Signs of Tension in Meta’s Partnership with Scale AI

Since June, Meta has allocated $14.3 billion towards Scale AI, placing CEO Alexandr Wang and other noteworthy figures at the helm of the Meta Superintelligence Labs (MSL). However, early indicators imply that this collaboration might face challenges.

Wang has brought on Ruben Mayer, the former Senior Vice President of GenAI Product and Operations at Scale AI, to join MSL. Sources from TechCrunch reveal that Mayer left Meta after a brief two-month tenure.

Mayer arrived with nearly five years of experience from two stints at Scale AI, leading teams in AI data operations under Wang’s leadership. However, he was not part of TBD Labs, the central initiative aiming to attain AI superintelligence, which has attracted several prominent researchers from OpenAI.

Mayer has not responded to numerous requests for comment from TechCrunch.

Sources indicate that TBD Labs is collaborating with various external data providers in addition to Scale AI for upcoming AI models. Companies such as Mercor and Surge are apparently included in this initiative.

Typically, AI labs partner with multiple data vendors—Meta has previously collaborated with Mercor and Surge even before TBD Labs was established—making exclusive reliance on a single provider unusual. This has sparked concerns among insiders, who claim that researchers at TBD Labs find Scale AI’s data inadequate, prompting them to seek alternatives from Surge and Mercor.

Initially, Scale AI employed a crowdsourcing model that utilized a vast, cost-effective workforce for basic data labeling. However, as AI models evolved, the focus shifted towards specialized professionals, such as doctors and scientists, to produce and refine high-quality data that enhances model performance.

As Scale AI aims to recruit these experts through its Outlier platform, competitors like Surge and Mercor have quickly gained market presence by honing their recruitment strategies to attract top-tier talent from the beginning.

A Meta representative downplayed concerns about Scale AI’s data quality, while Surge and Mercor opted not to comment. In response to questions regarding Meta’s dependency on competing data providers, a Scale AI spokesperson described the initial investment announcement as a sign of an evolving business partnership.

Meta’s collaborations with various third-party data vendors underscore its goal to diversify data sources while also making significant investments in Scale AI. Conversely, Scale AI has encountered difficulties: shortly after Meta’s major investment, both OpenAI and Google revealed intentions to terminate their relationships with the data provider.

Following the loss of these clients, Scale AI laid off 200 employees from its data labeling team in July, attributing this to shifts in market demand, according to new CEO Jason Droege. He noted that Scale AI seeks to hire in other sectors, especially after securing a $99 million contract with the U.S. Army.

Initially, speculation arose that Meta’s investment in Scale AI aimed to lock in Wang—a pivotal figure with substantial AI expertise since Scale AI’s inception in 2016—enhancing Meta’s allure to elite AI talent.

Beyond Wang, the overall significance of Scale AI for Meta remains uncertain.

A member of MSL remarked that many leaders from Scale brought on by Meta are not part of the core TBD Labs team, similar to Mayer. Moreover, it appears that Meta is not fully dependent on Scale AI for its data labeling requirements.

Meanwhile, the atmosphere within Meta’s AI division is said to have grown more chaotic since Wang’s arrival and the influx of several leading researchers, according to two former employees and one current MSL member. New hires from OpenAI and Scale AI have raised concerns about the bureaucracy typical in larger organizations, indicating that the impact of Meta’s previous GenAI team is waning.

These factors suggest that Meta’s largest AI investment to date encounters a distinct set of challenges while the company strives to address its AI development obstacles. Following the tepid release of Llama 4 in April, sources indicate that Meta CEO Mark Zuckerberg expressed dissatisfaction with the AI team’s advancements, based on insights from one current and one former employee shared with TechCrunch.

In light of these challenges and to stay competitive against players like OpenAI and Google, Zuckerberg has implemented decisive measures to encourage partnerships and initiated an aggressive recruitment strategy for top AI talent.

In addition to Wang, Zuckerberg has successfully drawn in prominent AI researchers from OpenAI, Google DeepMind, and Anthropic. Meta has also acquired AI voice startups like Play AI and WaveForms AI and forged partnerships with Midjourney, a firm focused on AI image generation.

To further its AI ambitions, Meta has publicly outlined plans for extensive data center expansions across the U.S., including a $50 billion facility in Louisiana named Hyperion, inspired by a titan in Greek mythology recognized as the father of the Sun God.

Wang, who lacks formal academic credentials in AI, is perceived as an unconventional choice to head an AI lab. Reports suggest that Zuckerberg considered more conventional candidates for the role, including OpenAI’s chief research officer, Mark Chen, as well as startups founded by Ilya Sutskever and Mira Murati—none of whom accepted the offers.

Recent reports from Wired indicate that several AI researchers recruited from OpenAI have already departed Meta. Additionally, numerous long-standing members of Meta’s GenAI unit have exited amidst recent organizational changes.

Rishabh Agarwal, a researcher at MSL, recently announced his resignation, stating on X this week that he will be leaving the organization.

“The pitch from Mark and @alexandr_wang to build in the Superintelligence team was incredibly compelling,” Agarwal stated. “However, I ultimately adhered to Mark’s advice: ‘In a world that’s changing so fast, the biggest risk you can take is not taking any risk.’”

When asked about his experiences at Meta and his decision to depart, Agarwal chose not to comment.

Recently, Chaya Nayak, Director of Product Management for Generative AI, and Rohan Varma, Research Engineer, also announced their departures from Meta. The pressing question now is whether Meta can stabilize its AI operations and retain essential talent for future success.

MSL is currently focused on developing its next-generation AI model, with Business Insider reporting an expected launch by the year’s end.