It’s only been since June that Meta invested $14.3 billion in the data-labeling vendor Scale AI, bringing on CEO Alexandr Wang and several of the startup’s top executives to run Meta Superintelligence Labs (MSL). But the relationship between the two companies is already showing signs of fraying.
At least one of the executives Wang brought over to help run MSL — Scale AI’s former Senior Vice President of GenAI Product and Operations, Ruben Mayer — has departed Meta after just two months with the company, two people familiar with the matter told TechCrunch.
Mayer spent roughly five years with Scale AI across two stints. In his short time at Meta, according to those sources, Mayer oversaw AI data operations teams and reported to Wang but wasn’t tapped to join the company’s TBD labs — the core unit tasked with building AI superintelligence, where top AI researchers from OpenAI have landed.
However, Mayer disputes some details about his role, telling TechCrunch that his initial position was “to help set up the lab, with whatever was needed” rather than run data operations, and that he was “part of TBD labs from day one” rather than being excluded from the core AI unit. Mayer also clarified that he “did not report directly to [Wang]” and was “very happy” with his Meta experience.
Beyond the personnel changes, Meta’s relationship with Scale AI appears to be shifting. TBD Labs is working with third-party data labeling vendors other than Scale AI to train its upcoming AI models, according to five people familiar with the matter. Those third-party vendors include Mercor and Surge, two of Scale AI’s largest competitors, the people said.
While AI labs commonly work with several data labeling vendors – Meta has been working with Mercor and Surge since before TBD Labs was spun up – it’s rare for an AI lab to invest so heavily in one data vendor. That makes this situation especially notable: even with Meta’s multi-billion-dollar investment, several sources said that researchers in TBD Labs see Scale AI’s data as low quality and have expressed a preference to work with Surge and Mercor.
Scale AI initially built its business on a crowdsourcing model that used a large, low-cost workforce to handle simple data labeling—the process of tagging and annotating raw information to train AI models. But as AI models have grown more sophisticated, they now require highly-skilled domain experts—such as doctors, lawyers, and scientists—to generate and refine the high-quality data needed to improve their performance.
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Although Scale AI has moved to attract these subject matter experts with its Outlier platform, competitors like Surge and Mercor have been growing quickly because their business models were built on a foundation of high-paid talent from the outset.
A Meta spokesperson disputed the fact that there are quality issues with Scale AI’s product. Surge and Mercor declined to comment. Asked about Meta’s deepening reliance on competing data providers, a Scale AI spokesperson directed TechCrunch to its initial announcement of Meta’s investment in the startup, which cites an expansion of the companies’ commercial relationship.
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