Meta's Chief AI Scientist Yann LeCun is reportedly leaving the tech giant to launch his own AI startup after declaring large language models (LLMs) a "dead end" for reaching human-like AI. This departure comes as Meta shifts its focus towards advanced AI systems and superintelligence research, with LeCun's long-term work at Meta's Fundamental AI Research (FAIR) lab being put on the backburner.
LeCun's exit marks another major shake-up at Meta, which is doubling down on its research into world models. According to sources familiar with the matter, LeCun's new venture will focus on training AI systems to understand the physical world rather than generating language alone. This move isn't surprising given his skepticism about LLMs, which he has previously called a "dead end" for achieving human-like intelligence.
LeCun believes that world models are key to developing AI that can reason, plan complex actions, and make predictions. He argues that training on text data will never be enough to achieve human-level intelligence. This perspective is echoed by other researchers and companies, including Stanford's Fei-Fei Li, who has raised over $230 million for her startup World Labs.
Google DeepMind has also explored world models through its Genie releases, while Nvidia is pushing into physical AI with products like its Cosmos world models. LeCun's new venture could potentially rival these efforts, as he brings his expertise and knowledge of machine learning to the table.
The French-American computer scientist joined Meta in 2013 and played a key role in launching the company's FAIR team. He became Meta's chief AI scientist in 2018 and was awarded the Turing Award for his contributions to neural networks. However, following the company's recent restructuring, LeCun now reports to Alexandr Wang, head of Meta's superintelligence division.
LeCun's departure from Meta marks a significant shift in the company's focus towards world models. The FAIR lab, which contributed to early versions of Meta's Llama model, has suffered setbacks in recent months, including the loss of its leader Joelle Pineau.
LeCun's exit marks another major shake-up at Meta, which is doubling down on its research into world models. According to sources familiar with the matter, LeCun's new venture will focus on training AI systems to understand the physical world rather than generating language alone. This move isn't surprising given his skepticism about LLMs, which he has previously called a "dead end" for achieving human-like intelligence.
LeCun believes that world models are key to developing AI that can reason, plan complex actions, and make predictions. He argues that training on text data will never be enough to achieve human-level intelligence. This perspective is echoed by other researchers and companies, including Stanford's Fei-Fei Li, who has raised over $230 million for her startup World Labs.
Google DeepMind has also explored world models through its Genie releases, while Nvidia is pushing into physical AI with products like its Cosmos world models. LeCun's new venture could potentially rival these efforts, as he brings his expertise and knowledge of machine learning to the table.
The French-American computer scientist joined Meta in 2013 and played a key role in launching the company's FAIR team. He became Meta's chief AI scientist in 2018 and was awarded the Turing Award for his contributions to neural networks. However, following the company's recent restructuring, LeCun now reports to Alexandr Wang, head of Meta's superintelligence division.
LeCun's departure from Meta marks a significant shift in the company's focus towards world models. The FAIR lab, which contributed to early versions of Meta's Llama model, has suffered setbacks in recent months, including the loss of its leader Joelle Pineau.