Google limits Meta's use of Gemini AI models, delaying AI projects

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Google has limited Meta’s access to Gemini AI models because it cannot meet Meta’s demand for computing capacity, delaying some of Meta’s AI projects.
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Meta staff were told to use AI tokens more efficiently after Google said it could not provide the full Gemini capacity Meta wanted to buy.
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Other Google clients also faced capacity limits, but Meta was hit hardest because its demand for Google’s AI models was especially high.
Google has limited Meta's use of its Gemini AI models as it could not meet the social media giant’s computing capacity demand, the Financial Times reported on Sunday.
The tech giant informed Meta that it would not be able to provide the full Gemini capacity that the company wanted to buy. The shortfall disrupted some of Meta's AI projects, with the staff informed to make more efficient use of AI tokens, the publication reported, citing three people familiar with the matter.
Meta is not the only tech firm affected. Several other Google clients faced the same capacity constraints, according to the FT, although to a lesser extent. Meta bore the brunt due to its exceptionally high demand for Google’s AI models.
Google and Meta did not immediately respond to Reuters' requests for comment.
Meta is ramping up its AI efforts through new initiatives like Superintelligence Labs, a major restructuring of Meta’s AI group. The company has said it plans to invest hundreds of billions of dollars in AI infrastructure and research in the years to come.
“As the pace of AI progress accelerates, developing superintelligence is coming into sight. I believe this will be the beginning of a new era for humanity, and I am fully committed to doing what it takes for Meta to lead the way,” CEO Mark Zuckerberg said at the time.
The capacity shortfall comes as demand for AI computing power continues to grow.
Speaking during Alphabet's first-quarter earnings call following the announcement that revenue at Google Cloud grew 63% to $20 billion, CEO Sundar Pichai said computing power remained a major constraint. According to him, it prevented even higher growth and nearly doubled Google's cloud backlog quarter on quarter to $460 billion.
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