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AMD Acquires World Labs, Founded by Fei-Fei Li, for $8.2 Billion
A breakdown of AMD's roughly $8.2 billion acquisition of World Labs describes its founders' and investors' returns and recounts Fei-Fei Li's history, including creating ImageNet, which she released free in 2009 and which helped spark the deep learning boom. Li becomes AMD's Chief Scientist.
Original post · 2 min read
Fei-Fei Li spent years hand-labeling 14 million images, gave the entire thing away for free, and watched it create a multi-trillion dollar industry that paid her nothing. Sixteen years later, AMD is finally paying her. $8.2 billion.
Rewind to 2007. She's a junior professor at Princeton, and the field's consensus is that progress comes from better algorithms, with data as an afterthought. Colleagues warn her that building a giant image dataset will kill her career. Money gets so tight she considers reopening her family's dry cleaning business in New Jersey, the same one she ran on weekends as a Princeton undergrad, to fund the project.
She builds ImageNet anyway and releases it free in 2009.
For three years, almost nothing happens. Then in 2012, two of Geoffrey Hinton's students train a neural net on a pair of $500 gaming GPUs and enter her competition. AlexNet drops the error rate from 26% to 15%, and that single result convinces the whole field that deep learning works.
Nvidia was a gaming chip company worth about $8 billion that day. It's worth over $5 trillion now, and the run started with two of its consumer cards winning a contest built on Fei-Fei's free dataset.
The entire industry monetized the wave except the person who started it. She stayed a professor.
Then in April 2024, at 47, she finally starts a company. Paul's math above puts the four co-founders' share at roughly $3.4 billion after just 2.5 years, call it $850 million each. And she walks into AMD as Chief Scientist reporting to Lisa Su, which puts the two most important women in AI inside the same company.
ImageNet made everybody in this business rich. It just took sixteen years to get around to her.
Rewind to 2007. She's a junior professor at Princeton, and the field's consensus is that progress comes from better algorithms, with data as an afterthought. Colleagues warn her that building a giant image dataset will kill her career. Money gets so tight she considers reopening her family's dry cleaning business in New Jersey, the same one she ran on weekends as a Princeton undergrad, to fund the project.
She builds ImageNet anyway and releases it free in 2009.
For three years, almost nothing happens. Then in 2012, two of Geoffrey Hinton's students train a neural net on a pair of $500 gaming GPUs and enter her competition. AlexNet drops the error rate from 26% to 15%, and that single result convinces the whole field that deep learning works.
Nvidia was a gaming chip company worth about $8 billion that day. It's worth over $5 trillion now, and the run started with two of its consumer cards winning a contest built on Fei-Fei's free dataset.
The entire industry monetized the wave except the person who started it. She stayed a professor.
Then in April 2024, at 47, she finally starts a company. Paul's math above puts the four co-founders' share at roughly $3.4 billion after just 2.5 years, call it $850 million each. And she walks into AMD as Chief Scientist reporting to Lisa Su, which puts the two most important women in AI inside the same company.
ImageNet made everybody in this business rich. It just took sixteen years to get around to her.
Paul Bonnet @PaulBonnetAMD acquires World Labs for ~$8.2b. But who gets the 💰? My usual breakdown below 👇
From founding to an $8.2b exit in ~2.5 years. A huge value creation event. This is a fantastic exit, especially for the co-founders and the team.
Investors will still share ~$2.3b of profits on $1.2b invested, a ~2.9x blended. Low-ish because most of the capital came in last. But it hides a lot of disparity between the various rounds!
So let's dive in:
1) The real home run: founders and team 🏆🥳
This is one of the best founder outcomes I've modelled.
@drfeifei, Justin Johnson, Christoph Lassner and Ben …
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