it in the show notes, but there's this article that comes out called Shoot to Kill.

And Jensen in this merger acquisition talk with AMD, insisted that he be the CEO of the combined company.

And that is the thing that blew up the deal.

And instead, AMD went and bought ATI and the rest is history.

Oh man, that is such a good what would have happened otherwise.

Well, should we use that to transition into analysis for this one?

Yeah, let's do it.

So I thought it'd be fun to do narratives.

Let's take it from this point in time.

The AMD ATI deal has just happened.

We're sort of looking forward.

It's 2006.

What's the bear and bull case for the company?

And I thought an interesting data point to sort of ground this discussion would be that if we look at the gross margins today for NVIDIA which we will talk in our whole next episode about everything that they do that's so insanely differentiated.

They sell their GPUs at a 66 gross margin.

Hardware business with a 66% gross margin.

Back in 2004, that gross margin was only 29 that they were able to command as a premium on their cards.

And so you can kind of see all of their economic potential was being competed away and they weren't doing anything to differentiate in a way to get any sort of pricing power.

And so you make that 29.

Then you need to use that to pay all your overhead and fixed costs and your engineers and develop the next product and pour it into RD.

And sure they had a few great years of doubling in revenue after going public, but It's not looking great right now, in 2006.

Yes.

And there's also another reason why their gross margins are so low in those years following 2001.

So they made this deal with Microsoft, right, to power the Xbox.

And it was absolutely the right strategic decision to power the Xbox to get Microsoft's support in creating CG for programmable shaders protect themselves from Intel.

But if you're going to deal with Microsoft, they're going to extract their pound of flesh.

So you'll note, there are three game consoles in the history of game consoles that NVIDIA has powered.

The original Xbox, the PlayStation 3, which we'll talk about next time, and the Nintendo Switch.

They have not done any others.

Really?

And people always ask Jensen about this.

He's diplomatic about this, but...

Because it's a crappy gross margin business, right?

Like, yeah, there's a $500 million a year revenue deal with Microsoft.

$500 million a year when their whole company revenue is a billion.

Well, that's $500 million a year of very low gross margin revenue.

Yeah, I think the way that he talks about this sort of opportunity.

In the talk that I watched him give he didn't name names, but he says people always ask me.

You know they come to me and say Jensen, why are you making this great game?

Console GPU.

Like, what a waste.

Why wouldn't you do that?

And he always talks about it like there's a lot of things we could spend our resources doing.

And if I don't think that we can do anything really unique and special and really change the world, then we have better things to spend our resources on.

And that is kind of Jensen speak for like, No, there's crap margins in that.

I'm not doing that.

But he is right that, like given a finite amount of resources, you have to allocate your capital and your resources in the most optimal, both short term cash flowing way, but also long term strategic way.

You know, it seems like from their sort of analysis, especially recently with game consoles, sure we might be able to make some low margin revenue on it, but it's not strategic for us long term to do that.

It's probably, at this point in time, a little too much of an exaggeration to say that they're out of the fire and into the frying pan, having solved their Intel existential strategic challenge and ending up now sort of at odds with Microsoft.

That's too much, but there's a lot of truth to that.

So you know if you're looking at this stock in those years, especially as revenue starts to flatten.

And a big part of that is coming out towards the end of the Xbox generation of consoles leading into the Xbox 360 which, of course, NVIDIA does not power.

That's a lot of gaming revenue, top line revenue going away.

Meanwhile, they're spending tons of resources investing in this new high power computing segment for these researchers.

You're a little bit like, okay, Jensen, do you really know what you're doing here?

And in 2006, Intel launches or announces this Project Larrabee, where they're going to be like a full-fledged GPU maker.

I mean, this is like a totally second foray of Intel's really into this.

So you're like okay, you've had to like be this commodity where you're living on Intel's motherboard.

Customers are only choosing to buy your product when the integrated card isn't good enough for them.

The person that makes the integrated card is now announced.

They're going to be like a real, honest to goodness.

GPU maker.

So like, are you betting the farm on scientific computing?

How big is that market?

So the answer is yes.

And that is also the bull case.

And it turns out scientific computing would be so much more than scientific computing.

And it would be, you know, the acceleration of all the other things in our computing world that has been very advantageous to become parallelizable.

But I will leave it there so I don't have too many spoilers.

But that is 100% the bull case and 100% what happened.

Yeah, it's interesting.

We're working on an episode episode two with Hamilton Helmer and his colleague Chen Yi at Strategy Capital about power.

Specifically with platforms, how to apply power to platform businesses.

It probably won't be out yet when this episode comes out, but it'll be coming out shortly thereafter.

They make the point and it's a very, very valid one that when you climb the mountain as a founder and a company of finding product market fit, It's very different than climbing the mountain of then having to go develop power.

It's a whole second journey that you have to go on.

It's a whole second invention.

And at this point NVIDIA had definitely found product market fit, but had not yet found their source of power.

So you know if you're looking at this company at this moment in time, especially as revenues flattening coming off the Xbox contract costs, OpEx is going way up investing in this sort of speculative new area.

Yeah.

I can totally see looking at this and being like wow, this is yet another Silicon Valley startup that had immense product market fit top line revenue soared.

But now we're kind of coming to the end of that and there's not a lot of power you know as defined by sustainable.

You know economic profit, you know operating cash flow coming out of this thing.

So then as we talk about power here, what power do they have?

And for listeners who are newer, this is really the.

What is it that enables the business to have persistent deferential returns or sort of, in a sustainable way, be more profitable than their closest competitor?

They really didn't have power.

I mean, I'm trying to think which of the seven powers can we make the best case that they did have?

It's not switching costs.

Switching costs are crazy easy.

So switching costs is interesting, right?

Like, I think they were trying really hard to develop it.

They did a really good job.

I mean, they made CG in collaboration with Microsoft and CG works on NVIDIA products.

But it's not like CUDA today to flash forward to next time.

Yeah, so it was like they had the inkling of how they could get power, but it was not yet implemented.

And Microsoft didn't have a lot of interest in helping NVIDIA create huge switching costs there.

Right, because Microsoft wants to play Switzerland.

Like hey, anyone that is an application developer for Windows should be able to use whatever hardware is on any PC in a really great way.

And so we want to commoditize all of our suppliers.

So maybe some...

An attempt at switching costs that was not fully realized.

I think they probably thought and did for a while have process power in this six-month shipping cycle that none of their competitors could match for a while.

Yep.

But certainly the delta of NVIDIA's shipping cycles versus competitors compressed over time.

Okay, Playbook?

I have one big one that we have not discussed.

We sprinkle in lots of like playbook themes, but there's one to me that I want to call out and draw a through line to something that's happening with NVIDIA today.

And that is simulation.

So there's a thing that we're going to talk about a lot on the next episode which is totally changing the world as we know it, which is things that we used to have to do physically we now do in simulation.

An obvious example of this is Boeing doesn't take every part and throw it into a wind tunnel.

Well, maybe Boeing does, but the zillion new space startups certainly don't do that.

They simulate the atmospheric effects on stuff and it happens way faster and it lowers your iteration time.

And another one is drug discovery.

Like, you look at how fast we came up with coronavirus vaccines.

Simulation.

It's an absolute miracle.

And everything in our world is being compressed 10 times, 100 times faster because we're able to simulate it rather than needing to do it in the real world.

The interesting thing is, a lot of that is actually powered by a lot of the machine learning advances that NVIDIA is doing in today's world with cool things that you can do on GPUs.

But the reason I'm talking about it in this episode is that DNA comes from the fact that, in order to survive when they had nine months left, the way that they saved themselves was with simulation.

So it became very clear to the company very early on the benefits of of being able to simulate something rather than having to do it in the real world.

Similarly, a playbook theme I wanted to highlight that we have not talked about explicitly yet is just the power of, like democratizing tools for developers.

You know and Jetson really saw this back in his AMD days before going to LSI logic but the ability for NVIDIA to use an emulator, a software emulator, to design their chips.

And then, of course, the massive, massive strides that the EDA industry has made since then, and then nvidia itself, you know, enabling.

You know we haven't really talked about it as much but, like jensen and chris and curtis's original vision did come true.

Like they created a new artistic platform for artists to tell their stories And without this industry and all the hardware, software tools that went into creating it, like there's no way that you know anybody, you would have to be a John Carmack to tell a story in this medium.

And there are very, very few John Carmacks out there in terms of being gifted enough developers to, and surrounded by storytellers too, and being a great storyteller himself to like be an artist you know to be.

Uh, nvidia talks about this now in their marketing materials to be da vinci and einstein, you know, together in one person.

Yeah, it reminds me of the people that do like the crazy cool art in microsoft excel by like painting each of the cells a different color.

You had to be that type of person to be a game developer in carmax era, because it was esoteric as hell to be able to actually figure out how to make this hardware do what you want.

Another big one i want to highlight.

You know, i just keep thinking back, going to the thinking, back to the original time when nvidia was funded.

I wonder what like, if they're really honest with themselves, like what sequoia and don valentine would think about that They made the wrong venture bet.

In a market like that, we see it all the time.

Look at Web3 right now.

If there's a team making some new vision for a class of applications in Web3, they're going to get term sheets from everybody.

And then there's going to be a million copycats the next day.

It is the beauty of proliferation and then consolidation.

I mean Buffett has.

I think it's in a 2000 Fortune article that he wrote it's weird that I know that, but I think that's right in an op-ed about how there were whatever it was 70 car companies before we narrowed it all the way down to Ford, GM and Chrysler.

And the airlines were sort of the same way.

There's this proliferation, there's massive.

There's no one can really differentiate, no one can build any power.

And so you only have a few survivors left.

And in general they compete on pretty low margins when there's only a few left and their defensibility comes from their scale.

You know, I think open question if that's sort of how the graphics market necessarily matured.

But you're absolutely right to like sort of self-reflect on the time when Sequoia, and Would you make that type of bet again?

You backed one of the two winning horses out of 90.

Should you do that and just say well, we're betting on amazing founders, or should you?

Well, I think that's So.

This is the nuance.

I think what is so cool and part of the fun of the art and the science of sort of what we do, the company they backed was wrong.

And yet it became, I don't know how long Sequoia has held.

I mean I think a lot of the GPs at Sequoia and certainly Mark Stevens, who was one of my professors at GSB, who was on the board for Sequoia, is still on the board have held their shares personally for like to this day.

Like that's one of the best venture investment returns of all time Full stop, period.

Anything going from a 6 million valuation to the eighth largest company in the world definitely has to be one of the best of all time.

Right?

And so, like, they were wrong intellectually, and yet they were right, right?

And, like, why were they right?

Like, they were right because... frankly, of Jensen.

It was a reasonable enough market.

The question is are you better off doing what they did and investing at the proliferation phase on someone you believe is going to figure it out and have a good shot at being one of the winners?

Or should you wait until consolidation and just pay that much higher price in order to back one of the ones that are already running away with the market?

Well, and back then in the day, there was no option, right?

There was no...

There were no stages of venture capital.

There was you raise your venture capital and then hopefully you're profitable enough to go public.

They did raise some more money in between that initial $2 million and going public.

I think they raised $20 million in total, but there wasn't a lot of window.

And I think it was Sequoia and Sutter Hill that put that capital in for the rest of that 20 million.

But it's really interesting to think about these cases.

Take Sequoia and Sutter Hill too, and specifically.

They've gotten it right so many times, but it's not a straight line.

So what's the lesson from that?

Yeah, and the magic was that Jensen really figured it out early that they were in a business that was totally at the mercy of Moore's Law.

And so, like in having that initial realization as early as they did, with the proliferation of competitors and everyone doing, you know, the triangles and direct tax and all that, that taught them the lesson early enough that oh, we are in a business where we must be reinventing.

There is no way to stay ahead other than ruthless self-examination and completely upending and rebetting the business.

Yeah.

Ship faster and reinvent.

Yeah.

So that I mean.

That to me is why they, why they survived.

If you think about the class of companies that are like the greatest venture returns of all time.

Some of them are like Nvidia where, like you look at the team, you look at the business plan, the thesis originally, and like yeah, it wasn't a straight line but it worked out.

Right.

Yeah.

So it's like, and I think you know, plenty of venture firms, but I have to hand it to Sequoia over history too.

Like they've done a really good job of doing both of these.

They do the Steve Jobs and they do the Jensen's.

Now is a great time to thank good friend of the show, ServiceNow.

We have talked to listeners about ServiceNow's amazing origin story and how they've been one of the best performing companies the last decade.

But we've gotten some questions from listeners about what ServiceNow actually does.

So today we are going to answer that question.

Well, to start, a phrase that has been used often here recently in the press is that ServiceNow is the quote-unquote AI operating system for the enterprise.

But to make that more concrete, ServiceNow started 22 years ago focused simply on automation.

They turned physical paperwork into software workflows, initially for the IT department within enterprises.

That was it.

And over time, they built on this platform going to more powerful and complex tasks.

They were expanding from serving just IT to other departments like HR finance, customer service, field operations and more.

And in the process, over the last two decades, ServiceNow has laid all the tedious groundwork necessary to connect every corner of the enterprise and enable automation to happen.

So when AI arrived, well, AI kind of just by definition is massively sophisticated task automation.

And who had already built the platform and the connective tissue within enterprises to enable that automation.

ServiceNow.

So to answer the question, what does ServiceNow do today?

We mean it when they say they connect and power every department.

IT and HR use it to manage people, devices, software licenses across the company.

Customer service uses ServiceNow for things like detecting payment failures and routing to the right team or process internally to solve it.

Or the supply chain org uses it for capacity planning, integrating with data and plans from other departments to ensure that everybody's on the same page.

No more swivel chairing between apps to enter the same data multiple times in different places.

And just recently ServiceNow launched AI agents so that anyone working in any job can spin up an AI agent to handle the tedious stuff.

Freeing up humans for bigger picture work.

ServiceNow was named to Fortune's World's Most Admired Companies list last year and Fast Company's Best Workplace for Innovators last year.

And it's because of this vision.

If you want to take advantage of the scale and speed of ServiceNow in every corner of your business, go to servicenowcom slash acquired and just tell them that Ben and David sent you.

Thanks, ServiceNow.

All right, David.

So what is the company that they invested in?

Ben, you are talking about Keyhole.

Yes, I thought you would know.

So I love this little foreshadow before we get to grading, because I think it's so interesting that Jensen basically saw the potential of Keyhole.

And without sharing what Keyhole became, I think astute listeners will know.

We've talked about it on Acquired.

And we have.

We've done an episode.

A whole episode on it.

Basically, this company that can't raise any money from anyone else comes and pitches Jensen and he's like, oh my God, I see this.

This is the future.

This is simulation.

Like you, are creating a model of the earth in software and people can just navigate around the earth.

And so now that I've given it away.

A graphical model of the earth.

Yes, Google acquired it.

It became Google Earth.

And NVIDIA was one of the early investors.

And that really goes to speak to where Jensen and the leadership team at NVIDIA sort of saw their business going from this point forward, where it was all about simulation.

I don't think there was any machine learning going on.

I think it was all sort of like the graphical use of the chip.

But this sort of like gets into the Omniverse stuff that they're doing now.

And one of the main reasons that I think they invested was because he wanted to stay alive so they could keep demoing it to customers, because it showed off NVIDIA technology so well.

But I just love that little tidbit.

Yeah, we did our episode years ago now, the Google Maps episode.

That was such a good one.

Yeah, where to keyhole and...

There were three companies that Google all bought and mashed up in the parlance of the day to ultimately become Google Maps.

Zipdash.

Zipdash, yes.

And they were all like $20, $30 million acquisitions.

Amazing.

That's what's so cool about this, and i think maybe this is the like where jensen and the nvidia story bridge from like the oh, it was the you know obvious investment market to bet on team, to bet on to go all-star engineers to go build this graphics card.

Nobody really could have seen that graphics were going to become a lot more than games.

Like you maybe could have seen it.

Like, you know, there was SGI and Hollywood and Jurassic park.

And there were some military applications for computer graphics but yeah, very few.

Even jetson and nvidia, they were like video games.

So the thing, fortunately that became the biggest entertainment medium and so, even if that was your only market keyhole on google earth and google maps is such a great example of like, computer graphics became so much more important than like, relevant beyond just video games.

And that's all computer.

You know dynamically generated programmable computer graphics that are making all of that, all that happen.

All right, so how are we going to grade this?

Yeah, so I'm thinking, given the market opportunity that existed between 1993 and 2006 for computer graphics, how did NVIDIA do at exploiting that market opportunity?

And share price is a reasonable way to think about it.

I think it's a second-order metric on how were they at creating value and capturing value.

And I'd say their value creation was amazing.

Their value capture, they did better than anyone else as far as I could figure out.

The question I was sort of trying to figure out is that there were 90 other competitors doing the same-ish thing.

Two-ish survived.

Was there anyone else in the value chain that was able to do a much better job capturing?

Like, would you rather have been Microsoft than NVIDIA?

Yeah.

This leads into the really interesting question to think about for NVIDIA in this period.

Microsoft did basically nothing.

Now, OK, that's like like that's not fair to Microsoft.

Sure, there was a large team that did DirectX.

Huge team, you know, and the Xbox project was amazing.

And like, I don't mean that in any way to throw shade at anybody at Microsoft.

But, like they were in this position where they could just sit there, they could watch the market develop for computer graphics and they could be pretty, you know, by making good, very good strategic decisions, they could capture a ton of the value, with other companies taking the risks of developing the market, figuring out all this stuff.

And then, you know, microsoft can come along and be like great nvidia.

We're gonna help save you from intel and in return you're gonna, you know, give us a really sweetheart deal on these chips and you're gonna put us in business with xbox and, by the way, the other side of your gaming and computer graphics business on pcs, we're going to become your primary partner for that too, and all of the development languages that you're going to create, and cg and all that.

Yeah we're, we're tightly coupled with that and it's all going to work only on Windows.

I think your assessment of Microsoft did basically nothing except make really good strategic decisions is like reasonable enough for DirectX but totally is not fair for Xbox.

No, it's not fair for Xbox at all.

It's not, it's not.

But it is an interesting way of like, to put it another way, and let's exclude Xbox for a moment.

You're basically just recognizing that Microsoft had an unbelievable position in the market and did an amazing capital allocation job, exploiting it, and basically saying hey, you know what?

You know what we don't need to do?

All that crap that like NVIDIA and ATI and all those guys are doing.

You know how we can still retain our market position and continue printing money the way that we do?

This thing.

And they did that.

And they didn't get into the commodity business and they were brilliant.

We don't need to be in this brutally competitive industry where, like if we don't ship six months ahead of our competitors, every cycle we're toast.

Yeah.

So I think you know, in this kind of like grading question, oh man, the longer we do this show, the more I realize this is like a mega theme of acquired that, like Microsoft in the nineties, early two thousands was such a a power and the antitrust you know, the DOJ case really, really crippled it, probably for good for the ecosystem.

Then the 3D chess version is and this kind of foreshadows the next episode because NVIDIA had to learn these hard lessons and had to develop, like was forced to develop these really crazy competencies, like eventually developing CUDA that would power this whole machine learning and scientific computing revolution.

Was it bad for Microsoft to not have to grow that DNA?

Yeah.

In the same way that it was bad for Microsoft to not have to grow the mobile DNA, and Apple beat them at that game.

Yeah, that's a great point.

I don't know enough yet about how the machine learning market is going to develop or has developed, in order to sort of make a call yet on that point.

But if you're just standing there in 2006 reflecting back, NVIDIA fought for their life and won multiple times and microsoft just leveraged the crap out of their amazing position yes, and probably achieved about the same outcome.

Yeah, both of these two fighting for their life, company defining moments from nvidia's first 10 to 15 years, the overcoming the 90 competitors.

And then the building and making the case that they're not going to get commoditized by Intel, that the GPU is going to be a standalone, important thing.

Microsoft profited hugely from both of those.

Yep, it's so true.

I will say, NVIDIA doing what they did has been net unbelievably positive for the world.

Like I watched the NVIDIA GTC conference, the 2021, because the 2022 is about to happen.

And just like the review of all the stuff they're involved in is so inarguably good for humanity, we need way less energy to do way more interesting stuff.

That's good for humans because nvidia exists and without doing this first 13 years they would not have laid the groundwork to be able to do all of that in the future.

So that's like one sort of contorted lens to look at it through.

I think i give nvidia for this period of time an A, because they're basically the only company that survived.

ATI did for sure, of course, but in a very different fashion.

And they created this whole industry, almost inarguably, created and shepherded this whole industry.

But it's not an A plus because Microsoft, well, shoot, there was the DOJ case.

Until the DOJ case.

Yeah, it's true.

Yeah.

All right.

I like that.

Hard to argue with it.

Carve outs.

I have a fun and very appropriate one for this episode.

Elden Ring.

Have you heard about this, Ben?

No.

You're not a gamer.

So you, you need to, we need to, like get you into gaming after you know doing all these episodes now.

It's so fun.

It's just like, it's great.

So Elden Ring for people who don't know is the latest from software game and it's on all the platforms console PC, et cetera.

Lots of people are saying this is probably going to be is up there with the conversation for greatest game of all time ever made.

These are the guys.

It's a Japanese developer.

They made the Dark Souls games.

If you've heard of them, they're like just these legendarily like incredibly hard games.

But like the world building is unbelievable.

And Elden Ring is the first one to come out on modern platforms and just like everything about it the graphics, the scale, the breadth of the world, the story George RR Martin helped develop the backstory to this.

Like, Oh wow.

If you needed another example of how video games have become like uh, the biggest, most ambitious storytelling medium out there.

Like this is it.

I've only just started playing the game because I've been researching Nvidia the whole time.

Yeah.

But even just in a few hours playing it, like it's, it's incredible.

You're not going to get an experience like this in anything else.

Cool.

I have an appropriate one that I didn't realize was going to be appropriate until you shared it earlier, which is I have been getting back into a lifting, like a weightlifting program that I haven't done for like 10 years.

Inspired by Jensen.

Called Starting Strength by Mark Ripito.

Yeah, apparently inspired by Jensen and I didn't even realize it.

But it's like I reactivated a gym membership and I went back to the gym.

You know, started kind of from square one in terms of like doing all the basic barbell lifts.

It's just been really fun.

Like it's a new hobby.

It's something I did like 10 years ago and then totally let atrophy.

And the way that I love to work out and at least historically have the last five to eight years has been like endurance sports.

So, you know, training for a marathon or doing week-long bike trips and stuff like that.

And it's just very fun to get back into the like every other day.

Try and lift as heavy as you possibly can for a few reps, rest for a long time, make sure you get all your sleep.

It's a very different mentality.

And so it's been fun doing that again.

I love it.

It's like a...

I feel like we're both becoming like better versions of our high school selves.

I'm like a like a full on like gamer again.

And you're getting back into weightlifting.

High school me would have been like, what?

Why would I work out?

That doesn't sound fun.

Okay, college you college you.

Fair.

All right, listeners, that's all we've got.

We are very excited to at some point, come back and talk to you about 2007 through 2022 with NVIDIA and the absolutely unfathomable things that they have done.

Imagine if you started a business in the early 90s doing a thing that seemed like a small market at the time, but you did the thing and then it turns out that that gave you line of sight to something that the same technology was uniquely able to do.

That was like 10 times bigger than the original thing.

And no one else was even close to you, because you had like 18 years of like building stuff and learning about these technologies to be the best company in the world to take advantage of that next thing, which obviously is machine learning.

It is just like an, oh my God story.

And then you layer on top of that the fact that gaming actually was like 10 to 100 times bigger than anybody ever thought it would be.

It's like a literally unbelievable story, except that it happened.

So you have to believe it.

Ah, so great.

This is the kind of stuff that we do Acquired for.

I've just been so jazzed about this.

Yeah.

I got a lot of research to do on parallel processing and why this was so perfect for all the machine learning and cryptography use cases.

But that's why we get some time between episodes to go and do more research and to watch GTC, the GPU Technology Conference, their annual developer conference 2022.

So...

Thank you so much for listening to us.

Leave us a review on Apple Podcasts if you listen there or with the new Spotify ratings feature on their mobile app.

Share it with a friend if you liked it.

We welcome lots of feedback.

And fortunately, in having a part two, we're going to be able to take your feedback and actually work it into the next part of the story.

So acquired.fm slash slack.

Come hang out with us.

Talk about this.

Check out the LP show.

And we've got a job board.

If you are looking for the next stage of your career, we have curated all of the positions at acquiredfm slash jobs.

And with that, thank you to Vanta Vouch and the SoftBank Latin America Fund, and we will see you next time.

We will see you next time indeed.

Who got the truth?

Is it you?

Who got the truth now?

Huh?

[엔비디아(NVIDIA)의 탄생과 초기 성장: 생존을 위한 처절한 혁신]-[Nvidia Part I: The GPU Company (1993-2006)]

📋 Summary

엔비디아의 탄생: 데니스(Denny's)에서의 시작과 위기 극복

1. 첫 번째 위기와 생존을 위한 결단

2. '리바 128(Riva 128)'과 개발 방식의 혁신

3. GPU의 탄생과 기술적 도약

4. 모어의 법칙과 경쟁 우위

결론: 지속적인 혁신과 파워의 확보

🎯Key Sentences

📝Key Phrases

📖 Transcript

[엔비디아(NVIDIA)의 탄생과 초기 성장: 생존을 위한 처절한 혁신]-[Nvidia Part I: The GPU Company (1993-2006)]

📋 Summary

엔비디아의 탄생: 데니스(Denny's)에서의 시작과 위기 극복

1. 첫 번째 위기와 생존을 위한 결단

2. '리바 128(Riva 128)'과 개발 방식의 혁신

3. GPU의 탄생과 기술적 도약

4. 모어의 법칙과 경쟁 우위

결론: 지속적인 혁신과 파워의 확보

ListenLeap으로 딥러닝 학습

🎯Key Sentences

📝Key Phrases

📖 Transcript

ListenLeap이 실제 문맥에서 학습하도록 이끌어줌