Yann LeCun, a recipient of the 2025 Queen Elizabeth Prize for Engineering for their contributions to the development of modern machine learning in the field of Artificial Intelligence, speaks to members of the media during a reception at St James’s Palace in London on November 5, 2025.” width=”970″ height=”670″ data-caption=’The Turing Award winner says A.I. needs broader foundations than just scaling text models. <span class=”lazyload media-credit”>Yui Mok / POOL / AFP via Getty Images</span>’>
Meta’s former chief A.I. scientist, Yann LeCun, helped lay the groundwork for the modern A.I. boom long before chatbots became an industry obsession. Now, after leaving Meta in late 2025, he is building a multibillion-dollar startup under the premise that the race toward A.I. superintelligence is starting from the wrong place. Speaking at the VivaTech conference on June 17, LeCun shared more details about why he believes his startup, Advanced Machine Intelligence (AMI Labs), is on a better path toward human-level A.I. Earlier this year, the Paris-based company raised $1.03 billion at a $3.5 billion valuation, giving LeCun and his team fresh backing to pursue an alternative to today’s generative A.I. models developed by tech giants.
“I think there is a requirement for new paradigms to go beyond the limitations of current systems,” LeCun, 65, told Wired’s Steven Levy onstage.
Building better language models, as many A.I. companies are doing, could be one path, LeCun said, but “it’s kind of a slow way.” According to LeCun, AMI Labs is building “world models” that learn from reality, understand consequences, predict what happens next, and choose the best actions based on those predictions. “We have good hopes that this will really be a complete change of the blueprints of intelligent systems,” LeCun said.
LeCun believes much of Silicon Valley has become “LLM-pilled” — or overly convinced that scaling large language models will eventually produce human-like intelligence. The result, he argued, is a “monoculture” of A.I. systems that are powerful in some areas but still fundamentally limited.
While LLMs are already highly capable in areas like coding, they are built around language. Real-world data from cameras, robots, and other sensors is messier and harder to predict, which is why he believes a different approach is necessary. For AMI Labs, the result could be “considerably more intelligent systems that can anticipate the outcome of their own actions, can plan, can reason and perhaps all the way to human intelligence,” he said.
Coming from LeCun, the critiques carry weight. A longtime New York University professor, he is among the trio of researchers often referred to as the “Godfathers of A.I.” The others are Geoffrey Hinton, a University of Toronto professor and former Googler, and Yoshua Bengio, a University of Montreal professor who founded Quebec’s A.I. institute, Mila. In 2018, they collectively won the prestigious Turing Award for breakthroughs that helped push deep learning into the mainstream.
From FAIR to AMI Labs
In 2013, LeCun joined Facebook to launch what would become Facebook A.I. Research, or FAIR, and later transitioned to chief A.I. scientist at Meta. He said AMI has its roots as an internal FAIR project and had support from company leaders, including Mark Zuckerberg and CTO Andrew Bosworth. But as Meta’s A.I. priorities shifted toward catching up with competitors, the environment became less favorable.
At that point, it made sense to “just leave the company, try to accelerate the development, and build the things we can build with it,” LeCun said. “And I realized I could also raise enough money to keep this going.”
In March, AMI Labs raised a $1.03 billion seed round—the largest in European startup history. Investors include Nvidia, Jeff Bezos and Eric Schmidt, among others. With LeCun serving as executive chairman, the startup is led by CEO Alex LeBrun, a former FAIR engineering head and co-founder of health A.I. company Nabla, AMI Labs’ first partner. The company has assembled a research-heavy team with experience at Meta, Google DeepMind and other leading A.I. labs.
AMI says it aims to build applications in areas where this approach matters, including industrial process control, automation, wearable devices, robotics, and health care. “It’s not going to happen next year,” LeCun said. “We’re not going to have a country of geniuses in a data center next year, okay?”
At VivaTech, the discussion also broadened to a bigger question: who should control the next generation of A.I.? If future assistants are built only by “a handful of companies” in Silicon Valley or China, LeCun warned, “culture is in big trouble” and “democracy is in big trouble.” Blocking open-source models in the name of safety, he argued, misses the role A.I. can play in spreading knowledge.
That stance also informs LeCun’s work as chief science adviser to Project Tapestry, an AI Alliance-led effort to build a shared global A.I. model through a distributed network of contributors. The AI Alliance is a nonprofit group, co-launched in 2023 by Meta and IBM, to support open-source A.I. development. With Tapestry, the goal is to let countries, companies, universities and others contribute data or computing power without giving up control of that data. As A.I. begins to mediate what people read, watch, and search for, LeCun argues that people need alternatives to what a few dominant American or Chinese companies decide to build.
LeCun’s comments also come as Meta’s own open-source stance has grown more complicated. Llama 2, released in 2023 for free commercial use, made Meta a rare Big Tech counterweight to more closed A.I. rivals. But Zuckerberg has since signaled that Meta may not release all of its future “superintelligence” models openly.
“We need access to a wide diversity of A.I. assistants for the same reason we need access to a wide diversity of the press to get multiple sources of information,” LeCun said. “The only way I can see that this can happen is if there is an open, free foundation model, on top of which anybody can build their own specialized assistant for their language or languages, their culture, their value system, their political biases, their centers of interest. And so open source has to exist.”
