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Hundreds of Billions: Meta Builds Huge Data Centers for AI

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by Giorgi Kostiuk

3 hours ago


Meta has announced ambitious plans to invest in data centers for the development of superintelligence, highlighting its ambitions in artificial intelligence.

Meta's Plans for Data Centers

CEO Mark Zuckerberg stated that the company plans to invest hundreds of billions of dollars in building large data centers for artificial intelligence. The first center, named Prometheus, is set to be operational in 2026. A second site, called Hyperion, is expected to scale up to around five gigawatts of power over the coming years. Zuckerberg emphasized, 'We are building multiple more titan clusters. Just one of these covers a significant part of the footprint of Manhattan', underlining the scale of the projects.

Strategy and Financial Stability

To quell investor fears about such immense spending, Zuckerberg highlighted Meta's strong advertising revenue sufficient to fund these projects. 'We have the capital from our business to do this,' he stated. Last year, the company generated nearly $165 billion, giving it substantial reserves for its AI ambitions. In April, Meta raised its projected capital expenditure for 2025 to between $64 billion and $72 billion, signaling its commitment to outpace rivals like OpenAI and Google.

Reorganization and Staffing Changes

In response to some setbacks with its open-source Llama 4 model and the departure of key personnel, Meta recently reorganized its AI efforts under a new division called Superintelligence Labs. The unit will be led by former Scale AI CEO Alexandr Wang and ex-GitHub chief Nat Friedman. Beyond raw computing power, Meta is also banking on new revenue streams from its Meta AI app and advertising tools. Analysts note that while AI has already boosted Meta's ad sales, this scale of investment is aimed at securing the company's lead in developing the foremost AI model.

Meta's series of investments in massive data centers underscores its commitment to leading the race in artificial intelligence. The attention will be on whether these efforts reshape the landscape of machine learning and play a crucial role in the tech race.

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