In brief
- Meta has acquired a 49% stake in Scale AI for $14.3B, its second-largest deal ever.
- Scale CEO Alexandr Wang has joined Meta to lead a new superintelligence lab.
- The investment illustrates Meta’s aggressive strategy to compete with the likes of OpenAI and Google.
American multinational tech company Meta has made a significant investment in Scale AI, the data-labeling startup essential for training artificial intelligence systems, recruiting its young founder Alexandr Wang to build out a “superintelligence” lab focused on achieving artificial general intelligence (AGI).
The $14.3 billion investment acquired a 49% stake in Scale AI, raising its valuation to over $29 billion. This is Meta’s second-largest investment, following its $19 billion WhatsApp acquisition in 2014.
Scale AI announced that Wang would continue to serve as a director on the company’s Board of Directors, with the firm’s Chief Strategy Officer, Jason Droege, stepping into his shoes as interim CEO.
In a tweet, Wang shared a note to employees, describing Meta’s investment as a “major milestone and a powerful validation of the hard work you’ve all put into Scale’s mission.”
For Meta, which has been working on its own AI strategies and recently released a new model and a standalone AI app in the past couple of months, the deal would “deepen the work” it has been engaged in for “producing data for A.I. models,” according to company statements shared with media.
Meta’s AI race
This speaks to the urgency of Meta’s move to catch up in the AI race, as it faces mounting pressure from other players working on “frontier models” which are advanced, large-scale systems pushing the boundaries of AI.
Yet the move also highlights a key tension between large tech firms such as Meta and others building on decentralized platforms, according to Renz Chong, CEO of a16z-backed modular on-chain platform Sovrun.
“Earlier this year, we saw the rise of open-source frontier models that can go toe-to-toe with closed models from Big Tech,” Chong told Decrypt. “That’s a clear signal: ‘state-of-the-art’ no longer has to mean centralized or proprietary.”
Because most other AI-on-chain projects still lean on “centralized inference endpoints or off-chain APIs,” the predicament places pressure on decentralized players.
“Early infrastructure players are laying critical groundwork, offering decentralized compute and incentivized training layers,” Chong noted.
What is Scale AI?
Scale AI specializes in data labeling services that are essential for training AI systems, working with clients including Google and OpenAI. The startup employs human annotators to classify data that fuels AI models, with much of the work conducted outside the U.S. through labor-intensive processes.
Meta’s investment would reportedly give it a minority stake in Scale AI, allowing the startup to maintain operational independence—a structure that could help Meta avoid additional regulatory scrutiny amid ongoing antitrust battles. Earlier in April, Meta was accused of assisting China’s AI ambitions, prompting a Senate inquiry.
Still, the consolidation of AI resources between tech giants has prompted alternative visions from the decentralized sector. Sovrun, for instance, recently entered a joint venture with Virtuals Protocol to build ReadyGamer, a platform that integrates AI-driven NPCs into popular game worlds.
While those projects experienced a decline in revenue earlier this year, a resurgence is underway, with daily numbers slowly returning to previous levels, according to data maintained by Virtuals Protocol.
Chong argues the real shift may be found not just in making better systems, but in “changing who gets to shape them” and building “outcomes that matter to the communities they serve.”
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