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Meta restructures AI lab into four units, eyes potential job cuts

Ollie Chang, Taipei; Sherri Wang, DIGITIMES Asia 0

Credit: Bloomberg

Meta has reportedly reorganized its recently formed 'superintelligence' lab into four units focused on research, products, infrastructure, and advanced model development, while considering possible staff reductions, according to Bloomberg and The New York Times.

In an internal memo, Meta's new chief AI officer, Alexandr Wang, detailed a major reorganization within the company's AI division. The lab will now be split into four groups: TBD Lab, focused on large language models like Llama; Fundamental AI Research, or FAIR, the company's long-running research arm; a Products and Applied Research team; and MSL Infra, which oversees the massive infrastructure behind Meta's AI push.

Wang will take charge of TBD Lab himself. Robert Fergus will remain at the helm of FAIR, Aparna Ramani will lead MSL Infra, and former GitHub CEO Nat Friedman will run the applied research unit.

Generative AI unit scrapped

The AGI Foundations team, which had been focused on generative AI, has been dismantled. Its leaders, Ahmad Al-Dahle and Amir Frenkel, will shift to strategic projects within the new superintelligence unit and report directly to Wang. Connor Hayes, who previously led AI product development, was earlier moved to the Threads team.

Internal friction over pay

Meta's AI division has grown to several thousand employees, and sources say the company is considering scaling back, which could involve cutting jobs or moving staff to other areas. Some senior executives are also expected to depart.

Within the company, longtime employees have become frustrated because newcomers are being offered pay packages in the nine figures. This has created resentment and deepened divisions across teams.

Pivot on AI models

Meta has also abandoned plans for its high-profile model, Llama 4 Behemoth. Instead, Wang's team is starting from scratch to build a new system that favors a closed-source design. This marks a major shift from the company's multi-year commitment to open source.

The company is also considering using third-party AI models, signaling a significant move away from its traditional strategy of relying solely on in-house development.

Article edited by Jerry Chen