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AMI Labs
Artificial Intelligence
AMI Labs (Advanced Machine Intelligence) is a Paris-based frontier AI research lab founded by Turing Award winner Yann LeCun to build "world models" that learn from physical reality rather than language.
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AMI Labs was founded in late 2025 by Yann LeCun, the Turing Award-winning computer scientist who spent more than a decade leading Meta's AI research organization before departing to pursue an alternative research direction he had long argued for internally: that large language models, which learn primarily by predicting the next word in text, are fundamentally limited in their ability to understand and reason about the physical world, and that a new generation of AI systems needs to instead learn directly from sensory data such as video, much as humans and animals learn through observation and interaction with their environment. LeCun serves as chairman, with day-to-day leadership under CEO Alexandre LeBrun, a fellow Meta AI research veteran and the founder of digital health AI startup Nabla. AMI's technical approach centers on what LeCun calls Joint Embedding Predictive Architectures, or JEPA, a family of models designed to learn abstract, predictive representations of the world from raw sensory input rather than generating outputs token by token or pixel by pixel. The company announced a $1.03 billion seed round in March 2026 at a $3.5 billion pre-money valuation, reportedly the largest seed round ever raised by a European company, from an unusually broad and high-profile investor base spanning Nvidia, Samsung, Temasek, Toyota Ventures, and individual backers including Jeff Bezos, Mark Cuban, and Eric Schmidt, despite having only a small team and no commercial product at the time. AMI operates across multiple hubs in Paris, New York, Montreal, and Singapore, with initial application areas expected to include healthcare, industrial automation, and robotics, and its first disclosed commercial partner is Nabla, LeBrun's digital health company. LeCun has framed AMI's roadmap around a multi-year research horizon rather than near-term products, positioning the company as a serious, well-capitalized alternative bet to the prevailing large language model paradigm pursued by labs like OpenAI, Anthropic, and Google DeepMind.
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