This week, I moderated a panel on world models at the All In conference (no relation to the podcast), and it gave me a chance to dig into one of the most mysterious corners of the AI world. The big players in the space are Yann LeCunâÂÂs AMI Labs and Fei-Fei LiâÂÂs World Labs â and while both have accumulated a lot of buzz and funding, they also rank pretty low on the trying-to-make-money scale.
At their core, world models are about automating spatial intelligence, so the field could head in lots of exciting and lucrative directions, from robotics to interactive video to more complex self-driving systems.ÃÂ
But when I started to press on where we would actually see the tech commercialized, things got foggy. The closest thing I found to an authority was Michael Rabbatt, a co-founder of AMI Labs and the companyâÂÂs VP of World Models, who joined me on the panel. But when I pressed him on exactly what the company was working on, he was cagey. âÂÂWeâÂÂll talk about it when weâÂÂre ready to talk about it.â Over email, he clarified, âÂÂWeâÂÂre still in a research and building phase, so weâÂÂre not talking publicly about any product plans or timeline.âÂÂ
To be fair, AMI is less than a year old, so itâÂÂs fair enough to keep quiet. But this sort of caginess extends to the whole world-modeling space. World Labsâ Marble is probably the most fully developed product in the space, and its demos range from straightforward media creation, building explorable environments for video games, or CGI effects. There are robotics use cases too, but the whole platform seems more designed to demonstrate capabilities.ÃÂ
That secrecy even extends to these companiesâ suppliers. On the sidelines of the same conference, I spoke to Alex de Vigan, CEO of Physicl â a data supplier for the burgeoning world model business. He says he knows PhysiclâÂÂs data has been useful for whatever theyâÂÂre building, but heâÂÂs still in the dark about what exactly that is. âÂÂI wish they would tell us more. We could build more useful data if we knew what they were working on,â de Vigan told me.
Part of the mystery comes from how versatile world models are as an idea. The simplest version is a navigable map of the world, similar to the AI models that power self-driving cars. But the same modeling approach that helps a Waymo weave through traffic could also help a humanoid robot carry boxes, or turn a few minutes of video footage into an explorable environment. AMI has already dipped its toe in manufacturing, biomedicine, robotics, and even AI software for doctors through its Nabia partnership. Surely it wonâÂÂt pursue all of those â but maybe one or two of them are standing out?
No one doubts that there are lots of viable businesses to be built on world model tech â and as long as itâÂÂs easy to fundraise, thereâÂÂs no particular pressure to focus on one. In fact, thereâÂÂs good reason not to. If AMI announced tomorrow that they had built a humanoid OpenClaw or a next-generation Hollywood rendering system, a lot of other labs would suddenly be very interested in the space. Soon, the lab would face potential competition from the other world model companies, the neolabs and even OpenAI and Anthropic.ÃÂ
In some ways, itâÂÂs the flip side of all that easy fundraising. Your competitors can fundraise, too â and the same money that lets you build under the radar is also funding lots of potential rivals once the path to market becomes clear. But even if that competition is inevitable, itâÂÂs best if you delay it for as long as possible, which means keeping quiet about exactly what youâÂÂre building.
Cixin Liu fans will recognize this as a Dark Forest scenario: if you donâÂÂt know who else is in the woods, itâÂÂs best not to attract attention.
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