Meta Loses 78% of Original LLaMA AI Team

Joëlle Pineau, who led Meta’s AI Research (FAIR) group and was pivotal in Llama’s development, left the company. Eleven of the fourteen auth...

Joëlle Pineau, who led Meta’s AI Research (FAIR) group and was pivotal in Llama’s development, left the company.

Eleven of the fourteen authors from Meta's foundational LLaMA paper have now left the company, raising questions about its ability to retain top AI talent and maintain momentum in the face of growing competition from leaner, faster-moving startups.

Originally announced in 2023, LLaMA (Large Language Model Meta AI) represented Meta’s answer to the surge of generative AI models like OpenAI’s GPT and Google’s PaLM. It was widely praised for its performance in smaller parameter sizes and its open-access research model, which helped it gain quick traction in both academia and open-source communities.

However, internal instability has begun to undercut Meta’s perceived leadership in the space. Many of the original researchers have left to join or create rival AI ventures. A notable cluster of talent has coalesced around Mistral AI, a Paris-based generative AI company that has rapidly attracted funding and talent. With five former LLaMA co-authors onboard, Mistral is seen by many as a rising European alternative in the AI arms race.

Joëlle Pineau, Meta’s former VP of AI Research and head of the FAIR (Fundamental AI Research) group, also stepped down in April 2024. Pineau played a key role in Meta’s early AI strategy, bridging academic rigor and real-world applications. Her exit underscores the challenge Meta faces in sustaining long-term research excellence amid shifting internal priorities.

While Meta has recently released LLaMA 3, its newest model family, the departure of key figures behind its predecessors has raised doubts about whether future releases will maintain the same level of innovation. Critics argue that Meta’s organizational structure and commercial focus may be driving away the kind of research-first thinkers that enabled LLaMA’s early success.

The AI industry as a whole is undergoing a major shift. Researchers are increasingly moving from Big Tech to agile startups, where they can build with fewer constraints and more equity. The fragmentation of top-tier AI talent signals a broader decentralization — where breakthroughs might come just as often from startups as they do from billion-dollar labs.

For Meta, the exodus of its LLaMA team is not just a talent loss — it’s a reputational risk. As the competition between open-source and proprietary models intensifies, maintaining credibility and continuity in research will be critical to staying relevant. Whether Meta can rebuild and re-energize its AI teams in time remains an open question.