26 October 2025, 07:00

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Meta to cut around 600 roles in its Superintelligence Labs AI unit

Meta to cut around 600 roles in its Superintelligence Labs AI unit

Meta (META.O) is cutting roughly 600 positions out of the several thousand roles within its Superintelligence Labs artificial intelligence unit, Axios reported this week.

The cuts will affect the company’s Facebook Artificial Intelligence Research (FAIR) unit, product-related AI and AI infrastructure units, while sparing the newly formed TBD Lab, according to the report, which cited an internal memo.

Fewer team members would streamline decision-making and increase the responsibility, scope and impact of each role, the report said, quoting Alexandr Wang, the company’s chief AI officer.

Meta did not immediately respond to a Reuters request for comment. Reuters could not independently verify the report.

The company is encouraging affected employees to apply for other jobs within Meta and expects most will find a position internally, the report said.

On Tuesday, Meta struck a $27 billion financing deal with Blue Owl Capital (OWL.N), the company’s largest-ever private capital agreement, to fund its biggest data center project.

Some analysts said the deal will allow Meta to achieve its massive AI ambitions by shifting much of the upfront cost and risk to external capital, while retaining a smaller ownership share in the project.

The parent of Facebook and Instagram reorganized its AI efforts under Superintelligence Labs in June after senior staff departures and a poor reception for its open-source Llama 4 model. CEO Mark Zuckerberg personally led an aggressive hiring spree for the unit to revitalize Meta’s AI efforts.

Zuckerberg said in July the company would spend hundreds of billions of dollars to build several massive AI data centers for superintelligence, a theoretical milestone where machines could match or surpass human capabilities.

The company began investing in AI in 2013, with the launch of FAIR and recruiting Yann LeCun, its chief AI scientist, to lead the effort and building a global research network focused on deep learning.

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