Acquired - Transcript of the NVIDIA Episode - Part 1

Who got the truth? Is it you? Is it you? Is it you? Who got the truth now Is it you? Is it you? Is it you? Cindy, sit down. Say it straight. Another story on the way Who got the truth.

2 (27s):

Welcome to season 10, episode five 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.

3 (41s):

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

2 (47s):

And we are your hosts. It is the eighth largest company in the world by market cap. Dang, when Nvidia began in 1993, it made computer graphics chips in a brutally competitive and low margin market. There were 90 undifferentiated competitors all doing basically the same thing at the same time. And yet today they have an 83% market share of standalone GPUs. That's graphics processing units. For those of you starting with us from square one that are supplied for desktop and laptop computers.

3 (1m 22s):

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

2 (1m 24s):

Sorry. Sorry. I'll just, I'll tease a few things here. So not only that but Of course followers of Nvidia know that they recently pioneered a completely new market, the hardware and software development tools to power machine learning, neural networks, deep learning, all of this in the cloud and the data center, which obviously is proving to define this whole decade of computing. And as David and I began our research, we realized this really could be a book and like a thriller of a book. Since the co-founder and CEO Jensen Wong 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.

3 (2m 6s):

All right, so here's everything you need to know about Jensen the Cliffs notes before we talk for like six hours about him. The dude used to drive a Toyota Supra like a fast and the furious style. Yes. Like like a death machine. And he almost died. He got in like a huge accident.

2 (2m 24s):

Just one more way. He is like Elon Musk.

3 (2m 27s):

Oh man. Crazy.

2 (2m 28s):

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 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 in saying that, just kind of set some context. This is a story that takes place from about 1993 to kind of the mid to late two thousands. And as hyped as Nvidia has been, you know, over the last five years, obviously with the stock runup and everyone's excitement around the company, I think Jensen is still an underrated CEO even rated

3 (3m 13s):

A hundred percent

2 (3m 14s):

Where the Nvidia bulls have put him. I think Jensen is one of those people where like if you know about him, you know what we're talking about and you have unbelievable reverence. But I think not enough people really know.

3 (3m 27s):

Just one more Jensen quote before we get into the episode. Who's the best my will to survive exceeds almost everybody else's will to kill me? Amazing.

2 (3m 42s):

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3 (3m 54s):

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2 (4m 27s):

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3 (4m 52s):

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2 (5m 10s):

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2 (5m 56s):

Here's a new thing if you haven't rated or reviewed this podcast yet. I think the last time we, we mentioned this was like years ago, Spotify in their mobile app just added the ability to rate. So if you listen in Spotify, oh nice. You should totally leave us a little rating in there. If you're on Apple Podcast, leave us a review. 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. We may hold positions in things we discuss on this show. This is for entertainment and informational purposes only. And David, take us in.

3 (6m 32s):

So we start in February of 1963. What was going on in Silicon Valley in 1963? Let's see. Fairchild had already started I think, and Silicon Valley was like underway but it was early days. But we start not in Silicon Valley but in

2 (6m 52s):

Taiwan.

3 (6m 54s):

Yes. The southern part of the island of Taiwan with the birth of Jen soon Huang later Americanized to Jensen. Jensen Huang. So his dad was an engineer 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 and he was like, wow, you know, this is amazing. I want my kids to grow up here and to have all the opportunities that are available.

3 (7m 37s):

So he comes home Jenssen's four. Jensen has a older brother who's a couple years older, you know, like nobody speaks English. So his mom gets an English dictionary and picks 10 words every day, grills the two kids and like quizzes them and teaches them English out of the dictionary. Huh. And if you listen to Jensen, 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 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, they don't have enough money but they found a boarding school in America that is cheap enough that they can afford it is called One Baptist Institute and it is in eastern Kentucky.

3 (8m 26s):

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 one. Whoa. Well it turns out that the reason that this school OBI, Anita Baptist Institute was so cheap 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 Jenssen's roommate when he shows up as a 9-year-old is a 17-year-old kid who had just gotten out of prison and was recovering from seven stab wounds that he got in a knife fight.

2 (9m 7s):

Classic American journey right here.

3 (9m 9s):

And amazingly this is so Jensen like they become great friends even though this kid is eight years older than him, like twice his age basically from a way different background. Jensen helps him with math and he gets Jensen into weightlifting. So you see Jensen today and you're, that dude

2 (9m 27s):

Is jacked. He is jacked.

3 (9m 28s):

He's been weightlifting since he was nine years old. He says about his time in Anita, you know, now I don't get scared very often. I don't worry about going places I haven't gone before. I can tolerate a lot of discomfort. Boy does that play out Wow. In his life as we will see. So it's pretty awesome actually now he and his wife Lori have given a few million dollars to the school and it's like a amazing institution. Now you can see Jensen gave the commencement address in 2020. We're gonna link to this in the sources. It's pretty awesome. So after a couple years at OBI, his parents are finally able to save up enough money to afford to come to the US themselves.

3 (10m 8s):

So they move first to Tacoma, Washington, the great state of Washington. And then they move a little farther south down to the suburbs of Portland, Oregon. Jensen and his brother go home, they live with them. They go to public school there. You know, Jensen continues his, his American upbringing. He gets really into table tennis. He places third in the junior nationals in table tennis and he gets his picture in Sports Illustrated going on. Oh

2 (10m 36s):

No

3 (10m 36s):

Way. Pretty amazing. But his parents continue their sort of like academic discipline and Jenson's super smart obviously he ends up skipping two grades and then going to college. He goes to, in-state college he goes to Oregon State University just down the road a little bit.

2 (10m 53s):

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

3 (10m 55s):

He got there when he was 16 'cause he had skipped a couple grades and he loves math. So he decides he's gonna major in electrical engineering at OSU and he totally falls in love in more ways than one. The first way that he falls in love is he just thinks 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 they don't use like enough precision when talking about like exact numbers.

2 (11m 26s):

Which he later comes to say that he respects the opposite position. I think some of the Nvidia employees call it CEO math when he sort of rounds all the numbers and he's like, 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.

3 (11m 44s):

That's so json like he understands like, yeah my employees get mad at me when I you know, round the numbers and you see O math and like I get it. Like I appreciate precision too but you know like the big picture is what matters here. The second way he falls in love is with his lab partner in electrical engineering fundamentals. His lab partner Lori who goes on to become his wife. That's a cool story. So he graduates in 1984, she graduates in 1985, they moved down to Silicon Valley and Jensen joins a MD as a sort of equivalent of like a chip design pm Hmm. It's very like engineering heavy but he's kind of like a pm.

3 (12m 25s):

He's sort of like helping as a junior manager of a, of a process for developing a chip. He's working on a then blazing fast one megahertz CPU chip.

2 (12m 36s):

Yeah. He talks about this and he says, you know, he's talking about how slow one megahertz is and he refers to it and says you could even see it coming. It's about how fast it was.

3 (12m 45s):

You could see it coming from a long way away and still coming and still coming. Amazing. And Of course now he makes literally the fastest chips in the entire world. So he starts at a MD, he starts at night working on a master's degree in electrical engineering at Stanford. It ultimately takes him eight years to finish this master's. He works all the time that he's at a MD and then at Ellis I logic where he goes to, we're gonna talked about in a sec, he ultimately does graduate right before they start Nvidia. This is like a super cool bit of trivia. Did you go back and watch the Don Valentine view from the top?

2 (13m 22s):

No, I didn't lecture

3 (13m 23s):

At GSP. Ugh. I watch that like once a year every year, every time there's an excuse. Is

2 (13m 27s):

That the one where he holds up Alfred's resume?

3 (13m 29s):

It's yeah. Where he holds up Alfred Lynn's resume. So also Easter egg in that talk, that was the day that the Jensen and Lori Huang engineering center at Stanford was dedicated. As Don says, Jensen did a building pretty awesome.

2 (13m 47s):

I did watch, he gives a talk where he wa he walks in and gives a talk at Stanford. I think it's the first time that Jensen has given a talk since the building opened and he says, I've donated, we have this nice building now so I I have no more money. Yeah.

3 (13m 60s):

A penniless I think on Penn

2 (14m 1s):

Less.

3 (14m 3s):

Right, right. Jetson So great. Just

2 (14m 6s):

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

3 (14m 11s):

I think he owns what like three and a half percent of Nvidia? So something like that. Something like that, yep. Yeah, he's not penniless. Okay. So he works at a MD for a couple years and while he's working there, probably from working on this chip that you can so fast, you can really see it coming. He realizes that designing chips is really freaking hard. Intel can do it, a MD can do it but you know there's not many companies, it's all like full stack at this time. You know, TSMC doesn't start till 1987.

2 (14m 39s):

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.

3 (14m 56s):

And Jensen talks about like when he was in school, the reason he wanted to go to a MD was he thought this was so cool that like you could do it all. And then once he's actually at a MD he's like, he realizes like it's actually not cool. Like it would be cooler if you could be really good at like a certain part of the stack and have tools and platforms and other companies to allow you to allow anybody to make chips.

2 (15m 17s):

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

3 (15m 22s):

So after a couple years his office mate at a MD leaves and goes to join a startup called LSI Logic, which had just gone public and we've talked about it on the show, made Don Valentine and Sequoia, the then largest venture return in an IPO in history. Maybe the largest venture return ever in history when they went public of $153 million on day one.

2 (15m 54s):

Boy has venture changed as an asset class.

3 (15m 56s):

But that, I'm trying to think that fund that probably would've been, I don't know Sequoia fund two or three maybe. I Mean I bet the fund was like, I don't know, 10, 15 million. Like so probably roughly 10 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 asics company as IC application specific integrated circuit companies. And so what they did and what that meant was they basically made custom design chips for other companies. That's what Jenssen'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.

3 (16m 43s):

So like defense companies, Lockheed Martin and the like. But lots of other companies now too are coming to LSA logic and the other asics companies and saying Hey we want to create these systems of chips. You help us design the chips to go into these systems and yeah we'll use processors from, you know, Intel too. But like it really helps democratize making end product systems.

2 (17m 7s):

Right? And the idea with Asics is really if you're not saying, hey 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, 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.

3 (17m 43s):

Yep. And the legacy of asics today still around, still used both Asics but the legacy is FPGAs field programmable array chips that are, you know, some might say is sort of a bear case for Nvidia these days. But we will, we will get to that far, far, far down the road. Sun Microsystems was one of their biggest customers and that was how Sun got started and made the shifts for their workstations. And in fact Jensen, when he shows up at LSI Sun is like just starting and coming to LSI and so he gets put on the project, he basically embeds with Sun like in the early days of Sun Microsystems to help them build out the chips for what would ultimately become the Spark Station one Sun's first big workstation product over the next few years.

3 (18m 33s):

He pretty much exclusively works with Sun while he is at LSI Logic, he works directly with Andy Bechtel Stein who you know, the founder of Sun and with Bocco look. Yeah he becomes super known and develops quite a reputation there as somebody who can really like take these visions for chips and these customer requirements from Sun and turn it into, you know, reality and production. So one day right around Thanksgiving 1992, Jensen has finally, after eight years finished his master's degree at Stanford. And Stanford is quite quite glad that he finished before this happens. Two of Jenssen's buddies who he's become close with at Sun, Chris Malachowski and Curtis Preme who in Jenssen's own words, he describes them as really, really fantastic engineers.

3 (19m 26s):

And when Jensen says that he means it, they come to Jensen and they're like, we're not like super happy. It's Sun the two of us. We have an idea that we want to talk to you about. And Jenssen's like, well sure let's go meet at my favorite spot Denny's. Really? Yeah. Like the man loves Denny's, he worked at Denny's in high school, like he's always going to Denny's. He, he orders the Superbird I think is like his go-to dish. Nice. He's so folksy. I love him. So they go all have dinner at Denny's and Chris and Curtis pitch him on their idea, which their idea is it's pretty good, it's pretty good. Tell me as a venture capitalist if you would fund this idea back then in late 1992.

3 (20m 6s):

So they see 3D graphics are really becoming a thing and you know, remember this is the era of Sun Now Logic, all this stuff. It's also the era of Silicon Graphics right down the street right there in Silicon Valley. SGI, so many great things that come out of there. You know, Jim Clark, Netscape, like all this great stuff. Jurassic Park. Jurassic Park is about to come out, it comes out in 1993. So there's this huge demand for 3D graphics the way 3D graphics are done. You need SGI workstations, you need like super custom, you know, very high end, very expensive stuff. Only something with the budget of like either the military or like a Jurassic Park can afford to do this.

3 (20m 49s):

But people love it. Like the consumers love 3D

2 (20m 52s):

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

3 (20m 57s):

Well we're still in the super Nintendo days, so we're not at 3D console graphics yet. That's coming very shortly. But what is happening is the PC wave is like really cresting right now. Like

2 (21m 12s):

We're like a year and a half from Windows 95 coming out

3 (21m 16s):

And I remember doing this I bet you do too. Or kids in 19 92, 19 93 doing on their PCs they're playing Wolfenstein 3D Oh yeah. And Doom Doom comes out in 1993. These are taken the world by storm and they're made by i i software in Texas and John Carmack and John Romero. But Carmack is like doing incredible feats of engineering to get 3D graphics to run on consumer PCs. It took somebody of CarMax caliber to make this happen and the market loved it. So the idea that Chris and Curtis has, they're like, we're really great chip engineers Jensen, you're a really great, 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 to enable 3D graphics like SGI is doing with professional workstations to enable them for consumer hardware, PCs.

3 (22m 17s):

We know that people love games. This will help the entire industry, you know, take off.

2 (22m 22s):

And you're not even saying it 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 games on, on a pc, right?

3 (22m 35s):

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. But they'll just develop on PCs. It's really about getting the, like the hardware into consumer's hands that they can actually play this stuff.

2 (22m 57s):

Hmm.

3 (22m 58s):

All right. So what do you think? Is this like a good pitch?

2 (23m 1s):

I Mean so what you're basically asking me to believe 1992 me is that video games on PCs are gonna be a thing that there's gonna be a 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.

3 (23m 23s):

Well I have this proof point of of IT software and, and Wolfenstein and Doom right there of like millions of people doing this. But

2 (23m 30s):

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 to totally change the development environment or can like there be like five or six different dooms out there, there's five or six CarMax who are all independently geniuses and can figure out how to do all the graphics on their own. Yeah, maybe. But there's a leap of faith.

3 (23m 55s):

Yeah, definitely a leap of faith. So yeah, okay. Not totally obvious 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 chips and cards that plug into consumers PCs, this was full swing. There are companies making sound cards, there were companies making networking cards, there were companies making serial port cards like god knows what.

2 (24m 25s):

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.

3 (24m 44s):

Yeah. And so the pitch is we're gonna make a custom graphics card take a graphics workload off the CPU specifically for gaming.

2 (24m 50s):

Great.

3 (24m 51s):

Okay. So yeah, it was pretty much a brain dead. Yes. But as you alluded to at the top of the show, the problem when something is a brain dead Yes for venture capitalists is that it's a brain dead. Yes. For lots of venture capitalists and lots and lots and lots of companies get funded to do this. But back to Denny's that night, Nvidia is the first, they are the first dedicated graphics card company. They all decide the three of them that they're gonna go in on this. Jensen goes to the CEO of LSI Logic walks into his office and tells him that he's gonna resign.

3 (25m 38s):

He's gonna go start this company with two engineers from Sun and this is what the business plan is gonna be. Now do you know who the CEO of LSI logic was?

2 (25m 48s):

No,

3 (25m 49s):

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

2 (25m 58s):

No way.

3 (25m 59s):

Damn right.

2 (26m 1s):

So is that how Don, 'cause Don Valentine obviously was the biggest investor in, well Sequoia was in Ellis I logic and he, did he know him from Fairchild? Yeah,

3 (26m 9s):

They were colleagues back in the day.

2 (26m 11s):

Ah, okay.

3 (26m 13s):

And then the biggest exit in in Sequoia's history to that point in time. So Wolf says, so lemme 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. And Wolf 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 we think if we build it like they'll come. So Wolf says, remember he was a Fairchild. He said, I was like, he knows when to make silicon for specific applications. And Wolf says, Hmm, All right, you'll be back.

3 (26m 52s):

I'm gonna hold your desk. But in the meantime before you go, I'm gonna call up Don, I'm gonna do, you've done good work for me. I'm gonna call up Don. He calls up Don and he is like, Don, I got a kid, he's gonna come see you. Standby.

2 (27m 9s):

Which this is a lesson for all founders and you know, aspiring founders out there, getting a reference from the CEO of a portfolio company is a really good way to come in with a venture capitalist already leaning toward investing. Especially if you're referred by the top performing company of all time in their portfolio. Yes. It's kind of hard for Jensen to mess up this pitch with the recommendation that he's coming in with.

3 (27m 36s):

It's literally impossible because he goes to see Don, you know Don, you know Don sits down and he is like so, and Jensen completely botches the pitch. He gets like really nervous

2 (27m 50s):

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 Barfs all over Don.

3 (28m 7s):

Yes, exactly. So Jenssen's walking out the door, he's like, you know, totally dejected. Don stops him and says, well that wasn't very good. But Wolf says to give you money, so against my best judgment based on what you just told me, I'm gonna give you money, but if you lose my money

2 (28m 33s):

I'll kill you.

3 (28m 35s):

Classic, classic Don line. So good. So the deal happens, Sutter Hill comes in too 'cause you know, again, like Alyssa's all dramatized at the end of the day, like this is a hot deal.

2 (28m 48s):

This is two episodes in a row for us with Sutter Hill.

3 (28m 53s):

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

2 (29m 0s):

They invested like a million each. Is that right? For a total of two.

3 (29m 4s):

So $2 million total round. I don't know who invested what, I assume a million each but $2 million total round at a $6 million post money valuation. Remember everybody, this is the eighth most valuable company in the world right now. Started at a $6 million post money valuation. So they're getting things ironed out and there's just one problem. They don't have a name for the company yet. Jensen and Chris and Curtis, they've just been, you know, working on this, working on the business plan but they don't have a name they need to incorporate the company and they were saving the files that they were working on for the chip design for the first graphics chip as nv NV being short for next version.

3 (29m 51s):

And so they're 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, 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 envy, this is awesome.

2 (30m 15s):

Of course they pick green so later on they can have that marketing campaign of green with envy.

3 (30m 20s):

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

2 (30m 31s):

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 wanna 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 they're doing a thing here that like, well 89 other people are also sort of simultaneously doing it is kind of a new frontier that they need to invent and then own like thought leadership in that area. And they do need to kind of like quickly build a brand not only with consumers but with PC manufacturers. Jensen, the way he sort of describes it is that their vision, although he doesn't like the word vision 'cause he thinks it's exclusionary to people.

2 (31m 16s):

So he said, our perspective is that they want to enable graphics to be a new medium to tell stories. And here's sort of like the way that he articulates at the time why video games today are $180 billion a year industry bigger than Hollywood, bigger than music. It, 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, but if you could, it's really interesting because it's not prerecorded 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.

2 (31m 56s):

And so therefore it's the only one that can really be like social and interactive. And so our reason for being is to create 3D graphics as a form of artistic storytelling for the future and everything will be in service of that. And I think that's not really what they are today necessarily. It's a piece of what they are today. But that kept them going for the first 20 years of their existence. Well

3 (32m 22s):

And baked into that is again, you know, Wolf kind of like hit on and and you did too, to your credit, you're a very good venture capitalist. You hit on really the key problem with this first iteration of Nvidia, which is they have to go evangelize to developers to like, yeah there's it and there's carmac out there, but like not a whole lot of other PC game developers out there. There not a whole lot of other 3D PC game developers at this time. There are 2D PC game developers, but they gotta convince a whole lot of people to go, you know, learn how to do 3D game development for PCs. And that's so like, oh we're gonna enable storytelling, all that.

3 (33m 2s):

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

2 (33m 17s):

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

3 (33m 23s):

Exactly. So at first things start off really well. Remember this is super hot. They're the first company, they're funded by Sequoia and Sutter Hill. Like they land a big deal with Sega to power their archaic consoles and their next generation home console to be the 3D graphics engine and would ultimately become the Sega Saturn. And as we know from our Sony episode,

2 (33m 50s):

Not quite the Sega Genesis,

3 (33m 51s):

Not quite the Seig 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 people probably know you create 3D graphics, you use polygons. That's why people are always talking about polygons in this industry. They have to decide on a sort of primitive for the polygon. They're like, oh well we'll use Quadrilaterals for Vertex. You know, and anybody who knows anything about video game development now is like, that's not how it's done. Like

2 (34m 21s):

I'm pretty sure people talk about triangles.

3 (34m 23s):

Yeah. And I'm pretty sure if you look at NVIDIA's amazing headquarters building today, it's you know, made out of triangles in a homage to game developers, not quadrilaterals. So this becomes a pretty big problem. You know, things go along for a while. It's like fine for about a year NVIDIA's leading, they got this big Sega deal.

2 (34m 42s):

There's not a reason to need standards yet. Right? The industry isn't complex enough yet to necessitate a whole bunch of collaboration and set of tools that everyone standardizes on using. You're like, okay well we're just going to put this chip in our game console, ship the game console. We're the only people that you know make an SDK, we being Sega. So everyone will have to kind of standardize on this thing anyway, so great. But obviously the ecosystem gets much more complex much more quickly and it sure would be nice to have some kind of compatibility.

3 (35m 13s):

Well here's what happens. So you know, Curtis and Chris and Jensen, they weren't the only people in Silicon Valley that saw that kids wanna play games on PCs with Doom. Microsoft is like, oh that's interesting. We like selling PCs and gosh there are all these graphics cards companies out there now that are doing this. And you know, what do we do as Microsoft? We really wanna encourage this in the ecosystem. Well we create standards.

2 (35m 44s):

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.

3 (35m 54s):

Yeah. You know, developers want to do 3D graphics directly into Windows without any of this, you know, crufty middleware from some no name company Nvidia out there. Why don't we just bake these APIs right into Windows directly for 3D graphics, we'll call it Direct 3D. And Of course anybody who knows about the history of this that becomes Direct X

2 (36m 17s):

And Direct X made some pretty different design decisions than Nvidia had made. Is that right? Yeah.

3 (36m 22s):

So they use triangles because triangles make sense. So now NVIDIA's really up a creek like all of their com, you know the 89 other competitors out there that started later, most of them are like, sure I'm gonna jump on board of this Microsoft ecosystem. Like I would be dumb not to. It's standardized on this completely different paradigm than Nvidia. And then Sega, you know, they've got Sega, they've got this one sort of customer and then in 1996 sega's like yeah we're not so sure about this quadrilaterals thing either. And

2 (36m 57s):

Just so that like this doesn't feel arbitrary why we're talking about this. And we're gonna say at a super high level on 3D graphics here, rather than really going into the weeds, but a triangle is the fewest vertices in a shape that you can have while still creating a two dimensional shape. And so it serves as a basic building block where assuming you can draw enough triangles and make the triangle 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.

3 (37m 31s):

Yep. 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. Nvidia was calling the NV two when Sega comes back and says We're switching horses, we're not gonna do this. So like they're screwed for so many reasons. Everything we've discussed. There's also in the interim, you know, year and a half since Nvidia started, the price of memory dropped because thank you Moore's law. So NVIDIA's chips were designed to be like super, super tight on memory and the memory cost about $200 in component, you know, parts to go into their chips, their competitors have more memory that's costing them like $50.

2 (38m 18s):

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 its advantage. But second of all, everyone else's cost structure was way lower or at least everyone else could see that the cost structure was getting way lower. And so Nvidia sort of designed for a constraint that was no longer true by the time everyone else came out with their stuff.

2 (38m 58s):

At this point, Jensen and his co-founders kind of had to look at each other and say, okay, do we scrap everything we did? And if so, how do we not make this mistake again? How do we make sure that in future generations we sort of premeditate the exponential curve of Moore's law and prices coming down and design for things that are, you know, 2, 3, 4 generations beyond what we actually have available to hardware right now.

3 (39m 24s):

So when all this goes down, the company has about nine months of runway left and like, 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 effed. And I can't imagine sitting there dreaming up a way out of this, but Jensen god he's such a g, he's like, no we're not going out like this. You know when you hear Jensen talk today about like NVIDIA's culture and he says that intellectual honesty is like the cornerstone of NVIDIA's culture. Like this is what he's freaking talking about. Like he sits down with Curtis and Chris and remember they're like they're engineers and they've recruited Nvidia a hundred plus engineers into the company at this point and sold them on this technological vision of we're gonna define the industry.

3 (40m 16s):

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 Jenssen's like guys, like this is a pipe dream. We need to throw it all out. If we're gonna survive, the only thing we can do is standardize on on the same Microsoft, you know, direct 3D as everyone else, same architecture. And our only shot is just to like compete on performance and try and become like the best chip out there in this now sea of commodity chips. And you know, his co-founder like don't want to do this. This is not an exciting vision for a Silicon Valley engineer.

2 (40m 56s):

When your CEO comes to you and says that what they're basically saying is, look, if my job was strategy and your job as 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 at a lower price point using less energy than our competitors. Because Microsoft being Microsoft had all the developer attention and because Microsoft set a standard Nvidia realized, look, we have no ability to uniquely get our own developers at least at that point in the company's history. And so we must just on our left look and see all the developers are coming from Microsoft using this API on our right is all the same consumers and we have to compete just head to head on raw engineering ability with everyone else.

3 (41m 46s):

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? Mm. Like how fast can you design the next generation of chip and can you ship it before everybody else because everybody knows what's gonna be in that ship and

2 (42m 5s):

Why is it, what fundamentally about was it about graphics cards that made it a commodity?

3 (42m 12s):

Well at this point, like all the other peripherals and 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 3D graphics processing out of the CPU and onto this other chip on the motherboard just like sound cards. Were doing the same thing for sound just like networking cards. Were doing the same thing for networking. And it was just like, what's the price performance ratio of doing that? The interfaces and the programming language that's all standardized by Microsoft. You're just commodity hardware.

2 (42m 47s):

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 in the highest resolution that I can or I suppose a standard predetermined resolution as

3 (43m 10s):

Fast as I can. And that'll drive the resolution

2 (43m 12s):

Output a 2D thing that goes on the screen. So I turn 3D stuff into 2D stuff and I have to do that better than other things that I'm competing against where basically all of us are, when you say commodity, you mean limited by Moore's law and doing right up to the edge of what integrated circuit manufacturing techniques enable us to do.

3 (43m 31s):

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 70% of the company, which they do, they go down to about 35 people and everybody who's staying knows we now have to design from scratch and ship a new chip before our runway runs out, which is nine months. You can't do that on a normal chip design cycle.

2 (44m 4s):

Takes like two years, right?

3 (44m 6s):

Yeah. The way that, you know, in the, with these fless chip companies, the way they would design chips is they would work on the design, they would send them over to the Fless company, the Fless company would produce some prototypes, they'd send them back, they'd test 'em, they'd go back and forth a few times.

2 (44m 20s):

You mean the foundry would produce 'em like the TSMC or the Samsung or the global foundries or

3 (44m 26s):

Now importantly Nvidia is not using TSMC at this point. 'cause they can't, they can't. T-S-M-M-C only works with the best and Nvidia is not the best. Huh? So they're using like second rate foundries and that process takes a long time. And then at the end of it, when you're sure you've got the, the design right, then you do what's called a tape out of the chip.

2 (44m 45s):

I love this term by the way.

3 (44m 46s):

It hearkens back to literally like when you used to tape, you know, masks to like do the photolithography on the chip back in the day.

2 (44m 54s):

So cool.

3 (44m 55s):

But it just means finalizing the design.

2 (44m 57s):

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

3 (45m 13s):

Yep. So they're like, we, we can't do this. They're like jenssen'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 and in our case we're gonna use it to emulate the graphics chip that we're, we're designing all in software. And it, you know, it works,

2 (45m 34s):

They're startups but they exist.

3 (45m 37s):

The problem is when you emulate it in software, you know, it's like it's really slow. So you know when you play a game and you're, you are looking at your computer or monitor or whatever, it's refreshing 30 to 60 times a second. If you're a professional gamer, you probably have it going at like 120 times a second, you know, frames per second. This emulator runs at one frame every 30 seconds. So they're gonna have to debug this thing in software to save this time going at one frame every 30 seconds.

2 (46m 5s):

It's just insane. That's

3 (46m 7s):

Brutal.

2 (46m 8s):

They're basically making this trade off of okay, if we wanna 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 30 seconds and look against some tests to verify that the output is correct. And if it is and this person does that mind numbing work and sits there just observing and observing and observing, then we will go right to manufacturing without ever producing a physical prototype and ship that.

3 (46m 47s):

And that is exactly what they do. They had to spend a million dollars just to get the emulator, you know, hardware and software to, to do this. Which

2 (46m 56s):

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.

3 (47m 3s):

So they go down to six months until their cash out in the company, they get it done in a few months and then they call up their foundry, I dunno if they're using United or or one of the, one of the other foundries in Taiwan, not TSMC. They're like, All right, we tape this thing out, send it to production and the Foundry's like, are you guys sure about that? They're like, yep, we're sure make you know, a hundred thousand units

2 (47m 28s):

If I'm remembering right. I think Nvidia basically was the only customer of that emulation software. Like that was a startup that really wasn't fully proven yet. But Nvidia was like, look we literally have no options.

3 (47m 42s):

Yeah they were the only customer and then that, that company went out of business after

2 (47m 46s):

It's wild.

3 (47m 47s):

Well and so the chip they designed so now the advantage like this is lunacy what they're doing. Obviously they have to do it 'cause their back is against the wall. The advantage of this though is they are now designing this chip with, you know, the same set of assumptions about what, 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 'em out for like 18 to 24 months. NVIDIA's gonna get this same, you know, generation of design out in six months. So this chip is called the Riva one twenty eight is what they call it.

3 (48m 27s):

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

2 (48m 33s):

It's big.

3 (48m 34s):

It's big. It's extremely powerful relative to anything else on the market.

2 (48m 38s):

Like more powerful than any customers are telling them they want. Yeah.

3 (48m 41s):

Way more powerful. Way, way, way, way, way more powerful. But you know, it comes with some downside with great power comes, you know, great 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 3D at the time had something like, let's call it like twenty four, twenty five different ways, like different sort of techniques.

2 (49m 7s):

These are the like blend modes.

3 (49m 8s):

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 'em. It just like freaking crashes. Like it just doesn't work. I

2 (49m 16s):

Thought even worse than that but basically like I, I think Nvidia had to launch a campaign going around to like 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 work. Great. You're gonna love 'em. They're so good and just use those.

3 (49m 39s):

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. But now they're actually going out and Jenssen's going to these developers trying to convince them to do this. And they all do it. Why do they do it? Because the only thing that matters is performance. Consumers are gonna buy hardware and games based on the quality of the graphics. This is like being discovered for the first time.

3 (50m 19s):

And so like people are willing to make a lot of compromises in, you know, service of performance. Nvidia is like the first one that figured this, this out because they have to go around and do this and developers all get on board.

2 (50m 31s):

And to be clear, it's because the consumer's making the buying decision right. On what graphics card they buy.

3 (50m 37s):

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, that's what NVIDIA's business is.

2 (50m 49s):

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.

3 (50m 60s):

Exactly. And the game developers are making decisions on what graphics cards to support,

2 (51m 9s):

Right.

3 (51m 10s):

And how to build their games with like the assumption of what's my target market of consumers like who do I think will this game run on? Do you need to have at least an X level performance rig in order to run my game or run my game in its fullest form?

2 (51m 27s):

So the developers are premeditating what graphics cards are going to be out in the market when their games launch and they're saying yes, it's gonna be the most performant one at the right price point. So whatever the mass market is, we kind of have to target that. And if you're telling us and we're 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, then people are going to buy that one. And so we must target

3 (51m 53s):

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

2 (52m 4s):

Yeah. What's the relationship between Crisis and Far Cry?

3 (52m 8s):

It was, oh no, far Cry was the first game. Yeah, the crisis engine. And then Crisis also. It was super convoluted. Basically my perception of this thing was when this came out, when Far Cry came out, this was like mid two thousands. The graphics were 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 played more than 10 minutes of it.

2 (52m 32s):

I'm pretty sure if your computer didn't support it, there was all these videos that people would record of like building a tower of like a thousand gasoline barrels and then shooting it and because it was too complex for their graphics card to handle their computer would just freeze. That was the failure mode of Far Cry with non-performance chips.

3 (52m 52s):

This is how the hardcore gaming industry evolves. Like Far Cry sold so much software and so much hardware just because people wanted to experience that, to attempt to experience that level of graphics. And so that's what the developers are starting to figure out and they're like, All right, well if you can ship this thing we'll use only those, you know, eight blend modes or whatever, like whatever it takes. 'cause we want, you know, graphical performance is the most important thing. So it works. They sell 1 million units of the Riva 1 28 within four months. Wow. I should have looked what the MSRP was of it, but that is a lot of revenue.

2 (53m 33s):

Yeah, no kidding. What year was this?

3 (53m 36s):

This was 1997.

2 (53m 38s):

Okay, so we're, it's an interesting era. Like the internet is a thing. We still have a few more years till the.com bubble crashes. PlayStation one is out, but PS two is not out yet I think.

3 (53m 51s):

Yep. PlayStation one. And with that, the gaming market kind of bifurcated into like sort of the, you know, 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. 'cause people are willing to spend so much money on this stuff. So at the end of this, Nvidia has now figured out these dynamics of the PC gaming market and they now have a process within the company to design and ship each next generation of their hardware in a six month timeline while the rest of the industry is on an 18 to 24 month timeline.

2 (54m 33s):

Necessity is the mother of invention.

3 (54m 35s):

To say this is huge is like understatement of the century. Huge. And it's huge for this market. But nobody even saw this at the time. Like Jensen didn't see this, nobody saw this. They're now shipping relatively, you know, doubling essentially the performance in each generation with their hardware and they're shipping it every six months. And you think about Moore's law, right, like Moore's Law was that the number of transistors on the chip equating to the compute power available at a given price point to the market would double every 18 to 24 months. Nvidia is now on a cycle, starting in 19 97, 19 98, where they are doubling the performance that they're delivering at a given price point to the market every six months.

2 (55m 23s):

It's fascinating. And they're also competing on a different vector than the CPU manufacturers because, and it's kind of amazing, we've made it an hour into the episode and haven't talked about this yet, but the magic of GPUs is that they're very, very parallel like cpu for anyone who's taken a low level computing class, you sort of know that like every time the clock ticks an instruction can sort of run and things move through the sort of long chain of operations that can happen within the CPU. And it's advancing things serially through the processor.

3 (55m 58s):

It's serial processing,

2 (55m 59s):

It can read from a register or it can add two things together. But like it's all happening serially.

3 (56m 5s):

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

2 (56m 16s):

Yes, exactly. And with graphics processing, like the magic of it is that it's super parallelizable. Like there's all these things that need to get outputted to the screen that do not depend on each other. And so you can do them independently. And so the vector that they're competing on is really like, oh, we can, and 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. Let's put a pin in that for now. But it's worth knowing the thing that they're doing is figuring out how to process more things in parallel faster.

3 (57m 4s):

Yes. So graphics cards like Nvidia is making at this point in time are really good at, in parallel lighting the pixels on a screen, you know, thirty, sixty, a hundred twenty times a second with the images that are being fed to them from like the game or the graphics program, which is living all in the CPU land. So like you're a game developer, you develop in, you know, Microsoft Direct 3D becomes Direct X or OpenGL is the open source, you know, competitor to this. You know, all that logic is really happening in the CPU realm.

3 (57m 44s):

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 N 64, you look at the graphics in those games or PC games from the time too.

2 (57m 59s):

They're all kind of the same.

3 (58m 1s):

They're all the same, right? All the lighting, like the lighting, it's all like pre-done. So like when you're a game developer, you set the scene, you'd never see like a character running around carrying a torch and that torch light like impacting the rest of the environment, it's all set in advance. Like no intelligence is happening in the GPU level with the screen. It's just lighting up the pixels

2 (58m 24s):

Basically in order to make it easy for developers. The software development kit is written at such a high level that you don't really get enough control to make your game stylistically different. You just get to lay out the items on screen.

3 (58m 40s):

It's all the same, it's all flat. Maybe you can program that like hard code that like, oh, time of day might change and like that might change the way things look but you're hard coding like what they look like. No computation is happening, right? If you're playing a game today, even the most basic, you know, mobile game or whatever, you're seeing dynamic lighting and shading, which we'll get into in a sec all over the place. So this is still like in the, you know, GPUs are like a really, really important sort of commodity, but they're a commodity. There's not a lot of smarts happening here. Yep. 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 now.

3 (59m 24s):

A lot of people start paying attention to them in a good way. TSMC that wouldn't even return Jenssen's calls back in the day. There's this amazing, amazing story. Did you watch the TSMC 30th anniversary? I did Celebration. This is so it's like three hours on YouTube.

2 (59m 40s):

This is worth a brief aside. This is how much pull Morris Chang from TSMC has. He gets the CEOs on stage of Nvidia

3 (59m 50s):

Arm,

2 (59m 51s):

Arm A SML, Qualcomm and Broadcom.

3 (59m 56s):

Yep. I don't think Lisa from a MD was there.

2 (59m 59s):

No, it was basically everyone but a MD of the sort of pillars of the TSMC ecosystem. I Mean Morris is playing interviewer, like it's very entertaining to watch him. It's

3 (1h 0m 9s):

Like a celebration of Morrison, of of TSMC. It's amazing. It's amazing.

2 (1h 0m 13s):

Yes.

3 (1h 0m 14s):

So in the section with Jensen, they tell the story of how Nvidia at this point it's gotta be TSM C'S biggest customer. I Mean they've been like tied at the hip forever of how this all came to be after the Reva 1 28 hits and it's become a big success. Jensen writes a letter to Mor, like a physical letter addresses it to Morris Chang in Taiwan

2 (1h 0m 40s):

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

3 (1h 0m 44s):

Exactly, exactly. They've all just been ignoring him as well. They should because they were a, you know, left for dead startup in a sea of startups. The letter gets to Morris, he opens it, he reads it in Taiwan, he does the most Morris Chang thing possible. He calls up Jensen on the phone right there and the phone rings as they tell the story in the Nvidia office. This is in the middle of their trying like mad scramble as a startup to ship these Riva one 20 eights that are coming in. They're testing 'em all by hand in the office. 'cause none of this stuff was, it's fresh off the line, it's not been tested, it's chaos. Jensen picks up the phone and is like, yeah, who's this? And Morris is like, hello, this is Morris Chang at tsmc.

3 (1h 1m 27s):

I got your letter and Morris says that there's like a silence on the other end for a couple seconds and then he hears Jensen yelling, everybody shut up. Morris Chang is on the phone. Oh amazing.

2 (1h 1m 42s):

And that's how TSMC became the manufacturer band video chips.

3 (1h 1m 46s):

Yep. The next year the two companies sign a huge multi-year deal for TSMC to become the primary foundry for Nvidia and still are today Jens and Morris are super close. It's a landmark landmark deal for both companies. So with now an actually really good foundry as their partner and this super unique chip development process, Nvidia just keeps accelerating. So in 1999 they rebrand their products. You know, they'd use the NV one first and then this REVA 1 28, they actually run a little contest of what they should name the products.

3 (1h 2m 28s):

And the winning name is geometry force forces with you, which they shorten to GForce, which anybody who knows who you know buys graphics card, the Nvidia GForce still the brand name they use for their gaming cards today and is probably the most, one of the most respected, you know, brands in the gaming ecosystem. And it's because this card that they ship the first G GForce in 1999, it's the GForce 2 56. It's so powerful. It has five x better graphics performance than like anything else on the market.

2 (1h 3m 7s):

And they call this like the first GPU, right? Don't they say like we're inventing the GPU. They

3 (1h 3m 12s):

Call it A GPU before this, the term GPU didn't exist. It was, these were graphics cards, graphics tips.

2 (1h 3m 19s):

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

3 (1h 3m 27s):

So they market this as the graphical processing unit. Now on the one hand that's like sort of like marketing bravado on the other hand that is like a very loaded statement to make and why, so what does Jensen and Nvidia mean by this? So Intel, you know, you think chips, you think Intel, right? You think Silicon, you think Intel. Intel's whole strategy at this point in time was basically they're almost like a biotech companies today. Like one of the big pharma companies and or, or put another way, it was another version of the Microsoft embrace extend extinguish thing.

3 (1h 4m 9s):

They would see they're all these peripherals sound cards, networking cards, all the see graphics cards, all the stuff we've talked about. They would let all these flowers bloom be like, oh yeah, yeah, yeah just plug into the PCI slots on our motherboards. No big deal. We're an open ecosystem, we want everybody to flourish. And then they would see which of these, you know, peripherals got consumer traction and then they would just turn 'em into, you know, a component in the motherboard

2 (1h 4m 36s):

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

3 (1h 4m 44s):

Well and before that, you know, integrated sound, integrated networking, like remember, oh it was so fun doing this research. Remember the company Creative and the sound blasters cards.

2 (1h 4m 53s):

Oh yeah, I remember

3 (1h 4m 54s):

Buying tons of that stuff. Like, and then at a certain point you stopped buying sound blaster cards, right?

2 (1h 4m 59s):

You're like, oh the motherboard does 90% of what I need to do and why would I spend extra money on a separate thing?

3 (1h 5m 6s):

Exactly. And so Intel, they'd just sit back, they'd watch all this happening, they'd integrate it game over for the startups.

2 (1h 5m 13s):

And there was like reasons for specialized stuff. Like I remember buying a special network card because the integrated networking capability of the motherboard on my, I don't know what it was a Mac 8,500 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 graphics card or you'd buy it directly from the OEM when they were making the computer and shipping it to you.

3 (1h 5m 47s):

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 outta

2 (1h 5m 55s):

Here. These things are like dead end businesses

3 (1h 5m 57s):

And there's no reason why graphics cards wouldn't be the same. So Jensen and Intel coming out and being like we're a graphical processing unit, we're a GPU, it's a big middle finger to Intel and this whole CPU dominant world

2 (1h 6m 15s):

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

3 (1h 6m 29s):

Yep. But this is where, you know, Jensen is just such a master strategist and Nvidia is so great, like this whole kind of orchestration of a bunch of things all hit over the next couple years. So first Nvidia goes public, you know, they've now shipped the REVO 1 28 was a huge hit. This new GForce 2 56 flying off the shelves, they go public in beginning of 1999 at a $600 million market cap. So a hundred x return from the $6 million post money valuation on the Sequoia and Sutter Hill round that gets them, you know, some more capital. And then behind the scenes they're working, they're in talks with Microsoft.

3 (1h 7m 12s):

Microsoft's got a secret project that they're working on at this time. The Xbox, which you know, we talked about a lot on the Sony episode and so many times on the show and Microsoft comes to Nvidia and like we want you to be a key supplier of the graphics at the GPU for the Xbox. And they do a huge, huge deal. $500 million a year deal for Nvidia to supply the graphics for the Xbox with a $200 million advance. Hmm. And the chip that they use is a modified version of this incredible new chip that NVIDIA's working on.

3 (1h 7m 57s):

This sound like Steve Jobs, David Jetson sounds like Steve Jobs talking about this. The GForce three which introduces for the first time programmable shaders and lighting on the GPU. Everything we just talked about about though like the GPU massively parallel can light all these pixels, but it's essentially just taken instructions that are pre, you know, hard-coded, baked in on what the lighting's gonna look like. Now you can program for these GPUs and you can make dynamic lighting in games and 3D graphics that is calculated.

2 (1h 8m 35s):

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 at the GPU level what is happening. And so this is like Of course it's cool because it's a wave of new consumer experiences that can happen because every game developer can kind of stylistically put their own stamp on games. But it's a totally different metaphor for the computer architecture where suddenly you can program A GPU and I guess that's why they're calling it A GPU.

2 (1h 9m 18s):

And this is different than a graphics card.

3 (1h 9m 20s):

And NVIDIA develops in conjunction with this, they call it CG, literally like they extend the C programming language with graphics libraries and capabilities to directly program graphics and lighting and shaders for the GPU. So this makes, you know that sort of like marketing, you know, oh this GForce 2 56, it's a GPU now it's real. Like this is a graphical processing unit that is intelligent, that is every bit is, you know, maybe not every bit as important as the CPU yet, but like this is like the stake in the ground of like this is no sound card, this is not gonna get commoditized.

3 (1h 10m 2s):

Do you

2 (1h 10m 2s):

Know if this was the GForce FX or if the GForce FX was a similar version of this that was available to pc?

3 (1h 10m 9s):

That's a good question. It was the GForce three was the, the PC version of this.

2 (1h 10m 14s):

Okay. This move to programmable shaders was a bet the company move and it was jenssen'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.

3 (1h 10m 42s):

Yeah, I Mean this is the, you know, 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 enormous. So at this point Intel's like we might have a problem here,

2 (1h 11m 15s):

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.

3 (1h 11m 22s):

Yep. And irony of ironies Jensen presses this even further. He does a big partnership with a MD. It's

2 (1h 11m 28s):

Worth knowing here when you're saying a MD, 'cause people probably know A MD and Nvidia are big competitors today in the GPU world.

3 (1h 11m 34s):

Not yet.

2 (1h 11m 35s):

Right? A MD primarily made CPUs at this point. They made processors and competed with Intel. They hadn't yet bought a TI, which is where the Rayon business comes from. That's all the graphics stuff that they do today.

3 (1h 11m 46s):

Yeah. A TI at this point was the number two competitor. Nvidia. Actually an amazing story too was a Canadian company started in the eighties and pivoted into graphics cards. Like very different, you know, I feel like there's a lesson in here, right? We could talk about this in playbook, but like when all the VCs funded these 90, you know, Silicon Valley startups to go make graphics cards, 3D graphics cards, the only two surviving ones were Nvidia, which went through this hellish journey and then these Canadian guys that were like totally outta the ecosystem and like did it sort of more in a boot, more bootstrapped way and evolved into this space.

2 (1h 12m 25s):

Jensen has a great quote about this and he's giving this lecture at at Stanford years later and he says, when technology moves this fast, if you're not reinventing yourself, you're just slowly dying. You're slowly dying, unfortunately at the rate of Moore's law, which is the fastest of any rate that we know. Yep. It's so clarifying of how he thinks about why Nvidia needed to do these like three complete transformations of the company. Bet at all. Risk at all. 'cause if you're not, you're one of those 89 companies.

3 (1h 12m 57s):

Exactly. So Intel's like holy crap, we might have a problem on it. Not, not a problem. Like this is not a problem for Intel.

2 (1h 13m 6s):

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

3 (1h 13m 11s):

Right. Intel is used to at this point just, you know, like Microsoft at this point. Oh sure. You know, you want to go make Word perfect, 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 dedicated Intel graphics, you know, GPUs, graphics cards competing as separate cards. Whoa, I don't know that Intel had ever done that. I Mean I may be speaking out of turn here, but like as far as I know, I don't, this is not a common strategy for Intel. It's usually integrate Yeah, into the motherboard and the CPU U.

3 (1h 13m 52s):

They come out with their own external cards right around this time, like 1999 to directly compete and like they suck. Like these are like some of the worst reviewed graphics cards in history.

2 (1h 14m 3s):

Talk about not your core competency,

3 (1h 14m 5s):

Not your core competency.

2 (1h 14m 6s):

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

3 (1h 14m 35s):

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 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. And especially leading into, you know, mobile. Although Intel and mobile is a story for another day, but for the hardcore market and that that's, that's making it sound too small for the market of anybody who cares about graphical performance and quality, which is not just gaming at this point, you know, it's 3D modeling it's architecture, it's lots and lots of graphical high performance graphical computing applications.

3 (1h 15m 25s):

You're always gonna want. It's this dynamic and it sets up just like Moore's Law, whatever the current maximum is, it's not enough. It's never enough. You always want more as good as graphics are today, it'll never be good enough 10 years from now, game graphics will make today's graphics look silly and we'll all be in the Metaverse or the Omniverse if Nvidia has their way. But it still won't be good enough. Like it's Moore's law, you always want as much performance as possible.

2 (1h 15m 51s):

All right listeners, it is time to talk about one of our favorite companies Stat Zig. It's funny David Stats Zig has gone from this little startup when we first started working with them a couple years ago to this total powerhouse now

3 (1h 16m 4s):

I know, it's wild. I was looking it up and they have added all these customers since we started working together. OpenAI, Figma, Atlassian, versa Notion, tons more at this point. If there's a growth stage tech company out there, there's a pretty good chance they're using Stat Zig.

2 (1h 16m 19s):

Yep. So listeners, if you are unfamiliar with Stat Zig, they basically took what was the standard product infrastructure at every big tech company and they built it as a standalone company. This includes advanced experimentation tools, AB testing, feature flags, product analytics, session replays and more. So if you're building the next great software company, this sort of infrastructure is essential because it allows your product and engineering teams to release things quickly, measure the impact of them and track progress over time.

3 (1h 16m 49s):

Totally. So I Mean as we've talked about on the show forever at companies like Facebook or Netflix, data was just a part of how everything was built, which contributed to all the crazy bottoms up organic growth that they had. Now with Stat Zg, you can get that from day one at your startup. And today they're not only trusted by startups but also by more mature enterprises like Bloomberg and Microsoft and electronic arts turns out that a single system for data-driven product decisions is useful at any scale.

2 (1h 17m 15s):

Yeah. And by the way, the scale they're operating at is completely insane. They process over 2 trillion events per day. Now by the way, David, this is updated, the last I checked it was 1 trillion and then this morning I pulled it up 2 trillion and they handle releases to billions of end users. If you're listening to this podcast and you've used software in the last few years, there is a very good chance you've been a part of many experiments orchestrated by stats.

3 (1h 17m 39s):

Yeah, it's just awesome. And as they've gone up market, they've also started to offer some interesting deployment models like being able to run the whole thing natively inside your existing data warehouse or just using Stat Z's fully hosted solution.

2 (1h 17m 51s):

If you want to leverage Stat Zig to grow your business, there are a bunch of great ways to get started. Stat Zig has a very generous free tier for small companies, a startup program with a billion free events that's $50,000 in value and significant discounts for enterprise customers. To get started, go to stats z.com/ Acquired and just tell 'em that Ben and David sent you

3 (1h 18m 13s):

Thank you stats Zig.

2 (1h 18m 14s):

Okay David, so Xbox comes out, Nvidia has a card in there that is the, the GPU of the Xbox that has programmable shaders. So you know, rather than, 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 What happens after that?

3 (1h 18m 37s):

Basically the company goes like Supernova in a good way, in a good way at this point in time. So the fiscal year that ends January 31st, 1999, this is like right before they go public or right as they go public. They did $158 million in revenue the next year. The fiscal year ended January 31st, 2000. So like the calendar year 1999 they do $375 million in revenue. So more than double that year. Wow. The next year they do $735 million in revenue the year after that, which is basically the calendar year 2001, the year the Xbox comes out, they do just about $1.4 billion in revenue,

2 (1h 19m 23s):

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

3 (1h 19m 30s):

Indeed. This is the company's essentially ninth year of existence. They're already doing over a billion dollars a year in revenue throughout

2 (1h 19m 37s):

The company's history. They basically have these like six to 10 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 themself again. And so we sort of saw it the first time before the competitors come in and then the competitors come in and then we see it again with them figuring out we gotta do the emulated version of letting our engineers design the chips and lay out the chips so we can be faster than everyone. And then everyone sort of catches up and 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.

2 (1h 20m 21s):

They did obviously close to $2 billion as we move through 2001. They stayed reasonably flat for a few years after that. I think they eventually did 2.8 billion in 2005, but it was kind of barely profitable. Like they never lost money. But net income for each of those years was only a couple hundred million or less. So it's not like they're this like super free 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.

3 (1h 20m 53s):

Yep. A TI Of course. And then in 2005, I think it is a MD, that's

2 (1h 20m 60s):

Where they start shopping around oh six is when the transaction actually happens.

3 (1h 21m 3s):

They buy a TI and Of course now A MD is the main competitor to Nvidia. So we're gonna tell those stories on the next episode. But basically like a little sort of teaser what's going on here? They kind 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 right around this time there's something that ultimately becomes pretty amazing that happens, which is they've achieved the dream at Nvidia. They've created a programmable GPU, it is truly A GPU, it rivals the CPU.

3 (1h 21m 48s):

This is the model they have driven forth. This new industry of computer graphics enabled a whole generation of storytellers to program their GPUs and tell stories. A whole new class of users and developers starts to tinker around with these GPUs and Jensen likes to tell a little story that's probably apocryphal, but you know, hey, we'll repeat it here as a little teaser for next time. Right around, you know, sort of the early two thousands, a quantum chemistry researcher at Stanford calls up Jensen 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 and it takes a couple weeks to, you know, finish the computation on these models.

3 (1h 22m 46s):

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 buying a bunch of your GForce cards. So I did and that I should try porting my models into CG into your, you know, graphics, computer language and, and just see what happens. Well I did it and my computation finished in a couple hours so I, I waited a couple weeks for the super computer here at Stanford to finish. I checked the results and they were identical.

2 (1h 23m 21s):

Boom

3 (1h 23m 23s):

Boom. And it's like, so I just wanna thank you Jensen for making my life's work achievable in my lifetime. This is for sure something that Jensen made up. Maybe he did, maybe he didn't. It's

2 (1h 23m 35s):

Probably cobbled together from a few different people's experiences

3 (1h 23m 37s):

Probably it's, it's a composite but every word of it is true in spirit.

2 (1h 23m 41s):

Yes there is a whole industry called scientific computing or a whole segment that Nvidia would be able to address in the future, but they need a whole lot of tools to be built for them to be able to really use GPUs for all those purposes and more with machine learning and everything else. But right now, yes you are buying off the shelf G-Force 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. What's interesting is the industry perception around this time was that Nvidia had started to sort of focus on this high performance computing segment and that they were starting to take their eye off the ball in gaming.

2 (1h 24m 28s):

So people were starting to think like, oh maybe it TI is actually more interesting as a gaming specific graphics card maker at this point. And there's a little known fact that is, so you mentioned this A-M-D-A-T-I deal and like we all think the A MD radi on at this point, you don't think about the A TI radi on which was the, it was the they, I think they retired the A TI brand in 2009. But AMD's first choice was actually in Nvidia. Ah. So a D tried to buy Nvidia to make that their graphics line and it was possible because it's not like the stock was blowing up at this point in time. It had had this sort of few years of reasonable stagnation before we get into late 2006, 2007.

2 (1h 25m 13s):

And certainly people didn't see the machine learning market, people didn't really see the scientific computing market and it was like, hey, maybe this company needs some guidance from a smart company like us, A MD. And so they make the offer and there's the cover story on Forbes, we'll put it in the show notes, but there's this article that comes out called Shoot to Kill and Jensen in this merger acquisition talk with a MD insisted that he be the CEO of the combined company and that is the thing that blew up the deal. And instead a MD went and bought a TI and the rest is history.

3 (1h 25m 51s):

Oh man that is such a good, what would've happened otherwise? Well should we use that to transition into analysis for this one?

2 (1h 25m 59s):

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 A-M-D-A-T-I deal has just happened. We're sort of looking forward. It's 2006, you know, what's the bear and bull case for the company? And I thought an interesting data point to sort of ground this discussion would be that if we look at the gross margins today for Nvidia, which we will talk in our whole next episode about everything that they do that's so insanely differentiated, they sell their GPUs at a 66% gross margin hardware business with a 66% gross margin back in 2004. That gross margin was only 29% that they were able to command as a premium on their cards.

2 (1h 26m 46s):

And so you can kind of see like all of their economic potential was being competed away and they weren't doing anything to differentiate in a way to get any sort of pricing power. And so you think you make that 29%, then you need to use that to pay all your overhead and fixed costs and your engineers and develop the next product and pour it into 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 2006.

3 (1h 27m 16s):

Yes. And there's also another reason why their gross margins are so low in those years following 2001. So they made this deal with Microsoft right to power the Xbox and it was absolutely the right strategic decision to power the Xbox to get Microsoft's support in creating CG for programmable shaders, 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 there are three game consoles in the history of game consoles that Nvidia has powered the original Xbox, the PlayStation three Oof.

3 (1h 28m 10s):

Which we'll talk about next time. Oof. And the Nintendo switch. Hmm. They have not done any others

2 (1h 28m 17s):

Really.

3 (1h 28m 18s):

And people always are like asking Jensen about this and whatnot and you know, he's, he's diplomatic about this but 'cause it's a crappy gross margin business, right? Like yeah there's a $500 million a year revenue deal with Microsoft, you know, $500 million a year when their whole company revenue is a billion. Well that's, that's $500 million a year of very low gross margin revenue.

2 (1h 28m 40s):

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 and really change the world, then we have better things to spend our resources on. And that is kind of Jensen speak for like no there's crap margins in that. I'm not doing that. But he is right that like given a finite amount of resources, you have to allocate your capital and your resources in the most optimal, both short-term cash flowing way but also long-term strategic way.

2 (1h 29m 24s):

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.

3 (1h 29m 34s):

It's probably at this point in time a little too much of an exaggeration to say that they're outta the fire and into the frying pan having solved their intel existential strategic challenge and ending up now sort of at odds with Microsoft. That's too much. But there's a lot of truth to that. So you know, if you're looking at this stock in those years, especially as revenue starts to flatten and a big part of that is coming out, you know, towards the end of the Xbox generation of consoles leading into the Xbox 360, which Of course Nvidia does not power, that's a lot of gaming revenue, top line revenue going away. Meanwhile they're spending tons of resources investing in this new high powered computing segment for these researchers.

3 (1h 30m 19s):

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

2 (1h 30m 25s):

And in 2006 Intel launches or announces this project Larrabee where they're gonna be like a full fledged GPU maker. I Mean this is like a totally 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 honest to goodness GPU maker. So like are you betting the farm on scientific computing?

3 (1h 30m 58s):

How big is that market?

2 (1h 30m 59s):

So the answer is yes and that is also the bull case and it turns out scientific computing would be so much more than scientific computing and it would be, you know, the acceleration of all the other things in our computing world that has been very advantageous to become parallelizable. But I will leave it there so I don't have too many spoilers but that is 100% the bull case and 100% what happened.

3 (1h 31m 23s):

Yeah, it's interesting. We're working on an episode episode two with Hamilton Hel Marin is colleague Chen y at Strategy Capital about power

2 (1h 31m 32s):

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

3 (1h 31m 37s):

It probably won't be out yet when this episode comes out but it'll be coming out shortly thereafter. They make the point and it's a very, very valid one that 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 then having to go develop power. It's a whole, you know, second journey that you have to go on.

2 (1h 32m 1s):

It's a whole second invention. And at at this point Nvidia had definitely found product market fit but had not yet found their source of power.

3 (1h 32m 11s):

So you know, if you're looking at this company at this moment in time, especially as revenues flattening coming off the Xbox contract costs, OPEX is going way up, investing in this sort of speculative new area, I can totally see looking at this and being like wow, this is yet another Silicon Valley startup that had immense product market fit, top line revenue soared. But now we're kind of coming to the end of that and there's not a lot of power, you know, as defined by sustainable, you know, economic profit, you know, operating cash flow coming out of this thing.

2 (1h 32m 51s):

So then as we talk about power here, what power do they have? And for listeners who are newer, this is really the what is it that enables the business to have persistent deferential returns or sort of in a sustainable way be more profitable than their closest competitor. They really didn't have power. I Mean I'm trying to think which of the seven powers can we make the best case that they did have? It's not switching costs. Switching costs are crazy easy.

3 (1h 33m 20s):

So switching costs is interesting, right? Like I think they were trying really hard to develop it. They did a really good job. I Mean they made CG in collaboration with Microsoft and CG works on Nvidia products but it is not like Cuda today to, to flash forward to next time.

2 (1h 33m 41s):

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

3 (1h 33m 46s):

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

2 (1h 33m 52s):

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 you wanna commoditize all of our suppliers

3 (1h 34m 6s):

So you maybe some an attempt at switching costs that was not fully realized. I think they probably thought it and did for a while have processed power in this six month shipping cycle that none of their competitors could match for a while.

2 (1h 34m 19s):

Yep.

3 (1h 34m 20s):

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

2 (1h 34m 27s):

Okay. Playbook. I have one big one that we have not discussed. We sprinkle in lots of like playbook themes, but there's one to me that I want to call out and draw a through line to something that's happening with Nvidia today and that is simulation. So there's a thing that we're 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 on stuff and it happens way faster and it lowers your iteration time.

2 (1h 35m 11s):

And another one is drug discovery. Like you look at how fast we came up with Coronavirus vaccines simulation, it's an absolute miracle and everything in our world is being compressed 10 times 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 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.

2 (1h 35m 52s):

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.

3 (1h 36m 2s):

Similarly, a playbook theme I wanted to highlight that we have not talked about explicitly yet is just the power of like democratizing tools for developers. You know, and Jetson really saw this back in his a MD days before going to LSI logic, but the ability for Nvidia to use an emulator software emulator to design their chips and then Of course the massive, massive strides that the EDA industry has made since then. And then Nvidia itself, you know, enabling, you know we haven't really talked about it as much, but like Jensen and Chris and Curtis's original vision did come true.

3 (1h 36m 43s):

Like they created a new artistic platform for artists to tell their stories. And without this industry and all the hardware software tools that went into creating it, like there's no way that you know any, but you would have to be a John Carmack to tell a story in this medium. And there are very, very few John CarMax out there in terms of being gifted enough developers and surrounded by storytellers too and being a great storyteller himself to like be an artist, you know, to be a Nvidia talks about this now in their marketing materials to be da Vinci and Einstein, you know, together in one person.

2 (1h 37m 26s):

Yeah. It reminds me of the people that do like the crazy cool art in Microsoft Excel by like painting each of the cells a different color. You had to be that type of person to be a game developer in CarMax era because it was esoteric as hell to be able to actually figure out how to make this hardware do what you want.

3 (1h 37m 44s):

Another big one I want to highlight, you know, I just keep thinking back, going to the thinking back to the original time when Nvidia was funded and I wonder what like if they're really honest with themselves, like what Sequoia and Don Valentine would think about that. Hmm. They made the wrong venture bet. Like in a, in a market like that we see it all the time. Like look at Web3 right now. If there's a team making some new vision for a class of applications in Web3, like they're gonna get term sheets from everybody and then there's gonna be a million copycats the next day.

2 (1h 38m 21s):

It is the beauty of proliferation and then consolidation. I Mean Buffet has, I think it's in a 2000 fortune article that he wrote. It's weird that I know that, but I think that's right in an op-ed about how there were whatever it was, 70 car companies before we narrowed it all the way down to four GM and Chrysler and the airlines were sort of the same way. There's this proliferation, there's massive, there's no one can really differentiate, no one can build any power and so you only have a few survivors left and in general they compete on pre low margins when there's only a few left and their defensibility comes from their scale. You know, I think open question if that's sort of how the graphics market necessarily matured, but you're absolutely right to like sort of self-reflect on the time when Sequoia and Su Hill invested to say, would you make that type of bet again?

2 (1h 39m 13s):

You backed one of the two winning horses out of 90. Should you do that and just say, well we're betting on amazing founders or should you

3 (1h 39m 21s):

Well I think that's, so this is the nuance. I think what is so cool in front, you know, the fun of the art and the science of sort of what we do, the company they backed was wrong and yet it became, I don't know how long Sequoia's held, I Mean I think a lot of the GPS at Sequoia and certainly Mark Stevens who is one of my professors at GSB, who was on the board for Sequoia, is still on the board, have held their shares personally for like to this day. Like that's one of the best venture investment returns of all time. Full stop period.

2 (1h 39m 54s):

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

3 (1h 40m 1s):

Right? And so like they were wrong intellectually and yet they were right, right. And like why were they right? Like they were right because frankly of Jensen

2 (1h 40m 13s):

It was a reasonable enough market. The question is what are you better off doing what they did and investing at the proliferation phase on someone you believe is going to figure it out and have a good shot at being one of the winners? Or should you wait until consolidation and just pay that much higher price in order to back one of the ones that are already running away with the market?

3 (1h 40m 34s):

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

2 (1h 40m 38s):

Were no stages of venture capital. There was, you raise your venture capital and then hopefully you're profitable enough to go public.

3 (1h 40m 44s):

They did raise some more money in between that initial 2 million and going public. I think they raised 20 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 20 million. But it's really interesting to think about these cases take Sequoia and Sutter Hill too, you know, and specifically like they've gotten it right so many times but it's not a straight line. So like what's the lesson from that?

2 (1h 41m 10s):

Yeah, and the magic was that Jensen really figured it out early that they were in a business that was totally at the mercy of Moore's law. And so like in having that initial realization as early as they did with the proliferation of competitors and everyone doing, you know, the triangles and direct 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 to stay ahead other than ruthless self-examination and completely upending and rebutting the business. Yep.

3 (1h 41m 47s):

Ship faster and and reinvent. Yep.

2 (1h 41m 49s):

Yeah. So that, I Mean that that to me is why they, why they survived.

3 (1h 41m 55s):

If you think about the class of companies that are like the greatest venture returns of all time, some of them are like Nvidia, where like you look at the team, you look at the business plan, the thesis originally and like yeah it wasn't a straight line but it worked out. But then some of them are, you know, Sequoia even used to talk about this on their website, the Misfits, the ones that look like Unfundable

2 (1h 42m 23s):

Steve Jobs smelling bad, you know, that sort of,

3 (1h 42m 26s):

Right. Yeah. So it's like, and I think you know, plenty of venture firms but I, I have to hand it to Sequoia over history too. Like they've done a really good job of doing both of these. They do the Steve Jobs and they do the the Jenssen's.

2 (1h 42m 40s):

Okay. Listeners, now is a great time to introduce a new friend of the show who many of you will be familiar with. Claude. Claude is an AI assistant built by Anthropic and it's quickly become an essential tool for us in creating Acquired and the go-to AI for millions of people and businesses around the world.

3 (1h 42m 58s):

Yep. We're excited to be partnering with them because Claude represents exactly the kind of step change technology that we love covering here at Acquired. It's a powerful tool that fundamentally changes how people work. I know Ben, you have used Claude for some Acquired work recently.

2 (1h 43m 13s):

Yes. So listeners, I used to take four plus hours the day before recording to take all the dates from my raw notes and put them in a table at the top of my script for recording day on the Rolex episode. I actually fed my raw notes into Claude and asked it if it could do that for me, which was amazing. I just got my most important a hundred dates for the episode done in like 20 seconds. You

3 (1h 43m 38s):

Texted me this table. It was awesome. Yeah,

2 (1h 43m 40s):

That freed up an extra half day that I used instead to focus on explaining how a mechanical watch works, which I'm so glad I got to spend the time doing that instead of making the table.

3 (1h 43m 49s):

Totally. So cool. I was actually just chatting with Claude to brainstorm ideas for something big that you and I are working on for later this summer and it was insanely helpful. Listeners stay tuned to hear all about that.

2 (1h 44m 1s):

Yes. So listeners, by using Claude as your personal or business AI assistant, you'll be in great company organizations like Salesforce, Figma, GitLab, Intercom, and Coinbase all use Claude in their products. So whether you are brainstorming alone or you're building with a team of thousands, Claude is here to help.

3 (1h 44m 18s):

And if you, your company or your portfolio companies wanna use Claude, head on over to claude.com, that's C-L-A-U-D e.com or click the link in show notes.

2 (1h 44m 30s):

All right David, so what is the company that they invested in?

3 (1h 44m 34s):

Ben, you are talking about Keyhole.

2 (1h 44m 37s):

Yes. I thought you would know. So I love this little foreshadow before we get to grading because I think it's so interesting that Jensen basically saw the potential of Keyhole and without sharing what Keyhole became, I think astute listeners will know

3 (1h 44m 50s):

We've talked about it un Acquired and

2 (1h 44m 51s):

We have, we've done an episode,

3 (1h 44m 52s):

A whole episode on it.

2 (1h 44m 54s):

Basically this company that can't raise any money from anyone else comes and pitches Jensen and he's like, oh my God, I see this, this is the future. This is simulation. Like you are creating a model of the earth in software and people can just navigate around the earth. And so now that I've given it away a

3 (1h 45m 12s):

Graphical model of the earth,

2 (1h 45m 14s):

Yes, Google Acquired it, it became Google Earth and Nvidia was one of the 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. And one of the main reasons that I think they invested was because he wanted to stay alive so they could keep demoing it to customers.

2 (1h 45m 56s):

Great. Because it showed off Nvidia technology so well. But I just love that little tidbit. Yeah,

3 (1h 46m 1s):

We did our episode, God, it was years ago now at the Google Maps episode. That was such a good one.

2 (1h 46m 6s):

Yeah. Where to keyhole And

3 (1h 46m 10s):

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

2 (1h 46m 19s):

Zip dash.

3 (1h 46m 20s):

Zip dash, yes. And they were all like 20, $30 million acquisitions. Amazing. That's what's so cool about this. And I think maybe this is the like where Jensen and the Nvidia story bridge from like the, oh it was the, you know, obvious investment market to bet on team to bet on, to go all star engineers to go build this graphics card. Nobody really could have seen that Graphics were gonna become a lot more than games. Like you maybe could have seen it like, you know, there was SGI and Hollywood and Jurassic Park and there were some military applications for computer graphics, but very few, even Jetson and Nvidia, they were like video games.

3 (1h 47m 6s):

So the thing, fortunately

2 (1h 47m 8s):

That became the biggest entertainment medium. And so even if that was your only market

3 (1h 47m 11s):

Keyhole on Google Earth, and Google Maps is such a great example of like computer graphics became so much more important than like relevant beyond just video games. And that's all computer, you know, dynamically generated programmable computer graphics that are making all of that, all of that happen. All right, so how are we gonna grade this?

2 (1h 47m 32s):

Yeah. So I'm thinking given the opportunity, the market opportunity that existed between 1993 and 2006 four computer graphics, how did Nvidia do at exploiting that market opportunity? And like 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 their value creation was amazing, their value capture.

3 (1h 48m 4s):

Yeah,

2 (1h 48m 5s):

They did better than anyone else as far as I could figure out. The question I was sort of trying to figure out is that there were 90 other competitors doing same-ish thing, two-ish survived. Was there anyone else in the value chain that was able to do a much better job capturing, like, would you rather have been Microsoft than Nvidia?

3 (1h 48m 27s):

This leads into the really interesting question to think about for Nvidia in this period, Microsoft did basically nothing. Now, okay, that's like, like that's not fair to Microsoft. Sure.

2 (1h 48m 38s):

There was a large team that did direct DirectX, huge

3 (1h 48m 41s):

Team, you know, and the Xbox project was amazing and like, I don't mean that in any way to throw shade at anybody at Microsoft, but like they were in this position where they could just sit there, they could watch the market develop for computer graphics and they could be pretty, you know, by making good, very good strategic decisions, they could capture a ton of the value with other companies taking the risks of developing the market, figuring out all this stuff. And then, you know, Microsoft can come along and be like, great Nvidia, we're gonna help save you from Intel and in return you're gonna, you know, give us a really sweetheart deal on these chips and you're gonna put us in business with Xbox and by the way, the other side of your gaming and computer graphics business on PCs, we're gonna become your primary partner for that too.

3 (1h 49m 37s):

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.

2 (1h 49m 48s):

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.

3 (1h 49m 59s):

No, it's not fair for Xbox at all. It's not. It's not.

2 (1h 50m 1s):

But it is an interesting way of, right, like to put it another way, and let's exclude Xbox for a moment. You're basically just recognizing that Microsoft had an unbelievable position in the market and did an amazing capital allocation job exploiting it and basically saying, Hey, you know what? You know what? We don't need to do all that crap that like Nvidia and a TI and all those guys are doing, you know how we can still retain our market position and continue printing money the way that we do this thing. And they did that and they didn't get into the commodity business and they were brilliant.

3 (1h 50m 35s):

We don't need to be in this brutally competitive industry where like if we don't ship six months ahead of our competitors, every cycle we're toast.

2 (1h 50m 44s):

Yeah.

3 (1h 50m 45s):

So I think, you know, in this kind of like grading question, oh man, the longer we do this show, the more I realize this is like a mega theme of Acquired that like Microsoft in the nineties, early two thousands was such a power and the antitrust, you know, the DOJ case really, really crippled it probably for good for the ecosystem.

2 (1h 51m 8s):

Then the 3D chess version is, and this kind of foreshadows the next episode because Nvidia had to learn these hard lessons and had to develop like was forced to develop these really crazy competencies like eventually developing Cuda that would power this whole machine learning and scientific computing revolution. Was it bad for Microsoft to not have to grow that DNA 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,

3 (1h 51m 35s):

That's a great point.

2 (1h 51m 36s):

I don't know enough yet about how the machine learning market is gonna develop or has developed in order to sort of make a call yet on that point. But if you are just standing there in 2006, reflecting back Nvidia fought for their life and won

3 (1h 51m 54s):

Multiple times

2 (1h 51m 55s):

And Microsoft just leveraged the crap out of their amazing position. Yes. And probably achieved about the same outcome.

3 (1h 52m 4s):

Yeah. Both of these two fighting for their life company. Defining moments from NVIDIA's first 10 to 15 years, the overcoming the 90 competitors and then the building and making the case that they're not gonna get commoditized by Intel. That the GPU is gonna be a standalone important thing. Microsoft profited hugely from both of those.

2 (1h 52m 29s):

Yep. It's so true. I will say Nvidia doing what they did has been net unbelievably positive for the world. Like I watched the Nvidia GTC conference, the 2021, 'cause the 2022 is about to happen. And just like the review of all the stuff they're involved in is so inarguably good for humanity, we need way less energy to do way more interesting stuff. That's good for humans because Nvidia exists and without doing this first 13 years, they would not have laid the groundwork to be able to do all of that in the future. So that's like one sort of contorted lens to look at it through.

3 (1h 53m 6s):

I think I give Nvidia for this period of time an A because they're basically the only company that survived a t. I did a for sure, Of course, but in a very different fashion. And they created this whole industry almost inarguably created and shepherded this whole industry. But it's not an A plus because Microsoft, well shoot, there was the DOJ case until the DOJ case. Yeah,

2 (1h 53m 38s):

It's true. All right. I like that. Hard to argue with it. Carve Outs.

3 (1h 53m 43s):

Carve Outs. I have a fun and very appropriate one for this episode. Elden Ring. Have you heard about this Ben? No. You're not a gamer. So you, you need to, we need to like get you into gaming after, you know, doing all these episodes now. It's so fun. It's just like, it's great. So Elden ring for people who don't know is the latest from software game and it's on all the platforms, console, pce, et cetera. Lots of people are saying this is probably gonna be, 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.

3 (1h 54m 26s):

But like these, the world building is unbelievable and Elden Ring is the first one to come out on modern platforms and just like everything about it, the graphics, the scale, the breadth of the world, the story George 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 researching Nvidia 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.

2 (1h 55m 7s):

Cool. 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 10 years.

3 (1h 55m 21s):

Inspired by Jensen

2 (1h 55m 22s):

Called Starting Strength by Mark Rippetoe. Yeah. Apparently inspired by Jensen and I didn't even realize it, but it's like I reactivated a gym membership and I went back to the gym, you know, started kind of from square one in terms of like doing all the basic barbell lifts. It's just been really f like it's a new hobby. It's something I did like 10 years ago and then totally led atrophy and the way that I love to work out and at least historically over the last five to eight years has been like endurance sports. So, you know, training for marathon or doing week long bike trips and stuff like that. And it's just very fun to get back into the like every other day try and, you know, lift as heavy as you possibly can for a few reps rest for a long time.

2 (1h 56m 5s):

You know, make sure you get all your sleep. It's a very different mentality. And so it's been fun doing that again.

3 (1h 56m 11s):

I love it. It's like a, I feel like we're both becoming like better versions of our high school selves. You know, I'm like a, like a full on like gamer again and you're getting back into weightlifting

2 (1h 56m 21s):

High school. Me would've been like, what? Why would I work out? That doesn't sound fun.

3 (1h 56m 26s):

Okay. College u, college U

2 (1h 56m 28s):

Fair. All right listeners, that's all we've got. We are very excited to at some point come back and talk to you about 2007 through 2022 with Nvidia and the absolutely unfathomable things that they have done. Imagine if you started a business in the early 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 that the same technology was uniquely able to do. That was like 10 times bigger than the original thing and no one else was even close to you. 'cause you had like 18 years of like building stuff and learning about these technologies to be the best company in the world to take advantage of that next thing, which obviously is machine learning, it is just like an oh my god story.

2 (1h 57m 18s):

And then you layer on top of that, the fact that gaming actually was like 10 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.

3 (1h 57m 29s):

Ah, so great. This, this is the kind of stuff that like we do acquire for. I just like been so jazzed about this. Yeah,

2 (1h 57m 37s):

I got a lot of research to do on parallel processing and like why this was so perfect for all the machine learning and cryptography use cases. But that's why we get some time between episodes to go and do more research and to watch GTC, the GPU Technology conference, their annual developer conference 2022. So thank you so much for listening to us. Leave us a review on Apple podcast. If you listen there or with the new Spotify ratings feature on their mobile app, share it with a friend if you like it. We welcome lots of feedback and fortunately in having a part two, we're gonna be able to take your feedback and actually work it into the next part of the story.

2 (1h 58m 17s):

So Acquired fm slash Slack, come hang out with us, talk about this, check out the LP show and we've got a job board. If you are looking for the next stage of your career, we have curated all of the positions at 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.

3 (1h 58m 38s):

We'll see you next time. Indeed. Who

1 (1h 58m 41s):

Got the truth? Is it you? Is it you? Is it you Who got the truth?Who got the truth? Is it you? Is it you? Is it you? Who got the truth now Is it you? Is it you? Is it you? Cindy, sit down. Say it straight. Another story on the way Who got the truth.

2 (27s):

Welcome to season 10, episode five 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.

3 (41s):

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

2 (47s):

And we are your hosts. It is the eighth largest company in the world by market cap. Dang, when Nvidia began in 1993, it made computer graphics chips in a brutally competitive and low margin market. There were 90 undifferentiated competitors all doing basically the same thing at the same time. And yet today they have an 83% market share of standalone GPUs. That's graphics processing units. For those of you starting with us from square one that are supplied for desktop and laptop computers.

3 (1m 22s):

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

2 (1m 24s):

Sorry. Sorry. I'll just, I'll tease a few things here. So not only that but Of course followers of Nvidia know that they recently pioneered a completely new market, the hardware and software development tools to power machine learning, neural networks, deep learning, all of this in the cloud and the data center, which obviously is proving to define this whole decade of computing. And as David and I began our research, we realized this really could be a book and like a thriller of a book. Since the co-founder and CEO Jensen Wong 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.

3 (2m 6s):

All right, so here's everything you need to know about Jensen the Cliffs notes before we talk for like six hours about him. The dude used to drive a Toyota Supra like a fast and the furious style. Yes. Like like a death machine. And he almost died. He got in like a huge accident.

2 (2m 24s):

Just one more way. He is like Elon Musk.

3 (2m 27s):

Oh man. Crazy.

2 (2m 28s):

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 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 in saying that, just kind of set some context. This is a story that takes place from about 1993 to kind of the mid to late two thousands. And as hyped as Nvidia has been, you know, over the last five years, obviously with the stock runup and everyone's excitement around the company, I think Jensen is still an underrated CEO even rated

3 (3m 13s):

A hundred percent

2 (3m 14s):

Where the Nvidia bulls have put him. I think Jensen is one of those people where like if you know about him, you know what we're talking about and you have unbelievable reverence. But I think not enough people really know.

3 (3m 27s):

Just one more Jensen quote before we get into the episode. Who's the best my will to survive exceeds almost everybody else's will to kill me? Amazing.

2 (3m 42s):

All right listeners, we want to share with you a new friend of the show. Roc Roc helps modern companies scale globally with automated sales tax and VAT. That's VAT compliance. Yeah,

3 (3m 54s):

ROC came on our radar screen because they're behind the scenes of many companies in the Acquired universe like Vanta, mutiny, stat, Zig and like them, they're also backed by Sequoia Capital. ARO is the first tax platform built specifically for modern business models like SaaS. As the digital economy has grown, its sparked new regulations and compliance requirements from governments in a natural move to capture some of that revenue. But most tax solutions are still stuck in the retail era. ARO saw a gap in the market for software companies that are built from the ground up to be global from day one. So

2 (4m 27s):

For modern companies, sales tax compliant is actually pretty high risk. SaaS businesses that take a reactive approach lose on average 4.3% of revenue to unpaid tax penalties and interest. Aroc puts you in control of that global risk one platform that monitors your exposure worldwide, automates compliance end-to-end and helps you forecast tax liability and stay audit ready as you scale.

3 (4m 52s):

This enables faster growth for software companies handling millions in revenue because when you're scaling, the last thing you want is tax complexity holding you back. Definitely not. Aroc is trusted by thousands of finance leaders at the fastest growing companies out there. Companies like Anthropic and Notion to handle billions in revenue for them.

2 (5m 10s):

We know everyone has their eye on efficiency goals right now and ARO is a great way to do that. They help eliminate the hidden costs of manual tax compliance. They're offering a free study on your tax nexus for Acquired listeners, which is typically a $7,000 cost to see your current sales tax exposure. So if you're scaling a company and you want to see how modern businesses are protecting their revenue against sales tax risk, head on over to nro.com/ Acquired. That's A NRO k.com/ Acquired. Or click the link in the show notes 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 could do that with 11,000 other smart members of the Acquired community at Acquired fm slash Slack.

2 (5m 56s):

Here's a new thing if you haven't rated or reviewed this podcast yet. I think the last time we, we mentioned this was like years ago, Spotify in their mobile app just added the ability to rate. So if you listen in Spotify, oh nice. You should totally leave us a little rating in there. If you're on Apple Podcast, leave us a review. 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. We may hold positions in things we discuss on this show. This is for entertainment and informational purposes only. And David, take us in.

3 (6m 32s):

So we start in February of 1963. What was going on in Silicon Valley in 1963? Let's see. Fairchild had already started I think, and Silicon Valley was like underway but it was early days. But we start not in Silicon Valley but in

2 (6m 52s):

Taiwan.

3 (6m 54s):

Yes. The southern part of the island of Taiwan with the birth of Jen soon Huang later Americanized to Jensen. Jensen Huang. So his dad was an engineer 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 and he was like, wow, you know, this is amazing. I want my kids to grow up here and to have all the opportunities that are available.

3 (7m 37s):

So he comes home Jenssen's four. Jensen has a older brother who's a couple years older, you know, like nobody speaks English. So his mom gets an English dictionary and picks 10 words every day, grills the two kids and like quizzes them and teaches them English out of the dictionary. Huh. And if you listen to Jensen, 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 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, they don't have enough money but they found a boarding school in America that is cheap enough that they can afford it is called One Baptist Institute and it is in eastern Kentucky.

3 (8m 26s):

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 one. Whoa. Well it turns out that the reason that this school OBI, Anita Baptist Institute was so cheap 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 Jenssen's roommate when he shows up as a 9-year-old is a 17-year-old kid who had just gotten out of prison and was recovering from seven stab wounds that he got in a knife fight.

2 (9m 7s):

Classic American journey right here.

3 (9m 9s):

And amazingly this is so Jensen like they become great friends even though this kid is eight years older than him, like twice his age basically from a way different background. Jensen helps him with math and he gets Jensen into weightlifting. So you see Jensen today and you're, that dude

2 (9m 27s):

Is jacked. He is jacked.

3 (9m 28s):

He's been weightlifting since he was nine years old. He says about his time in Anita, you know, now I don't get scared very often. I don't worry about going places I haven't gone before. I can tolerate a lot of discomfort. Boy does that play out Wow. In his life as we will see. So it's pretty awesome actually now he and his wife Lori have given a few million dollars to the school and it's like a amazing institution. Now you can see Jensen gave the commencement address in 2020. We're gonna link to this in the sources. It's pretty awesome. So after a couple years at OBI, his parents are finally able to save up enough money to afford to come to the US themselves.

3 (10m 8s):

So they move first to Tacoma, Washington, the great state of Washington. And then they move a little farther south down to the suburbs of Portland, Oregon. Jensen and his brother go home, they live with them. They go to public school there. You know, Jensen continues his, his American upbringing. He gets really into table tennis. He places third in the junior nationals in table tennis and he gets his picture in Sports Illustrated going on. Oh

2 (10m 36s):

No

3 (10m 36s):

Way. Pretty amazing. But his parents continue their sort of like academic discipline and Jenson's super smart obviously he ends up skipping two grades and then going to college. He goes to, in-state college he goes to Oregon State University just down the road a little bit.

2 (10m 53s):

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

3 (10m 55s):

He got there when he was 16 'cause he had skipped a couple grades and he loves math. So he decides he's gonna major in electrical engineering at OSU and he totally falls in love in more ways than one. The first way that he falls in love is he just thinks 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 they don't use like enough precision when talking about like exact numbers.

2 (11m 26s):

Which he later comes to say that he respects the opposite position. I think some of the Nvidia employees call it CEO math when he sort of rounds all the numbers and he's like, 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.

3 (11m 44s):

That's so json like he understands like, yeah my employees get mad at me when I you know, round the numbers and you see O math and like I get it. Like I appreciate precision too but you know like the big picture is what matters here. The second way he falls in love is with his lab partner in electrical engineering fundamentals. His lab partner Lori who goes on to become his wife. That's a cool story. So he graduates in 1984, she graduates in 1985, they moved down to Silicon Valley and Jensen joins a MD as a sort of equivalent of like a chip design pm Hmm. It's very like engineering heavy but he's kind of like a pm.

3 (12m 25s):

He's sort of like helping as a junior manager of a, of a process for developing a chip. He's working on a then blazing fast one megahertz CPU chip.

2 (12m 36s):

Yeah. He talks about this and he says, you know, he's talking about how slow one megahertz is and he refers to it and says you could even see it coming. It's about how fast it was.

3 (12m 45s):

You could see it coming from a long way away and still coming and still coming. Amazing. And Of course now he makes literally the fastest chips in the entire world. So he starts at a MD, he starts at night working on a master's degree in electrical engineering at Stanford. It ultimately takes him eight years to finish this master's. He works all the time that he's at a MD and then at Ellis I logic where he goes to, we're gonna talked about in a sec, he ultimately does graduate right before they start Nvidia. This is like a super cool bit of trivia. Did you go back and watch the Don Valentine view from the top?

2 (13m 22s):

No, I didn't lecture

3 (13m 23s):

At GSP. Ugh. I watch that like once a year every year, every time there's an excuse. Is

2 (13m 27s):

That the one where he holds up Alfred's resume?

3 (13m 29s):

It's yeah. Where he holds up Alfred Lynn's resume. So also Easter egg in that talk, that was the day that the Jensen and Lori Huang engineering center at Stanford was dedicated. As Don says, Jensen did a building pretty awesome.

2 (13m 47s):

I did watch, he gives a talk where he wa he walks in and gives a talk at Stanford. I think it's the first time that Jensen has given a talk since the building opened and he says, I've donated, we have this nice building now so I I have no more money. Yeah.

3 (13m 60s):

A penniless I think on Penn

2 (14m 1s):

Less.

3 (14m 3s):

Right, right. Jetson So great. Just

2 (14m 6s):

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

3 (14m 11s):

I think he owns what like three and a half percent of Nvidia? So something like that. Something like that, yep. Yeah, he's not penniless. Okay. So he works at a MD for a couple years and while he's working there, probably from working on this chip that you can so fast, you can really see it coming. He realizes that designing chips is really freaking hard. Intel can do it, a MD can do it but you know there's not many companies, it's all like full stack at this time. You know, TSMC doesn't start till 1987.

2 (14m 39s):

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.

3 (14m 56s):

And Jensen talks about like when he was in school, the reason he wanted to go to a MD was he thought this was so cool that like you could do it all. And then once he's actually at a MD he's like, he realizes like it's actually not cool. Like it would be cooler if you could be really good at like a certain part of the stack and have tools and platforms and other companies to allow you to allow anybody to make chips.

2 (15m 17s):

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

3 (15m 22s):

So after a couple years his office mate at a MD leaves and goes to join a startup called LSI Logic, which had just gone public and we've talked about it on the show, made Don Valentine and Sequoia, the then largest venture return in an IPO in history. Maybe the largest venture return ever in history when they went public of $153 million on day one.

2 (15m 54s):

Boy has venture changed as an asset class.

3 (15m 56s):

But that, I'm trying to think that fund that probably would've been, I don't know Sequoia fund two or three maybe. I Mean I bet the fund was like, I don't know, 10, 15 million. Like so probably roughly 10 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 asics company as IC application specific integrated circuit companies. And so what they did and what that meant was they basically made custom design chips for other companies. That's what Jenssen'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.

3 (16m 43s):

So like defense companies, Lockheed Martin and the like. But lots of other companies now too are coming to LSA logic and the other asics companies and saying Hey we want to create these systems of chips. You help us design the chips to go into these systems and yeah we'll use processors from, you know, Intel too. But like it really helps democratize making end product systems.

2 (17m 7s):

Right? And the idea with Asics is really if you're not saying, hey 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, 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.

3 (17m 43s):

Yep. And the legacy of asics today still around, still used both Asics but the legacy is FPGAs field programmable array chips that are, you know, some might say is sort of a bear case for Nvidia these days. But we will, we will get to that far, far, far down the road. Sun Microsystems was one of their biggest customers and that was how Sun got started and made the shifts for their workstations. And in fact Jensen, when he shows up at LSI Sun is like just starting and coming to LSI and so he gets put on the project, he basically embeds with Sun like in the early days of Sun Microsystems to help them build out the chips for what would ultimately become the Spark Station one Sun's first big workstation product over the next few years.

3 (18m 33s):

He pretty much exclusively works with Sun while he is at LSI Logic, he works directly with Andy Bechtel Stein who you know, the founder of Sun and with Bocco look. Yeah he becomes super known and develops quite a reputation there as somebody who can really like take these visions for chips and these customer requirements from Sun and turn it into, you know, reality and production. So one day right around Thanksgiving 1992, Jensen has finally, after eight years finished his master's degree at Stanford. And Stanford is quite quite glad that he finished before this happens. Two of Jenssen's buddies who he's become close with at Sun, Chris Malachowski and Curtis Preme who in Jenssen's own words, he describes them as really, really fantastic engineers.

3 (19m 26s):

And when Jensen says that he means it, they come to Jensen and they're like, we're not like super happy. It's Sun the two of us. We have an idea that we want to talk to you about. And Jenssen's like, well sure let's go meet at my favorite spot Denny's. Really? Yeah. Like the man loves Denny's, he worked at Denny's in high school, like he's always going to Denny's. He, he orders the Superbird I think is like his go-to dish. Nice. He's so folksy. I love him. So they go all have dinner at Denny's and Chris and Curtis pitch him on their idea, which their idea is it's pretty good, it's pretty good. Tell me as a venture capitalist if you would fund this idea back then in late 1992.

3 (20m 6s):

So they see 3D graphics are really becoming a thing and you know, remember this is the era of Sun Now Logic, all this stuff. It's also the era of Silicon Graphics right down the street right there in Silicon Valley. SGI, so many great things that come out of there. You know, Jim Clark, Netscape, like all this great stuff. Jurassic Park. Jurassic Park is about to come out, it comes out in 1993. So there's this huge demand for 3D graphics the way 3D graphics are done. You need SGI workstations, you need like super custom, you know, very high end, very expensive stuff. Only something with the budget of like either the military or like a Jurassic Park can afford to do this.

3 (20m 49s):

But people love it. Like the consumers love 3D

2 (20m 52s):

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

3 (20m 57s):

Well we're still in the super Nintendo days, so we're not at 3D console graphics yet. That's coming very shortly. But what is happening is the PC wave is like really cresting right now. Like

2 (21m 12s):

We're like a year and a half from Windows 95 coming out

3 (21m 16s):

And I remember doing this I bet you do too. Or kids in 19 92, 19 93 doing on their PCs they're playing Wolfenstein 3D Oh yeah. And Doom Doom comes out in 1993. These are taken the world by storm and they're made by i i software in Texas and John Carmack and John Romero. But Carmack is like doing incredible feats of engineering to get 3D graphics to run on consumer PCs. It took somebody of CarMax caliber to make this happen and the market loved it. So the idea that Chris and Curtis has, they're like, we're really great chip engineers Jensen, you're a really great, 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 to enable 3D graphics like SGI is doing with professional workstations to enable them for consumer hardware, PCs.

3 (22m 17s):

We know that people love games. This will help the entire industry, you know, take off.

2 (22m 22s):

And you're not even saying it 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 games on, on a pc, right?

3 (22m 35s):

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. But they'll just develop on PCs. It's really about getting the, like the hardware into consumer's hands that they can actually play this stuff.

2 (22m 57s):

Hmm.

3 (22m 58s):

All right. So what do you think? Is this like a good pitch?

2 (23m 1s):

I Mean so what you're basically asking me to believe 1992 me is that video games on PCs are gonna be a thing that there's gonna be a 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.

3 (23m 23s):

Well I have this proof point of of IT software and, and Wolfenstein and Doom right there of like millions of people doing this. But

2 (23m 30s):

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 to totally change the development environment or can like there be like five or six different dooms out there, there's five or six CarMax who are all independently geniuses and can figure out how to do all the graphics on their own. Yeah, maybe. But there's a leap of faith.

3 (23m 55s):

Yeah, definitely a leap of faith. So yeah, okay. Not totally obvious 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 chips and cards that plug into consumers PCs, this was full swing. There are companies making sound cards, there were companies making networking cards, there were companies making serial port cards like god knows what.

2 (24m 25s):

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.

3 (24m 44s):

Yeah. And so the pitch is we're gonna make a custom graphics card take a graphics workload off the CPU specifically for gaming.

2 (24m 50s):

Great.

3 (24m 51s):

Okay. So yeah, it was pretty much a brain dead. Yes. But as you alluded to at the top of the show, the problem when something is a brain dead Yes for venture capitalists is that it's a brain dead. Yes. For lots of venture capitalists and lots and lots and lots of companies get funded to do this. But back to Denny's that night, Nvidia is the first, they are the first dedicated graphics card company. They all decide the three of them that they're gonna go in on this. Jensen goes to the CEO of LSI Logic walks into his office and tells him that he's gonna resign.

3 (25m 38s):

He's gonna go start this company with two engineers from Sun and this is what the business plan is gonna be. Now do you know who the CEO of LSI logic was?

2 (25m 48s):

No,

3 (25m 49s):

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

2 (25m 58s):

No way.

3 (25m 59s):

Damn right.

2 (26m 1s):

So is that how Don, 'cause Don Valentine obviously was the biggest investor in, well Sequoia was in Ellis I logic and he, did he know him from Fairchild? Yeah,

3 (26m 9s):

They were colleagues back in the day.

2 (26m 11s):

Ah, okay.

3 (26m 13s):

And then the biggest exit in in Sequoia's history to that point in time. So Wolf says, so lemme 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. And Wolf 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 we think if we build it like they'll come. So Wolf says, remember he was a Fairchild. He said, I was like, he knows when to make silicon for specific applications. And Wolf says, Hmm, All right, you'll be back.

3 (26m 52s):

I'm gonna hold your desk. But in the meantime before you go, I'm gonna call up Don, I'm gonna do, you've done good work for me. I'm gonna call up Don. He calls up Don and he is like, Don, I got a kid, he's gonna come see you. Standby.

2 (27m 9s):

Which this is a lesson for all founders and you know, aspiring founders out there, getting a reference from the CEO of a portfolio company is a really good way to come in with a venture capitalist already leaning toward investing. Especially if you're referred by the top performing company of all time in their portfolio. Yes. It's kind of hard for Jensen to mess up this pitch with the recommendation that he's coming in with.

3 (27m 36s):

It's literally impossible because he goes to see Don, you know Don, you know Don sits down and he is like so, and Jensen completely botches the pitch. He gets like really nervous

2 (27m 50s):

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 Barfs all over Don.

3 (28m 7s):

Yes, exactly. So Jenssen's walking out the door, he's like, you know, totally dejected. Don stops him and says, well that wasn't very good. But Wolf says to give you money, so against my best judgment based on what you just told me, I'm gonna give you money, but if you lose my money

2 (28m 33s):

I'll kill you.

3 (28m 35s):

Classic, classic Don line. So good. So the deal happens, Sutter Hill comes in too 'cause you know, again, like Alyssa's all dramatized at the end of the day, like this is a hot deal.

2 (28m 48s):

This is two episodes in a row for us with Sutter Hill.

3 (28m 53s):

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

2 (29m 0s):

They invested like a million each. Is that right? For a total of two.

3 (29m 4s):

So $2 million total round. I don't know who invested what, I assume a million each but $2 million total round at a $6 million post money valuation. Remember everybody, this is the eighth most valuable company in the world right now. Started at a $6 million post money valuation. So they're getting things ironed out and there's just one problem. They don't have a name for the company yet. Jensen and Chris and Curtis, they've just been, you know, working on this, working on the business plan but they don't have a name they need to incorporate the company and they were saving the files that they were working on for the chip design for the first graphics chip as nv NV being short for next version.

3 (29m 51s):

And so they're 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, 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 envy, this is awesome.

2 (30m 15s):

Of course they pick green so later on they can have that marketing campaign of green with envy.

3 (30m 20s):

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

2 (30m 31s):

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 wanna 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 they're doing a thing here that like, well 89 other people are also sort of simultaneously doing it is kind of a new frontier that they need to invent and then own like thought leadership in that area. And they do need to kind of like quickly build a brand not only with consumers but with PC manufacturers. Jensen, the way he sort of describes it is that their vision, although he doesn't like the word vision 'cause he thinks it's exclusionary to people.

2 (31m 16s):

So he said, our perspective is that they want to enable graphics to be a new medium to tell stories. And here's sort of like the way that he articulates at the time why video games today are $180 billion a year industry bigger than Hollywood, bigger than music. It, 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, but if you could, it's really interesting because it's not prerecorded 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.

2 (31m 56s):

And so therefore it's the only one that can really be like social and interactive. And so our reason for being is to create 3D graphics as a form of artistic storytelling for the future and everything will be in service of that. And I think that's not really what they are today necessarily. It's a piece of what they are today. But that kept them going for the first 20 years of their existence. Well

3 (32m 22s):

And baked into that is again, you know, Wolf kind of like hit on and and you did too, to your credit, you're a very good venture capitalist. You hit on really the key problem with this first iteration of Nvidia, which is they have to go evangelize to developers to like, yeah there's it and there's carmac out there, but like not a whole lot of other PC game developers out there. There not a whole lot of other 3D PC game developers at this time. There are 2D PC game developers, but they gotta convince a whole lot of people to go, you know, learn how to do 3D game development for PCs. And that's so like, oh we're gonna enable storytelling, all that.

3 (33m 2s):

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

2 (33m 17s):

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

3 (33m 23s):

Exactly. So at first things start off really well. Remember this is super hot. They're the first company, they're funded by Sequoia and Sutter Hill. Like they land a big deal with Sega to power their archaic consoles and their next generation home console to be the 3D graphics engine and would ultimately become the Sega Saturn. And as we know from our Sony episode,

2 (33m 50s):

Not quite the Sega Genesis,

3 (33m 51s):

Not quite the Seig 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 people probably know you create 3D graphics, you use polygons. That's why people are always talking about polygons in this industry. They have to decide on a sort of primitive for the polygon. They're like, oh well we'll use Quadrilaterals for Vertex. You know, and anybody who knows anything about video game development now is like, that's not how it's done. Like

2 (34m 21s):

I'm pretty sure people talk about triangles.

3 (34m 23s):

Yeah. And I'm pretty sure if you look at NVIDIA's amazing headquarters building today, it's you know, made out of triangles in a homage to game developers, not quadrilaterals. So this becomes a pretty big problem. You know, things go along for a while. It's like fine for about a year NVIDIA's leading, they got this big Sega deal.

2 (34m 42s):

There's not a reason to need standards yet. Right? The industry isn't complex enough yet to necessitate a whole bunch of collaboration and set of tools that everyone standardizes on using. You're like, okay well we're just going to put this chip in our game console, ship the game console. We're the only people that you know make an SDK, we being Sega. So everyone will have to kind of standardize on this thing anyway, so great. But obviously the ecosystem gets much more complex much more quickly and it sure would be nice to have some kind of compatibility.

3 (35m 13s):

Well here's what happens. So you know, Curtis and Chris and Jensen, they weren't the only people in Silicon Valley that saw that kids wanna play games on PCs with Doom. Microsoft is like, oh that's interesting. We like selling PCs and gosh there are all these graphics cards companies out there now that are doing this. And you know, what do we do as Microsoft? We really wanna encourage this in the ecosystem. Well we create standards.

2 (35m 44s):

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.

3 (35m 54s):

Yeah. You know, developers want to do 3D graphics directly into Windows without any of this, you know, crufty middleware from some no name company Nvidia out there. Why don't we just bake these APIs right into Windows directly for 3D graphics, we'll call it Direct 3D. And Of course anybody who knows about the history of this that becomes Direct X

2 (36m 17s):

And Direct X made some pretty different design decisions than Nvidia had made. Is that right? Yeah.

3 (36m 22s):

So they use triangles because triangles make sense. So now NVIDIA's really up a creek like all of their com, you know the 89 other competitors out there that started later, most of them are like, sure I'm gonna jump on board of this Microsoft ecosystem. Like I would be dumb not to. It's standardized on this completely different paradigm than Nvidia. And then Sega, you know, they've got Sega, they've got this one sort of customer and then in 1996 sega's like yeah we're not so sure about this quadrilaterals thing either. And

2 (36m 57s):

Just so that like this doesn't feel arbitrary why we're talking about this. And we're gonna say at a super high level on 3D graphics here, rather than really going into the weeds, but a triangle is the fewest vertices in a shape that you can have while still creating a two dimensional shape. And so it serves as a basic building block where assuming you can draw enough triangles and make the triangle 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.

3 (37m 31s):

Yep. 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. Nvidia was calling the NV two when Sega comes back and says We're switching horses, we're not gonna do this. So like they're screwed for so many reasons. Everything we've discussed. There's also in the interim, you know, year and a half since Nvidia started, the price of memory dropped because thank you Moore's law. So NVIDIA's chips were designed to be like super, super tight on memory and the memory cost about $200 in component, you know, parts to go into their chips, their competitors have more memory that's costing them like $50.

2 (38m 18s):

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 its advantage. But second of all, everyone else's cost structure was way lower or at least everyone else could see that the cost structure was getting way lower. And so Nvidia sort of designed for a constraint that was no longer true by the time everyone else came out with their stuff.

2 (38m 58s):

At this point, Jensen and his co-founders kind of had to look at each other and say, okay, do we scrap everything we did? And if so, how do we not make this mistake again? How do we make sure that in future generations we sort of premeditate the exponential curve of Moore's law and prices coming down and design for things that are, you know, 2, 3, 4 generations beyond what we actually have available to hardware right now.

3 (39m 24s):

So when all this goes down, the company has about nine months of runway left and like, 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 effed. And I can't imagine sitting there dreaming up a way out of this, but Jensen god he's such a g, he's like, no we're not going out like this. You know when you hear Jensen talk today about like NVIDIA's culture and he says that intellectual honesty is like the cornerstone of NVIDIA's culture. Like this is what he's freaking talking about. Like he sits down with Curtis and Chris and remember they're like they're engineers and they've recruited Nvidia a hundred plus engineers into the company at this point and sold them on this technological vision of we're gonna define the industry.

3 (40m 16s):

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 Jenssen's like guys, like this is a pipe dream. We need to throw it all out. If we're gonna survive, the only thing we can do is standardize on on the same Microsoft, you know, direct 3D as everyone else, same architecture. And our only shot is just to like compete on performance and try and become like the best chip out there in this now sea of commodity chips. And you know, his co-founder like don't want to do this. This is not an exciting vision for a Silicon Valley engineer.

2 (40m 56s):

When your CEO comes to you and says that what they're basically saying is, look, if my job was strategy and your job as 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 at a lower price point using less energy than our competitors. Because Microsoft being Microsoft had all the developer attention and because Microsoft set a standard Nvidia realized, look, we have no ability to uniquely get our own developers at least at that point in the company's history. And so we must just on our left look and see all the developers are coming from Microsoft using this API on our right is all the same consumers and we have to compete just head to head on raw engineering ability with everyone else.

3 (41m 46s):

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? Mm. Like how fast can you design the next generation of chip and can you ship it before everybody else because everybody knows what's gonna be in that ship and

2 (42m 5s):

Why is it, what fundamentally about was it about graphics cards that made it a commodity?

3 (42m 12s):

Well at this point, like all the other peripherals and 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 3D graphics processing out of the CPU and onto this other chip on the motherboard just like sound cards. Were doing the same thing for sound just like networking cards. Were doing the same thing for networking. And it was just like, what's the price performance ratio of doing that? The interfaces and the programming language that's all standardized by Microsoft. You're just commodity hardware.

2 (42m 47s):

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 in the highest resolution that I can or I suppose a standard predetermined resolution as

3 (43m 10s):

Fast as I can. And that'll drive the resolution

2 (43m 12s):

Output a 2D thing that goes on the screen. So I turn 3D stuff into 2D stuff and I have to do that better than other things that I'm competing against where basically all of us are, when you say commodity, you mean limited by Moore's law and doing right up to the edge of what integrated circuit manufacturing techniques enable us to do.

3 (43m 31s):

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 70% of the company, which they do, they go down to about 35 people and everybody who's staying knows we now have to design from scratch and ship a new chip before our runway runs out, which is nine months. You can't do that on a normal chip design cycle.

2 (44m 4s):

Takes like two years, right?

3 (44m 6s):

Yeah. The way that, you know, in the, with these fless chip companies, the way they would design chips is they would work on the design, they would send them over to the Fless company, the Fless company would produce some prototypes, they'd send them back, they'd test 'em, they'd go back and forth a few times.

2 (44m 20s):

You mean the foundry would produce 'em like the TSMC or the Samsung or the global foundries or

3 (44m 26s):

Now importantly Nvidia is not using TSMC at this point. 'cause they can't, they can't. T-S-M-M-C only works with the best and Nvidia is not the best. Huh? So they're using like second rate foundries and that process takes a long time. And then at the end of it, when you're sure you've got the, the design right, then you do what's called a tape out of the chip.

2 (44m 45s):

I love this term by the way.

3 (44m 46s):

It hearkens back to literally like when you used to tape, you know, masks to like do the photolithography on the chip back in the day.

2 (44m 54s):

So cool.

3 (44m 55s):

But it just means finalizing the design.

2 (44m 57s):

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

3 (45m 13s):

Yep. So they're like, we, we can't do this. They're like jenssen'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 and in our case we're gonna use it to emulate the graphics chip that we're, we're designing all in software. And it, you know, it works,

2 (45m 34s):

They're startups but they exist.

3 (45m 37s):

The problem is when you emulate it in software, you know, it's like it's really slow. So you know when you play a game and you're, you are looking at your computer or monitor or whatever, it's refreshing 30 to 60 times a second. If you're a professional gamer, you probably have it going at like 120 times a second, you know, frames per second. This emulator runs at one frame every 30 seconds. So they're gonna have to debug this thing in software to save this time going at one frame every 30 seconds.

2 (46m 5s):

It's just insane. That's

3 (46m 7s):

Brutal.

2 (46m 8s):

They're basically making this trade off of okay, if we wanna 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 30 seconds and look against some tests to verify that the output is correct. And if it is and this person does that mind numbing work and sits there just observing and observing and observing, then we will go right to manufacturing without ever producing a physical prototype and ship that.

3 (46m 47s):

And that is exactly what they do. They had to spend a million dollars just to get the emulator, you know, hardware and software to, to do this. Which

2 (46m 56s):

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.

3 (47m 3s):

So they go down to six months until their cash out in the company, they get it done in a few months and then they call up their foundry, I dunno if they're using United or or one of the, one of the other foundries in Taiwan, not TSMC. They're like, All right, we tape this thing out, send it to production and the Foundry's like, are you guys sure about that? They're like, yep, we're sure make you know, a hundred thousand units

2 (47m 28s):

If I'm remembering right. I think Nvidia basically was the only customer of that emulation software. Like that was a startup that really wasn't fully proven yet. But Nvidia was like, look we literally have no options.

3 (47m 42s):

Yeah they were the only customer and then that, that company went out of business after

2 (47m 46s):

It's wild.

3 (47m 47s):

Well and so the chip they designed so now the advantage like this is lunacy what they're doing. Obviously they have to do it 'cause their back is against the wall. The advantage of this though is they are now designing this chip with, you know, the same set of assumptions about what, 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 'em out for like 18 to 24 months. NVIDIA's gonna get this same, you know, generation of design out in six months. So this chip is called the Riva one twenty eight is what they call it.

3 (48m 27s):

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

2 (48m 33s):

It's big.

3 (48m 34s):

It's big. It's extremely powerful relative to anything else on the market.

2 (48m 38s):

Like more powerful than any customers are telling them they want. Yeah.

3 (48m 41s):

Way more powerful. Way, way, way, way, way more powerful. But you know, it comes with some downside with great power comes, you know, great 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 3D at the time had something like, let's call it like twenty four, twenty five different ways, like different sort of techniques.

2 (49m 7s):

These are the like blend modes.

3 (49m 8s):

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 'em. It just like freaking crashes. Like it just doesn't work. I

2 (49m 16s):

Thought even worse than that but basically like I, I think Nvidia had to launch a campaign going around to like 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 work. Great. You're gonna love 'em. They're so good and just use those.

3 (49m 39s):

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. But now they're actually going out and Jenssen's going to these developers trying to convince them to do this. And they all do it. Why do they do it? Because the only thing that matters is performance. Consumers are gonna buy hardware and games based on the quality of the graphics. This is like being discovered for the first time.

3 (50m 19s):

And so like people are willing to make a lot of compromises in, you know, service of performance. Nvidia is like the first one that figured this, this out because they have to go around and do this and developers all get on board.

2 (50m 31s):

And to be clear, it's because the consumer's making the buying decision right. On what graphics card they buy.

3 (50m 37s):

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, that's what NVIDIA's business is.

2 (50m 49s):

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.

3 (50m 60s):

Exactly. And the game developers are making decisions on what graphics cards to support,

2 (51m 9s):

Right.

3 (51m 10s):

And how to build their games with like the assumption of what's my target market of consumers like who do I think will this game run on? Do you need to have at least an X level performance rig in order to run my game or run my game in its fullest form?

2 (51m 27s):

So the developers are premeditating what graphics cards are going to be out in the market when their games launch and they're saying yes, it's gonna be the most performant one at the right price point. So whatever the mass market is, we kind of have to target that. And if you're telling us and we're 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, then people are going to buy that one. And so we must target

3 (51m 53s):

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

2 (52m 4s):

Yeah. What's the relationship between Crisis and Far Cry?

3 (52m 8s):

It was, oh no, far Cry was the first game. Yeah, the crisis engine. And then Crisis also. It was super convoluted. Basically my perception of this thing was when this came out, when Far Cry came out, this was like mid two thousands. The graphics were 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 played more than 10 minutes of it.

2 (52m 32s):

I'm pretty sure if your computer didn't support it, there was all these videos that people would record of like building a tower of like a thousand gasoline barrels and then shooting it and because it was too complex for their graphics card to handle their computer would just freeze. That was the failure mode of Far Cry with non-performance chips.

3 (52m 52s):

This is how the hardcore gaming industry evolves. Like Far Cry sold so much software and so much hardware just because people wanted to experience that, to attempt to experience that level of graphics. And so that's what the developers are starting to figure out and they're like, All right, well if you can ship this thing we'll use only those, you know, eight blend modes or whatever, like whatever it takes. 'cause we want, you know, graphical performance is the most important thing. So it works. They sell 1 million units of the Riva 1 28 within four months. Wow. I should have looked what the MSRP was of it, but that is a lot of revenue.

2 (53m 33s):

Yeah, no kidding. What year was this?

3 (53m 36s):

This was 1997.

2 (53m 38s):

Okay, so we're, it's an interesting era. Like the internet is a thing. We still have a few more years till the.com bubble crashes. PlayStation one is out, but PS two is not out yet I think.

3 (53m 51s):

Yep. PlayStation one. And with that, the gaming market kind of bifurcated into like sort of the, you know, 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. 'cause people are willing to spend so much money on this stuff. So at the end of this, Nvidia has now figured out these dynamics of the PC gaming market and they now have a process within the company to design and ship each next generation of their hardware in a six month timeline while the rest of the industry is on an 18 to 24 month timeline.

2 (54m 33s):

Necessity is the mother of invention.

3 (54m 35s):

To say this is huge is like understatement of the century. Huge. And it's huge for this market. But nobody even saw this at the time. Like Jensen didn't see this, nobody saw this. They're now shipping relatively, you know, doubling essentially the performance in each generation with their hardware and they're shipping it every six months. And you think about Moore's law, right, like Moore's Law was that the number of transistors on the chip equating to the compute power available at a given price point to the market would double every 18 to 24 months. Nvidia is now on a cycle, starting in 19 97, 19 98, where they are doubling the performance that they're delivering at a given price point to the market every six months.

2 (55m 23s):

It's fascinating. And they're also competing on a different vector than the CPU manufacturers because, and it's kind of amazing, we've made it an hour into the episode and haven't talked about this yet, but the magic of GPUs is that they're very, very parallel like cpu for anyone who's taken a low level computing class, you sort of know that like every time the clock ticks an instruction can sort of run and things move through the sort of long chain of operations that can happen within the CPU. And it's advancing things serially through the processor.

3 (55m 58s):

It's serial processing,

2 (55m 59s):

It can read from a register or it can add two things together. But like it's all happening serially.

3 (56m 5s):

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

2 (56m 16s):

Yes, exactly. And with graphics processing, like the magic of it is that it's super parallelizable. Like there's all these things that need to get outputted to the screen that do not depend on each other. And so you can do them independently. And so the vector that they're competing on is really like, oh, we can, and 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. Let's put a pin in that for now. But it's worth knowing the thing that they're doing is figuring out how to process more things in parallel faster.

3 (57m 4s):

Yes. So graphics cards like Nvidia is making at this point in time are really good at, in parallel lighting the pixels on a screen, you know, thirty, sixty, a hundred twenty times a second with the images that are being fed to them from like the game or the graphics program, which is living all in the CPU land. So like you're a game developer, you develop in, you know, Microsoft Direct 3D becomes Direct X or OpenGL is the open source, you know, competitor to this. You know, all that logic is really happening in the CPU realm.

3 (57m 44s):

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 N 64, you look at the graphics in those games or PC games from the time too.

2 (57m 59s):

They're all kind of the same.

3 (58m 1s):

They're all the same, right? All the lighting, like the lighting, it's all like pre-done. So like when you're a game developer, you set the scene, you'd never see like a character running around carrying a torch and that torch light like impacting the rest of the environment, it's all set in advance. Like no intelligence is happening in the GPU level with the screen. It's just lighting up the pixels

2 (58m 24s):

Basically in order to make it easy for developers. The software development kit is written at such a high level that you don't really get enough control to make your game stylistically different. You just get to lay out the items on screen.

3 (58m 40s):

It's all the same, it's all flat. Maybe you can program that like hard code that like, oh, time of day might change and like that might change the way things look but you're hard coding like what they look like. No computation is happening, right? If you're playing a game today, even the most basic, you know, mobile game or whatever, you're seeing dynamic lighting and shading, which we'll get into in a sec all over the place. So this is still like in the, you know, GPUs are like a really, really important sort of commodity, but they're a commodity. There's not a lot of smarts happening here. Yep. 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 now.

3 (59m 24s):

A lot of people start paying attention to them in a good way. TSMC that wouldn't even return Jenssen's calls back in the day. There's this amazing, amazing story. Did you watch the TSMC 30th anniversary? I did Celebration. This is so it's like three hours on YouTube.

2 (59m 40s):

This is worth a brief aside. This is how much pull Morris Chang from TSMC has. He gets the CEOs on stage of Nvidia

3 (59m 50s):

Arm,

2 (59m 51s):

Arm A SML, Qualcomm and Broadcom.

3 (59m 56s):

Yep. I don't think Lisa from a MD was there.

2 (59m 59s):

No, it was basically everyone but a MD of the sort of pillars of the TSMC ecosystem. I Mean Morris is playing interviewer, like it's very entertaining to watch him. It's

3 (1h 0m 9s):

Like a celebration of Morrison, of of TSMC. It's amazing. It's amazing.

2 (1h 0m 13s):

Yes.

3 (1h 0m 14s):

So in the section with Jensen, they tell the story of how Nvidia at this point it's gotta be TSM C'S biggest customer. I Mean they've been like tied at the hip forever of how this all came to be after the Reva 1 28 hits and it's become a big success. Jensen writes a letter to Mor, like a physical letter addresses it to Morris Chang in Taiwan

2 (1h 0m 40s):

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

3 (1h 0m 44s):

Exactly, exactly. They've all just been ignoring him as well. They should because they were a, you know, left for dead startup in a sea of startups. The letter gets to Morris, he opens it, he reads it in Taiwan, he does the most Morris Chang thing possible. He calls up Jensen on the phone right there and the phone rings as they tell the story in the Nvidia office. This is in the middle of their trying like mad scramble as a startup to ship these Riva one 20 eights that are coming in. They're testing 'em all by hand in the office. 'cause none of this stuff was, it's fresh off the line, it's not been tested, it's chaos. Jensen picks up the phone and is like, yeah, who's this? And Morris is like, hello, this is Morris Chang at tsmc.

3 (1h 1m 27s):

I got your letter and Morris says that there's like a silence on the other end for a couple seconds and then he hears Jensen yelling, everybody shut up. Morris Chang is on the phone. Oh amazing.

2 (1h 1m 42s):

And that's how TSMC became the manufacturer band video chips.

3 (1h 1m 46s):

Yep. The next year the two companies sign a huge multi-year deal for TSMC to become the primary foundry for Nvidia and still are today Jens and Morris are super close. It's a landmark landmark deal for both companies. So with now an actually really good foundry as their partner and this super unique chip development process, Nvidia just keeps accelerating. So in 1999 they rebrand their products. You know, they'd use the NV one first and then this REVA 1 28, they actually run a little contest of what they should name the products.

3 (1h 2m 28s):

And the winning name is geometry force forces with you, which they shorten to GForce, which anybody who knows who you know buys graphics card, the Nvidia GForce still the brand name they use for their gaming cards today and is probably the most, one of the most respected, you know, brands in the gaming ecosystem. And it's because this card that they ship the first G GForce in 1999, it's the GForce 2 56. It's so powerful. It has five x better graphics performance than like anything else on the market.

2 (1h 3m 7s):

And they call this like the first GPU, right? Don't they say like we're inventing the GPU. They

3 (1h 3m 12s):

Call it A GPU before this, the term GPU didn't exist. It was, these were graphics cards, graphics tips.

2 (1h 3m 19s):

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

3 (1h 3m 27s):

So they market this as the graphical processing unit. Now on the one hand that's like sort of like marketing bravado on the other hand that is like a very loaded statement to make and why, so what does Jensen and Nvidia mean by this? So Intel, you know, you think chips, you think Intel, right? You think Silicon, you think Intel. Intel's whole strategy at this point in time was basically they're almost like a biotech companies today. Like one of the big pharma companies and or, or put another way, it was another version of the Microsoft embrace extend extinguish thing.

3 (1h 4m 9s):

They would see they're all these peripherals sound cards, networking cards, all the see graphics cards, all the stuff we've talked about. They would let all these flowers bloom be like, oh yeah, yeah, yeah just plug into the PCI slots on our motherboards. No big deal. We're an open ecosystem, we want everybody to flourish. And then they would see which of these, you know, peripherals got consumer traction and then they would just turn 'em into, you know, a component in the motherboard

2 (1h 4m 36s):

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

3 (1h 4m 44s):

Well and before that, you know, integrated sound, integrated networking, like remember, oh it was so fun doing this research. Remember the company Creative and the sound blasters cards.

2 (1h 4m 53s):

Oh yeah, I remember

3 (1h 4m 54s):

Buying tons of that stuff. Like, and then at a certain point you stopped buying sound blaster cards, right?

2 (1h 4m 59s):

You're like, oh the motherboard does 90% of what I need to do and why would I spend extra money on a separate thing?

3 (1h 5m 6s):

Exactly. And so Intel, they'd just sit back, they'd watch all this happening, they'd integrate it game over for the startups.

2 (1h 5m 13s):

And there was like reasons for specialized stuff. Like I remember buying a special network card because the integrated networking capability of the motherboard on my, I don't know what it was a Mac 8,500 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 graphics card or you'd buy it directly from the OEM when they were making the computer and shipping it to you.

3 (1h 5m 47s):

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 outta

2 (1h 5m 55s):

Here. These things are like dead end businesses

3 (1h 5m 57s):

And there's no reason why graphics cards wouldn't be the same. So Jensen and Intel coming out and being like we're a graphical processing unit, we're a GPU, it's a big middle finger to Intel and this whole CPU dominant world

2 (1h 6m 15s):

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

3 (1h 6m 29s):

Yep. But this is where, you know, Jensen is just such a master strategist and Nvidia is so great, like this whole kind of orchestration of a bunch of things all hit over the next couple years. So first Nvidia goes public, you know, they've now shipped the REVO 1 28 was a huge hit. This new GForce 2 56 flying off the shelves, they go public in beginning of 1999 at a $600 million market cap. So a hundred x return from the $6 million post money valuation on the Sequoia and Sutter Hill round that gets them, you know, some more capital. And then behind the scenes they're working, they're in talks with Microsoft.

3 (1h 7m 12s):

Microsoft's got a secret project that they're working on at this time. The Xbox, which you know, we talked about a lot on the Sony episode and so many times on the show and Microsoft comes to Nvidia and like we want you to be a key supplier of the graphics at the GPU for the Xbox. And they do a huge, huge deal. $500 million a year deal for Nvidia to supply the graphics for the Xbox with a $200 million advance. Hmm. And the chip that they use is a modified version of this incredible new chip that NVIDIA's working on.

3 (1h 7m 57s):

This sound like Steve Jobs, David Jetson sounds like Steve Jobs talking about this. The GForce three which introduces for the first time programmable shaders and lighting on the GPU. Everything we just talked about about though like the GPU massively parallel can light all these pixels, but it's essentially just taken instructions that are pre, you know, hard-coded, baked in on what the lighting's gonna look like. Now you can program for these GPUs and you can make dynamic lighting in games and 3D graphics that is calculated.

2 (1h 8m 35s):

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 at the GPU level what is happening. And so this is like Of course it's cool because it's a wave of new consumer experiences that can happen because every game developer can kind of stylistically put their own stamp on games. But it's a totally different metaphor for the computer architecture where suddenly you can program A GPU and I guess that's why they're calling it A GPU.

2 (1h 9m 18s):

And this is different than a graphics card.

3 (1h 9m 20s):

And NVIDIA develops in conjunction with this, they call it CG, literally like they extend the C programming language with graphics libraries and capabilities to directly program graphics and lighting and shaders for the GPU. So this makes, you know that sort of like marketing, you know, oh this GForce 2 56, it's a GPU now it's real. Like this is a graphical processing unit that is intelligent, that is every bit is, you know, maybe not every bit as important as the CPU yet, but like this is like the stake in the ground of like this is no sound card, this is not gonna get commoditized.

3 (1h 10m 2s):

Do you

2 (1h 10m 2s):

Know if this was the GForce FX or if the GForce FX was a similar version of this that was available to pc?

3 (1h 10m 9s):

That's a good question. It was the GForce three was the, the PC version of this.

2 (1h 10m 14s):

Okay. This move to programmable shaders was a bet the company move and it was jenssen'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.

3 (1h 10m 42s):

Yeah, I Mean this is the, you know, 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 enormous. So at this point Intel's like we might have a problem here,

2 (1h 11m 15s):

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.

3 (1h 11m 22s):

Yep. And irony of ironies Jensen presses this even further. He does a big partnership with a MD. It's

2 (1h 11m 28s):

Worth knowing here when you're saying a MD, 'cause people probably know A MD and Nvidia are big competitors today in the GPU world.

3 (1h 11m 34s):

Not yet.

2 (1h 11m 35s):

Right? A MD primarily made CPUs at this point. They made processors and competed with Intel. They hadn't yet bought a TI, which is where the Rayon business comes from. That's all the graphics stuff that they do today.

3 (1h 11m 46s):

Yeah. A TI at this point was the number two competitor. Nvidia. Actually an amazing story too was a Canadian company started in the eighties and pivoted into graphics cards. Like very different, you know, I feel like there's a lesson in here, right? We could talk about this in playbook, but like when all the VCs funded these 90, you know, Silicon Valley startups to go make graphics cards, 3D graphics cards, the only two surviving ones were Nvidia, which went through this hellish journey and then these Canadian guys that were like totally outta the ecosystem and like did it sort of more in a boot, more bootstrapped way and evolved into this space.

2 (1h 12m 25s):

Jensen has a great quote about this and he's giving this lecture at at Stanford years later and he says, when technology moves this fast, if you're not reinventing yourself, you're just slowly dying. You're slowly dying, unfortunately at the rate of Moore's law, which is the fastest of any rate that we know. Yep. It's so clarifying of how he thinks about why Nvidia needed to do these like three complete transformations of the company. Bet at all. Risk at all. 'cause if you're not, you're one of those 89 companies.

3 (1h 12m 57s):

Exactly. So Intel's like holy crap, we might have a problem on it. Not, not a problem. Like this is not a problem for Intel.

2 (1h 13m 6s):

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

3 (1h 13m 11s):

Right. Intel is used to at this point just, you know, like Microsoft at this point. Oh sure. You know, you want to go make Word perfect, 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 dedicated Intel graphics, you know, GPUs, graphics cards competing as separate cards. Whoa, I don't know that Intel had ever done that. I Mean I may be speaking out of turn here, but like as far as I know, I don't, this is not a common strategy for Intel. It's usually integrate Yeah, into the motherboard and the CPU U.

3 (1h 13m 52s):

They come out with their own external cards right around this time, like 1999 to directly compete and like they suck. Like these are like some of the worst reviewed graphics cards in history.

2 (1h 14m 3s):

Talk about not your core competency,

3 (1h 14m 5s):

Not your core competency.

2 (1h 14m 6s):

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

3 (1h 14m 35s):

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 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. And especially leading into, you know, mobile. Although Intel and mobile is a story for another day, but for the hardcore market and that that's, that's making it sound too small for the market of anybody who cares about graphical performance and quality, which is not just gaming at this point, you know, it's 3D modeling it's architecture, it's lots and lots of graphical high performance graphical computing applications.

3 (1h 15m 25s):

You're always gonna want. It's this dynamic and it sets up just like Moore's Law, whatever the current maximum is, it's not enough. It's never enough. You always want more as good as graphics are today, it'll never be good enough 10 years from now, game graphics will make today's graphics look silly and we'll all be in the Metaverse or the Omniverse if Nvidia has their way. But it still won't be good enough. Like it's Moore's law, you always want as much performance as possible.

2 (1h 15m 51s):

All right listeners, it is time to talk about one of our favorite companies Stat Zig. It's funny David Stats Zig has gone from this little startup when we first started working with them a couple years ago to this total powerhouse now

3 (1h 16m 4s):

I know, it's wild. I was looking it up and they have added all these customers since we started working together. OpenAI, Figma, Atlassian, versa Notion, tons more at this point. If there's a growth stage tech company out there, there's a pretty good chance they're using Stat Zig.

2 (1h 16m 19s):

Yep. So listeners, if you are unfamiliar with Stat Zig, they basically took what was the standard product infrastructure at every big tech company and they built it as a standalone company. This includes advanced experimentation tools, AB testing, feature flags, product analytics, session replays and more. So if you're building the next great software company, this sort of infrastructure is essential because it allows your product and engineering teams to release things quickly, measure the impact of them and track progress over time.

3 (1h 16m 49s):

Totally. So I Mean as we've talked about on the show forever at companies like Facebook or Netflix, data was just a part of how everything was built, which contributed to all the crazy bottoms up organic growth that they had. Now with Stat Zg, you can get that from day one at your startup. And today they're not only trusted by startups but also by more mature enterprises like Bloomberg and Microsoft and electronic arts turns out that a single system for data-driven product decisions is useful at any scale.

2 (1h 17m 15s):

Yeah. And by the way, the scale they're operating at is completely insane. They process over 2 trillion events per day. Now by the way, David, this is updated, the last I checked it was 1 trillion and then this morning I pulled it up 2 trillion and they handle releases to billions of end users. If you're listening to this podcast and you've used software in the last few years, there is a very good chance you've been a part of many experiments orchestrated by stats.

3 (1h 17m 39s):

Yeah, it's just awesome. And as they've gone up market, they've also started to offer some interesting deployment models like being able to run the whole thing natively inside your existing data warehouse or just using Stat Z's fully hosted solution.

2 (1h 17m 51s):

If you want to leverage Stat Zig to grow your business, there are a bunch of great ways to get started. Stat Zig has a very generous free tier for small companies, a startup program with a billion free events that's $50,000 in value and significant discounts for enterprise customers. To get started, go to stats z.com/ Acquired and just tell 'em that Ben and David sent you

3 (1h 18m 13s):

Thank you stats Zig.

2 (1h 18m 14s):

Okay David, so Xbox comes out, Nvidia has a card in there that is the, the GPU of the Xbox that has programmable shaders. So you know, rather than, 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 What happens after that?

3 (1h 18m 37s):

Basically the company goes like Supernova in a good way, in a good way at this point in time. So the fiscal year that ends January 31st, 1999, this is like right before they go public or right as they go public. They did $158 million in revenue the next year. The fiscal year ended January 31st, 2000. So like the calendar year 1999 they do $375 million in revenue. So more than double that year. Wow. The next year they do $735 million in revenue the year after that, which is basically the calendar year 2001, the year the Xbox comes out, they do just about $1.4 billion in revenue,

2 (1h 19m 23s):

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

3 (1h 19m 30s):

Indeed. This is the company's essentially ninth year of existence. They're already doing over a billion dollars a year in revenue throughout

2 (1h 19m 37s):

The company's history. They basically have these like six to 10 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 themself again. And so we sort of saw it the first time before the competitors come in and then the competitors come in and then we see it again with them figuring out we gotta do the emulated version of letting our engineers design the chips and lay out the chips so we can be faster than everyone. And then everyone sort of catches up and 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.

2 (1h 20m 21s):

They did obviously close to $2 billion as we move through 2001. They stayed reasonably flat for a few years after that. I think they eventually did 2.8 billion in 2005, but it was kind of barely profitable. Like they never lost money. But net income for each of those years was only a couple hundred million or less. So it's not like they're this like super free 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.

3 (1h 20m 53s):

Yep. A TI Of course. And then in 2005, I think it is a MD, that's

2 (1h 20m 60s):

Where they start shopping around oh six is when the transaction actually happens.

3 (1h 21m 3s):

They buy a TI and Of course now A MD is the main competitor to Nvidia. So we're gonna tell those stories on the next episode. But basically like a little sort of teaser what's going on here? They kind 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 right around this time there's something that ultimately becomes pretty amazing that happens, which is they've achieved the dream at Nvidia. They've created a programmable GPU, it is truly A GPU, it rivals the CPU.

3 (1h 21m 48s):

This is the model they have driven forth. This new industry of computer graphics enabled a whole generation of storytellers to program their GPUs and tell stories. A whole new class of users and developers starts to tinker around with these GPUs and Jensen likes to tell a little story that's probably apocryphal, but you know, hey, we'll repeat it here as a little teaser for next time. Right around, you know, sort of the early two thousands, a quantum chemistry researcher at Stanford calls up Jensen 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 and it takes a couple weeks to, you know, finish the computation on these models.

3 (1h 22m 46s):

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 buying a bunch of your GForce cards. So I did and that I should try porting my models into CG into your, you know, graphics, computer language and, and just see what happens. Well I did it and my computation finished in a couple hours so I, I waited a couple weeks for the super computer here at Stanford to finish. I checked the results and they were identical.

2 (1h 23m 21s):

Boom

3 (1h 23m 23s):

Boom. And it's like, so I just wanna thank you Jensen for making my life's work achievable in my lifetime. This is for sure something that Jensen made up. Maybe he did, maybe he didn't. It's

2 (1h 23m 35s):

Probably cobbled together from a few different people's experiences

3 (1h 23m 37s):

Probably it's, it's a composite but every word of it is true in spirit.

2 (1h 23m 41s):

Yes there is a whole industry called scientific computing or a whole segment that Nvidia would be able to address in the future, but they need a whole lot of tools to be built for them to be able to really use GPUs for all those purposes and more with machine learning and everything else. But right now, yes you are buying off the shelf G-Force 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. What's interesting is the industry perception around this time was that Nvidia had started to sort of focus on this high performance computing segment and that they were starting to take their eye off the ball in gaming.

2 (1h 24m 28s):

So people were starting to think like, oh maybe it TI is actually more interesting as a gaming specific graphics card maker at this point. And there's a little known fact that is, so you mentioned this A-M-D-A-T-I deal and like we all think the A MD radi on at this point, you don't think about the A TI radi on which was the, it was the they, I think they retired the A TI brand in 2009. But AMD's first choice was actually in Nvidia. Ah. So a D tried to buy Nvidia to make that their graphics line and it was possible because it's not like the stock was blowing up at this point in time. It had had this sort of few years of reasonable stagnation before we get into late 2006, 2007.

2 (1h 25m 13s):

And certainly people didn't see the machine learning market, people didn't really see the scientific computing market and it was like, hey, maybe this company needs some guidance from a smart company like us, A MD. And so they make the offer and there's the cover story on Forbes, we'll put it in the show notes, but there's this article that comes out called Shoot to Kill and Jensen in this merger acquisition talk with a MD insisted that he be the CEO of the combined company and that is the thing that blew up the deal. And instead a MD went and bought a TI and the rest is history.

3 (1h 25m 51s):

Oh man that is such a good, what would've happened otherwise? Well should we use that to transition into analysis for this one?

2 (1h 25m 59s):

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 A-M-D-A-T-I deal has just happened. We're sort of looking forward. It's 2006, you know, what's the bear and bull case for the company? And I thought an interesting data point to sort of ground this discussion would be that if we look at the gross margins today for Nvidia, which we will talk in our whole next episode about everything that they do that's so insanely differentiated, they sell their GPUs at a 66% gross margin hardware business with a 66% gross margin back in 2004. That gross margin was only 29% that they were able to command as a premium on their cards.

2 (1h 26m 46s):

And so you can kind of see like all of their economic potential was being competed away and they weren't doing anything to differentiate in a way to get any sort of pricing power. And so you think you make that 29%, then you need to use that to pay all your overhead and fixed costs and your engineers and develop the next product and pour it into 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 2006.

3 (1h 27m 16s):

Yes. And there's also another reason why their gross margins are so low in those years following 2001. So they made this deal with Microsoft right to power the Xbox and it was absolutely the right strategic decision to power the Xbox to get Microsoft's support in creating CG for programmable shaders, 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 there are three game consoles in the history of game consoles that Nvidia has powered the original Xbox, the PlayStation three Oof.

3 (1h 28m 10s):

Which we'll talk about next time. Oof. And the Nintendo switch. Hmm. They have not done any others

2 (1h 28m 17s):

Really.

3 (1h 28m 18s):

And people always are like asking Jensen about this and whatnot and you know, he's, he's diplomatic about this but 'cause it's a crappy gross margin business, right? Like yeah there's a $500 million a year revenue deal with Microsoft, you know, $500 million a year when their whole company revenue is a billion. Well that's, that's $500 million a year of very low gross margin revenue.

2 (1h 28m 40s):

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 and really change the world, then we have better things to spend our resources on. And that is kind of Jensen speak for like no there's crap margins in that. I'm not doing that. But he is right that like given a finite amount of resources, you have to allocate your capital and your resources in the most optimal, both short-term cash flowing way but also long-term strategic way.

2 (1h 29m 24s):

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.

3 (1h 29m 34s):

It's probably at this point in time a little too much of an exaggeration to say that they're outta the fire and into the frying pan having solved their intel existential strategic challenge and ending up now sort of at odds with Microsoft. That's too much. But there's a lot of truth to that. So you know, if you're looking at this stock in those years, especially as revenue starts to flatten and a big part of that is coming out, you know, towards the end of the Xbox generation of consoles leading into the Xbox 360, which Of course Nvidia does not power, that's a lot of gaming revenue, top line revenue going away. Meanwhile they're spending tons of resources investing in this new high powered computing segment for these researchers.

3 (1h 30m 19s):

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

2 (1h 30m 25s):

And in 2006 Intel launches or announces this project Larrabee where they're gonna be like a full fledged GPU maker. I Mean this is like a totally 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 honest to goodness GPU maker. So like are you betting the farm on scientific computing?

3 (1h 30m 58s):

How big is that market?

2 (1h 30m 59s):

So the answer is yes and that is also the bull case and it turns out scientific computing would be so much more than scientific computing and it would be, you know, the acceleration of all the other things in our computing world that has been very advantageous to become parallelizable. But I will leave it there so I don't have too many spoilers but that is 100% the bull case and 100% what happened.

3 (1h 31m 23s):

Yeah, it's interesting. We're working on an episode episode two with Hamilton Hel Marin is colleague Chen y at Strategy Capital about power

2 (1h 31m 32s):

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

3 (1h 31m 37s):

It probably won't be out yet when this episode comes out but it'll be coming out shortly thereafter. They make the point and it's a very, very valid one that 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 then having to go develop power. It's a whole, you know, second journey that you have to go on.

2 (1h 32m 1s):

It's a whole second invention. And at at this point Nvidia had definitely found product market fit but had not yet found their source of power.

3 (1h 32m 11s):

So you know, if you're looking at this company at this moment in time, especially as revenues flattening coming off the Xbox contract costs, OPEX is going way up, investing in this sort of speculative new area, I can totally see looking at this and being like wow, this is yet another Silicon Valley startup that had immense product market fit, top line revenue soared. But now we're kind of coming to the end of that and there's not a lot of power, you know, as defined by sustainable, you know, economic profit, you know, operating cash flow coming out of this thing.

2 (1h 32m 51s):

So then as we talk about power here, what power do they have? And for listeners who are newer, this is really the what is it that enables the business to have persistent deferential returns or sort of in a sustainable way be more profitable than their closest competitor. They really didn't have power. I Mean I'm trying to think which of the seven powers can we make the best case that they did have? It's not switching costs. Switching costs are crazy easy.

3 (1h 33m 20s):

So switching costs is interesting, right? Like I think they were trying really hard to develop it. They did a really good job. I Mean they made CG in collaboration with Microsoft and CG works on Nvidia products but it is not like Cuda today to, to flash forward to next time.

2 (1h 33m 41s):

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

3 (1h 33m 46s):

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

2 (1h 33m 52s):

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 you wanna commoditize all of our suppliers

3 (1h 34m 6s):

So you maybe some an attempt at switching costs that was not fully realized. I think they probably thought it and did for a while have processed power in this six month shipping cycle that none of their competitors could match for a while.

2 (1h 34m 19s):

Yep.

3 (1h 34m 20s):

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

2 (1h 34m 27s):

Okay. Playbook. I have one big one that we have not discussed. We sprinkle in lots of like playbook themes, but there's one to me that I want to call out and draw a through line to something that's happening with Nvidia today and that is simulation. So there's a thing that we're 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 on stuff and it happens way faster and it lowers your iteration time.

2 (1h 35m 11s):

And another one is drug discovery. Like you look at how fast we came up with Coronavirus vaccines simulation, it's an absolute miracle and everything in our world is being compressed 10 times 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 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.

2 (1h 35m 52s):

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.

3 (1h 36m 2s):

Similarly, a playbook theme I wanted to highlight that we have not talked about explicitly yet is just the power of like democratizing tools for developers. You know, and Jetson really saw this back in his a MD days before going to LSI logic, but the ability for Nvidia to use an emulator software emulator to design their chips and then Of course the massive, massive strides that the EDA industry has made since then. And then Nvidia itself, you know, enabling, you know we haven't really talked about it as much, but like Jensen and Chris and Curtis's original vision did come true.

3 (1h 36m 43s):

Like they created a new artistic platform for artists to tell their stories. And without this industry and all the hardware software tools that went into creating it, like there's no way that you know any, but you would have to be a John Carmack to tell a story in this medium. And there are very, very few John CarMax out there in terms of being gifted enough developers and surrounded by storytellers too and being a great storyteller himself to like be an artist, you know, to be a Nvidia talks about this now in their marketing materials to be da Vinci and Einstein, you know, together in one person.

2 (1h 37m 26s):

Yeah. It reminds me of the people that do like the crazy cool art in Microsoft Excel by like painting each of the cells a different color. You had to be that type of person to be a game developer in CarMax era because it was esoteric as hell to be able to actually figure out how to make this hardware do what you want.

3 (1h 37m 44s):

Another big one I want to highlight, you know, I just keep thinking back, going to the thinking back to the original time when Nvidia was funded and I wonder what like if they're really honest with themselves, like what Sequoia and Don Valentine would think about that. Hmm. They made the wrong venture bet. Like in a, in a market like that we see it all the time. Like look at Web3 right now. If there's a team making some new vision for a class of applications in Web3, like they're gonna get term sheets from everybody and then there's gonna be a million copycats the next day.

2 (1h 38m 21s):

It is the beauty of proliferation and then consolidation. I Mean Buffet has, I think it's in a 2000 fortune article that he wrote. It's weird that I know that, but I think that's right in an op-ed about how there were whatever it was, 70 car companies before we narrowed it all the way down to four GM and Chrysler and the airlines were sort of the same way. There's this proliferation, there's massive, there's no one can really differentiate, no one can build any power and so you only have a few survivors left and in general they compete on pre low margins when there's only a few left and their defensibility comes from their scale. You know, I think open question if that's sort of how the graphics market necessarily matured, but you're absolutely right to like sort of self-reflect on the time when Sequoia and Su Hill invested to say, would you make that type of bet again?

2 (1h 39m 13s):

You backed one of the two winning horses out of 90. Should you do that and just say, well we're betting on amazing founders or should you

3 (1h 39m 21s):

Well I think that's, so this is the nuance. I think what is so cool in front, you know, the fun of the art and the science of sort of what we do, the company they backed was wrong and yet it became, I don't know how long Sequoia's held, I Mean I think a lot of the GPS at Sequoia and certainly Mark Stevens who is one of my professors at GSB, who was on the board for Sequoia, is still on the board, have held their shares personally for like to this day. Like that's one of the best venture investment returns of all time. Full stop period.

2 (1h 39m 54s):

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

3 (1h 40m 1s):

Right? And so like they were wrong intellectually and yet they were right, right. And like why were they right? Like they were right because frankly of Jensen

2 (1h 40m 13s):

It was a reasonable enough market. The question is what are you better off doing what they did and investing at the proliferation phase on someone you believe is going to figure it out and have a good shot at being one of the winners? Or should you wait until consolidation and just pay that much higher price in order to back one of the ones that are already running away with the market?

3 (1h 40m 34s):

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

2 (1h 40m 38s):

Were no stages of venture capital. There was, you raise your venture capital and then hopefully you're profitable enough to go public.

3 (1h 40m 44s):

They did raise some more money in between that initial 2 million and going public. I think they raised 20 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 20 million. But it's really interesting to think about these cases take Sequoia and Sutter Hill too, you know, and specifically like they've gotten it right so many times but it's not a straight line. So like what's the lesson from that?

2 (1h 41m 10s):

Yeah, and the magic was that Jensen really figured it out early that they were in a business that was totally at the mercy of Moore's law. And so like in having that initial realization as early as they did with the proliferation of competitors and everyone doing, you know, the triangles and direct 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 to stay ahead other than ruthless self-examination and completely upending and rebutting the business. Yep.

3 (1h 41m 47s):

Ship faster and and reinvent. Yep.

2 (1h 41m 49s):

Yeah. So that, I Mean that that to me is why they, why they survived.

3 (1h 41m 55s):

If you think about the class of companies that are like the greatest venture returns of all time, some of them are like Nvidia, where like you look at the team, you look at the business plan, the thesis originally and like yeah it wasn't a straight line but it worked out. But then some of them are, you know, Sequoia even used to talk about this on their website, the Misfits, the ones that look like Unfundable

2 (1h 42m 23s):

Steve Jobs smelling bad, you know, that sort of,

3 (1h 42m 26s):

Right. Yeah. So it's like, and I think you know, plenty of venture firms but I, I have to hand it to Sequoia over history too. Like they've done a really good job of doing both of these. They do the Steve Jobs and they do the the Jenssen's.

2 (1h 42m 40s):

Okay. Listeners, now is a great time to introduce a new friend of the show who many of you will be familiar with. Claude. Claude is an AI assistant built by Anthropic and it's quickly become an essential tool for us in creating Acquired and the go-to AI for millions of people and businesses around the world.

3 (1h 42m 58s):

Yep. We're excited to be partnering with them because Claude represents exactly the kind of step change technology that we love covering here at Acquired. It's a powerful tool that fundamentally changes how people work. I know Ben, you have used Claude for some Acquired work recently.

2 (1h 43m 13s):

Yes. So listeners, I used to take four plus hours the day before recording to take all the dates from my raw notes and put them in a table at the top of my script for recording day on the Rolex episode. I actually fed my raw notes into Claude and asked it if it could do that for me, which was amazing. I just got my most important a hundred dates for the episode done in like 20 seconds. You

3 (1h 43m 38s):

Texted me this table. It was awesome. Yeah,

2 (1h 43m 40s):

That freed up an extra half day that I used instead to focus on explaining how a mechanical watch works, which I'm so glad I got to spend the time doing that instead of making the table.

3 (1h 43m 49s):

Totally. So cool. I was actually just chatting with Claude to brainstorm ideas for something big that you and I are working on for later this summer and it was insanely helpful. Listeners stay tuned to hear all about that.

2 (1h 44m 1s):

Yes. So listeners, by using Claude as your personal or business AI assistant, you'll be in great company organizations like Salesforce, Figma, GitLab, Intercom, and Coinbase all use Claude in their products. So whether you are brainstorming alone or you're building with a team of thousands, Claude is here to help.

3 (1h 44m 18s):

And if you, your company or your portfolio companies wanna use Claude, head on over to claude.com, that's C-L-A-U-D e.com or click the link in show notes.

2 (1h 44m 30s):

All right David, so what is the company that they invested in?

3 (1h 44m 34s):

Ben, you are talking about Keyhole.

2 (1h 44m 37s):

Yes. I thought you would know. So I love this little foreshadow before we get to grading because I think it's so interesting that Jensen basically saw the potential of Keyhole and without sharing what Keyhole became, I think astute listeners will know

3 (1h 44m 50s):

We've talked about it un Acquired and

2 (1h 44m 51s):

We have, we've done an episode,

3 (1h 44m 52s):

A whole episode on it.

2 (1h 44m 54s):

Basically this company that can't raise any money from anyone else comes and pitches Jensen and he's like, oh my God, I see this, this is the future. This is simulation. Like you are creating a model of the earth in software and people can just navigate around the earth. And so now that I've given it away a

3 (1h 45m 12s):

Graphical model of the earth,

2 (1h 45m 14s):

Yes, Google Acquired it, it became Google Earth and Nvidia was one of the 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. And one of the main reasons that I think they invested was because he wanted to stay alive so they could keep demoing it to customers.

2 (1h 45m 56s):

Great. Because it showed off Nvidia technology so well. But I just love that little tidbit. Yeah,

3 (1h 46m 1s):

We did our episode, God, it was years ago now at the Google Maps episode. That was such a good one.

2 (1h 46m 6s):

Yeah. Where to keyhole And

3 (1h 46m 10s):

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

2 (1h 46m 19s):

Zip dash.

3 (1h 46m 20s):

Zip dash, yes. And they were all like 20, $30 million acquisitions. Amazing. That's what's so cool about this. And I think maybe this is the like where Jensen and the Nvidia story bridge from like the, oh it was the, you know, obvious investment market to bet on team to bet on, to go all star engineers to go build this graphics card. Nobody really could have seen that Graphics were gonna become a lot more than games. Like you maybe could have seen it like, you know, there was SGI and Hollywood and Jurassic Park and there were some military applications for computer graphics, but very few, even Jetson and Nvidia, they were like video games.

3 (1h 47m 6s):

So the thing, fortunately

2 (1h 47m 8s):

That became the biggest entertainment medium. And so even if that was your only market

3 (1h 47m 11s):

Keyhole on Google Earth, and Google Maps is such a great example of like computer graphics became so much more important than like relevant beyond just video games. And that's all computer, you know, dynamically generated programmable computer graphics that are making all of that, all of that happen. All right, so how are we gonna grade this?

2 (1h 47m 32s):

Yeah. So I'm thinking given the opportunity, the market opportunity that existed between 1993 and 2006 four computer graphics, how did Nvidia do at exploiting that market opportunity? And like 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 their value creation was amazing, their value capture.

3 (1h 48m 4s):

Yeah,

2 (1h 48m 5s):

They did better than anyone else as far as I could figure out. The question I was sort of trying to figure out is that there were 90 other competitors doing same-ish thing, two-ish survived. Was there anyone else in the value chain that was able to do a much better job capturing, like, would you rather have been Microsoft than Nvidia?

3 (1h 48m 27s):

This leads into the really interesting question to think about for Nvidia in this period, Microsoft did basically nothing. Now, okay, that's like, like that's not fair to Microsoft. Sure.

2 (1h 48m 38s):

There was a large team that did direct DirectX, huge

3 (1h 48m 41s):

Team, you know, and the Xbox project was amazing and like, I don't mean that in any way to throw shade at anybody at Microsoft, but like they were in this position where they could just sit there, they could watch the market develop for computer graphics and they could be pretty, you know, by making good, very good strategic decisions, they could capture a ton of the value with other companies taking the risks of developing the market, figuring out all this stuff. And then, you know, Microsoft can come along and be like, great Nvidia, we're gonna help save you from Intel and in return you're gonna, you know, give us a really sweetheart deal on these chips and you're gonna put us in business with Xbox and by the way, the other side of your gaming and computer graphics business on PCs, we're gonna become your primary partner for that too.

3 (1h 49m 37s):

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.

2 (1h 49m 48s):

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.

3 (1h 49m 59s):

No, it's not fair for Xbox at all. It's not. It's not.

2 (1h 50m 1s):

But it is an interesting way of, right, like to put it another way, and let's exclude Xbox for a moment. You're basically just recognizing that Microsoft had an unbelievable position in the market and did an amazing capital allocation job exploiting it and basically saying, Hey, you know what? You know what? We don't need to do all that crap that like Nvidia and a TI and all those guys are doing, you know how we can still retain our market position and continue printing money the way that we do this thing. And they did that and they didn't get into the commodity business and they were brilliant.

3 (1h 50m 35s):

We don't need to be in this brutally competitive industry where like if we don't ship six months ahead of our competitors, every cycle we're toast.

2 (1h 50m 44s):

Yeah.

3 (1h 50m 45s):

So I think, you know, in this kind of like grading question, oh man, the longer we do this show, the more I realize this is like a mega theme of Acquired that like Microsoft in the nineties, early two thousands was such a power and the antitrust, you know, the DOJ case really, really crippled it probably for good for the ecosystem.

2 (1h 51m 8s):

Then the 3D chess version is, and this kind of foreshadows the next episode because Nvidia had to learn these hard lessons and had to develop like was forced to develop these really crazy competencies like eventually developing Cuda that would power this whole machine learning and scientific computing revolution. Was it bad for Microsoft to not have to grow that DNA 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,

3 (1h 51m 35s):

That's a great point.

2 (1h 51m 36s):

I don't know enough yet about how the machine learning market is gonna develop or has developed in order to sort of make a call yet on that point. But if you are just standing there in 2006, reflecting back Nvidia fought for their life and won

3 (1h 51m 54s):

Multiple times

2 (1h 51m 55s):

And Microsoft just leveraged the crap out of their amazing position. Yes. And probably achieved about the same outcome.

3 (1h 52m 4s):

Yeah. Both of these two fighting for their life company. Defining moments from NVIDIA's first 10 to 15 years, the overcoming the 90 competitors and then the building and making the case that they're not gonna get commoditized by Intel. That the GPU is gonna be a standalone important thing. Microsoft profited hugely from both of those.

2 (1h 52m 29s):

Yep. It's so true. I will say Nvidia doing what they did has been net unbelievably positive for the world. Like I watched the Nvidia GTC conference, the 2021, 'cause the 2022 is about to happen. And just like the review of all the stuff they're involved in is so inarguably good for humanity, we need way less energy to do way more interesting stuff. That's good for humans because Nvidia exists and without doing this first 13 years, they would not have laid the groundwork to be able to do all of that in the future. So that's like one sort of contorted lens to look at it through.

3 (1h 53m 6s):

I think I give Nvidia for this period of time an A because they're basically the only company that survived a t. I did a for sure, Of course, but in a very different fashion. And they created this whole industry almost inarguably created and shepherded this whole industry. But it's not an A plus because Microsoft, well shoot, there was the DOJ case until the DOJ case. Yeah,

2 (1h 53m 38s):

It's true. All right. I like that. Hard to argue with it. Carve Outs.

3 (1h 53m 43s):

Carve Outs. I have a fun and very appropriate one for this episode. Elden Ring. Have you heard about this Ben? No. You're not a gamer. So you, you need to, we need to like get you into gaming after, you know, doing all these episodes now. It's so fun. It's just like, it's great. So Elden ring for people who don't know is the latest from software game and it's on all the platforms, console, pce, et cetera. Lots of people are saying this is probably gonna be, 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.

3 (1h 54m 26s):

But like these, the world building is unbelievable and Elden Ring is the first one to come out on modern platforms and just like everything about it, the graphics, the scale, the breadth of the world, the story George 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 researching Nvidia 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.

2 (1h 55m 7s):

Cool. 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 10 years.

3 (1h 55m 21s):

Inspired by Jensen

2 (1h 55m 22s):

Called Starting Strength by Mark Rippetoe. Yeah. Apparently inspired by Jensen and I didn't even realize it, but it's like I reactivated a gym membership and I went back to the gym, you know, started kind of from square one in terms of like doing all the basic barbell lifts. It's just been really f like it's a new hobby. It's something I did like 10 years ago and then totally led atrophy and the way that I love to work out and at least historically over the last five to eight years has been like endurance sports. So, you know, training for marathon or doing week long bike trips and stuff like that. And it's just very fun to get back into the like every other day try and, you know, lift as heavy as you possibly can for a few reps rest for a long time.

2 (1h 56m 5s):

You know, make sure you get all your sleep. It's a very different mentality. And so it's been fun doing that again.

3 (1h 56m 11s):

I love it. It's like a, I feel like we're both becoming like better versions of our high school selves. You know, I'm like a, like a full on like gamer again and you're getting back into weightlifting

2 (1h 56m 21s):

High school. Me would've been like, what? Why would I work out? That doesn't sound fun.

3 (1h 56m 26s):

Okay. College u, college U

2 (1h 56m 28s):

Fair. All right listeners, that's all we've got. We are very excited to at some point come back and talk to you about 2007 through 2022 with Nvidia and the absolutely unfathomable things that they have done. Imagine if you started a business in the early 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 that the same technology was uniquely able to do. That was like 10 times bigger than the original thing and no one else was even close to you. 'cause you had like 18 years of like building stuff and learning about these technologies to be the best company in the world to take advantage of that next thing, which obviously is machine learning, it is just like an oh my god story.

2 (1h 57m 18s):

And then you layer on top of that, the fact that gaming actually was like 10 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.

3 (1h 57m 29s):

Ah, so great. This, this is the kind of stuff that like we do acquire for. I just like been so jazzed about this. Yeah,

2 (1h 57m 37s):

I got a lot of research to do on parallel processing and like why this was so perfect for all the machine learning and cryptography use cases. But that's why we get some time between episodes to go and do more research and to watch GTC, the GPU Technology conference, their annual developer conference 2022. So thank you so much for listening to us. Leave us a review on Apple podcast. If you listen there or with the new Spotify ratings feature on their mobile app, share it with a friend if you like it. We welcome lots of feedback and fortunately in having a part two, we're gonna be able to take your feedback and actually work it into the next part of the story.

2 (1h 58m 17s):

So Acquired fm slash Slack, come hang out with us, talk about this, check out the LP show and we've got a job board. If you are looking for the next stage of your career, we have curated all of the positions at 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.

3 (1h 58m 38s):

We'll see you next time. Indeed. Who

1 (1h 58m 41s):

Got the truth? Is it you? Is it you? Is it you Who got the truth?