AMI expands world-model talent as team reaches 40, with research advances already appearing in code
This week we added four new names to the AMI roster who had shared lineage with Meta FAIR's world-model and self-supervised learning. Meanwhile, the `stable-worldmodel` repository is churning through its heavy sustained development. This continues a pattern of AMI co-founders, most notably Yann LeCun, continuing to build a research lab by luring previous collaborators, a mix of both established researchers and promising students. Speaking of LeCun, he has become omnipresent thanks to a slew of public appearances at both VivaTech in June and the RAISE Summit in Paris, where he repeated philosophical framing: LLMs are bounded and physical intelligence is unsolved.
Four ex-Meta FAIR hires continue a raid on world-model expertise
hiringAMI's four confirmed new Members of Technical Staff include: Adrien Bardes (self-supervised visual learning and world-model architectures), Quentin Garrido (self-supervised learning, computer vision, world models), Tengyu Ma (visual grounding and segmentation, including SAM 2 and SAM 3), and Andrew Brown (generative video, multimodal representation learning). They all come from Meta FAIR. Of course, this is not coincidental. These are people whose published research often includes LeCun as a cited co-author and so naturally sits almost precisely at the intersection AMI has staked out: learning structured representations of the world from raw sensory data without dense human labels.
The breadth within that focus is also telling. Bardes and Garrido bring the representation-learning theory. Ma brings the grounding and segmentation capability needed to link that representation to the physical world. Brown brings the generative-video side, which matters enormously for training and evaluating world models against real visual dynamics. Taken together, the four cover the full pipeline from learning a world model to deploying it in a perception-action loop. Alongside this, AMI added Marina Farthouat in Paris and Sonia Rattan in NYC as dedicated AI recruiters, signaling that the hiring pace will continue to accelerate. Which is not surprising when a company has a few hundred million euros burning a hole in its pocket from a Seed Round.
The `stable-worldmodel` repo is where the theory meets the code — and it is moving fast
researchOf AMI's 34 GitHub events this week, 15 belong to Quentin Le Lidec, almost all concentrated in a single repository: `galilai-group/stable-worldmodel`. The activity is substantive rather than cosmetic, with new branches named `buffer` and `episode-table`, multiple pull requests opened and merged, issues reviewed and closed. The naming is revealing: 'episode-table' suggests a structured data layer for storing interaction episodes, a standard component in model-based reinforcement learning and world-model training pipelines; 'buffer' points to the replay or experience-buffer infrastructure those pipelines depend on. This is not exploratory prototyping; it is the kind of iterative, issue-tracked engineering you do when a system is being stabilized for use by a growing team.
Rohit Girdhar also registered seven events this week, and Li Jing contributed two.
New Job Posting: Talent Intelligence & Sourcing Partner, Paris
What is AMI Labs?
Advanced Machine Intelligence is one of the most closely watched AI startups in the world. Founded in 2025 by Yann LeCun and Alexandre LeBrun, it's building AI systems that reason about the physical world, not just language.
About the company →What are World Models?
World Models are AI systems that learn an internal representation of how the world works — enabling machines to plan, predict, and reason about physical reality the way humans do.
The science →The Team
AMI Labs has assembled researchers, engineers, and operators across Paris, New York, Montreal, and Singapore. We track every key hire and leadership change as the team grows.
Meet the team →How a world model sees the future
Given what it observes, the model reconstructs the present and rolls out what happens next — a prediction of physics, not a retrieval of text. Below: a reacher arm, its reconstruction, and the model's forecast, side by side.
Global hiring accelerates
AMI Labs begins scaling its team across Paris, New York, Montreal, and Singapore — recruiting world-class researchers, engineers, and operators to build World Models.
$1.03B seed round at $3.5B valuation
AMI Labs closes a landmark $1.03 billion seed round — one of the largest in AI history — backed by Jeff Bezos, Bezos Expeditions, NVIDIA, Samsung, Eric Schmidt, and 60+ investors.
Yann LeCun joins as Executive Chairman
Turing Award laureate and former Meta Chief AI Scientist Yann LeCun co-founds AMI Labs, bringing his vision for World Models and next-generation machine intelligence.
AMI Labs brand launched
PengyouCo rebrands as Advanced Machine Intelligence (AMI Labs), unveiling its mission to build AI systems that go beyond language — grounded in the physical world.
Corporate structure formalised
Articles of association updated with early share restructuring: 1,000,000 shares divided into ordinary shares and SP preference shares carrying 10× voting rights.
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