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A close-up of an Nvidia-made computer chip with its name and logo printed on it.
Nvidia, founded in California in 1993, originally made chips mainly used for gaming. | Jakub Porzycki/NurPhoto via Getty Images

The company you might not have heard of is now worth $2 trillion — more than Google or Amazon.

Only four companies in the world are worth over $2 trillion. Apple, Microsoft, the oil company Saudi Aramco — and, as of 2024, Nvidia. It’s understandable if the name doesn’t ring a bell. The company doesn’t exactly make a shiny product attached to your hand all day, every day, as Apple does. Nvidia designs a chip hidden deep inside the complicated innards of a computer, a seemingly niche product more are relying on every day.

Rewind the clock back to 2019, and Nvidia’s market value was hovering around $100 billion. Its incredible speedrun to 20 times that already enviable size was really enabled by one thing — the AI craze. Nvidia is arguably the biggest winner in the AI industry. ChatGPT-maker OpenAI, which catapulted this obsession into the mainstream, is currently worth around $80 billion, and according to market research firm Grand View Research, the entire global AI market was worth a bit under $200 billion in 2023. Both are just a paltry fraction of Nvidia’s value. With all eyes on the company’s jaw-dropping evolution, the real question now is whether Nvidia can hold on to its lofty perch — but here’s how the company got to this level.

From games to crypto mining to AI

In 1993, long before uncanny AI-generated art and amusing AI chatbot convos took over our social media feeds, three Silicon Valley electrical engineers launched a startup that would focus on an exciting, fast-growing segment of personal computing: video games.

Nvidia was founded to design a specific kind of chip called a graphics card — also commonly called a GPU (graphics processing unit) — that enables the output of fancy 3D visuals on the computer screen. The better the graphics card, the more quickly high-quality visuals can be rendered, which is important for things like playing games and video editing. In the prospectus filed ahead of its initial public offering in 1999, Nvidia noted that its future success would depend on the continued growth of computer applications relying on 3D graphics. For most of Nvidia’s existence, game graphics were Nvidia’s raison d’etre.

Ben Bajarin, CEO and principal analyst at the tech industry research firm Creative Strategies, acknowledged that Nvidia had been “relatively isolated to a niche part of computing in the market” until recently.

Nvidia became a powerhouse selling cards for video games — now an entertainment industry juggernaut making over $180 billion in revenue last year — but it realized it would be smart to branch out from just making graphics cards for games. Not all its experiments panned out. Over a decade ago, Nvidia made a failed gambit to become a major player in the mobile chip market, but today Android phones use a range of non-Nvidia chips, while iPhones use Apple-designed ones.

Another play, though, not only paid off, it became the reason we’re all talking about Nvidia today. In 2006, the company released a programming language called CUDA that, in short, unleashed the power of its graphics cards for more general computing processes. Its chips could now do a lot of heavy lifting for tasks unrelated to pumping out pretty game graphics, and it turned out that graphics cards could multitask even better than the CPU (central processing unit), what’s often called the central “brain” of a computer. This made Nvidia’s GPUs great for calculation-heavy tasks like machine learning (and, crypto mining). 2006 was the same year Amazon launched its cloud computing business; Nvidia’s push into general computing was coming at a time when massive data centers were popping up around the world.

That Nvidia is a powerhouse today is especially notable because for most of Silicon Valley’s history, there already was a chip-making goliath: Intel. Intel makes both CPUs and GPUs, as well as other products, and it manufactures its own semiconductors — but after a series of missteps, including not investing into the development of AI chips soon enough, the rival chipmaker’s preeminence has somewhat faded. In 2019, when Nvidia’s market value was just over the $100 billion mark, Intel’s value was double that; now Nvidia has joined the ranks of tech titans designated the “Magnificent Seven”, a cabal of tech stocks with a combined value that exceeds the entire stock market of many rich G20 countries.

“Their competitors were asleep at the wheel,” says Gil Luria, a senior analyst at the financial firm D.A. Davidson Companies. “Nvidia has long talked about the fact that GPUs are a superior technology for handling accelerated computing.”

Today, Nvidia’s four main markets are gaming, professional visualization (like 3D design), data centers, and the automotive industry, as it provides chips that train self-driving technology. A few years ago, its gaming market was still the biggest chunk of revenue at about $5.5 billion, compared to its data center segment, which raked in about $2.9 billion. Then the pandemic broke out. People were spending a lot more time at home, and demand for computer parts, including GPUs, shot up — gaming revenue for the company in fiscal year 2021 jumped a whopping 41 percent. But there were already signs of the coming AI wave, too, as Nvidia’s data center revenue soared by an even more impressive 124 percent. In 2023, its revenue was 400 percent higher than the year before. In a clear display of how quickly the AI race ramped up, data centers have overtaken games, even in a gaming boom.

When it went public in 1999, Nvidia had 250 employees. Now it has over 27,000. Jensen Huang, Nvidia’s CEO and one of its founders, has a personal net worth that currently hovers around $70 billion, an over 1,700 percent increase since 2019.

It’s likely you’ve already brushed up against Nvidia’s products, even if you don’t know it. Older gaming consoles like the PlayStation 3 and the original Xbox had Nvidia chips, and the current Nintendo Switch uses an Nvidia mobile chip. Many mid- to high-range laptops come packed up with an Nvidia graphics card as well.

But with the AI bull rush, the company promises to become more central to the tech people use every day. Tesla cars’ self-driving feature utilizes Nvidia chips, as do practically all major tech companies’ cloud computing services. These services serve as a backbone for so much of our daily internet routines, whether it’s streaming content on Netflix or using office and productivity apps. To train ChatGPT, OpenAI harnessed tens of thousands of Nvidia’s AI chips together. People underestimate how much they use AI on a daily basis, because we don’t realize that some of the automated tasks we rely on have been boosted by AI. Popular apps and social media platforms are adding new AI features seemingly every day: TikTok, Instagram, X (formerly Twitter), even Pinterest all boast some kind of AI functionality to toy with. Slack, a messaging platform that many workplaces use, recently rolled out the ability to use AI to generate thread summaries and recaps of Slack channels.

Nvidia’s chips continue to sell out — for now

For Nvidia’s customers, the problem with sizzling demand is that the company can charge eye-wateringly high prices. The chips used for AI data centers cost tens of thousands of dollars, with the top-of-the-line product sometimes selling for over $40,000 on sites like Amazon and eBay. Last year, some clients clamoring for Nvidia’s AI chips were waiting as much as 11 months.

Just think of Nvidia as the Birkin bag of AI chips. A comparable offering from another chipmaker, AMD, is reportedly being sold to customers like Microsoft for about $10,000 to $15,000, just a fraction of what Nvidia charges. It’s not just the AI chips, either. Nvidia’s gaming business continues to boom, and the price gap between its high-end gaming card and a similarly performing one from AMD has been growing wider. In its last financial quarter, Nvidia reported a gross margin of 76 percent. As in, it cost them just 24 cents to make a dollar in sales. AMD’s most recent gross margin was only 47 percent.

Nvidia’s fans argue that its yawning lead was earned by making an early bet that AI would take over the world — its chips are worth the price because of its superior software, and because so much of AI infrastructure has already been built around Nvidia’s products. But Erik Peinert, a research manager and editor at the American Economic Liberties Project who helped put together a recent report on competition within the chip industry, notes that Nvidia has gotten a price boost because TSMC, the biggest semiconductor maker in the world, has struggled for years to keep up with demand. A recent Wall Street Journal report also suggested that the company may be throwing its weight around to maintain dominance; the CEO of an AI chip startup called Groq claimed that customers were scared Nvidia would punish them with order delays if it got wind they were meeting with other chip makers.

It’s undeniable that Nvidia put in the investment into courting the AI industry well before others started paying attention, but its grip on the market isn’t unshakable. An army of competitors are on the march, ranging from smaller startups to deep-pocketed opponents, including Amazon, Meta, Microsoft, and Google, all of which currently use Nvidia chips. “The biggest challenge for Nvidia is that their customers want to compete with them,” says Luria.

It’s not just that their customers want to make some of the money that Nvidia has been raking in — it’s that they can’t afford to keep paying so much. Microsoft “went from spending less than 10 percent of their capital expenditure on Nvidia to spending nearly 40 percent,” Luria says. “That’s not sustainable.”

The fact that over 70 percent of AI chips are bought from Nvidia is also cause for concern for antitrust regulators around the world — the EU recently started looking into the industry for potential antitrust abuses. When Nvidia announced in late 2020 that it wanted to spend an eye-popping $40 billion to buy Arm Limited, a company that designs a chip architecture that most modern smartphones and newer Apple computers use, the FTC blocked the deal. “That acquisition was pretty clearly intended to get control over a software architecture that most of the industry relied on,” says Peinert. “The fact that they have so much pricing power, and that they’re not facing any effective competition, is a real concern.”

Will the AI love affair cool off?

Whether Nvidia will sustain itself as a $2 trillion company — or rise to even greater heights — depends, fundamentally, on whether both consumer and investor attention on AI can be sustained. Silicon Valley is awash with newly founded AI companies, but what percentage of them will take off, and how long will funders keep pouring money into them?

Widespread AI awareness came about because ChatGPT was an easy-to-use — or at least easy-to-show-off-on-social-media — novelty for the general public to get excited about. But a lot of AI work is still focusing on AI training rather than what’s called AI inferencing, which involves using trained AI models to solve a task, like the way that ChatGPT answers a user’s query or facial recognition tech identifies people. Though the AI inference market is growing (and maybe growing faster than expected), much of the sector is still going to be spending a lot more time — and money — on training. For training, Nvidia’s first-class chips will likely remain the most coveted, at least for a while. But once AI inferencing explodes, there will be less of a need for such high-performance chips, and Nvidia’s primacy could slip.

Some financial analysts and industry experts have expressed wariness over Nvidia’s stratospheric valuation, suspecting that AI enthusiasm will slow down and that there may already be too much money going toward making AI chips. Traffic to ChatGPT has dropped off since last May and some investors are slowing down the money hose.

“Every big technology goes through an adoption cycle,” says Luria. “As it comes into consciousness, you build this huge hype. Then at some point, the hype gets too big, and then you get past it and get into the trough of disillusionment.” He expects to see that soon with AI — though that doesn’t mean it’s a bubble.

Nvidia’s revenue last year was about $60 billion, which was a 126 percent increase from the prior year. Its high valuation and stock price is based not just on that revenue, though, but for its predicted continued growth — for comparison, Amazon currently has a lower market value than Nvidia yet made almost $575 billion in sales last year. The path to Nvidia booking large enough profits to justify the $2 trillion valuation looks steep to some experts, especially knowing that the competition is kicking into high gear.

There’s also the possibility that Nvidia could be stymied by how fast microchip technology can advance. It has moved at a blistering pace in the last several decades, but there are signs that the pace at which more transistors can be fitted onto a microchip — making them smaller and more powerful — is slowing down. Whether Nvidia can keep offering meaningful hardware and software improvements that convince its customers to buy its latest AI chips could be a challenge, says Bajarin.

Yet, for all these possible obstacles, if one were to bet whether Nvidia will soon become as familiar a tech company as Apple and Google, the safe answer is yes. AI fever is why Nvidia is in the rarefied club of trillion-dollar companies — but it may be just as true to say that AI is so big because of Nvidia.

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