Google has limited Meta's access to its Gemini AI models because of capacity constraints, according to the Financial Times. This constraint is affecting Meta's internal projects and forcing the company to rely more heavily on its own AI systems. The situation underscores how control over data centers and computing capacity is becoming a key lever of power in the AI industry.
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Alphabet has limited Meta's access to Gemini AI models due to capacity constraints, disrupting some of Meta's internal projects. Meta had been using Gemini for content moderation and scam detection, but is now relying more on its own Muse Spark model to reduce dependence on outside AI providers.
Why it matters
The restriction signals that even the largest technology companies are feeling the squeeze of AI infrastructure demand. Control over data centers, chips, and cloud capacity is becoming a source of competitive leverage in the AI supply chain.
What to watch
The move reflects a broader AI infrastructure crunch that may reshape how large companies source and build their own AI capabilities rather than relying on third-party models.
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