Former Meta chief AI scientist Yann Lecun has publicly questioned the appointment of Alexander Wang as the company’s new AI boss, raising concerns about potential talent retention issues for Mark Zuckerberg’s social media giant.
CNBC reports that Yann Lecun, widely recognized as one of the “Godfathers of AI” and Meta’s former chief AI scientist, has criticized the company’s decision to appoint 29-year-old billionaire Alexander Wang as its chief AI officer, warning that the hiring could trigger a significant exodus of staff from the tech giant.
In an interview with the Financial Times, Lecun expressed concerns about Wang’s qualifications for leading Meta’s AI research initiatives. Wang, who co-founded the AI startup Scale AI, joined Meta in 2025 after the company acquired a 49 percent stake in his company. His appointment came as Meta intensified its efforts to compete in the rapidly evolving artificial intelligence market, reportedly offering signing bonuses of up to $100 million to attract top talent from competitors like OpenAI.
Lecun, 65, described Wang as “young” and “inexperienced,” particularly in the realm of AI research. While acknowledging that Wang “learns fast” and “knows what he doesn’t know,” Lecun pointed to a critical gap in his background. “There’s no experience with research or how you practice research, how you do it. Or what would be attractive or repulsive to a researcher,” Lecun stated.
The criticism comes amid broader concerns about Meta’s AI strategy and organizational changes. According to Lecun, Meta CEO Mark Zuckerberg “basically lost confidence in everyone who was involved” after the company faced accusations of gaming benchmarks to make its Llama 4 model appear more impressive than it actually was. In response, Zuckerberg reportedly “basically sidelined the entire Gen AI organization,” Lecun said.
These organizational shifts have already begun to impact Meta’s workforce, according to Lecun. “A lot of people have left, a lot of people who haven’t yet left will leave,” he warned. Lecun, who departed Meta in November, suggested that the company’s conservative approach to AI development contributed to talent attrition. “We had a lot of new ideas and really cool stuff that they should implement. But they were just going for things that were essentially safe and proved,” he explained. “When you do this, you fall behind.”
Wang currently heads Meta’s new AI research unit, TBD Labs, where he is tasked with developing new AI models. His appointment represents Meta’s effort to consolidate its AI leadership amid fierce competition from other technology giants racing to develop the most advanced AI systems.
When asked about Meta’s aggressive AI hiring strategy, Lecun remained skeptical. “The future will say whether that was a good idea or not,” he commented. He also challenged the fundamental approach Meta appears to be taking with large language models (LLMs), stating that “LLMs basically are a dead end when it comes to superintelligence.”
Lecun added, “I’m sure there’s a lot of people at Meta, including perhaps Alex, who would like me to not tell the world that.” This statement suggests potential disagreement within Meta’s AI community about the technological direction the company should pursue.
Since leaving Meta, Lecun has founded his own startup, Advanced Machine Intelligence Labs, which focuses on developing “world models” – AI systems that learn from videos and physical data in addition to language. This approach differs significantly from the LLM-based systems that have dominated recent AI development.
Nabla, a health tech AI startup that partnered with Lecun’s company in December, highlighted the limitations of current LLM technology in a press release. The company noted that unlike world models, LLMs “still face some structural constraints, including hallucinations, non-deterministic reasoning and limited handling of continuous multimodal data, which make autonomous decision-making challenging.”
Read more at CNBC here.
Lucas Nolan is a reporter for Breitbart News covering issues of free speech and online censorship.
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