This is what hundreds of millions of gamers in the world play on. It’s a GeForce. This is the chip that’s inside. For nearly 30 years, Nvidia’s chips have been coveted by gamers, shaping what’s possible in graphics and dominating the entire market since it first popularized the term Graphics Processing Unit with the GeForce 256. Now, its chips are powering something entirely different.
ChatGPT has started a very intense conversation. He thinks it’s the most revolutionary thing since the iPhone. Venture capital interest in AI startups has skyrocketed. All of us working in this field have been optimistic that at some point the broader world would understand the importance of this technology. And it’s actually really exciting that that’s starting to happen. As the engine behind large language models like ChatGPT, Nvidia is finally reaping rewards for its investment in AI, even as other chip giants suffer in the shadow of U.S.-China trade tensions and an ease in the chip shortage that’s weakened demand.
But the California-based chip designer relies on Taiwan Semiconductor Manufacturing Company to make nearly all its chips, leaving it vulnerable. The biggest risk is really kind of U.S.-China relations and the potential impact to TSMC. That’s, if I’m a shareholder in Nvidia, that’s really the only thing that keeps me up at night.
This isn’t the first time Nvidia has found itself teetering on the leading edge of an uncertain emerging market. It’s neared bankruptcy a handful of times in its history when founder and CEO Jensen Huang bet the company on impossible-seeming ventures. Every company makes mistakes and I make a lot of them. And some of them puts the company in peril. Especially in the beginning, because we were small and we’re up against very, very large companies and we’re trying to invent this brand new technology.
We sat down with Huang at Nvidia’s Silicon Valley headquarters to find out how he pulled off this latest reinvention and got a behind-the-scenes look at all the ways it powers far more than just gaming. Now one of the world’s top ten most valuable companies, Nvidia is one of the rare Silicon Valley giants that, 30 years in, still has its founder at the helm.
60-year-old Jensen Huang, a Fortune Businessperson of The Year and one of Time’s most influential people in 2021, immigrated to the U.S. from Taiwan as a kid and studied engineering at Oregon State and Stanford. In the early 90s, Huang met fellow engineers Chris Malachowsky and Curtis Priem at Denny’s, where they talked about dreams of enabling PCs with 3D graphics, the kind made popular by movies like Jurassic Park at the time.
The friends launched Nvidia out of a condo in Fremont, California, in 1993. The name was inspired by N.V. for next version and Invidia, the Latin word for envy. They hoped to speed up computing so much, everyone would be green with envy. At more than 80% of revenue, its primary business remains GPUs. Typically sold as cards that plug into a PC’s motherboard, they add computing power to central processing units, CPUs, from companies like AMD and Intel.
This is not a chip business. This is a business of figuring out things end to end. But at the start, its future was far from guaranteed. In the beginning, there weren’t that many applications for it, frankly, and we smartly chose one particular combination that was a home run. It was computer graphics and we applied it to video games. Now Nvidia is known for revolutionizing gaming and Hollywood with rapid rendering of visual effects. Nvidia designed its first high performance graphics chip in 1997. Designed, not manufactured, because Huang was committed to making Nvidia a fabless chip company, keeping capital expenditure way down by outsourcing the extraordinary expense of making the chips to TSMC.
In 1999, after laying off the majority of workers and nearly going bankrupt to do it, Nvidia released what it claims was the world’s first official GPU, the GeForce 256. It was the first programmable graphics card that allowed custom shading and lighting effects. By 2000, Nvidia was the exclusive graphics provider for Microsoft’s first Xbox. Microsoft and the Xbox happened at exactly the time that we invented this thing called the programmable shader and it defines how computer graphics is done today.
Nvidia went public in 1999 and its stock stayed largely flat until demand went through the roof during the pandemic. In 2006, it released a software toolkit called CUDA that would eventually propel it to the center of the AI boom. It’s essentially a computing platform and programming model that changes how Nvidia GPUs work, from serial to parallel compute.
Nvidia’s big steps haven’t always been in the right direction. In the early 2010s, it made unsuccessful moves into smartphones with its Tegra line of processors. In 2020, Nvidia closed a long-awaited $7 billion deal to acquire data center chip company Mellanox. Despite some setbacks, today, Nvidia has 26,000 employees, a newly built polygon-themed headquarters in Santa Clara, California, and billions of chips used for far more than just graphics.
More than a decade ago, Nvidia’s CUDA and GPUs were the engine behind AlexNet, what many consider AI’s Big Bang moment. It was a new, incredibly accurate neural network that obliterated the competition during a prominent image recognition contest in 2012. Turns out the same parallel processing needed to create lifelike graphics is also ideal for deep learning, where a computer learns by itself rather than relying on a programmer’s code.
What are some real world applications for Nvidia’s AI? Healthcare is one big area. Think far faster drug discovery and DNA sequencing that takes hours instead of weeks. There’s also art powered by Nvidia AI, like Rafik Anadol’s creations that cover entire buildings. And when crypto started to boom, Nvidia’s GPUs became the coveted tool for mining the digital currency. Gaming cards go out of stock and prices get bid up and then when the crypto mining boom collapses, then there’s a big crash on the gaming side.
Although Nvidia did create a simplified GPU made just for mining, it didn’t stop crypto miners from buying up gaming GPUs, sending prices through the roof. And although that shortage is over, Nvidia caused major sticker shock among some gamers last year by pricing its new 40-series GPUs far higher than the previous generation. Now there’s too much supply and the most recently reported quarterly gaming revenue was down 46% from the year before.
But Nvidia still beat expectations in its most recent earnings report, thanks to the AI boom, as tech giants like Microsoft and Google fill their data centers with thousands of Nvidia A100s, the engines used to train large language models like ChatGPT.
Nvidia’s DGX A100 server board has eight Ampere GPUs that work together to enable things like the insanely fast and uncannily humanlike responses of ChatGPT. More than a decade ago, Nvidia’s CUDA and GPUs were the engine behind AlexNet, what many consider AI’s Big Bang moment. It was a new, incredibly accurate neural network that obliterated the competition during a prominent image recognition contest in 2012.
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