Nvidia: The GPU Company (1993-2006)
Ben Gilbert (host), David Rosenthal (host)
In this episode of Acquired, featuring Ben Gilbert and David Rosenthal, Nvidia: The GPU Company (1993-2006) explores nvidia’s scrappy early bets that turned graphics into computing power This episode (part one) covers Nvidia’s origin story from 1993 through the mid-2000s, focusing on how Jensen Huang and co-founders Chris Malachowsky and Curtis Priem survived a brutally competitive graphics market and repeatedly reinvented the company.
Nvidia’s scrappy early bets that turned graphics into computing power
This episode (part one) covers Nvidia’s origin story from 1993 through the mid-2000s, focusing on how Jensen Huang and co-founders Chris Malachowsky and Curtis Priem survived a brutally competitive graphics market and repeatedly reinvented the company.
Key inflection points include an early misstep with Sega and nonstandard technical choices, a dramatic reset with massive layoffs, and a make-or-break pivot to win the PC gaming market via faster chip iteration.
Nvidia’s breakthrough shift from “fixed-function” graphics cards to the first widely marketed “GPU” (GeForce 256) and then programmable shaders (GeForce 3/Xbox) helped it escape pure commoditization pressure from Intel’s integrated strategy.
By 2006, Nvidia had achieved product-market fit but still faced margin pressure, platform dependency risks (Microsoft), and looming competition (ATI/AMD, Intel), while hinting at future expansion into scientific computing and simulation (foreshadowing CUDA/AI in part two).
Key Takeaways
Resilience and discomfort tolerance can be a strategic advantage.
Huang’s early life—reform-school environment, cultural displacement, and discipline—maps directly to Nvidia’s willingness to endure brutal pivots, layoffs, and repeated “bet-the-company” moments.
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Being first is often a disadvantage if standards haven’t settled.
Nvidia’s early Sega strategy and quadrilateral primitive looked clever initially, but Microsoft’s Direct3D standardized triangles, instantly making Nvidia’s path a liability and forcing a reset.
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When a market commoditizes, speed becomes a temporary moat.
Nvidia escaped death by compressing chip development to ~6 months (via emulation) while rivals took 18–24 months—effectively outpacing Moore’s Law for a period and grabbing share.
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Performance can outweigh “correctness” in early platform adoption.
RIVA 128 shipped with partial Direct3D support, yet developers adapted because consumer demand rewarded frame rates and visual quality—teaching Nvidia that market pull can tolerate constraints.
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Category design (“GPU”) plus programmability is how Nvidia aimed to avoid Intel’s integration playbook.
Intel historically absorbed peripheral functions into motherboards; Nvidia countered by making graphics a programmable computing substrate (shaders + Cg), raising differentiation and making “graphics” harder to subsume.
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Platform partners both enable and extract value.
Microsoft helped standardize the ecosystem (DirectX) and elevated Nvidia via Xbox, but also pressured margins and limited Nvidia’s ability to build deep switching costs on the PC graphics stack.
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Simulation was an early cultural DNA, not a late AI-era invention.
Nvidia’s survival depended on emulating chips in software instead of prototyping; later, Huang’s interest in Keyhole/Google Earth reinforces a long-running belief that simulated worlds and compute acceleration are core.
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Notable Quotes
“My will to survive exceeds almost everybody else's will to kill me.”
— Jensen Huang (quoted by hosts)
“Well, that wasn’t very good. But Wilf says to give you money… But if you lose my money, I’ll kill you.”
— Don Valentine (recounted by hosts)
“We need to throw it all out if we're gonna survive.”
— Jensen Huang (paraphrased by hosts)
“Everybody shut up! Morris Chang is on the phone.”
— Jensen Huang (recounted by hosts)
“When technology moves this fast, if you're not reinventing yourself, you're just slowly dying… at the rate of Moore’s Law.”
— Jensen Huang (quoted by hosts)
Questions Answered in This Episode
What exactly about quadrilaterals (vs triangles) made Nvidia’s early Sega approach collapse once Direct3D standardized triangles?
This episode (part one) covers Nvidia’s origin story from 1993 through the mid-2000s, focusing on how Jensen Huang and co-founders Chris Malachowsky and Curtis Priem survived a brutally competitive graphics market and repeatedly reinvented the company.
Get the full analysis with uListen AI
How did Nvidia’s emulation-based development workflow work in practice, and what organizational habits did it create that persisted afterward?
Key inflection points include an early misstep with Sega and nonstandard technical choices, a dramatic reset with massive layoffs, and a make-or-break pivot to win the PC gaming market via faster chip iteration.
Get the full analysis with uListen AI
Why were consumers—not OEMs—the decisive force in early PC GPU purchasing, and how did that shape Nvidia’s go-to-market strategy?
Nvidia’s breakthrough shift from “fixed-function” graphics cards to the first widely marketed “GPU” (GeForce 256) and then programmable shaders (GeForce 3/Xbox) helped it escape pure commoditization pressure from Intel’s integrated strategy.
Get the full analysis with uListen AI
RIVA 128 shipped with incomplete Direct3D feature support; how did Nvidia decide what to cut, and what did they learn from negotiating directly with developers?
By 2006, Nvidia had achieved product-market fit but still faced margin pressure, platform dependency risks (Microsoft), and looming competition (ATI/AMD, Intel), while hinting at future expansion into scientific computing and simulation (foreshadowing CUDA/AI in part two).
Get the full analysis with uListen AI
To what extent did Microsoft’s DirectX standard “save” the GPU market versus commoditize it—and was Nvidia’s eventual success dependent on Microsoft?
Get the full analysis with uListen AI
Transcript Preview
Hello, Acquired listeners. We, uh, we are coming at you with a little bit of an announcement, uh, some late-breaking news. We recorded this episode, what, David, a week ago?
Yeah, a little over a week ago. We got some time travel going on here. I feel like I'm Jensen in, like, a deep fake Nvidia keynote. [laughing]
[laughing] We sit here, uh, Saturday, March 26th, getting ready to release this episode in about twenty-four hours, but we wanna tell you, we've got something that you don't wanna miss. Save the date of May 4th, Star Wars Day, for something in Seattle, Washington, and we hope to be able to see you in person. We'll be able to share more soon, but for now, save the date.
Consider this our save-the-date card that we're sending to each and every one of you.
[upbeat music] Yep, all right, now on to Nvidia.
Who got the truth? Is it you? Is it you? Is it you? Who got the truth now? Is it you? Is it you? Is it you? Sit me down, say it straight, another story on the way. Who got the truth?
Welcome to season ten, 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.
And I'm David Rosenthal, and I am an angel investor based in San Francisco.
And we are your hosts. It is the eighth largest company in the world by market cap.
Dang!
When Nvidia began in 1993, it made computer graphics chips in a brutally competitive and low-margin market. There were ninety undifferentiated competitors, all doing basically the same thing at the same time, and yet today, they have an eighty-three percent market share of standalone GPUs, that's graphics processing units, for those of you starting with us from square one, that are supplied for desktop and laptop computers.
Ben, you're telling, like, the whole story here. [chuckles]
[chuckles] 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, Jen-Hsun Huang, really has bet the company, like, the whole company, three separate times, nearly going bankrupt each time. But obviously, as we reflect back here today, that certainly did not happen.
All right, so here's everything you need to know- [laughing]
[chuckles]
... about Jen-Hsun. The CliffsNotes before we talk for, like, six hours about him. The dude used to drive a Toyota Supra, [chuckles] like a Fast and Furious style-
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