SAN FRANCISCO (Diya TV) — Meta has made a bold move in the race for artificial general intelligence (AGI), investing $14.3 billion in Scale AI and acquiring a 49% stake in the data-labeling startup. The deal values Scale at over $29 billion, making it Meta’s second-largest investment after acquiring WhatsApp for $19 billion in 2014.
The investment also recruits Scale’s 27-year-old founder, Alexandr Wang, to lead a new “superintelligence” lab at Meta focused on AGI—AI systems that rival or surpass human intelligence. Wang will remain on Scale’s Board of Directors, while Chief Strategy Officer Jason Droege steps in as interim CEO, the company confirmed in a statement.
Meta’s move signals an urgent push to catch up with rivals like OpenAI, Google DeepMind, and Anthropic, who are advancing high-performing “frontier models.” Meta recently released a new large language model and standalone AI app, and the Scale partnership appears designed to sharpen its data pipeline for training next-gen systems.
In a note to Scale employees shared on X, Wang called the investment a “major milestone and a powerful validation of the hard work you’ve all put into Scale’s mission.”
Meta, meanwhile, described the deal as an opportunity to “deepen the work” it has already been doing to produce quality data for AI training, according to statements shared with media outlets including The New York Times.
Scale AI has long specialized in labeling the massive volumes of data required to train large AI models. Its clients include tech heavyweights like Google and OpenAI. Most of this data annotation work is labor-intensive and takes place outside the United States—an aspect that has raised both operational and ethical questions.
While Meta’s partnership with Scale signals further consolidation in the AI industry, it also reignites tensions around control and centralization.
“Earlier this year, we saw the rise of open-source frontier models that can go toe-to-toe with closed models from Big Tech,” said Renz Chong, CEO of Sovrun, a modular on-chain platform backed by Andreessen Horowitz, in a statement to Decrypt. “That’s a clear signal: ‘state-of-the-art’ no longer has to mean centralized or proprietary.”
Chong emphasized that many so-called decentralized AI projects still rely on centralized APIs or cloud endpoints. In contrast, early infrastructure players like Sovrun are attempting to build foundational layers that offer decentralized compute power and incentivized model training.
Sovrun recently teamed up with Virtuals Protocol to launch ReadyGamer, a platform integrating AI-driven non-playable characters (NPCs) into game environments. Despite a temporary revenue dip earlier this year, activity on the platform has been rebounding, Virtuals Protocol confirmed in its usage metrics.
The investment structure allows Scale AI to maintain operational independence, a crucial detail as Meta faces mounting regulatory scrutiny. In April, U.S. lawmakers accused Meta of indirectly supporting China’s AI development, triggering a Senate inquiry.
By avoiding a full acquisition, Meta potentially sidesteps additional antitrust concerns, particularly as regulators take a closer look at Big Tech’s dominance in emerging technologies.
Still, the Meta-Scale deal underscores the increasing pressure on decentralized AI projects to differentiate themselves. Chong believes the future hinges not only on better algorithms but also on shifting power dynamics: “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.”
