Su likes to tail the incumbent, and wait for it to falter. Unlike Huang, she is not afraid to compete with Intel, and, in the past decade, A.M.D. has captured a large portion of Intel’s C.P.U. business, a feat that analysts once regarded as impossible. Recently, Su has turned her attention to the A.I. market. “Jensen does not want to lose. He’s a driven guy,” Forrest Norrod, the executive overseeing A.M.D.’s effort, said. “But we think we can compete with Nvidia.”
On a gloomy Friday afternoon in September, I drove to an upscale resort overlooking the Pacific to watch Huang be publicly interviewed by Hao Ko, the lead architect of Nvidia’s headquarters. I arrived early to find the two men facing the ocean, engaged in quiet conversation. They were dressed nearly identically, in black leather jackets, black jeans, and black shoes, although Ko was much taller. I was hoping to catch some candid statements about the future of computing; instead, I got a six-minute roast of Ko’s wardrobe. “Look at this guy!” Huang said. “He’s dressed just like me. He’s copying me—which is smart—only his pants have too many pockets.” Ko gave a nervous chuckle, and looked down at his designer jeans, which did have a few more zippered pockets than function would strictly demand. “Simplify, man!” Huang said, before turning to me. “That’s why he’s dressed like me. I taught this guy everything he knows.” (Huang’s wardrobe is widely imitated, and earlier this year he was featured in the Style section of the Times.)
The interview was sponsored by Gensler, one of the world’s leading corporate-design firms, and there were several hundred architects in attendance. As the event approached, Huang increased the intensity of his shtick, cracking a series of weak jokes and rocking back and forth on his feet. Huang does dozens of speaking gigs a year, and had given a talk to a different audience earlier that day, but I realized that he was nervous. “I hate public speaking,” he said.
Onstage, though, he seemed relaxed and confident. He explained that the skylights on the undulating roof of his headquarters were positioned to illuminate the building while blocking direct sunlight. To calculate the design, Huang had strapped Ko into a virtual-reality headset and then attached the headset to a rack of Nvidia G.P.U.s, so that Ko could track the flow of light. “This is the world’s first building that needed a supercomputer to be possible,” Huang said.
Following the interview, Huang took questions from the audience, including one about the potential risks of A.I. “There’s the doomsday A.I.s—the A.I. that somehow jumped out of the computer and consumes tons and tons of information and learns all by itself, reshaping its attitude and sensibility, and starts making decisions on its own, including pressing buttons of all kinds,” Huang said, pantomiming pressing the buttons in the air. The room grew very quiet. “No A.I. should be able to learn without a human in the loop,” he said. One architect asked when A.I. might start to figure things out on its own. “Reasoning capability is two to three years out,” Huang said. A low murmur went through the crowd.
Afterward, I caught up with Ko. Like a lot of Huang’s jokes, the crack about teaching Ko “everything he knows” contained a pointed truth. Ko hadn’t yet made partner at Gensler when Huang chose him for the Nvidia headquarters, bypassing Ko’s boss. I asked Ko why Huang had done so. “You probably have heard stories,” Ko said. “He can be very tough. He will undress you.” Huang had no architecture experience, but he would often tell Ko that he was wrong about the building’s design. “I would say ninety per cent of architects would battle back,” Ko said. “I’m more of a listener.”
Ko recalled Huang challenging Nvidia’s engineering staff on the speed of the V.R. headset. The headset originally took five hours to render design changes; at Huang’s urging, the engineers got the speed down to ten seconds. “He was tough on them, but there was a logic to it,” Ko said. “If the headset took five hours, I’d probably settle on whatever shade of green looked adequate. If it took ten seconds, I’d take the time to pick the best shade of green there was.”
The buildings’ design won several awards and made Ko’s career. Still, Ko recalled his time on the project with mixed emotions. “The place was finished, it looks amazing, we’re doing the tour, and he’s questioning me about the placement of the water fountains,” Ko said. “He was upset because they were next to the bathrooms! That’s required by code, and this is a billion-dollar building! But he just couldn’t let it go.”
“I’m never satisfied,” Huang told me. “No matter what it is, I only see imperfections.”
I asked Huang if he was taking any gambles today that resemble the one he took twenty years ago. He responded immediately with a single word: “Omniverse.” Inspired by the V.R.-architecture gambit, the Omniverse is Nvidia’s attempt to simulate the real world at an extraordinary level of fine-grained detail. Huang has described it as an “industrial metaverse.”
Since 2018, Nvidia’s graphics cards have featured “ray-tracing,” which simulates the way that light bounces off objects to create photorealistic effects. Inside a triangle of frosted glass in Nvidia’s executive meeting center, a product-demo specialist showed me a three-dimensional rendering of a gleaming Japanese ramen shop. As the demo cycled through different points of view, light reflected off the metal counter and steam rose from a bubbling pot of broth. There was nothing to indicate that it wasn’t real.
The specialist then showed me “Diane,” a hyper-realistic digital avatar that speaks five languages. A powerful generative A.I. had studied millions of videos of people to create a composite entity. It was the imperfections that were most affecting—Diane had blackheads on her nose and trace hairs on her upper lip. The only clue that Diane wasn’t truly human was an uncanny shimmer in the whites of her eyes. “We’re working on that,” the specialist said.
Huang’s vision is to unify Nvidia’s computer-graphics research with its generative-A.I. research. As he sees it, image-generation A.I.s will soon be so sophisticated that they will be able to render three-dimensional, inhabitable worlds and populate them with realistic-seeming people. At the same time, language-processing A.I.s will be able to interpret voice commands immediately. (“The programming language of the future will be ‘human,’ ” Huang has said.) Once the technologies are united with ray-tracing, users will be able to speak whole universes into existence. Huang hopes to use such “digital twins” of our own world to safely train robots and self-driving cars. Combined with V.R. technology, the Omniverse could also allow users to inhabit bespoke realities.
I felt dizzy leaving the product demo. I thought of science fiction; I thought of the Book of Genesis. I sat on a triangular couch with the corners trimmed, and struggled to imagine the future that my daughter will inhabit. Nvidia executives were building the Manhattan Project of computer science, but when I questioned them about the wisdom of creating superhuman intelligence they looked at me as if I were questioning the utility of the washing machine. I had wondered aloud if an A.I. might someday kill someone. “Eh, electricity kills people every year,” Catanzaro said. I wondered if it might eliminate art. “It will make art better!” Diercks said. “It will make you much better at your job.” I wondered if someday soon an A.I. might become self-aware. “In order for you to be a creature, you have to be conscious. You have to have some knowledge of self, right?” Huang said. “I don’t know where that could happen.” ♦