Competition among major tech companies in the world of Artificial Intelligence (AI) is intensifying. Amidst this, a new report claims that Google refused to provide Meta with the full amount of computing power it requested for using its Gemini AI models. Reportedly, this has slowed down some of Meta's AI projects.

According to a *Financial Times* report, Google informed Meta around March that it could not provide the full computing capacity requested for the Gemini AI models. The report states that this shortfall impacted some of Meta's internal AI projects, causing delays.

It is reported that this limitation remains in effect. Consequently, Meta has advised its employees to use AI tokens more efficiently. AI tokens serve as a unit for measuring AI model usage, allowing for better control over AI-related costs.

**Rising AI Demand Poses a Major Challenge**
The report indicates that it is not just Meta; other Google clients are also facing a shortage of computing capacity. However, Meta has been hit harder due to the sheer scale of its demand.

This situation highlights that global computing resources are falling short of the surging demand for AI models. Major tech companies are investing billions of dollars in chips, data centers, and power infrastructure, yet capacity constraints persist.

**No Response from Google or Meta**
Meta has been actively expanding its AI business. According to the report, the company explored using Google's Gemini models following delays in its own next-generation 'Avocado' AI model.
However, neither Google nor Meta has issued an official statement regarding this matter so far. While this information is based on reports, it clearly suggests that the biggest challenge in the AI ​​race is no longer just building superior models, but also ensuring adequate infrastructure to run them.

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