Orthodontist Jim Woods invested $65,000 in Nvidia in 2000, and by 2024, his stake reached $15 million. He held the stock for 24 years as the company shifted from graphics to AI chips. His patient approach showed how long-term holding turned a modest early investment into a massive fortune today.
Synopsis
In 2000, Jim Woods was working full-time as an orthodontist. That same year, he placed $65,000 into Nvidia, then a relatively young tech company known mostly for PC graphics hardware. Twenty-four years later, that single trade reached a value of $15 million.
Jim Woods was an orthodontist when he put $65,000 into Nvidia in 2000. By 2024, that stake was worth $15 million, according to The Wall Street Journal.
He's one of the early amateur investors the paper featured. Some of them made life-changing money.
Divide $15 million by $65,000 and you get about 231. His money grew roughly 230 times.
Spread over 24 years, that's about 25% a year, compounded. But that figure assumes he never added money or sold any shares.
Why 2,000% isn't as big as it sounds
Nvidia is up about 2,000% since 2019. A 2,000% gain means every $1 became $21.
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Next to Woods's 230-fold gain, that looks small. It isn't, once you account for time. If "since 2019" means roughly five years, 21 times your money works out to something like 84% a year. That's more than three times Woods's pace.
His multiple was bigger because he held for nearly five times as long. A slower rate, compounded over decades, can beat a much faster one over a short stretch.
Nvidia stock
Nvidia has more than doubled so far in 2024. That makes it the best performer in the S&P 500 this year.
There have been recent wobbles, though. Anyone holding a stock like this sits through the drops as well as the climbs. A gain on paper is only a gain if you don't sell on the way down, and the long-term figures above say nothing about how rough the ride felt.
What today's buyers are paying for
Nvidia's chips power the artificial-intelligence systems that have taken off over the past couple of years. That's where the demand comes from. Investors are buying because they expect the company to be at the front of wider AI adoption.
The company's business has shifted over time. It moved from graphics chips into powering AI, and that shift helped turn early shareholders into some of its biggest winners.
Nvidia total return since IPO (Image credit: FactSet)
A buyer today is paying for something different from what Woods bought. The stock has already more than doubled this year. A new purchase is a bet on how far AI spreads, not a reward for what Nvidia has already delivered. Nobody knows yet how far that will go.
Woods waited 24 years. The 2019 buyers got a 21-fold gain in about five.
Jensen Huang: How Nvidia grew from a small chip company into a $5 trillion AI giant
Jensen Huang, Chris Malachowsky and Curtis Priem met at a San Jose Denny's in 1993 to discuss a chip that would make video game graphics faster and more realistic. Malachowsky and Priem came from Sun Microsystems. Huang had spent nine years at LSI Logic and AMD.
Jensen Huang, Chris Malachowsky and Curtis Priem (Image credit: linkedin)
He was 30. His former boss at LSI Logic called Sequoia's Don Valentine, and Sequoia ended up funding the company.
Huang was born in Taiwan. At nine he was sent to the U.S. to live with an uncle. At ten he landed at the Oneida Baptist Institute in Kentucky, which turned out to be a reform academy where he was badly bullied. His family reunited in Oregon later. He studied electrical engineering at Oregon State, then Stanford.
His first job was at a Denny's, where he worked from 1978 to 1983 as a dishwasher, busboy and waiter. He chose the same chain for the company's first meeting.
Nvidia's first chip, the NV1, arrived in 1995. Huang then negotiated a buyout of the Sega contract, and that money paid for the next chip. Without that cash, the company probably wouldn't have lasted.
Things changed in 1999. Nvidia launched GeForce and went public that year. It also began calling its chip a GPU.
What a GPU does, and why AI needs it
An ordinary processor works through tasks in sequence, very quickly. A GPU runs thousands of small calculations at once. Games need that to color every pixel.
GPU
AI training needs the same kind of math, only far more of it. AlexNet, an image-recognition model from 2012, showed what Nvidia's chips could do for deep learning. Nvidia had also built CUDA, software that let programmers use its chips for tasks beyond graphics. Customers who write code for CUDA find it hard to leave.
Today Nvidia sells chips, networking equipment and complete data-center systems. OpenAI, Tesla, xAI, Meta, Amazon and Oracle are among its biggest customers.
On October 29, 2025, Nvidia became the first public company valued at $5 trillion, more than Germany's GDP the year before. Going from $4 trillion to $5 trillion took 79 trading days.
The cause was demand. Appetite for its chips is the main reason the stock climbed so fast after early 2023. Cloud companies kept buying, and Nvidia supplied most of what they bought. One analysis puts its share of the AI chip market above 90%.
Market value is what investors think the company is worth. It isn't cash or profit. Revenue is a firmer measure. Nvidia reported $216 billion for fiscal 2026. The latest quarter in that report brought in $68.1 billion, up 73% from a year earlier.
Huang's wealth tracked the stock. Forbes estimated $2.7 billion in 2017 and $21.1 billion in 2023. At the $5 trillion mark, it was $178.9 billion.
All of this depends on AI spending staying high. If cloud companies pull back, Nvidia would feel it first. The company's forecasts have kept rising, but forecasts can be wrong.
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