Now Nava, 19, not only has a summer internship at Nvidia, he’s also a stockholder. Using cash saved from gifts and part-time jobs, he bought an undisclosed amount of Nvidia shares last month. He’s already seen a 15 percent gain.
“It’s impressive how they’ve transitioned from a company with the greatest graphics chips to an AI powerhouse,” said Nava, who plans to hold on to his investment “indefinitely.”
As its stock price has soared nearly 300 percent over the past year, Nvidia fever has swept Silicon Valley and computer science programs across America. At college job fairs, hundreds of students line up to meet the company’s recruiters. On TikTok and Reddit, people debate whether it’s too late to invest. And along the highway between the valley and downtown San Francisco, billboards trumpet the availability of Nvidia’s chief product — microprocessors known as GPUs — from start-ups that have bought the chips to cash in on the overwhelming demand.
Nvidia’s chips power the AI models behind the artificial intelligence boom, including popular tools like ChatGPT. Big Tech companies from Google to Meta to Amazon need the chips to power their AI tools and big data centers. Demand is skyrocketing, driving the price per chip to as much as $30,000 — if you can find one. The company is now worth more than $2 trillion — more than Google or Amazon — and trailing only Microsoft and Apple in the competition to claim the title as the most valuable company in the world. This week, Nvidia’s stock price increase drove the S&P 500 to a record close.
Top college grads who in previous years might have fought for a spot at Google or a flashy start-up are now applying to Nvidia instead. The company’s upcoming annual conference, which in past years was attended mostly by chip-buyers from gadget makers, has become a must-attend event on the AI conference calendar. Google, Amazon and Facebook are buying more Nvidia chips for their own data centers to handle the massive — and growing — demands of AI processing.
Nvidia CEO Jensen Huang, who has the company’s logo tattooed on his left shoulder and wears a black leather jacket at public events, has become like a god in tech and business circles, referred to in awed and jealous tones simply as “Jensen.”
His trips to Taiwan, where Nvidia’s chips are manufactured and where he lived before immigrating to the United States with his parents as a child, are now media events. On one recent trip, locals recognized him at a tofu pudding shop in a night market and asked for selfies, spurring a TV news report.
The company’s rapid rise is thanks to an “accident of history,” said Oren Etzioni, a AI professor at the University of Washington and founder of AI deepfake detection nonprofit TrueMedia.org. The chips Nvidia designed for running video game graphics turned out to be well-suited to run the massive calculations needed to train and run modern AI algorithms. Years before ChatGPT kicked off the AI boom in 2022, Nvidia began tailoring its chips and software to better serve AI researchers.
“It’s better to be lucky than smart. In this case, they were lucky, they were smart and they were hard-working,” Etzioni said. “They’re riding an exponential wave, and that is the reason you have a $2 trillion company so quickly.”
A spokesperson for Nvidia declined to comment.
Nvidia was founded in a Denny’s in 1993 by Huang — who had been a chip designer at Advanced Micro Devices — former Sun Microsystems engineer Chris Malachowsky and former IBM engineer Curtis Priem. Video games were taking off, and the three guessed that a new kind of chip specialized for computer graphics would be needed as games became more visually complex. The bet paid off, and Nvidia grew steadily to become one of the main providers of GPUs, short for “graphics processing units.”
Around 2014, researchers working on AI realized that GPUs worked better for training AI than other chips. While the more-common computer processing units, or CPUs, are optimized to handle a small number of highly complicated tasks, GPUs are better at doing the math for many simple calculations at the same time. Because training AI requires making many connections between billions of different words or images, GPUs worked well. Many of the major AI breakthroughs that helped set the foundation for the large language models at the center of today’s AI revolution were made by running AI algorithms on Nvidia GPUs.
Recognizing what was happening, the company doubled down on the AI industry. And as Big Tech executives began orienting their companies toward AI, Nvidia’s revenue and stock price began to rise. By the time OpenAI made its ChatGPT chatbot public, kicking off the AI craze, Nvidia already was miles ahead.
“It’s a piece of technology no others in the market have been able to come close to in terms of functionality and reliability,” said Fred Havemeyer, an analyst with Macquarie Group.
Not only does Nvidia have the best chips, but the software it built to help program them is the most widely used among AI researchers and engineers. At this point, switching to a different company’s chip would force them to learn a new software system.
In 2023, Nvidia sold about 78 percent of the AI chips destined for data centers around the world, up from 63 percent in 2022, according to London-based research firm Omdia.
If AI were a gold rush, Nvidia would be the biggest supplier of pickaxes, and experts say its dominance isn’t likely to wane anytime soon.
“The picture may well look different five years from now, but right now Nvidia is king,” Etzioni said.
Is it too late to get in?
Last month, as Nvidia posted another record-breaking quarterly report, the fervor around the company was palpable on social media. In tweets and TikTok posts, former investors bitterly posted calculations of how much their shares would have been worth if they’d held on, while those who cashed in bragged about their hauls and posted images from the movie “The Wolf of Wall Street.”
On Reddit threads about the stock, users debated whether it was too late to get in on the action.
“At this point if you don’t see Nvidia’s opportunity … then you are truly lost,” one user posted, along with the facepalm emoji.
Kaitlin Mackie, a director of brand design for the digital health company Welldoc, saw the impact AI image generators were having on her field and Googled “How to invest in AI.” The web led her to Nvidia, and she picked up 2.6 shares in November.
“I bought it because it was a company powering the future, especially in my industry,” Mackie said in an interview.
On dates last year, men would tell her the stock was overvalued, or question why she’d bother owning so few shares in a single company. She ignored them. It paid off when Nvidia reported earnings in late February and her holdings jumped by $900. She used some of the money for lip filler and the rest to pick up more of the stock.
Her 3.96 shares of Nvidia are now valued around $3,480, and she’s a believer in the company.
“Even if it goes back down, I’ll just hold it,” Mackie said.
Nvidia’s boom stands out among the general doom and gloom in Silicon Valley. While the rest of the industry has laid off tens of thousands of workers in the past two years, Nvidia’s head count has grown 30 percent to 29,600, according to company filings.
That growth has helped boost the economy in Santa Clara, a suburb wedged between San Jose and Apple’s home of Cupertino. Some start-ups are moving their headquarters to the area to have better access to Nvidia’s executives and sales representatives.
In February, a line of several hundred eager students wrapped around a building on Georgia Tech’s campus in Atlanta, all waiting to meet with visiting Nvidia engineers about internships and jobs at the company, according to Denitsa Dimitrova, an electrical engineering student who attended.
Dimitrova, a senior, hadn’t heard of the company before the fall of 2022, when a friend landed an internship there.
“I didn’t think I’d desire to work there someday. Now, they’re a huge name,” Dimitrova said. “Everyone is interested in the top of the top, and Nvidia has joined those ranks.”
On Handshake, a recruiting platform that connects college students and employers, Nvidia internships received seven times as many applications in January as they did a year ago.
Silicon Valley companies have traditionally used the promise of stock growth as a key way to win over top prospects from colleges across the country. Over the past decade, thousands of young people have made their fortunes working for Big Tech companies and highflying start-ups like Airbnb, Uber and Spotify.
But wave after wave of layoffs have damaged morale among Silicon Valley workers and cut into the perception that Big Tech offers job security. AI is the bright spot, with investors pouring huge sums of money into the space and AI researchers and engineers winning seven-figure compensation packages.
Even without the potential to make money from stock grants, Nvidia’s salaries are already as high or higher than those at Google, Facebook and Apple, the traditional top-tier employers of the last decade, according to data from Glassdoor, which surveys tech workers.
Shiva Kumar Appam is set to graduate from San José State University with a master’s in electrical engineering in May. He’s applying to a few places, but Nvidia is one of his top choices.
“I would be on top of the world,” Appam, 25, said about the possibility of landing a job there. “It’s a dream company.”
