Many tech executives present as philosophers. The CEO of the most valuable company in the world just want make chips.
Nvidia's Jensen Huang likes talking about chips but not AI by Joshua Brustine read by Ramesh Metani. Last July, Meta Platform's Inc. Chief executive Officer Mark Zuckerberg sat on stage at a conference with Nvidia Korp CEO Jensen Huang, marveling at the wonders of artificial intelligence. The current AI models were so good, Zuckerberg said that even if they never got any better, it take five years just to figure out the best products to build with them. It's a pretty wild time, he added, then talking over Huang as he tried to get a question in, and it's all you know, you kind of made this happen. Zuckerberg's compliment called Huang off guard, and he took a second to regain his composure, smiling bashfully and saying that CEOs can use the little praise from time to time. He might not have acted so surprised. After decades in the tra ventures, Huang has suddenly become one of the most celebrated executives in Silicon Valley. The current AI boom has been built entirely on the graphics processing units that his company makes, leaving Nvidia to reap the payoff from a long shot bet Huang made far before the phrase large language model LM meant anything to anyone. It only makes sense that people like Zuckerberg, whose company is a major Nvidia customer, would take the chance to flatter him in public. Modern day Silicon Valley has helped cultivate the mythos of the founder who puts a dent in the universe through a combination of vision, ruthlessness, and sheer will. The sixty two year old Huang, usually referred to simply as Jensen, has joined the ranks. Two recent books, last December's The Nvidia Way W. W. Norton, by Baron's writer and former Bloomberg opinion columnist, Take Him and the Thinking Machine Viking April a by the journalist Stephen Witt, tell the story of Nvidia's rapid rise. In doing so, they tried to fill out Huang's place alongside more prominent tech leaders such as Steve jobs Elon Musk and Zuckerberg. Both authors have clearly talked to many of the same people, and each book hits the major points of Nvidia's corporate history and Huang's biography. Huang was born in Taipei in nineteen sixty three, his parents sent him and his brother to live with an uncle in the US when Huang was ten. The brothers went to boarding school in Kentucky, and Huang developed into an accomplished competitive table tennis player and talented electrical engineer. After graduating from Oregon State University, he landed a job designing microchips in Silicon Valley. Huang was working at the chip designer ELSI Logic when Chris Malachowski and Curtis Prim, two engineers who worked at ELISI customer Sun Microsystems, suggested it was time for all of them to found a startup that would make graphics chips for consumer video games. Huang ran the numbers and decided it was a plausible idea, and the three men sealed a deal at a Denny's and San Jose, officially starting Nvidia in nineteen ninety three. Like many startups, Nvidia spent its early years bouncing between near fatal crises. The company designed its first chip on the assumption that developers would be willing to rewrite their software to take advantage of its unique capabilities. Few developers did, which meant that many games performed poorly on Nvidia chips, including crucially the mega hit first person shooter Doom. Nvidia's second chip didn't do so well either, and there were several moments where collapse seemed imminent. That collapse never quite came, allowing those early stumbles to be integrated into nvidia law. They're now seen as a key reason the company's sped up the pace at which it developed new products and ingrained the efficient and hard charging culture that exists to this day. The real turning point for Endvidia, though, was Huang's decision to position its chips to reach beyond its core consumers. Relatively early in his company's existence, Huang realized that the same architecture that worked well for graphics processing could have other users. He began pushing Nvidia to tailor its physical chips to reduce those capabilities, while also building software tools for scientists and non gaming applications in its core gaming business, and Vidia faced intense competition, but it had this new market basically to itself, mostly because the market didn't exist. It was as if Wright's wit. Huang was going to build a baseball diamond in a corn field and wait for players to arrive. And Vidia was a public company at this point, and many of its customers and shareholders were irked by Huang's attitude to semiconductor design. But Huang exerted substantial control of the company and stayed the course, and eventually those new players arrived, bringing with them a reward that surpassed what anyone could have reasonably wished for. Without much prompting from Nvidia, the people who were building the technology that would evolve into today's AI models noticed that its GPUs were ideal for their purposes. They began building their systems around Nvidia chips, first as academics and then within commercial operations, with untold billions to spend. By the time everyone else noticed what was going on, and Vidio was so far ahead that it was too late to do much about it. Gaming hardware now makes up less than ten percent of the company's overall business. Huang had done what basically every start up founder sets out to do. He had made a long shot bet on something no one else could see, and then carried through on that vision with a combination of pathological self confidence and feverish workaholism. That he done so with a company already established in a different field only made the feat that much more impressive. Both Kim and Wit are open in their admiration for Huang as they seek to explain his formula for success, even choosing some of the same telling personal details. From Huang's affection for Clayton Christensen's The Innovator's Dilemma, to his strategic temper to his attractive handwriting. The takeaway from each book is that Huang is an effective leader with significant personal charisma who has remained genuinely popular with his employees even as he works them to the bone. Still, their differing approaches are obvious from the first paragraphs. Kim, who approaches Nvidia as a case study in effective business leadership, starts with an extended metaphor in which Huang's enthusiastic use of whiteboards explains his approach to management. This tendency to kill him represents Huang's demand that his employees approach problems from first principles and not get too attached to any one idea at the whiteboard. He writes later in the book, there's no place to hide, and when you finish, no matter how brilliant your thoughts are, you must always wipe them away and start anew This rhapsodic attitude extends to more or less every aspect of Huang's leadership. It has been well documented in these books and elsewhere that Nvidia's internal culture tilts towards the brutal. Kim Describeshuang's tendency to berate employees in front of audiences instead of abuse, though this is interpreted as an act of kindness, just Huang's way of, in his words, torturing them into greatness. Kim does draw the line at Huang's insistence on annihilating employees in ping pong, which he describes as petty. The Thinking Machine, by contrast, begins by marveling at the sheer unlikeliness of Nvidia's sob and rise. This is the story of how niche vendor of video game hardware became the most valuable company in the world, which writes in its first sentence, As the technology and videos enabling progresses, some obvious questions arise about the impact on people outside the company. In large part, the story of modern Silicon Valley has been about how companies respond to such consequences. More than other industries, tech has earned a reputation for seeing its work as more than simply commerce. Venture capitalists regularly present as philosophers and start up founders as not only building chatbots, but also developing plans for how to implement universal basic income once that chatbots achieve superhuman intelligence. The AI industry has always had a quasi religious streak. It's not unheard of for employees to debate whether their day jobs are an existential threat to the human race. This is not Huang's or by extension and vidious style. Technologists such as Elon Musk might see themselves standing on Mars and then work backward from there, but Wit Wrights Huang went in the opposite direction. He started with the capabilities of the circuits sitting in front of him, then projected forward as far as logic would allow. Huang is certainly a step further removed from the public than the men running the handful of other trillion dollar U S tech companies, all of which make software applications directly for consumers. WIT's book ends with the author attempting to engage Huang on some of the headier issues surrounding artificial intelligence. Huang first tells him that these are questions better posed to someone like Musk, and then loses his temper before shutting the conversation down completely. In contrast with other tech leaders, many of whom were weaned on science fiction and draw on it for inspiration, Huang is basically an engineer. It's not only that he doesn't seem to believe that the most alarmous scenarios about AI will come to pass. It's that he doesn't think that he should have to discuss it at all. That's someone else's job.