There are two reasons to write a business book, according to Brad Stoneauthor of “The Everything Store”. You are either writing a thriller or a how-to manual.
In “The Nvidia Way,” veteran technology journalist Tae Kim manages to do both.
Kim charts Nvidia’s improbable rise from a three-person graphics chip startup in the ’90s, one of countless others in a crowded and cutthroat field, to the largest and most influential computer company in the world.
Kim also outlines the reasons for Nvidia’s success. It wasn’t just that they had talented leaders, good timing, or cutting-edge technology.
Nvidia has succeeded because it cultivates a unique culture of excellence that it calls “The Nvidia Way.”
At the center of this story is CEO Jensen Huang, described by an employee in the book as an “extremely persuasive and extremely hard-working” leader, who has led the company and shaped that culture since its founding in 1993.
Huang is one of the longest-serving CEOs in tech and one of the few solo founders still running the show.
As Kim readily admits, the Nvidia Way is actually the Jensen Way. It defines culture.
What is the Nvidia method? First, hire the best people.
When in doubt, choose raw talent over experience. Second, reward performance and pay your best people very well. Third, constantly demand excellence and accountability from everyone, starting at the top.
Huang is a Taiwanese immigrant of humble origins who excelled in mathematics and table tennis and graduated from high school at age 16.
He later became friends with fellow Nvidia co-founders Curtis Priem, who also started programming computers in high school, and Chris Malachowsky, who realized midway through his MCAT exam that he didn’t want to become doctor, in the close-knit community of Silicon Valley.
Over countless coffees at a local Denny’s, they convinced themselves to quit their jobs and start a new business. From day one, Huang was CEO.
Priem and Malachowsky are interesting characters, and we get to know them a little, but if Nvidia’s story was the Avengers, Huang is Iron Man, the star of the series.
Nvidia launched “at the perfect time,” Kim says. By 1993, demand for graphics chips powering video games like “Doom” was exploding.
But despite favorable market conditions, Nvidia’s first chip, the NV1, was a failure.
“No one goes to the store to buy a Swiss army knife. It’s something you get for Christmas,” Huang later recounted of the product, which was fatally over-engineered.
“When we were younger, we were terrible at a lot of things,” Huang says, adding that Nvidia could have done better if he just hadn’t been there in the first five years.
A new chip, the RIVA 128, saves the company. Nvidia even made a modest profit in its first year. This success will be short-lived.
The next half-decade was characterized by both great victories and significant setbacks. “Starting a business is a new skill,” admits Huang.
Nvidia often found itself behind in the beginning. Designing and launching a graphics card took more than a year, but chip buyers were refreshing their PC lineup every six months, which meant no company could ever stay on top.
Huang’s solution: “We will fundamentally restructure the engineering department to align with refresh cycles. » This decision changed the chip industry, as all other competitors were forced to keep pace or die.
Huang calls this “moving at the speed of light,” the theoretical limit at which anything can move to win. A fan of “Star Trek”, he was dissuaded from nicknamed this culture of speed, much geekier, “Mycelium Spore Drive”.
After a few years, Nvidia began to take off, going public in 1999 and then winning the contract for Microsoft’s first Xbox.
Later, Nvidia took over 85% of Apple’s entire computer lineup.
As the company became more successful, Huang became obsessed with the “innovator’s dilemma,” a concept coined by Professor Clayton Christensen, which describes how incumbent companies are often disrupted by more agile newcomers.
Huang’s fear of being disturbed motivates him. “The only thing that lasts longer than our products is sushi,” he likes to joke. That’s why he has a soft spot for erasable whiteboards, which “represent the belief that a successful idea, no matter how brilliant, must ultimately be erased and a new one must follow suit.”
Nvidia’s first true flagship product was the graphics processing unit, or GPU, launched in 2003.
The GPU changed market perception by putting the GPU (the graphics engine) on par with a more familiar CPU or central processing unit. This was more than just marketing hyperbole.
The new class of chips were programmable, which meant they could be used for a myriad of use cases.
At first, Nvidia had no idea how versatile the GPU really was. “We stumbled upon the modern GPU,” said David Kirk, a scientist at Nvidia.
It turned out that super-powerful graphics engines were perfect for other types of computing, including the burgeoning field of AI research. In fact, academics credit Nvidia’s GPU for leveling the playing field in research by democratizing computing power.
Recognizing the AI opportunity early on, Huang said in 2012: “We must treat this work as our highest priority. »
To make GPU programming easier for non-graphics users, Nvidia created a software interface known as CUDA (Compute Unified Device Architecture).
Over time, CUDA has become the company’s greatest asset. Once you get used to programming chips in an environment, you never want to leave it.
Nvidia has also begun aggressively training AI researchers through grants, joint ventures and partnerships with academia. This decades-long effort helped effectively create a market for its GPUs.
As Nvidia has grown, they have remained vigilant against corporate hypertrophy and inertia that are killing businesses. Huang hates corporate hierarchy. “You want a company as big as you need to do the job well, but as small as possible. »
For him, the goal is to merge the Vulcan mind (another “Star Trek” reference) with his people, where people can share and anticipate each other’s thoughts.
Kim’s book leaves readers with the impression that the era of AI is only just beginning. Nvidia, for its part, estimates that the entire data center market, composed mainly of CPUs, will have to move to GPUs, which represents more than a trillion dollars in chip purchases.
The “big bang” for Nvidia occurred in 2023, shortly after the release of ChatGPT, when the company exceeded its revenue estimates by a staggering $4 billion.
For some, Nvidia’s rapid rise to become the world’s largest company came as a shock.
To anyone paying attention, Kim says, their eventual success should have been obvious.
“It was Jensen’s personal drive that shaped Nvidia,” Kim says, wondering what would happen when he and the company parted ways. This question remains unanswered. For now, Nvidia is unassailable at the top of the mountain, surrounded by a cultural divide that few can cross.
Alex Tapscott is the author of “Web3: Charting the Internet’s Next Economic and Cultural Frontier” and managing director of Digital Asset Group, a division of Ninepoint Partners LP.