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Meta’s Chief AI Scientist Is Leaving to Start a New AI Company

Meta's Chief AI Scientist Is Leaving to Start a New AI Company

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Yann LeCun, Meta’s chief AI scientist and one of the most influential figures in the field, is leaving the company to start a new AI venture, a Meta spokesperson confirmed to Business Insider.

LeCun announced the move on Facebook, sharing that he is building a startup centered on his long-standing interest in world-model research. Meta will partner with LeCun on his new venture, a Meta spokesperson told Business Insider, but didn’t reveal any details about the nature of the partnership.

LeCun’s departure comes during a period of instability inside Meta’s AI organization. Over the past few months, Meta has hired dozens of top researchers and engineers from rivals and reorganized its AI efforts under the new Superintelligence Labs division, led by former Scale AI CEO Alexandr Wang. Tensions emerged within the newly formed team between the highly compensated new hires and the existing researchers, some of whom have threatened to quit, Business Insider previously reported.

In August, the company made the biggest reorganization of its artificial intelligence operations to date, creating four distinct teams that focus on research, training, products, and infrastructure.

This shift followed the company’s pivot toward out-competing OpenAI, Google DeepMind, and Anthropic on large-scale AI models. At the same time, researchers have cycled in and out of key roles, and Meta’s Llama 4 release drew muted reactions internally and externally. Earlier this week, Souminth Chintala, the creator of Meta’s open source AI framework PyTorch, left the company after 11 years to join Mira Murati’s Thinking Machines Lab.

LeCun’s departure isn’t entirely surprising. He’s been a vocal critic of relying too heavily on large language models, arguing instead for his JEPA approach — a method that trains AI to understand and predict the physical world from images and sensory data, rather than generating text. Meta, meanwhile, has increasingly focused on scaling LLMs and pushing commercially driven model development.

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