AMI Labs, a new AI startup co-founded by Yann LeCun, has raised $1.03 billion at a $3.5 billion valuation to develop "world models"—AI that learns from reality, not just language. The company, which sees healthcare as a key application, acknowledges this is a long-term research project that may take years to yield commercial products, unlike typical fast-moving AI startups.
Despite the extended timeline, investor interest in world models is significant, as evidenced by AMI's large funding round and other major investments in the field. The startup attracted a prestigious investor syndicate and will use the capital primarily for computing power and recruiting top talent across several global hubs.
The main topics covered are the startup's substantial funding, its focus on developing world model AI, the long-term research nature of the project, and the growing investor trend in this specific AI category.
AMI Labs, the new venture cofounded by Turing Prize winner Yann LeCun after he left Meta, has raised $1.03 billion at a $3.5 billion pre-money valuation. AMI is working on world models, or AI that learns from reality, not just from language.
This category has fewer players than generative AI, but maybe not for long. “My prediction is that ‘world models’ will be the next buzzword,” AMI Labs CEO Alexandre LeBrun told TechCrunch. “In six months, every company will call itself a world model to raise funding.”
LeBrun said this with a smile because he thinks AMI Labs is fundamentally different: its goal is to understand the real world. This could have applications in healthcare, where AMI Labs’ first partner will be Nabla, the digital health startup of which he’s now chairman.
As CEO of Nabla, LeBrun had reached the same conclusion as LeCun on the limitations of large language models (LLMs) where hallucinations could have life-threatening repercussions. But he also knows it will take a while for the startup to offer a viable alternative based on JEPA, the Joint Embedding Predictive Architecture proposed by LeCun in 2022.
“AMI Labs is a very ambitious project, because it starts with fundamental research. It’s not your typical applied AI startup that can release a product in three months, have revenue in six months and make $10 million in [annual recurring revenue] in 12 months,” LeBrun said. In contrast, it could take years for world models to go from theory to commercial applications.
Despite this time horizon, companies developing world models have attracted big checks. SpAItial raised a $13 million seed round — unusually large for a European startup; while Fei-Fei Li’s World Labs secured a whopping $1 billion last month alone. Now, AMI Labs joins the club with more funding than initially rumored.
The French AI lab was reportedly seeking just €500 million last December, but ended up raising some €890 million, likely thanks to its team. In addition to LeCun’s involvement as chairman and to LeBrun’s track record as an entrepreneur, it also boasts Meta’s VP for Europe Laurent Solly as COO, and high-profile researchers Saining Xie as chief science officer, Pascale Fung as chief research & innovation officer and Michael Rabbat as VP of world models.
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According to LeBrun, high interest gave the startup a chance to have its pick of investors, both in terms of expectation alignment and background. The round was co-led by Cathay Innovation, Greycroft, Hiro Capital, HV Capital and Bezos Expeditions, with participation from several other funds and industry-tied backers, as well as individuals including Tim and Rosemary Berners-Lee, Jim Breyer, Mark Cuban, Mark Leslie, Xavier Niel and Eric Schmidt.
Value-add aside, this funding will give AMI Labs some meaningful runway to bankroll its two main cost centers: compute and talent. LeBrun said he will prioritize quality over quantity to build AMI Labs’ team in four key locations: Paris, where it is headquartered; New York, where LeCun teaches at NYU; in Montreal, where its Rabbat is based; and in Singapore, both to recruit AI talent and to be close to future clients in Asia.
Although AMI Labs has no plans to generate revenue for the time being, it still plans to engage with prospective customers early on. “We are developing world models that seek to understand the world, and you can’t do that locked up in a lab. At some point, we need to put the model in a real-world situation with real data and real evaluations,” LeBrun said.
When the time comes, AMI Labs will turn to partners to explore deployments — and Nabla is the first disclosed partner expecting to access these early models, but definitely not the last. “This may explain the presence and strong interest of certain industrial players and potential partners in the investment round,” LeBrun said.
In addition to its lead investors and angels, AMI Labs is backed by NVIDIA, Samsung, Sea, Temasek and Toyota Ventures, as well as French players Association Familiale Mulliez, Groupe Industriel Marcel Dassault and Publicis Groupe. Aglaé Lab, Alpha Intelligence Capital, Artémis, Bpifrance Digital Venture, New Legacy Ventures, SBVA and ZEBOX Ventures also participated.
These investments may take a while to turn into commercial applications. But staying true to LeCun’s beliefs, AMI Labs will publish papers as it goes.
“We will also make a lot of code open source,” said LeBrun, who had also worked at Meta’s AI research laboratory, FAIR. While open research is “increasingly rare,” this startup’s founders still believe in it. “We think things move faster when they’re open, and it’s in our best interest to build a community and a research ecosystem around us.”
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