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    Home»Startups»Beyond LLMs: AI pioneer Yann LeCun’s new venture AMI raises €890 million to build “world model” AI systems
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    Beyond LLMs: AI pioneer Yann LeCun’s new venture AMI raises €890 million to build “world model” AI systems

    Editor Times FeaturedBy Editor Times FeaturedMarch 10, 2026No Comments3 Mins Read
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    Advanced Machine Intelligence (AMI),  a brand new Paris-based startup based by the previous Chief AI Scientist at Meta and co-recipient of the 2018 ACM A.M. Turing Award, Yann LeCun, has raised almost €890 million ($1.03 billion) at a €3 billion ($3.5 billion) pre-money valuation. 

    AMI is creating a brand new type of AI methods that comprehend the world, possess persistent reminiscence, and are able to reasoning, planning, and remaining controllable and protected.

    That is among the many largest Seed rounds ever raised by a European firm. It was co-led by Cathay Innovation, Greycroft, Hiro Capital, HV Capital, Bezos Expeditions, and varied different traders and angels worldwide.

    AMI is moreover backed by a bunch of long-term worldwide traders and strategic companions, reminiscent of Toyota Ventures, New Legacy Ventures, Temasek, SBVA, NVIDIA, Mark Cuban, Affiliation Familiale Mulliez, Groupe industriel Marcel Dassault, Sea, and Alpha Intelligence Capital.

    Further notable participation comes from Eric Schmidt, Aglaé Lab, ZEBOX Ventures, Artémis, Xavier Niel, Publicis Groupe, Samsung, Bpifrance Digital Enterprise, Jim Breyer, Tim & Rosemary Berners-Lee, and Mark Leslie.

    Alexandre LeBrun, the co-founder and CEO of Paris-based healthcare AI startup Nabla, will be part of AMI as its co-founder and CEO, whereas transitioning from CEO of Nabla to Chief AI Scientist and Chairman. Nabla is AMI’s first companion.

    In keeping with AMI, real-world information is steady, high-dimensional, and noisy, whether or not it’s obtained by cameras or another sensor modality. It believes that generative architectures, skilled by self-supervised studying to anticipate the longer term, have achieved outstanding success in language understanding and technology. Nevertheless, since a lot real-world sensor information is unpredictable, generative strategies typically fall quick.

    LeBrun mentioned in his LinkedIn submit, “Whereas the options we’ve shipped have (I hope) had a optimistic impression and helped folks, all of them relied on “shortcuts”. Generative structure skilled by self-supervised studying intelligence; they don’t genuinely perceive the world. Predicting tokens, although highly effective, works greatest for discrete and low-dimensional duties like info retrieval, summarisation, coding, and arithmetic.

    “Nevertheless, factories, hospitals, and robots working in open environments demand AI that grasps actuality. And actuality just isn’t tokenised: it’s steady, noisy and high-dimensional. Regardless of their immense energy, I don’t imagine that generative architectures are the trail to attaining this true understanding. It’s time to transfer past shortcuts and work on a foundational answer.”

    That is the place world information is available in. “AMI is creating world fashions that be taught summary representations of real-world sensor information, ignoring unpredictable particulars, and that make predictions in illustration area. Motion-conditioned world fashions permit agentic methods to foretell the results of their actions, and to plan motion sequences to perform a activity, topic to security guardrails,” the corporate stated in a press release asserting the funding.

    AMI claims that it’s going to improve AI analysis and develop purposes centered on reliability, controllability, and security, significantly in industrial course of management, automation, wearable gadgets, robotics, healthcare, and extra. It has been working in Paris, New York, Montreal and Singapore from day one.





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