Tech Giants Build Natural Gas Plants to Power AI Data Centers
Microsoft, Google, and Meta are building large natural gas power plants to meet the growing energy demands of their AI data centers. The projects are concentrated in the southern United States, where natural gas reserves are abundant.
Microsoft is collaborating with Chevron and Engine No. 1 on a power plant in West Texas that could generate up to 5 gigawatts of electricity. Google is working with Crusoe to construct a 933-megawatt plant in North Texas. Meta is expanding its Hyperion data center in Louisiana with seven new natural gas plants, raising the facility’s total capacity to 7.46 gigawatts.
The surge in demand for natural gas infrastructure has created shortages of turbines, with prices expected to rise nearly 200% compared to 2019 levels. Delivery times for new turbines have extended to six years, and new orders are not expected to be fulfilled until 2028.
Analysts note that while natural gas remains plentiful, production growth in key U.S. shale regions has slowed. As tech firms move to secure direct fuel supplies and build behind-the-meter plants, concerns are emerging about potential impacts on fuel availability and electricity prices for other sectors and consumers.
The trend highlights the scale of the energy challenge associated with AI infrastructure expansion, as companies seek reliable power sources for increasingly energy-intensive data operations.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Silicon Brief or Daily AI Brief.
Also, consider following us on social media:
More from Data Centers
Oct 17 BlackRock CEO Warns Data Center Construction Pause Could Trigger US Recession Oct 17 NVIDIA RTX Spark Laptops Go on Sale From $2,599 Oct 17 ADIPEC 2026 Receives More Than 1,200 AI and Digital Submissions Oct 16 EverWind Plans 420 Megawatt AI Data Centre in Nova Scotia Oct 16 Gartner Says $3.5 Trillion in AI Infrastructure Spending Faces Impairment Risk by 2030Silicon Brief
Weekly coverage of AI hardware developments including chips, GPUs, cloud platforms, and data center technology.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
Schneider Electric Says AI Can Cut Building Energy Use by Up to 22%
Data Center Infrastructure Market Reaches $14 Billion as AI Demand Grows
Rising rates strain AI data center fundraising
DIGITIMES Examines 800 VDC Power for AI Data Centers
Utility Survey Finds 78% Deploying AI for Interconnection Demand
Daily AI Brief: the AI news that matters, in your inbox.