Key topicsNvidia’s value soared from $330bn to $3.3trn in just 19 months.CEO Jensen Huang's bold bets and leadership style fuelled Nvidia’s rise.Nvidia's AI dominance stems from early bets on parallel processing and neural nets..Sign up for your early morning brew of the BizNews Insider to keep you up to speed with the content that matters. The newsletter will land in your inbox at 5:30am weekdays. Register here.Support South Africa's bastion of independent journalism, offering balanced insights on investments, business, and the political economy, by joining BizNews Premium. Register here.If you prefer WhatsApp for updates, sign up to the BizNews channel here.From The Economist, published under licence. The original article can be found on www.economist.com© 2025 The Economist Newspaper Limited. All rights reserved..The Economist.Keeping up with Nvidia is hard. No other company has created so much shareholder value so quickly. In just 19 months, from November 2022 to June 2024, its market capitalisation rose from $330bn to $3.3trn. It took Microsoft nine years to achieve that growth; Apple needed 13. Nvidia has taken the title of the world’s most valuable firm three times in the past year.Its rise has been so rapid that investors still mispronounce its name (“en-vidia”, not “nuh-vidia”). That is not the only thing observers struggle to parse. The firm—and the man who turned it from a pedlar of graphics chips for computer gamers into the semiconductor titan at the heart of the artificial-intelligence (AI) revolution—remain misunderstood.Jensen Huang co-founded Nvidia in 1993 and has run it since, making him one of Silicon Valley’s longest-serving CEOs. He is among the most approachable—happy to entertain journalists when other tech bosses skulk behind a PR firewall—and, with his signature black leather jacket, among the most recognisable. Yet he remains an elusive subject. Nvidia’s $73bn in net profit last year, not far behind Microsoft’s $88bn, points to a strategic genius at work. His rambling disquisitions on earnings calls scream dumb luck. Which is it?A new book suggests the answer is both. “The Thinking Machine” by Stephen Witt, a journalist, is the second such corporate biography; “The Nvidia Way” by Tae Kim, a former equity analyst, was published in December and covers similar ground. But Mr Witt approaches his subject with a more critical eye and more verve. He weaves together the story of the man, his company and the computer science that led to large language models (llms) such as ChatGPT, which brought “generative” AI to the masses in 2022..Read more:.The Economist: DeepSeek disrupts Nvidia, competition heats up in AI chip war.Mr Huang’s academic brilliance shone from the moment he landed in America in 1973, aged ten. He was always the class nerd, from his time at a juvenile reform academy in rural Kentucky (which his Taiwanese immigrant family may have mistaken for a preppy boarding school) to his years at Oregon State University.After a decade working at established chipmakers, he was persuaded by two collaborators, Curtis Priem and Chris Malachowsky, to run their chip-design startup. Their preferred name, Nvision, was taken by a toilet-roll manufacturer. They chose Nvidia, evoking the Latin word for “envy”.That is what its rivals—first in 3D graphics, then in AI hardware—have felt as Nvidia left them in the dust. Its success stems from an early embrace of two ideas on the fringes of computer science. The first, in the 1990s, was parallel processing, which breaks a big task like rendering a scene in a computer game into many smaller ones. The second was neural networks—an approach to AI which mimics in silicon how human brains work. Once relegated to simulating backgammon, today they underpin all llms.Mr Huang could not have known that neural networks needed parallel processing to thrive; that was mathematical happenstance. But some of Nvidia’s success is a result of deliberate choices about corporate culture, the book says. In order to be agile, the firm does not have a siloed structure. Mr Huang has 55 direct reports (compared with ten or so for a typical CEO). This keeps him busy: “His hobbies are work, email and work,” says one executive.From the start he encouraged speed among his engineers. When an early chip flopped, bringing Nvidia to its knees, he gambled on replacing physical prototypes with digital simulations. This cut product-upgrade cycles from a year to a quarter. Mr Huang reasoned that gamers would take every upgrade until they could not tell a game from reality; so will model-makers, until their AIs are as clever as humans.This pushing often devolves into angry public berating of underperformers. Yet Mr Huang’s temper coexists with a tenderness recalled by current and former subordinates. He screams instead of giving you the sack, they say. Most take the trade. Nvidia regularly ranks highly in surveys of employee satisfaction.Another contradiction is between Mr Huang’s thoughtfulness about the AI business and his unthinking dismissal of the technology’s risks. In contrast to other AI bosses, he sees zero danger. “It’s no different than how microwaves work,” he shrugs. Maybe. But whether AI kills humanity or saves it, Mr Witt writes, “It was going to happen on Jensen’s chips.”
