Even as Yann LeCun’s AI startup raised more than $1 billion in seed funding, it appointed a new CEO. Entrepreneur and former Facebook researcher Alex LeBrun said he is joining LeCun and the founding team of Advanced Machine Intelligence (AMI) Labs, also known as AMI Labs, as the chief executive officer. AMI Labs said in an X post on Tuesday that the round was co-led by Cathay Innovation, Greycroft, Hiro Capital, HV Capital, and Bezos Expeditions, alongside other investors.LeCun departed Meta after spending 12 years leading its AI research efforts, to start the new venture AMI Labs that focuses on building world models – a type of AI system designed to better understand and reflect how the real world works.LeCun recently announced that the startup raised $1.03 billion in seed funding, which he said may represent a record for Europe. “Unveiling our new startup Advanced Machine Intelligence (AMI Labs). We just completed our seed round: $1.03B / 890M€, one the largest seeds ever, probably the largest for a European company,” LeCun wrote. The Paris-based startup added that it is building a team of researchers and engineers across Paris, New York, Montreal, and Singapore.
Who is Alex LeBrun and read his full LinkedIn post
LeBrun previously cofounded the healthcare startup Nabla, which created an agentic AI assistant for clinicians. I am thrilled to announce that I am joining Yann LeCun and an exceptional founding team to lead AMI – Advanced Machine Intelligence as CEO.We have secured a $1.03 billion USD (approximately €890 million) seed round to fuel our mission to build intelligent systems capable of truly understanding the real world—a long-term scientific endeavor.Having spent 24 years building AI products—including work on chatbots (VirtuOz, 2002), natural language understanding (Wit.ai, 2012), Facebook’s M assistant (2015), and healthcare AI (Nabla, 2019)—I have witnessed the strengths and, crucially, the limitations of machine learning methodologies.While the solutions we’ve shipped have (I hope) had a positive impact and helped people, they all relied on “shortcuts”. Generative architecture trained by self-supervised learning 𝑚𝑖𝑚𝑖𝑐 intelligence; they don’t genuinely understand the world. Predicting tokens, though powerful, works best for discrete and low-dimensional tasks like information retrieval, summarization, coding, and mathematics.However, factories, hospitals, and robots operating in open environments demand AI that grasps reality. And reality is not tokenized: it’s continuous, noisy and high-dimensional. Despite their immense power, I do not believe that generative architectures are the path to achieving this true understanding.It is time to move beyond shortcuts and work on a foundational solution. 𝐖𝐨𝐫𝐥𝐝 𝐦𝐨𝐝𝐞𝐥𝐬 learn abstract representations of real-world data, ignoring unpredictable details, and make predictions in representation space. Action-conditioned world models allow agentic systems to predict the consequences of their actions, and to plan action sequences to accomplish a task, subject to safety guardrails.AMI will advance AI research and develop applications where reliability, controllability, and safety really matter, especially for industrial process control, automation, wearable devices, robotics, healthcare, and beyond.Nabla is AMI’s first partner. Nabla’s customers will gain early access to our next-generation world models research, which will complement LLMs, strengthening our strategy to build safe, reliable, and clinically meaningful AI systems for healthcare. I will be transitioning from CEO of Nabla to Chief AI Scientist and Chairman, continuing to work closely with my co-founders Martin Raison Delphine Groll Laurent Landowski and the incredible team that has already made a profound impact on millions of physicians and patients.If AMI’s mission resonates with you, we invite you to join us on this journey!𝐑𝐞𝐚𝐥 𝐰𝐨𝐫𝐥𝐝. 𝐑𝐞𝐚𝐥 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞.AI researcher and New York University computer science professor Saining Xie has also joined the founding team. Xie serves as cofounder and chief science officer wrote that “AMI isn’t a conventional lab.”
