In June, Meta invested a staggering $14.3 billion in Scale AI, a data-labeling vendor, bringing on CEO Alexandr Wang and several top executives to run Meta Superintelligence Labs (MSL). However, just two months into the partnership, signs of friction are emerging.
Executive Exodus
One of the executives Wang brought over, Ruben Mayer, has already departed Meta. Mayer, who spent five years at Scale AI, was tasked with overseeing AI data operations teams. However, he disputes some details about his role, stating that his initial position was « to help set up the lab, with whatever was needed » and that he was « part of TBD Labs from day one. » Mayer’s departure raises questions about the stability of the partnership.
Shifting Relationship
Beyond personnel changes, Meta’s relationship with Scale AI appears to be evolving. TBD Labs is now working with third-party data labeling vendors, including Mercor and Surge, two of Scale AI’s largest competitors. This is unusual, given Meta’s massive investment in Scale AI. Several sources indicate that researchers in TBD Labs view Scale AI’s data as low quality and prefer working with Surge and Mercor.
Data Quality Issues
Scale AI’s business model, which relies on a crowdsourcing model, has been criticized for producing low-quality data. As AI models become more sophisticated, they require high-quality data to improve their performance. Competitors like Surge and Mercor, which have built their businesses on high-paid talent, are gaining traction.
Meta’s AI Ambitions
Meta’s investment in Scale AI was meant to address the company’s AI development challenges. However, the partnership’s rocky start raises concerns about Meta’s ability to stabilize its AI operations and retain top talent. The company has faced challenges in integrating new AI researchers from OpenAI and Scale AI, leading to frustration and departures.
The Future of AI at Meta
As Meta prepares to launch its next-generation AI model by the end of the year, the question remains whether the company can overcome its current challenges and achieve its AI ambitions. With the AI landscape rapidly evolving, Meta’s success will depend on its ability to adapt and innovate.