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American Focus > Blog > Tech and Science > Can Scale AI and Alexandr Wang reignite Meta’s AI efforts?
Tech and Science

Can Scale AI and Alexandr Wang reignite Meta’s AI efforts?

Last updated: June 12, 2025 1:49 am
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Can Scale AI and Alexandr Wang reignite Meta’s AI efforts?
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Meta Makes Bold Move with $15 Billion Investment in Scale AI

Meta, formerly known as Facebook, is making headlines once again with reports of a massive investment in the data-labeling firm Scale AI. The tech giant is said to be putting nearly $15 billion into the startup, acquiring a 49% stake in the company, and bringing on CEO Alexandr Wang to lead a new “superintelligence” lab within Meta.

This move by Meta is reminiscent of its past risky acquisitions, such as the $19 billion purchase of WhatsApp and the $1 billion acquisition of Instagram. While these deals were initially met with skepticism, both platforms have since become integral parts of Meta’s empire. The question now is whether the Scale AI investment will pay off for Meta or if it’s a desperate attempt to keep up with competitors like OpenAI and Google.

Unlike previous acquisitions of social media platforms, Meta’s investment in Scale AI is focused on the data used to train AI models. Scale AI has been a key player in providing data labeling services for leading AI labs like OpenAI. Meta’s leaders have expressed a need for innovation in data within the company’s AI teams, making Scale AI an attractive partner.

In addition to the investment in Scale AI, Meta is also counting on CEO Alexandr Wang to lead the new superintelligence team. Wang, known for his ambition and strong connections in Silicon Valley, has been actively engaging with world leaders to discuss the societal impact of AI. However, Wang lacks the traditional AI research background of other lab leaders, prompting Meta to recruit top talent like DeepMind’s Jack Rae.

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The future of Scale AI post-acquisition remains unclear, especially as the role of real-world data in AI training evolves. Some AI labs are bringing data collection in-house, while others are exploring synthetic data. Scale AI reportedly missed revenue targets earlier this year, indicating a shift in the data landscape for AI model training.

Meta’s investment in Scale AI could potentially disrupt relationships with other AI labs that traditionally work with the company. Competitors like Turing and Surge AI may benefit from increased interest from customers seeking neutral partners. Only time will tell if Meta’s investment will pay off in its AI efforts, as competition from OpenAI and others continues to intensify.

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