According to God of Prompt on X, AMI Labs raised $1.03B to pursue Yann LeCun’s world model architecture, positioning it as a thesis bet against scaling transformer LLMs that focus on next‑token prediction (as reported by AMI Labs and God of Prompt). According to AMI Labs, the company aims to build systems with persistent memory, reasoning, planning, and controllability, operating from Paris, New York, Montreal, and Singapore. As reported by AMI Labs, the round is co-led by Cathay Innovation, Greycroft, Hiro Capital, HV Capital, and Bezos Expeditions, signaling institutional support for Path B: interactive world-model learning over Path A: larger LLMs. According to God of Prompt, if world models scale, prompt engineering practices and tooling could shift toward agents that learn via interaction, offering business opportunities in robotics, autonomous systems, simulation platforms, and memory-centric AI infrastructure.

According to Yann LeCun on X (Twitter), Advanced Machine Intelligence (AMI Labs) has closed a $1.03B (~€890M) seed round to develop AI systems centered on world models with persistent memory, reasoning, planning, and controllability. As reported by TechCrunch, the round is co-led by Cathay Innovation, Greycroft, Hiro Capital, HV Capital, and Bezos Expeditions, positioning AMI among the largest seed financings globally and likely the largest for a European AI startup. According to AMI Labs’ website, the company will operate from Paris, New York, Montreal, and Singapore from day one, focusing on building universally intelligent systems that understand the real world. As reported by TechCrunch, the business implications include accelerated R&D in embodied and agentic AI, opportunities for enterprise copilots that plan across long horizons, and a potential platform for safety-aligned control in real-world applications such as robotics, logistics, autonomous operations, and multimodal assistants. According to AMI Labs, the emphasis on controllability and safe planning suggests near-term partnerships with enterprises seeking reliable long-context agents, with hiring underway across research and engineering.