by SAN FRANCISCO – In high school, all Pablo Nava Barrera knew about Nvidia was the graphics card inside his video gaming computer. But as he began looking for internships last fall, the computer science sophomore at San José State University discovered that the company’s chips were behind “generative” AI tools like ChatGPT and self-driving cars.
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 has already seen a 15 percent gain.
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“It’s amazing how they’ve gone from a company with the biggest graphics chips to an AI powerhouse,” said Nava, who plans to hold onto 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 attend company 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 disrupt the availability of Nvidia’s main product — microprocessors called GPUs — from startups that have bought the chips to cash in on the booming demand.
Nvidia 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 $30,000 – if you can get one. The company is now worth more than $2 trillion – more than Google or Amazon – and is trailing only Microsoft and Apple in the competition to claim the title of the world’s most valuable company. This week, a surge in Nvidia’s stock price led the S&P 500 to the bottom.
Top college graduates who might have been fighting for a spot at Google or a startup in previous years are applying to Nvidia instead. The company’s upcoming annual conference, which in recent years has been largely attended by chip buyers from device makers, is 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 huge – and growing – AI processing demands.
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 something of a god in tech and business circles, referred to in horrified and jealous tones simply as ” Jensen.”
His trips to Taiwan, where Nvidia chips are made and where he lived before immigrating to the United States with his parents as a child, have become media events. On one recent trip, locals recognized him at a tofu pudding shop in a night market and asked for selfies, prompting a TV news report.
The company’s rapid rise is the result of an “accident of history,” said Oren Etzioni, an AI professor at the University of Washington and founder of AI deepfake detection nonprofit TrueMedia.org. The chips designed by Nvidia to run video game graphics have been successful in handling the massive calculations required to train and run modern AI algorithms. Years before ChatGPT kicked off the AI boom in 2022, Nvidia began adapting its chips and software to better serve AI researchers.
“Better to be lucky than smart. In this case, they were lucky, they were smart and they worked hard,” said Etzioni. “They’re riding an exponential wave, and that’s why you have a $2 trillion company so quickly.”
A spokesman for Nvidia declined to comment.
Nvidia was founded in Denny’s in 1993 by Huang – who was 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 trio guessed that as games became more visually complex, a new type of specialized computer graphics chip would be needed. The bet paid off, and Nvidia steadily grew to become one of the leading suppliers 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 very complex tasks, GPUs are better at doing the math with many simple calculations at once. Because AI training requires making a lot of connections between billions of different words or images, GPUs worked well. Many of the big AI breakthroughs that helped lay the groundwork for the big language models at the heart 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 to point their companies toward AI, Nvidia’s revenue and stock price began to rise. By the time OpenAI made its chatbot ChatGPT public, starting the AI craze, Nvidia was already miles ahead.
“It’s a piece of technology that nobody else in the market has 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 them compute is the most used among AI researchers and engineers. At this point, switching to another company’s chip would force them to learn a new software system.
In 2023, Nvidia sold about 78 percent of AI chips destined for data centers worldwide, up from 63 percent in 2022, according to London-based research firm Omdia.
If AI were to be rewarded, Nvidia would be the largest supplier of pickaxes, and experts say its dominance is unlikely to diminish anytime soon.
“The picture may look different five years from now, but right now Nvidia is king,” Etzioni said.
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Is it too late to enter?
Last month, as Nvidia posted another record-breaking quarterly report, the enthusiasm surrounding the company was palpable on social media. In tweets and TikTok posts, former investors have painstakingly put up calculations of how much their shares would have been worth if they had owned them, while those who have turned around have bragged about their holdings 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 take action.
“At this point if you don’t see the Nvidia opportunity … you are truly missing out,” one user posted, along with the facepalm emoji.
Kaitlin Mackie, director of brand design for digital health company Welldoc, saw the impact AI image generators were having on her field and Googled “How to invest in AI.” The web brought her to Nvidia, and she picked up 2.6 shares in November.
“I bought it because it was a company that had the power of the future, especially in my industry,” Mackie said in an interview.
On dates last year, men would tell her the stock was overvalued, or ask why she would bother with so few shares in one company. She ignored them. It paid off when Nvidia reported earnings in late February and its holdings increased by $900. She used some of the money for lip fillers and the rest for a pick-up.
Her 3.96 shares of Nvidia are now worth about $3,480, and she believes in the company.
“Even if it goes back down, I’m just going to keep it,” Mackie said.
Nvidia’s boom stands out amid the general doom and gloom in Silicon Valley. While the rest of the industry has laid off thousands of workers over the past two years, Nvidia’s headcount 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. Several startups are moving their headquarters to the area to have better access to Nvidia executives and sales representatives.
In February, hundreds of eager students crowded around a building on the Georgia Tech campus in Atlanta, all waiting to meet visiting Nvidia engineers about internships and jobs at the company, according to Denitsa Dimitrova, an electrical engineering student who ‘attend.
Dimitrova, a senior, hadn’t heard of the company before the fall of 2022, when a friend got an internship there.
“I never thought I would want to work there someday. Now, they are a huge name,” Dimitrova said. “Everyone is interested in the top of the line, and Nvidia has entered those ranks.”
On Handshake, a recruiting platform that connects college students and employers, Nvidia internships received seven times more applications in January than they did a year ago.
Silicon Valley companies have traditionally used the promise of growth stock as a key way to lure top prospects from colleges across the country. Over the past decade, thousands of young people have found success working for Big Tech companies and world-class start-ups such as Airbnb, Uber and Spotify.
But wave after wave of layoffs has damaged the morale of Silicon Valley workers and eroded the perception that Big Tech offers job security. AI is the bright spot, with investors pouring large sums of money into the space and AI researchers and engineers winning seven-figure compensation packages.
Even without the ability to cash in on stock grants, Nvidia’s salaries are already as high or higher than those at Google, Facebook and Apple, the traditional top-tier employers for the past decade, according to data from Glassdoor, which surveys technology workers.
Shiva Kumar Appam is set to graduate from San José State University with a master’s degree in electrical engineering in May. It’s affecting a few places, but Nvidia is one of its best options.
“I would be on top of the world,” Appam, 25, said of the possibility of bringing in a job there. “It’s a dream company.”
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Graphic:
https://washingtonpost.com/documents/26f09c00-e3c8-40fb-b729-062cdb7b117d.pdf
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