AMD Acquires Fei-Fei Li's World Labs For $8.2 Billion (cnbc.com)
(Monday September 28, 2026 @11:30PM (BeauHD)
from the definitive-agreements dept.)
- Reference: 0185891738
- News link: https://slashdot.org/story/26/09/28/2042235/amd-acquires-fei-fei-lis-world-labs-for-82-billion
- Source link: https://www.cnbc.com/2026/09/28/amd-fei-fei-li-world-labs.html
AMD has [1]agreed to [2]acquire Fei-Fei Li's World Labs for about $8.2 billion in stock , making it the chipmaker's second-largest acquisition and giving it a major foothold in "world models" that simulate 3D environments for robotics and other physically grounded AI. CNBC reports:
> AI researchers expect world models will be able to help develop robots and other physically-grounded artificial intelligence applications. AMD plans to keep World Labs separate from its chipmaking business until the transaction closes later this year. The lab's research on next-generation models will allow AMD to plan for what its AI chips need to be capable of years in advance.
>
> World Labs was founded by AI researcher Fei-Fei Li, who is widely seen as an AI pioneer as a Stanford professor, and who previously worked for Google leading AI research. Li will become an AMD's chief scientist and an executive vice president at the company.
>
> In a demo presented by Li and AMD CEO Lisa Su earlier this year, the two executives showed a World Labs model called Marble creating a three-dimensional scene out of a few images. "Intelligent agents, whether it's robots or vehicles or even tools, can learn inside very-rich physics-aware digital worlds before they even need to be deployed into the real one, making them much safer," Li said at the presentation.
[1] https://www.worldlabs.ai/blog/amd-announcement
[2] https://www.cnbc.com/2026/09/28/amd-fei-fei-li-world-labs.html
> AI researchers expect world models will be able to help develop robots and other physically-grounded artificial intelligence applications. AMD plans to keep World Labs separate from its chipmaking business until the transaction closes later this year. The lab's research on next-generation models will allow AMD to plan for what its AI chips need to be capable of years in advance.
>
> World Labs was founded by AI researcher Fei-Fei Li, who is widely seen as an AI pioneer as a Stanford professor, and who previously worked for Google leading AI research. Li will become an AMD's chief scientist and an executive vice president at the company.
>
> In a demo presented by Li and AMD CEO Lisa Su earlier this year, the two executives showed a World Labs model called Marble creating a three-dimensional scene out of a few images. "Intelligent agents, whether it's robots or vehicles or even tools, can learn inside very-rich physics-aware digital worlds before they even need to be deployed into the real one, making them much safer," Li said at the presentation.
[1] https://www.worldlabs.ai/blog/amd-announcement
[2] https://www.cnbc.com/2026/09/28/amd-fei-fei-li-world-labs.html
there isn't a deep enough hole (Score:1)
by metac0rtex ( 3682733 )
Fei-Fei Li famously created ImageNet using Amazon mechanical turk slaves to label the images. At least until they figured out that they could lock the Internet behind captchas and have everyone be their slaves.
Frauds frauding frauds (Score:2)
by Quakeulf ( 2650167 )
This is laughably unscalable and noisy with only static models and zero useful topology or anything except that it looks halfways decent when covered with motion blur. Anything in a still falls apart after a bit because they just keep ignoring physics and insisting on having it both slow and imprecise, when you would rather have a tradeoff between speed and accuracy... I guess glossing it with photorealism helped, along with probably some insider deals.
Only makes training them safer and cheaper (Score:3)
Training the robots' models in a simulation before training them in the real world won't make them safer. In fact if anything it will make them less safe due to their earliest training being subtly different from reality. What it does is make it cheaper and less dangerous to train them, and faster because you can run the simulation faster than reality.