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

0:10 Who got the Is it you, is it you, is it you Who got the truth now? Is it you, is it you, is it you? Down.

0:22 Train. Another story. 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.

0:45 Bast. In San Francisco. And we. Are your hosts. It is the eighth largest company in the world by market cap.

0:53 When NVIDIA began in nineteen ninety three, It made computer graphic chips in a brutally competitive and low margin market. There were ninety undifferentiated competitors all doing basically the same thing at the same time, and yet today They have an eighty three percent market share.

1:12 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

1:31 pioneered a completely new market. 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

1:49 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. Alright, so here's everything you need to know about Jetson. The cliff's notes before we talk for like six hours about him.

2:12 The dude. used to drive a Toyota Supra. Like a fast and a 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 gonna tell the wild story of NVIDIA's founding.

2:37 to its rise in prominence, powering the computer graphics and gaming revolution. This really is a story of Like true invention and innovation, it reminds you that engineering breakthroughs really do push our world forward. And

2:52 In saying that, to s kind of set some context, this is a story that takes place from about nineteen ninety three to to kind of the mid to late two thousands. 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

3:09 I think Jensen is still an underrated CEO, even rated hundred percent. 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.

3:23 But I think not enough people really know. Just one more Jensen quote. Before we get into the episode. The best. My will to survive exceeds almost everybody else's will to kill me.

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6:00 And just tell'em that Ben and David sent you. Listeners, after you finish this episode. And you're thinking to yourself, Gosh, I wish I could talk about this with people. We have good news for you. you can do that with eleven thousand other smart members of the acquired community at acquire.fm slash slack. Here's a new thing. If you haven't rated or review this podcast yet.

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6:36 We really, really, really appreciate it when you help share your experience as a listener. With others. All right, listeners, this is not financial advice. positions in things we discuss on the show. This is for entertainment and informational purposes only.

6:51 And David. Take us in. So We start. In February.

6:57 Of Nineteen sixty three. What's going on in Silicon Valley in nineteen sixty three? Let's see, Fairchild had already started, I think. And Silicon Valley was like Underway, but it was early days.

7:10 But we start. Not in Silicon Valley, but in Taiwan? Yes. The southern part.

7:17 Of the island of Taiwan. With the birth. Uh Jen soon. One.

7:24 Later Americanized to Jensen. Jetson Huang. So His dad was an engineer

7:32 for the Air conditioning company carrier? Oh yeah. Yeah, you see those like big like 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.

7:48 And he was like Wow, you know, this is Amazing. I want my Kids to grow up here. And to have

7:56 All the opportunities that are Available. So he comes home, Jensen's four. Jensen has a older brother who's a couple of years older. You know, like nobody speaks English. So his mom gets an English dictionary. And

8:08 picks ten words every day, grills the two kids, like quizzes them, and teaches them English out of the dictionary. Huh. Where does that accent come from? 'Cause it's not what you would think. The family ends up moving to Thailand a few years later.

8:23 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 the parents can't move to America yet. They do they don't have enough money. But they found A boarding school. In America.

8:38 That Is cheap enough that they can afford It is called Onita. Baptist Institute. And it is in eastern Kentucky.

8:47 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 Onita. Wow. Well it turns out that the reason that this school

9:02 OBI Onita Baptist Institute was so cheap that Was it's actually not a prep school. It's a reform school. So this is a school for like troubled kids. It's a reform school. So Jensen's roommate when he shows up as a nine year old. Is a seventeen year old kid.

9:21 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.

9:40 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 and I need a

9:54 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 Laurie have given a few million dollars to the school and it's like a

10:12 Amazing institution now. You can see Jensen gave The commencement address in twenty twenty. We're gonna link to this in the sources. It's pretty awesome. So after a couple years at OBI

10:24 His parents are finally able to save up enough money to To afford to come to the US themselves. So they move first to Tacoma, Washington. Great state of Washington.

10:35 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. Yeah, Jensen continues his uh his American upbringing. He gets really into table tennis. Yeah.

10:51 places third in the junior nationals in uh Table tennis and he gets his picture in sports illustrated going. No, no way. Pretty amazing. But his parents continue their sort of like academic Discipline. And Jetson's super smart, obviously. He ends up skipping

11:05 Two grades. And than 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 sixteen, right? He got there when he was sixteen'cause he had skipped a couple of grades.

11:19 And he loves math, so he decides he's gonna major in electrical. Engineering. At OSU. And he totally

11:26 Falls in love. In more ways than one. The first way. That he falls in love. Is uh

11:33 He just thinks like electrical engineering is The coolest thing in the world. becomes one of the top students. In the school. He talks about how like he gets mad at the professors because

11:43 They don't use like enough precision when talking about like 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 uh he sort of rounds all the numbers and he's like, I I 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 Jen said, like he understands, like Yeah, my employees get mad at me when I, you know, round the numbers and use CEO math. And like I get it. Like I appreciate precision too, but You know, like the big picture is what matters here.

12:16 The second way he falls in love is with his lab partner in uh electrical engineering fundamentals. His lab partner Lori, who goes on to become his wife. Such a cool story.

12:29 So he graduates in nineteen eighty four, she graduates in nineteen eighty five. They move down to Silicon Valley. And Jensen.

12:37 Joins. AMD As a sort of equivalent of like a Chip design PM. It's very like engineering heavy, but he's kinda like a P at me sort of like helping as a junior manager of a

12:49 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, uh 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

13:13 literally the fastest chips in the entire world. So He starts at A M D. 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

13:29 At AMD and then at LSI Logic where he goes too. We're gonna talk about it 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.

13:43 No, I didn't. Lecture at GSP. I watch 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 the up where he holds up Affordloon's resume. So also Easter egg in that talk. That was the day that the Jensen and Lori Huang.

13:59 Engineering Center. Had Stanford was dedicated it as Dan says. Jensen did a building. Pretty awesome. I did watch he gives a talk where he walk he walks in and gives a talk at uh Stanford. I think it's the first time that Jensen has given a talk since the building opened and he says, uh I've donated we have this nice building now, so I I have no more money.

14:21 Yeah, I'm peniless. Right, right, Jensen. Uh so great. Just to set context for people, if you look at his NVIDIA shares, he's worth about twenty billion dollars right now. I think he owns what, like three and a half percent of NVIDIA something like that. Yeah, he's not penniless. Okay, so he works at AMD for a couple years. And while he's working there Probably from working on this.

14:44 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

14:54 You know, there's not Many companies. It's all like Full stack at this time. You know, TSM C doesn't start till nineteen eighty seven. Not only are you manufacturing in house, but for the most part the like 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.

15:17 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 easily, he realizes like It's actually not cool. Like it would be cooler.

15:31 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 they were like design tools to help you make chips. So

15:44 After a couple of years, his office me at AMD. Leaves and goes to join a startup called LSI. Logic. Which had just gone public? And

15:55 We've talked about it on the show. Made. Don Valentine and Sequoia. The then Largest.

16:03 Venture return in an IPO. in history, maybe the largest venture return ever in history when they went public. Of a hundred and fifty three Million dollars. On

16:14 Day one. Boy has venture changed as an asset class. But that 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. Ten, fifteen million like

16:30 So that probably roughly ten X the fund in in one day. Right. Pretty awesome. So what was LSI? It was one of the first and was sort of the premier. Asex company. A yes.

16:43 I see application specific. Integrated. Circuit companies. And so what they did and what that meant was They basically made

16:51 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

17:06 Defense companies like Heed Martin and the like, um, but lots of other companies now too are coming to LSA Logic and the other ASIC 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

17:26 And product systems. Right. And the idea with A6 is really If You're not saying, hey, th there's gonna 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.

17:46 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 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.

18:04 Yep. And the legacy of ASICs today. Still around. Still use both A6, but the legacy is FPGA's field programmable. Array chips that are um You know, some might say is sort of a bear case for NVIDIA these days, but we will we will get to that.

18:20 Far, far, far down the road. Son. Microsystems. Yeah. Customers. That was house sun.

18:29 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 L SI. And so he gets put on the project. He basically embeds

18:42 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 one, Sun's first big workstation. Product. Over the next few years he pretty much exclusively works with Sun while he's at LSI Logic.

18:59 He works directly with Andy Bechtelstein, who, you know, the founder of Sun and with Veno Kosla. Yeah. He becomes super Well known. And develops quite a reputation there as somebody who can really like Take these visions for Chips.

19:14 And these customer requirements from Sun And turn it into, you know, reality and production. So One day.

19:22 Right around Thanksgiving, nineteen ninety two. Jensen has finally After eight years finished his master's degree at Stanford. And uh Stand for this. Quite, quite glad that he finished before this happens.

19:34 Two of Jensen's buddies. who he's become close with at sun. Chris Malachowski and Curtis Priam. who in Jensen's own words he describes them as Really, really fantastic engineers.

19:47 And when Jensen says that, he means it. They come to Denson 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 Denson's like, Well, sure. Let's go meet at my Favorite spot.

20:00 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 uh he orders uh The super bird, 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.

20:18 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 nineteen ninety two. So they see Three D graphics.

20:30 are really becoming a thing. And you know, remember this is the era of sun, analysis logic, all this stuff. It's also the era of Silicon Graphics, right down the street, right there in Silicon Valley, STI. So many great things that come out of there, you know, Jim Clark, Netscape, like all this great stuff. Jurassic Park.

20:48 Jurassic Park is about to come out. Comes out in nineteen ninety three. So there's this huge demand for three D 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.

21:09 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 three D Console graphics yet.

21:24 That's coming. Very shortly. But what is happening is The PC.

21:30 Wave is like really cresting right now. Like We're like a year and a half from Windows ninety five coming out. Mm-hmm. And

21:38 I remember doing this, I bet you do too. Or kids in nineteen ninety two, nineteen ninety three doing on their PCs. They're playing. Wolfenstein three D and Doom. Doom comes out in nineteen ninety three.

21:51 These are Taken the world by storm. And they're made by ID, ID Software, in Texas, and John Carmack and John Romero. But Carmac is like doing incredible feats of engineering.

22:03 three D graphics to run on consumer PCs. It took somebody of Carmac's calibre. 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

22:19 You know, chip PM essentially. Let's Make. A graphics card, let's make a chip that can accelerate the graphics of a normal PC.

22:30 three D graphics like SGI is doing with professional workstations. To enable them for Consumer Hardware PCs We know that

22:39 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 gonna try and make it so you can develop games on a PC. You're saying like just so you can play

22:53 games on a on a PC, right? Well, both. I mean, mostly that you can play games on the PC But then you're also gonna have to create, you know, all the APIs and SDKs and developer ecosystem for developers to access this new hardware. On PCs.

23:10 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. Okay.

23:19 Alright, so what do you think? It's just like a good pitch. I mean, so what you're basically asking me to believe Nineteen ninety to me. Is that Video games on PCs are gonna be a thing that there's gonna be a

23:34 big economic wave around that lots of consumers are going to want to do this. They're gonna wanna do it on PCs instead of on Super Nintendo and dedicated systems. Maybe. Well, I have this proof point of of id software and and Wolfenstein and Doom right there. Like millions of people doing this.

23:51 But still maybe, because it's not clear that like video games are gonna 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

24:03 to totally change the development environment or can like There'd be like five or six different Dooms out there. There's five or six Karmacs 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 yeah, okay, not Totally yeah.

24:21 But still like 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

24:33 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 cereal pork cards, like God knows what.

24:46 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 gonna make a custom graphics card. take a graphics workload off the CPU, specifically for gaming. Great.

25:13 Okay. So Yeah, it was pretty much a brain dead, yes. But as you Alluded. Two at the top of the show.

25:22 The problem when something is a brain dead, yes. For venture capitalists. is that it's a brain dead yes for lots of venture capitalists and lots and lots and lots.

25:35 Get funded. To do this. But back to Denny's. That night. NVIDIA is the first.

25:41 They are the first Dedicated. Graphics card. Company. They all decide the three of them that they're gonna go in on this.

25:50 Jensen goes. To the CEO. of LSI logic. Walks into his office and tells him that he's gonna resign. He's gonna go start this company with two engineers from Sun.

26:03 And uh this is what the business plan is gonna 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.

26:18 Semiconductor. No way. Damn right. So is that how Don'cause Don Valentine obviously was the biggest investor in well Sequoia was in LSI Logic and he did he know him from Fairchild? Yeah, they were colleagues back in the day. And then the biggest exit in uh in Sequoia's history to that point in time. So Wilf says

26:39 So let me get this straight, he says to Jensen. You're gonna go build these. Graphics cards and kind of just like you were saying there, Ben. Who's gonna use these and and what for? It's like well you know. You're gonna be in PCs, they're for gaming, they're for a bunch of kids.

26:52 And Wilf hones in on the critical question. He's like, Well, who makes PC? Games is there a developer ecosystem for this? So that's kinda like the uh we think if we build it like they'll come. So Wolf says, uh remember he was a fair child, he's felt like he knows When to make silicon for specific applications. And uh Wolf says, Hm.

27:12 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.

27:23 I'm gonna call up Don. He calls up Don. And he's like Don I got a kid. He's gonna come see you. Stand by.

27:30 Which this is a lesson for all founders and uh, you know, aspiring founders out there. Getting A reference. from the CEO of a portfolio company. is a really good way to come in.

27:43 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. 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 and

28:03 You know, 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 and didn't finish the plan. So he comes into this meeting and just kind of like

28:26 Barf's all over Don. Yes, exactly. So Jensen's walking out the door. He's like, you know, totally Dejected. And Don stops him and says.

28:38 Well That wasn't very good. But uh Wilf says to give you money. So against my best judgment. Based on what you just told me.

28:51 I'm gonna give you money. But if you lose my money I'll kill you.

28:57 Classic. Classic downline. So good. So the deal happens. Uh Sutter Hill comes in too,'cause you know, again, like it list is all. Dramatized at the end of the day. Like this is a hot deal.

29:09 This is uh Two. In a row for us with uh Sutter Hill. I know. Oh geez, they're so good. But it was a hot deal. They wanted in this fits central casting. of at this point in time. They invested like a million each, is that right, for a total of two?

29:25 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.

29:37 Remember. Everybody. This is the eighth most valuable company in the world right now. Started at a Six million dollar post money valuation. So they're getting things ironed out.

29:47 And there's just one problem. They don't have a name. For the company yet. Denson 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.

29:59 And uh they were saving The files that they were working on for the chip design for the first graphics chip. As Dot N V

30:08 Envy being short for Next version. And so like, oh we kinda 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 NVIDIA, I N V I D I A

30:27 Which means envy. And they're like, Great, we'll be the envy of the industry. NVIDIA we'll drop the I at the beginning, so we start with NV. 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

30:44 Again, as we've been saying, literally eighty nine other companies get funded within a couple of 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 with meaning because

31:07 They're doing a thing here that like, well, eighty nine other people are also sort of simultaneously doing It is kind of a new frontier that they need to Invent and then Own

31:21 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 graphic to be a new medium to tell stories.

31:45 And here's sort of like the way that he articulates at the time. Why video games today are a hundred and eighty billion dollar a year industry bigger than Hollywood, bigger than music. It it's the biggest entertainment medium. But at the time he sort of has this thesis that like You really can't through computer graphics tell stories today.

32:04 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.

32:21 And so our reason for being is Is 3D graphics as a form of artistic storytelling for the future, and everything will be in service of that. And I think

32:34 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 twenty years of their existence. Well. And baked into that. Is

32:46 Again, you know, Wilf kinda 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

32:55 This first iteration of NVIDIA. Which is They have to go evangelize to developers to Like Yeah, there's it and there's Carmac out there, but like not a whole lot of other PC game developers out there. Th not a whole lot of other three D

33:10 PC game developers at this time. There are two D P C game developers, but They gotta convince a whole lot of people to go You know, learn how to do Three D game development for PCs. And that's all like, Oh, we're gonna enable storytelling all that.

33:24 So to do that they have to go right their own, you know, APIs and SDK and development framework to develop for this new graphics chip that they come out when 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.

33:44 Exactly. Things start off really well. Remember the super hot. They're the first company. They're funded by Sequoia and Sutter Hill, like They land a big deal. With Sega.

33:56 Two power their arcade consoles and their next generation. Home console. To be the three D graphics. Engine.

34:06 And 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 gonna create, you know.

34:24 people probably know you create three D 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 is like That's not how it's done. I'm pretty sure people talk about triangles. Yeah.

34:45 And I'm pretty sure if you look at NVIDIA's Amazing headquarters building today. It's you know, made out of triangles and uh Homage to game developers. Not quadrilaterals. So

34:56 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 gonna put this chip in our game console, ship the game console. We're the only people that

35:21 You know, make an STK, we being Sega, so everyone will have to kinda 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 uh

35:40 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

35:49 That's interesting. We like selling PCs. And uh 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

36:04 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 three D graphics. directly into Windows without any of this, you know.

36:23 Crufty middleware from some no name company NVIDIA out there. Why don't we just bake these APIs right into Windows? Directly. For three D graphics. We'll call it. Direct.

36:34 Three D. And of course, anybody who knows about the history of this, that becomes Direct X. Direct X made some pretty different design decisions than NVIDIA had made, is that right? Yeah. So they use triangles.'Cause triangles make sense. So now NVIDIA's really up a creek. Like all of their com you know, the eighty nine other competitors out there that started later.

36:53 Most of them. I like sure, I'm gonna jump on board of this. Microsoft. Ecosystem like I would be dumb not to.

37:01 It's standardized on this completely different paradigm than NVIDIA. And then Sega. They've got Sega. They've got this one sort of Customer. And then in nineteen ninety six

37:14 Sega's like Yeah. We're not so sure about this quadrilateral 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 three D graphics here, rather than really going into the weeds, but A triangle is the fewest

37:30 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 curve surface. It's sort of the most fundamental building block that you could use to create something that is perceived as 3D.

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39:41 So NVIDIA at this point, they're halfway down the road of Developing the next Chip. that they think Sega's gonna adopt for what ultimately would become the Dreamcast.

39:52 NVIDIA was calling the N V two. When Sega comes back and says We're switching horses. We're not gonna Do this. So like They're screwed.

40:01 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 Draft because

40:11 Thank you Moores Law. So NVIDIA's chips were designed to be like super, super tight on memory. And the memory cost about two hundred dollars in component You know. Yeah.

40:24 Their competitors have more memory that's costing them like fifty dollars. 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,'cause 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,

40:53 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 at 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 have to look at each other and say, Okay, do we scraping 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.

41:22 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

41:40 Like literally anybody else, like you pull the plug. Like it's over. Like everything in the deck is stacked against you, like You're F and uh I can't imagine sitting there dreaming up a way out of this. But Jensen. God, he's such a G. He's like

41:57 No, we're not going out like this. You know, when you hear Jensen talk. today about like invidious culture. And he says that intellectual honesty is like the cornerstone of invidious culture. Like This is what he's freaking talking about. Like He sits down with Curtis and Chris. And remember, they're like they're engineers and they've recruited NVIDIA

42:17 a hundred plus engineers into the company at this point and sold them on this technological vision of we're gonna define the industry. We set the standards, like We're not gonna use some, you know, off the shelf stuff. And like It's all toast. And so Jensen's like, guys, like this is a pipe dream.

42:36 We need to throw it all out. If we're gonna survive, the only thing we can do is standardized on on the same Microsoft, you know, direct three D. As everyone else. Same architecture.

42:48 And our Only shot. is just to like compete on performance and try and become like The best Ship out there in this now sea of

42:57 commodity chips. And uh His co founders like don't wanna 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 like literally out engineer all of our competitors. We need to be smarter at engineering decisions so we can be more performant.

43:24 at a lower price point. Using less energy. than our competitors. Because Microsoft.

43:30 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.

43:55 Well, you're saying engineering ability. But remember, like 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?

44:11 before everybody else. Because everybody knows what's gonna be in that ship. And why is it? What fundamentally about Was it about graphics cards that Made it. A commodity.

44:22 Well, at this point, like all the other peripherals. We're gonna get into this in a sec. There was nothing that special about it. They all did the same thing, which was take Polygon level

44:35 three D 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.

44:56 And so what GPUs actually do or did at least in this point in time is say Okay. the system is gonna 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

45:14 in the highest resolution that I can, or I suppose a standard As fast as I can. That'll drive the resolution. Output a two D thing that goes on the screen. So I turn three D stuff into two D stuff. And I have to do that. Better than

45:29 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 like they gotta ship faster than their competitors, and they also gotta ship faster than their competitors'cause they're About to go bankrupt. So they draw up this plan that's like they're trying to thread like the tightest needle possible here. They have to lay off seventy percent of the company. Which they do. They go down to about thirty five people.

46:00 And everybody who's staying No. 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?

46:15 Yeah, the way that you know, in the with these fabulous chip companies, the way they would design chip 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 go back and forth a few times. You mean the foundry would produce them? Like the T SMC or the Samsung or the Global Foundry or No, importantly. NVIDIA is not using TSM C at this point'cause they can't they can't. T S M C only works with the best and NVIDIA is not the best. Huh. So they're using like second rate foundries.

46:47 And that process takes a a long time and then at the end of it when you're sure you got the the design right. Then you do what's called a tape out of the tip. 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.

47:05 But it just means finalizing the design. But you actually do run it on some prototypes first. Like the 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 um, you know, that process takes two years to get a a full sort of iteration on. Yep.

47:24 So they're like we can't we can't do this. So like Jensen's here like here's what we're gonna do. I've heard about there's this new technology, some new machines out there that enable Emulation. Of Chips.

47:36 And in our case we're gonna use it to emulate. The graphics chip that were We're designing. Hall in software. And it you know, it works.

47:44 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 you're looking at your computer or monitor or whatever, it's refreshing.

47:57 Thirty to sixty times a second. If you're a professional gamer, you probably have it going at like a hundred and twenty times a second, frames per second. This emulator runs at one frame every thirty seconds. So they're gonna have to debug this thing in software. To save this time. Going at one frame every thirty seconds. It's just insane. That's brutal.

48:17 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 are going to make the trade off of our testing being mind numbing, like running whatever our graphics tests are where we're looking for like this certain specified output. We need to plant someone in front of a screen to watch the new frame render once every thirty seconds. and look against some test to verify that the output is correct. And if it is

48:45 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 have to spend a million dollars just to get the emulator, you know, hardware and software to 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 they're cash out in the company. They get it done in a few months, and

49:19 And then they call up their foundry. I don't know if they're using um United or or one of the one of the other foundries in Taiwan, not T SMC. Like, all right. We tape this thing out.

49:29 Send it to production. And the foundry's like, Uh you guys sure about that? Yep, we're sure. Make, you know, 100,000 units. If I'm remembering right, I think NVIDIA Basically was the only customer that of that emulation software. Like that was a startup that really wasn't fully proven yet.

49:48 But NVIDIA was like, look, we literally have no options. Yeah, they were the only customer. And then that that company went out of business after it's wild. What 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.

50:11 With You know, the same set of assumptions about what, you know, technology is available. as all their competitors, but their competitors are working on those designs. They're not gonna be able to get them out for like eighteen to twenty four months. Nvidia's gonna get this same

50:28 you know, generation of design out in six months. So this chip It's called the Riva one twenty eight, is 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 big. It's extremely powerful relative to anything else on the market. Like more powerful than any customers are telling them they want.

50:50 Yeah. Way more powerful. Way, way, way, way, way more powerful. But you know, it comes with some downside. With great power comes, you know, responsibility. Because they built this thing in such a manner. It like barely works. Like there's a lot of stuff wrong with it. I forget the exact Number of this, but like essentially Direct Three D at the time had

51:12 Something like let's call it like twenty four, twenty five 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 of'em. Like one third of it just like freaking crashes. Like it just doesn't work. I thought even worse than that, but uh basically like I I think NVIDIA had to launch a campaign. going around to like

51:33 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 gonna do where you need to use that fancy stuff? Do us a favor for this generation of the chip. These eight were great. You're gonna love them. They're so good. And just use those.

51:48 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 gonna build all this technology, we're gonna drive the market. They didn't know Anything about the market. They were just making all these assumptions about what people wanted.

52:07 But now they're actually going out and Jensen's going to these developers trying to convince them. And They all do it. Why do they do it? Because the only thing that matters is performance.

52:18 Consumers are gonna 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.

52:34 NVIDIA is like the first one that figures 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's making the buying decision, right? On what graphics card they buy. It's 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.

52:57 That's what NVIDIA's business is. Whether they're buying it as a fully like 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

53:11 The game developers are making decisions on What? Graphics cards to support. Right. and how to build their games with like the assumption of what's my target market of consumers like

53:25 Who do I think? will this game run on you need to have at least an X level performance. rig in order to run my game or run my game. And it's Fullest form.

53:36 So the developers are premeditating what Graphics cards are going to be out in the market when their games launch. And they're saying. it's gonna be the most performant one at the right price point. So whatever the mass market is, we kinda have to target that. And if you're telling us and we're gonna 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.

53:59 then people are going to buy that one. And so we must Target it. That card and they're gonna buy my game. I mean I remember like this is a few years later. This is a you know a trope that happened. There was a game called Crisis.

54:11 C R Y S I S remember this? Oh yeah. What's the relationship between crisis and far cry? Uh it was oh no, Far Cry was the first game. Yeah, the Crisis engine, and then Crisis also be it was super convoluted. Basically my perception of this thing was when this came out, when Far Cry came out, this was like mid two thousands. The graphics were.

54:30 Unbelievable. Unbelievable. And if you had a rig powerful enough to run it, like just unbelievable. The game itself was Total crap. Like I don't think I ever

54:40 played more than ten 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.

54:56 That was the failure mode of Far cry. with non performant chips. This is how the hardcore gaming industry evolves. Like Far cry.

55:05 Sold. So much software and so much hardware. Just because people wanted to experience that. You to attempt to experience that level of graphics. And so that's what the developers are starting to figure out and they're like, All right, well

55:19 If you can ship this thing, we'll use only those, you know, eight blend modes or whatever, like whatever it takes. 'Cause we want, you know, graphical performance is the most important thing. So It works. They Sell.

55:32 One million units of the Riva one twenty eight 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 nineteen ninety seven.

55:48 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 one is out, but PS two is not out yet. I think PlayStation One.

56:02 And with that the gaming market kinda bifurcated into like sort of the Yeah, the console market. which was standardized and you knew it was all gonna work. And then the 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.

56:21 NVIDIA has now figured out. these dynamics of the PC gaming market. And they Now have A process within the company.

56:31 To Design And ship. Each next generation of their hardware. In a six month timeline. While the rest of the industry is on an eighteen to twenty four month timeline. Necessity is the mother of invention.

56:45 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. There now.

56:58 shipping r 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

57:12 That the number of transistors on the chip Equating to the compute power available at a given price point. to the market would double every eighteen to twenty four months. NVIDIA is now on a cycle starting in

57:24 Nineteen ninety seven, nineteen ninety eight. Where they are Doubling. the performance that they are delivering at a given price point to the market. Every six months.

57:33 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

57:46 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.

57:56 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 uh the I Love Lucy um 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

58:29 The magic of it is that it's super parallelizable. Like there's all these things that need to get output into 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.

58:45 we can and that 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. Uh let's put a pin in that for now, but it's worth knowing.

59:07 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

59:20 In parallel. lighting the pixels on a screen, you know, thirty, sixty, a hundred and twenty times. A second. With the images that are being fed to them from like

59:33 the game or the graphics. Programming. Which is living all in the CPU land. So like you're a game developer. You develop in you know Microsoft Direct 3D becomes Direct X or uh OpenGL is the open source

59:48 Competitor to this. You know, all that. logic is really happening in the CPU realm. And what that means is like if you think back to games from this time. You know. Think console games. Playstation one, even Playstation Two.

1:00:02 N sixty four. And you look at the graphics in those games. Or PC games from the time too. They're all kind of the same. They're all the same.

1:00:11 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.

1:00:28 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

1:00:42 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 though

1:01:05 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

1:01:20 They're a commodity. There's not a lot of smarts happening here. Yeah. No programming. But NVIDIA's figured this out, they can now ship on a six month time cycle. They're starting to like really Take huge market share.

1:01:32 Now a lot of people start paying attention to them in a good way. T S M C that wouldn't Even return Jensen's calls. Back in the day. There's this amazing, amazing story. Did you watch the TSM C thirtieth anniversary celebration. This is so it's like three hours on YouTube. This is worth a brief aside. This is how much pull Morris Chang from TSM C has. He gets the CEOs on stage

1:01:57 of NVIDIA Arm? Harm. ASML. Qualcom and Broadcom?

1:02:05 Yeah. I don't think Lisa from AMD was there. No. It's basically everyone but AMD of the sort of pillars of the TSMC Ecosystems. I mean Morris is playing interviewer, like it's very entertaining to watch him. It's like a celebration of Morris and of of TSM C. It's amazing. It's amazing.

1:02:23 Yes. So in the section with Jensen, uh they tell the story of how NVIDIA. At this point it's gotta be T S M C's biggest custom. I mean they've been like

1:02:36 Of how this all came to be. After The Reva one twenty eight hits and it's become a big success. Jensen writes a letter. Tomorrow. Like a physical letter.

1:02:47 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,'cause they were a You know, left for dead startup in a See of the Startups.

1:03:02 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

1:03:20 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. Denson picks up the phone and is like, Yeah, who's this? Morris is like Hello. This is Morris Chang at TSM C.

1:03:37 I got your letter. And Morris says that there's like a silence on the other end for a couple of seconds. And then he hears Jensen yelling, Everybody shut up. Morris Chang is on the phone. Oh amazing. And that's how TSM C became the manufacturer of NVIDIA chips. Yep, the next year.

1:03:57 The two companies sign a huge Multi year deal. for T S M C to become the primary foundry for NVIDIA and Still are. Today

1:04:08 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

1:04:20 Tip development process. Nvidia disp. Keeps accelerating. So, yeah. In nineteen ninety nine. They rebrand

1:04:28 They're products. You know, they'd use the N V one first and then this Revolve one twenty eight. They actually run a little contest of what they should name the products and the winning name. Is

1:04:40 Geometry force. Anybody who knows who, you know, buys graphics cards of 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.

1:04:58 Ecosystem. And it's because this card that they ship, the first G Force. Uh in nineteen ninety nine. It's the G Force two fifty six. It's so powerful.

1:05:09 It has Five X. Better graphics performance. than like anything else on the market. And they call this like the first GPU, right?

1:05:19 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 graphic cards. Graphics tips. 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

1:05:40 Graphical. Processing unit. Now, on the one hand, that's like sort of like marketing. Bravado. On the

1:05:47 Other hand. That is like a very loaded statement to make. And why so? What do Jensen and NVIDIA mean by this?

1:05:57 So Intel you know, you think chips. Think Intel, right? You think Silicon you think Intel? Intel's whole strategy. At this

1:06:06 Point in time. was basically they're almost like a biotech company's day, like one of the big pharma companies. In uh or or put another way, it was another version of the Microsoft embrace, extend, extinguish thing. They would see there are all these peripherals, sound cards, networking cards, all the C graphics cards. All the stuff we've talked about.

1:06:25 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 open ecosystem. We want everybody to flourish. And then they would see which of these, you know Peripherals got. Consumer traction.

1:06:42 And then they would just turn'em into, you know, a component in the motherboard. And th thus began the wave of being able to buy a PC with uh an Intel motherboard and integrated graphics. Well, and before that, you know, integrated sound, integrated networking. Like remember um Oh so fun doing this research. Remember the company creative and the sound blaster cards? Oh yeah. I remember buying tons of that stuff. Like and then at a certain point You stopped buying sound blaster cards, right? You're like, Oh, the motherboard does ninety percent of what I needed to do and why would I spend extra money on a separate thing.

1:07:15 Exactly. And so until they just sit back, they'd watch all this happening. They'd integrate it. Game over for The startups. And there was like reasons for specialized stuff. Like I remember buying a special network card because the integrated

1:07:29 networking capability of the motherboard on my I don't know what it was, a Mac eighty five hundred or something, wasn't as fast as like 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

1:07:51 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. B.

1:08:10 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.

1:08:23 Dominant. World. And it really wasn't true yet. It wasn't a processing unit in the same way that A CPU was a processing unit where it was

1:08:32 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 you know Jensen is just such a master strategist in NVIDIA was so great. Like This whole kind of orchestration of a bunch of things all hit.

1:08:50 over the next couple of years. So first NVIDIA goes public. Yeah, they've now shipped. The reboot one twenty eight was a huge hit. This new G Force two fifty six. flying off the shelves, they go public in. Begin in nineteen ninety nine at a six hundred million dollar market cap.

1:09:06 So a hundred X return from the six million dollar post money valuation on the Sequoia and Sutter Hill round. That gets them Yeah, some more Capital. And then behind the scenes they're working.

1:09:19 They're in talks with Microsoft. Microsoft's got A secret project. that they're working on at this time. The Xbox. Mm-hmm. Which we talked about a lot on the Sony episode and

1:09:30 So many times on the show. Mm. Microso comes to NVIDIA. And like we want you to be a key Supplier of the graphics.

1:09:40 Yeah, the GPU for The Xbox and they do a huge, huge deal. Five hundred million dollar a year. Deal. For NVIDIA To supply the graphics.

1:09:52 for the Xbox with a two hundred million dollar Advance. Hm. And the chip that they use is a modified version of this.

1:10:02 Incredible new Chip. that NVIDIA's working on this sound like Steve Jobs David Jetson sounds like Steve Jobs talking about this. The G Force Three. Which

1:10:14 Introduces for the first time. programmable. Shaders and lighting. On The GPU. Everything we just talked about, though like

1:10:25 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 three D graphics.

1:10:43 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 to actually program

1:11:04 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

1:11:23 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 CG. Literally like they extend the C programming language. With graphics.

1:11:41 libraries and capabilities to directly program. Graphics and lighting and shaders. Four. the GPU. So this makes you know that Sort of like marketing, you know, oh this G Force two fifty six, it's a GPU. Now it's real. Like this is a graphical processing unit.

1:11:59 That is intelligent. That is Every bit as you know, maybe not every bit as important as the CPU yet. But like This is like the stake in the ground of like

1:12:09 This is no sound card. This is not gonna get commoditized. Do you know if this was the G Force FX or if the G Force FX was a similar version of this that was available to PC. That's a good question. It was the G Force three was the the PC version of this. Okay. This move to programmable shaders was a bet the company move and it was

1:12:30 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

1:12:53 And back to that original sort of quixotic vision for the company of we're gonna create an industry We're gonna create the APIs, the SDK to interface with it. We're gonna 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

1:13:16 Enormous. So at this point. Intel's like We might have a problem here. Right. It's gonna be more difficult than we thought to just take whatever these people are doing and integrate it directly into our our motherboards.

1:13:31 Yep. And uh 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 graphic stuff that they do today.

1:13:56 Yeah, ATI at this point was the Number two competitor to NVIDIA. Actually an amazing story too. It was a Canadian company. uh started in the eighties and pivoted into graphics cards like very different Yeah. I feel like there's a lesson in here, right? We could talk about this in playbook, but like

1:14:12 When all the VCs funded these ninety You know Silicon Valley startups to go. Make graphics cards, three D graphic cards. The only two surviving ones were NVIDIA which

1:14:23 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 boot more bootstrapped way and evolved into the space. Jensen has a great quote about this. Uh and he's giving this lecture at at Stanford years later and he says

1:14:40 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.

1:14:50 Which is the fastest of any rate that we know. Yeah. 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.

1:15:04 'Cause if you're not, you're one of those eighty nine companies. Exactly. So Intel's like holy crap. We might have a problem on our head. Not a not a pro like this is not a problem for Intel. It just is uh a thing they're gonna have to deal with instead of it being part of their extinguished strategy. Right. Intel is used to at this point just you know, like Microsoft at this point. Oh.

1:15:25 Sure, you know, you want to go make word perfect, uh we'll we'll 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 gonna have some trouble doing this on their own. So they actually at first Come out with their Own

1:15:44 Dedicated intel Graphics. You know, GPUs. Graphics cards. Competing.

1:15:50 As separate cards that Intel had ever I may 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 to usually integrate into The motherboard and the CPU. They come out with their own external cards. Right around this time, like nineteen ninety nine. To directly compete and like

1:16:08 They suck. Like these are like some of the worst review 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.

1:16:29 Uh 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.

1:16:44 So Intel does make a big push and this actually, you know, 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

1:16:57 If you don't care about graphical applications for laptops and the like and And that's great. You know, that ends up you know, that's a big market for them for a long time. Uh and especially leading into, you know, mobile. Although Intel and Mobile's a story for another day. But

1:17:12 For The hardest core market. And that that's that's making it sound too small. For the market of anybody who cares about graphical performance and quality.

1:17:23 Which is not just gaming at this point, you know, it's three D modeling, it's architecture, it's Lots and lots of Graphical. high performance graphical computing applications. You're always gonna want

1:17:37 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. Ten 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 more's law, you always want as much performance as possible.

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1:19:44 Go check out service now.com slash acquired and tell'em that Ben and David sent you. Okay, David, so Xbox comes out. NVIDIA. Has

1:19:54 a card in there that is the uh the GPU of the Xbox that has programmable shaders, so you know, rather than Um you know, literally just spitting out triangles to put on screen. They actually are running these little programs in in in shaders. It's super cool. Uh what happens after that.

1:20:11 Basically the company goes like Supernova. In a good way. In a good way at this point in time. So the fiscal that ends January thirty first, nineteen ninety nine. This is like right before they go public or right as they go public.

1:20:25 They did a hundred and fifty eight. million dollars in revenue. The next year. Fiscal ended. January thirty first, two thousand, so but like the calendar year nineteen ninety nine.

1:20:36 They do three hundred and seventy five million dollars in revenue. So more than double. That year. Wow. The next year. They do Seven hundred and thirty five million dollars in revenue.

1:20:47 The year after that, which is basically the calendar year two thousand one, the year the Xbox comes out. They do just about one point four Billion dollars. In revenue? Which makes them the fastest semiconductor ever to reach a billion in revenue and gets them added to the S P five hundred.

1:21:04 Indeed. This is The company's essentially ninth year of existence. They're already doing over a billion dollars a year in revenue. Throughout the company's history, they basically have these like six to ten year epochs. And during those they have like a 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.

1:21:27 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 gotta do um 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 then 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.

1:21:56 they did obviously close to two billion dollars as we move through two thousand and one. They stayed reasonably flat for a few years after that. I think they eventually did two point eight billion in two thousand and five 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 cash flow 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 two thousand five, I think it is.

1:22:33 AMD. That's where they start shopping around. Oh six is when the transaction actually happens. They buy ATI. And of course now. A M D is the main.

1:22:41 Competitor to NVIDIA. So We're gonna tell those stories. On the next episode. But basically like a little Sort of tease her what's going on here.

1:22:52 They kinda 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

1:23:03 Right around this time. There's something that ultimately becomes pretty amazing. That happens. Which is They've achieved the dream.

1:23:12 And 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.

1:23:28 enabled a whole generation of storytellers. To program Their GPUs and tell stories. A whole new class. Of uh

1:23:38 Users and developers. Starts to tinker around. With these GPUs. And uh Jensen likes to tell uh

1:23:47 whole story that's probably apocryphal, but you know, hey we'll repeat it here as a little teaser for next time. Right around. Yeah, sort of the early two thousands. A uh quantum chemistry. Researcher at Stanford calls up Jensen.

1:24:02 And he's like I need to thank you because You know, I do this 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.

1:24:17 And it takes a couple of weeks to, you know, 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 Electronic store. And uh buying a bunch of your G Force cards. So I did.

1:24:33 And that I should try porting. My models into CG, into your, you know, graphics. Computer. language and and just see what happens.

1:24:43 Well I did it. And my computation finished in a couple hours. So I uh I waited a couple weeks for the supercomputer here at Stanford to finish. I checked the results and they were identical. Um

1:24:57 Boom. It's like so I just want to thank you, Jensen, for making my life's work achievable In my lifetime. This is for sure something that Jetson made up of. 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 a whole industry called scientific computing or whole segment.

1:25:21 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 two thousands 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.

1:25:48 What's interesting is The industry perception around this time was 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.

1:26:01 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

1:26:14 So you mentioned this AMD ATI deal, and like we all think the AMD radion at this point. You don't think about the ATI radion, which was the It was the they I think they retired the ATI brand in two thousand and nine. But AMD's first choice was actually NVIDIA. So AMD tried to buy NVIDIA to make that their graphics line. And

1:26:35 It was possible because it's not like the stock was blowing up at this point in time. And it had this sort of few years of reasonable stagnation. before we get into late two thousand six, two thousand seven. And

1:26:49 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.

1:27:02 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.

1:27:12 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 uh 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?

1:27:34 Yeah, let's do it. So I thought it'd be fun to do narratives. Like let's take it from this point in time. The AMD ATI deal has just happened. We're sort of looking forward. It's two thousand and six. You know, what's the barren 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

1:27:57 in our whole next episode about everything that they do that's so insanely differentiated. They sell Their GPUs. Uh A sixty six percent gross margin.

1:28:07 hardware business with a sixty six percent gross margin. Back in two thousand and four. That Gross margin. was only twenty nine percent.

1:28:16 that they were able to command as a premium on their cards. And so you can kind of see like All of their own. economic potential was being competed away. And they weren't doing anything to differentiate in a way to get any sort of pricing power.

1:28:31 And so you think you make that twenty nine percent, then you need to use that to pay all your overhead and fix costs and your engineers and develop the next product and pour it into R and D and Sure they had a few great years of doubling in revenue after going public, but It's not looking Great. right now in two thousand six.

1:28:50 Yes. And there's also another reason why Their gross margins are so low. In those years following. Two thousand one.

1:29:00 So they made this deal with Microsoft, right? To um Power the Xbox. And it was Absolutely. The right.

1:29:09 Strategic decision. To power the Xbox. To Get Microsoft's support

1:29:17 Mm-hmm. Creating CG for programmable shaders, you know, protect themselves from Intel. But if you're gonna deal with Microsoft, they're gonna extract their pound of flesh. So you'll note.

1:29:31 There are Three Game consoles. in the history of game consoles that NVIDIA Has powered.

1:29:40 The original Xbox. Mm-hmm. The PlayStation Three. Which we'll talk about next time. Oof. And the Nintendo Switch.

1:29:48 They have not done any Others. Really? And people always are like Asking Jensen about this one. And you know he's all he's

1:29:57 diplomatic about this, but Because it's a crappy gross margin business, right? Like yeah, there's a five hundred million dollar a year revenue deal with Microsoft. No, five hundred million dollars a year when their whole company revenue is a billion. Well that's It's five hundred million dollars a year of very low gross margin revenue.

1:30:15 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 aren't 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

1:30:37 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

1:30:49 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.

1:31:08 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.

1:31:23 That's too much. 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, you know, towards the end of the Xbox.

1:31:36 generation of consoles leading into the Xbox three sixty, 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 powered computing segment for these researchers. You're a little bit like

1:31:56 Okay, Jensen. Do you really know what you're doing here? And in two thousand and six, Intel launches or announces this project Larabi, where they're gonna be like a full fledged GPU maker. I mean, this is like a totally uh second foray of 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 gonna be like a real

1:32:26 Honest to goodness. GPU maker. So like are you betting the farm on scientific computing? How big is that market? So the answer is

1:32:35 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 uh, you know, the acceleration of all the other things in our computing world that has been very advantageous to become parallelizable. But I will uh leave it there so I don't have too many spoilers. But that is one hundred percent the bull case and one hundred percent what happened. Yeah, it's interesting. We're working on an episode.

1:33:01 Episode two with Hamilton Hellmarin is Colleague Chen Yi at Strategy Capital. About power. Specifically with platforms. How to apply power to platform businesses. It probably won't be out.

1:33:12 Yeah, 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 like 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

1:33:29 Then having to go develop power. It's a whole You know, second journey that you have to go on. It's a whole second invention and at at this point Uh NVIDIA had definitely found product market fit, but had not yet found their source of power.

1:33:45 So you know, if you're looking at this company At this moment in time, especially as Revenue's flattening. Coming off the Xbox contract. Costs opEx is going way up investing in this

1:33:58 sort of speculative New area. 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 sword.

1:34:11 But now we're kinda 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.

1:34:25 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

1:34:46 Can we make the best case that they did have? It's not switching costs. The 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

1:35:06 And CG Works on. NVIDIA products. But It's not like

1:35:12 Cuda today to 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.

1:35:25 Huge switching costs there. Right,'cause 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

1:35:42 An attempt at switching costs that was not fully realized. I think they probably thought and and did for a while have process power in this six month shipping cycle that none of their competitors could match for a while. Yeah. But Certainly the delta of NVIDIA's shipping cycles versus competitors compressed.

1:36:00 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 wanna call out and draw a through line.

1:36:12 to something that's happening with NVIDIA today. And That is simulation. So there's a thing that we're gonna 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.

1:36:41 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.

1:36:55 in our world is being compressed. 10 times, a hundred 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

1:37:17 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 being able to simulate something rather than having to do it in the real world. Similarly,

1:37:38 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.

1:37:49 Yeah, and Jensen 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.

1:38:01 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 Yeah, we haven't really talked about it as much, but like Jensen and Chris and Curtis's

1:38:15 original vision did come true. Like they created a new artistic platform. For artists to tell their stories. And without

1:38:26 This industry and all the Hardware, software, tools. That went into creating it, like

1:38:35 And but you would have to be a John Carmack. to tell a story in this medium. And There are very, very few John Carmacs out there in terms of being gifted enough developers. And surrounded by

1:38:48 storytellers too, and he being a great story teller 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

1:39:06 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 wanna highlight.

1:39:21 Yeah, I just keep thinking back going to the Thinking back to that. Original time. When NVIDIA was funded. And I wonder what like if they're really honest with themselves, like what's Sequoia

1:39:33 And Don Valentine would think about that. Hm. They made the wrong venture bet. Like in a in a market like that. We see it all the time. Like look at web three right now. If there's a team making some new vision for a class of applications in web three. Like they're gonna get term sheets from everybody.

1:39:52 And then there's gonna 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 Two thousand 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 seventy car companies before we narrowed it all the way down to for GM and Chrysler.

1:40:13 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. Yeah, I think open question if that's sort of how the graphics market necessarily matured, but you're absolutely right to like Sort of uh.

1:40:37 Self reflect on the time when Sequoia and Sutter Hill invested to say Would you Make that type of bet. Again.

1:40:47 You backed one of the two winning horses out of ninety. 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 you know, the fun of the art and the science of sort of what we do. The

1:41:04 Company. They backed was wrong. And yet it became I don't know how long. I mean I think a lot of the G Sitskoya and certainly Mark Stevens, who was one of my professors.

1:41:15 At G S B. 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

1:41:25 All time. Full stop, period. Anything going from a six million dollar valuation to the eighth largest company in the world definitionally has to be one of the best of all time. Right. And so like They were wrong. Intellectually.

1:41:41 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 what are you better off doing what they did? and investing at the proliferation phase.

1:41:56 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 were there was no option, right? There was no uh 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.

1:42:19 some more money in between that initial two million and going public. I think they raised twenty million in total. But like 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 twenty million. But it's really interesting to think about these cases. Takes a quoi and Sutter Hill too, you know, and specifically. Like they've gotten it right so many times.

1:42:41 But it's not a straight line. So like 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.

1:42:55 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 tags 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

1:43:14 to stay ahead other than ruthless self examination and completely upending and rebetting the business. Yep. Ship faster. And and reInvent. Yeah. Yeah. So that I mean that that to me is why they Why they survived.

1:43:29 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.

1:43:45 And like, yeah, it wasn't a straight line, but it worked out. But then some of them are I think Sequoia even used to talk about this on their website, the Misfits. The ones that look like Unfundable.

1:43:57 Steve Jobs smelling bad. You know, that sort of right. Yeah. So it's like and I think you know Plenty of venture firms, but I I have to hand it to Like they've done a really good job of Doing both of these. They do the Steve Jobs.

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1:45:16 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 greeting because I think it's so interesting that Jensen basically saw the potential of Keyhole and without sharing what Keyhole became. I think

1:45:34 Astute listeners will know. We've talked about it on Acquired. And we have. We've done an episode. Did 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

1:45:50 A model of the earth. in software and people can just navigate around the earth. And so now that I've given it away. Yes, Google acquired it. It became Google Earth. And and video was one of the

1:46:05 the early investors and that really goes to speak to like Where Jensen and the leadership team at NVIDIA sort of saw their business going from this point forward, where it was all about simulation. It was all about using massively parallel computing to build brand new experiences to enable research, to enable 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.

1:46:34 And one of the main reasons that I think they invested was because he wanted just 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 god years ago now, at the Google Maps episode. That was such a good one. Yeah, where to keyhole and Uh there were three companies that Google I'll buy.

1:46:58 And Mashed up. In the parlance of the day. to uh ultimately become Google Maps. Zip dash.

1:47:06 Zip dash, yes. And they were all like twenty, thirty million dollar acquisitions. Amazing. That's what's so cool about this. And I think maybe this is the like Where Jensen and the NVIDIA story.

1:47:19 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.

1:47:35 The graphics were gonna become a lot more than games. Like you maybe could have seen it like Yeah, there was STI and Hollywood and Jurassic Park and there were some military applications for computer graphics. But

1:47:49 Very few. Even Jetson and NVIDIA. They were like video games are the thing. Fortunately, that became the biggest entertainment medium. And so even if that was your only market. Keyhole and Google or I think 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 a computer, you know. Dynamically generated programmable computer graphics.

1:48:13 That are making all of that. How that happened. All right, so how are we gonna grade this? Yeah, so I'm thinking Given the opportun the market opportunity that existed between nineteen ninety three and two thousand and six.

1:48:25 Four. Computer graphics. How did NVIDIA do? at exploiting that market opportunity. And like

1:48:35 Share price is a reasonable way to think about it. I think it's a second order metric on Like how were they at creating value and capturing value. And I'd say like

1:48:45 Their value creation was amazing. Their value capture Yeah. They did better than anyone else as far as I could figure out. The question I was sort of

1:48:56 Trying to figure out is That There were ninety other competitors. Doing same ish thing, two ish survived. Was there anyone else in the value chain

1:49:06 it was able to like do a much better job capturing like would you rather have been Microsoft? Than NVIDIA. This leads into the really interesting question to think about for NVIDIA. in this period. Microsoft did

1:49:20 Basically nothing. No, okay, that's like like that's not fair to Microsoft. Sure, there was a large team that did Direct X. 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.

1:49:39 They could watch the market develop and For computer graphics. And they could be pretty, you know, by making good, very good strategic decisions. They could capture a ton.

1:49:51 of the value with Other companies taking The risks of Developing the market. Figuring out all this stuff.

1:49:59 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.

1:50:20 We're gonna become your primary partner for that too. And all of the development languages that you're gonna create and CG and all that. Yeah, we're We're tightly coupled with that and it's all gonna work only on Windows.

1:50:33 I think your assessment of Microsoft did basically nothing except make really good strategic decisions. Is like reasonable enough for direct X. 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

1:50:49 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

1:51:03 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? Uh And continue printing money the way that we do. This thing.

1:51:16 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 were toast.

1:51:30 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

1:51:46 A power. And the antitrust, you know, the DOJ case really, really crippled it, probably for good for the ecosystem. Then the three D 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.

1:52:07 that would power this whole machine learning and scientific computing revolution. Was it bad for Microsoft to not have to grow that DNA 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

1:52:25 market. is gonna develop or has developed. in order to sort of make a call yet on that point. But If you're s just standing there in two thousand and six reflecting back. Nvidia fought for their life.

1:52:38 And one. Multiple times. And Microsoft. just leverage the crap out of their amazing position. Yes. And probably achieved about the same outcome. Yeah.

1:52:50 Both of these two Fighting for their life, company defining moments from NVIDIA's first ten to fifteen years. The overcoming the ninety competitors. And then the building and making the case that they're not gonna get commoditized by Intel, that the GPU is gonna be a standalone important thing.

1:53:10 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

1:53:23 The NVIDIA GTC conference, the twenty twenty one, because the twenty twenty two 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

1:53:42 without doing this first thirteen 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 it a little bit. NVIDIA. For this period of time.

1:53:58 And Okay. Because They're basically the only company that survived. A T I did of sh for sure, of course, but in a very different fashion.

1:54:08 And a created this whole industry. Almost inarguably. Created and shepherded this whole industry. But it's not an A plus because

1:54:19 Microsoft. Well, shoot, there was the D O J case. Until the D O J case. Yeah, it's true. All right, I like that. Hard to argue with it. Carve outs. Carve outs.

1:54:29 I have a fun and very appropriate one for this episode. Elden Ring. You heard about this, Ben? No. You're not a gamer, so you You need to we need to like

1:54:40 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 gonna be

1:54:58 is up there with the conversation for greatest game of all time ever made. These are the guys, it's 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 these the world building is

1:55:14 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.

1:55:26 the story George R R Martin helped develop the backstory to this, like Oh wow. If you needed another example of how video games have become like The biggest, most ambitious. storytelling medium out there, like this is it. I've only just started playing the game'cause I've been

1:55:44 Researching in video the whole time. Yeah. But even just in a few hours playing it, like it's It's incredible. You're not gonna get an experience like this in Anything else. Cool.

1:55:54 I have an appropriate one that I didn't realize was gonna 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 ten years. Inspired by Jensen. Uh called Starting Strength by uh 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.

1:56:18 You know, started kind of from square one in terms of like doing all the basic barbell lifts. It's just been really f like it's a new hobby. It's something I did like ten 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.

1:56:39 And uh it's just very fun to get back into the like Every other day trying you know, lift as heavy as you possibly can for a few reps. Rest for a long time. You know, make sure you get all your sleep. It's a very different

1:56:53 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.

1:57:08 What why would I work out? That doesn't sound fun. Yeah. Okay, college you, college you. Sure. All right, listeners, that's all we've got. We are very excited to at some point

1:57:18 Come back and talk to you about Two thousand seven through twenty twenty two with NVIDIA. And the absolutely unfathomable things that they have done.

1:57:29 Imagine if you started a business in the early nineties. Doing a thing. That seemed like a small market at the time, but you You did the thing. And then it turns out that that gave you line of sight to something

1:57:40 that the same technology was uniquely able to do that was like ten times bigger than the original thing and no one else was even close to you'cause you had like eighteen years of like Building stuff. And learning about these technologies to

1:57:56 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 ten to a hundred 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.

1:58:15 Oh so great. This this is the kind of stuff that like we do acquired for. I just like Been so jazzed about this. Yeah. I got a lot of research to do on uh parallel processing and like why

1:58:27 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 uh the uh GPU technology conference, their annual developer conference.

1:58:42 Twenty twenty two. So Thank you so much for listening to us. Uh 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 gonna be able to

1:58:59 take your feedback and actually work it into the next part of the story. So acquire.fm slash Slack, come hang out with us, talk about this. Check out the LP show and uh 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 acquired.fm slash jobs. And with that, thank you to Vanta, Vouch, and the SoftBank Latin America Fund, and we will see you next time. We'll see you. Next time indeed.

1:59:26 Who got the truth? Is it you, is it you, is it you Who got the truth now

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