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Yann LeCun thinks today’s AI is, to put it politely, kind of shallow. The pioneering researcher and Executive Chairman of AMI Labs took the stage at VivaTech in Paris on June 17 to lay out a vision for artificial intelligence that goes far beyond the chatbot era. His core argument: the future of AI depends on systems that can predict what happens in the physical world, not just which word comes next in a sentence.
LeCun, who previously served as Chief AI Scientist at Meta and is widely considered one of the godfathers of deep learning, has been beating this drum for years. The difference now is that he has a startup flush with over a billion dollars to prove his point.
The problem with predicting the next word
Large language models that power tools like ChatGPT predict the next token, the next chunk of text, based on patterns learned from enormous datasets. LeCun’s argument is that this approach has a ceiling: no matter how much data you feed an LLM, it will never truly understand that a ball rolls downhill or that a glass shatters when dropped.
LeCun’s alternative is what he calls “world models.” World models are AI systems designed to learn from sensory interactions with the real world, building internal representations of how physical systems behave. The technical framework underpinning this at AMI Labs is called Joint Embedding Predictive Architecture, or JEPA.
A billion-dollar bet on a paradigm shift
AMI Labs, which LeCun co-leads alongside CEO Alexandre LeBrun, launched in Paris in December 2025 with an explicit mission to build this next generation of AI. Just three months later, in March 2026, the company raised $1.03 billion in seed funding at a pre-money valuation of $3.5 billion, one of the largest early-stage funding rounds in European tech history.
NVIDIA participated in the round, alongside Bezos Expeditions, Jeff Bezos’ personal investment vehicle, and other high-profile venture capitalists.
AMI Labs has established research hubs across four cities: Paris, New York, Montreal, and Singapore. The company is targeting applications in healthcare, robotics, and various industrial sectors.
What this means for the tech investment landscape
LeCun’s position is that LLM scaling alone will not lead to human-level intelligence. With a billion-dollar war chest, AMI Labs represents the most well-funded test of that thesis to date.
NVIDIA’s involvement is particularly notable. The chipmaker has been the single biggest beneficiary of the AI boom, selling the GPUs that train and run large language models. Its decision to invest in a company explicitly building an alternative architecture signals that serious capital is moving toward a world where next-token prediction isn’t the only game in town.
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