AI pioneer Yann LeCun joins Nexar board as mobility artificial intelligence scales
LeCun, former chief AI scientist at Meta, launched Advanced Machine Intelligence two months ago to build AI systems grounded in real-world understanding rather than abstract models or simulations.
Israeli-founded startup Nexar, which develops AI-powered mobility solutions, announced on Thursday that Yann LeCun, one of the most influential figures in artificial intelligence, has joined its Board of Directors.
LeCun, a professor at New York University and former chief AI scientist at Meta, is widely recognized as a pioneer of deep learning, convolutional neural networks, and world models, internal representations that allow machines to reason, predict, and plan within complex environments. He helped define modern AI and earned the 2018 Turing Award, often called the “Nobel Prize of computing,” alongside Yoshua Bengio and Geoffrey Hinton.
In recent months, LeCun has been in the news for his candid commentary on the AI industry, particularly Meta’s large-scale investment in generative AI and large language models. He has criticized the overemphasis on LLMs, arguing that they are limited in achieving “superintelligence” or reliable decision-making in real-world contexts. He left Meta in November 2025 to focus on his new venture, Advanced Machine Intelligence, which seeks to build AI systems grounded in real-world understanding rather than purely in abstract models or simulations.
At Nexar, LeCun will advise on the use of the company’s BADAS platform, which aggregates real-world driving video and translates it into predictive intelligence for autonomous and connected vehicles. Nexar’s network transforms ordinary cars into vision sensors, capturing video across geographies, road types, weather conditions, and rare edge cases. This continuous stream of real-world data provides the foundation for AI systems to build “world models” that can perform reliably in unpredictable environments, a key requirement for safety-critical applications.
"Building capable AI systems requires learning accurate models of how the world works," said LeCun. "Those models don't emerge from abstractions alone. They come from sustained exposure to reality—with all its variability, ambiguity, and edge cases."
Zach Greenberger, Nexar’s CEO, said LeCun’s perspective reinforces the company’s mission. "As intelligence moves into real environments, the companies that succeed will be those grounded in reality. Yann's perspective reinforces how we think about Nexar's role: providing the real-world experience AI systems need to build reliable world models and earn the right to deploy."
