Why AMI Labs' Alexandre LeBrun Won't Call His AI 'AGI' or 'Superintelligence'

While the rest of the AI industry races to label its work as "AGI" or "superintelligence," Alexandre LeBrun, the CEO of Yann LeCun's world model startup, AMI Labs, avoids the terms altogether. "We never used the word AGI. And I just noticed that nobody is using it anymore; they switched to superintelligence," he said in an interview with TechCrunch. "Next time we'll switch to something else." He isn't sold on the new label either. "There's no good definition. What is superintelligence? I don't know. It's not a very useful word".

It's a pointed stance from a founder sitting at the center of AI's newest race. AMI Labs, co-founded by Turing Award winner Yann LeCun after he left Meta, raised $1.03 billion in March at a $3.5 billion pre-money valuation despite having no product yet. The massive investment, which included participation from Samsung Electronics, SBVA, Jeff Bezos' Bezos Expeditions, and Nvidia, reflects the tech industry's bet on "world models" as the next frontier after large language models.

What Is a World Model?

A large language model (LLM) predicts the next word or text. A world model predicts the next state. Nudge a glass off the table, and you already know it will tip and spill; that's the intuition a world model is meant to capture .

"The solution to AI's chronic hallucination problem lies in world models," LeBrun said. While LLMs predict the statistically most likely next word, world models predict the next "action". AMI Labs is building what's called a Joint Embedding Predictive Architecture (JEPA) a "world model" designed to move AI beyond statistical pattern recognition .

During an interview in Seoul, LeBrun pushed an open water bottle toward the edge of a table. Onlookers gasped. "Even a 4- to 5-year-old child intuitively knows that pushing the bottle further will make it fall and spill water. Understanding such physical principles is the world model we aim to build" .

He isn't claiming world models are better than LLMs. They are "complementary, not replaceable" when it comes to AI systems that understand the physical world . Drawing a parallel to the human brain's distinct language and reasoning functions, LeBrun said LLMs will remain the most efficient tools for processing language. At the same time, world models will provide context and real-world understanding.

Why Physical AI Needs a Different Approach

Almost every industry that "touches the real world" could eventually make use of robotics based on world models, LeBrun said, arguing that physical environments remain where LLMs are weakest. A factory robot repeating the same motion works well enough today, he said. The challenge begins when "you take your robot outside into a more open environment, in your household, or in the street," where it must understand its surroundings and operate safely. "Robots are not safe right now," he said. "There's no solution for that today".

"The hardware is very advanced; progress in hardware in the last few months is incredible, but there's no brain" . Such context-aware AI would have been useful, for example, in preventing a robot that was dancing and doing kung fu at a public event from approaching and kicking a child .

Healthcare offers a more personal example for LeBrun, whose previous company was Nabla, an AI health startup. He likened today's AI systems to a doctor trained only on textbooks and without a residency. LLMs may be useful in medicine, he said, but they cover "only 1% of healthcare." The rest depends on real-world experience .

The Asia Strategy

A world model can't be built inside a lab. To train on reality, AMI needs real environments and close partners. "We need access to the real world," and it's "easier for us to do that with partners" . That is part of what pulls him toward Asia, where the robots, chips, and factories actually are.

The pull toward South Korea comes down to two things. First, Korea has advanced industries in robotics, semiconductors, and manufacturing the hardware-heavy sectors that the first wave of AI barely touched. The second attraction is speed. "Korea was the fastest adopter of the internet 25 years ago," he said. It's that combination of a deep industrial base plus a willingness to embrace AI fast that he calls "unique," and the reason "we want to be here from day one".

JP Lee, the CEO of SBVA and one of AMI's backers in Asia, told TechCrunch: "I've been telling Alex and the team to come to Korea". He points to Seoul's June plan to mobilize some $880 billion for chips, AI data centers, and physical AI, as one of its three declared pillars: "They should coexist".

For all the star power and the billion-dollar check, AMI has nothing to sell yet. There's no product yet, and no timeline he'll commit to. "We'll make a surprise when we're ready," LeBrun said.