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Meta Invests $1.5B in Texas AI Data Center, Creating 100 Jobs

Key Takeaways

  • Meta is investing $1.5 billion in a new gigawatt-scale data center in El Paso, Texas.
  • The facility will create 100 operational jobs and employ over 1,800 construction workers at peak.
  • Meta has committed $72 billion in capital expenditures this year to accelerate its AI ambitions.

Meta is significantly expanding its AI infrastructure with a massive new data center in Texas. The company will invest over $1.5 billion to build a gigawatt-scale facility in El Paso, scheduled for completion by 2028.

This will be Meta’s 29th data center globally, designed to support both current servers and future AI hardware generations. The El Paso facility is expected to create approximately 100 permanent operational roles and employ more than 1,800 construction workers during peak building phases.

Sustainability and Local Impact

The new data center will operate entirely on renewable energy and has committed to restoring 200% of its water consumption to local watersheds. Meta selected El Paso due to its robust infrastructure and skilled workforce.

This investment adds to Meta’s substantial Texas footprint, where the company has already invested over $10 billion across three data centers and employs more than 2,500 full-time staff across its facilities, offices, and research labs.

Meta’s Aggressive AI Investment Strategy

Meta is competing intensely in the AI race against rivals like OpenAI, Google, and Anthropic. The company established a Superintelligence Lab earlier this year and appointed former Scale AI CEO Alexandr Wang to lead it, while recruiting top talent from across the industry.

CEO Mark Zuckerberg has emphasized that overspending on AI is preferable to underspending, stating that the risk of missing superintelligence emergence outweighs financial waste concerns. The company has allocated $72 billion for capital expenditures this year alone.

Superintelligence, or Artificial General Intelligence (AGI), represents a hypothetical stage where AI systems could perform most tasks at human proficiency levels or better. While precisely defined, major AI labs are heavily investing in infrastructure to achieve this goal.

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