Us must prioritize natural gas to compete with china in ai race

In an opinion piece, Nathan Lord argues that America cannot lead in artificial intelligence without securing reliable energy sources, particularly natural gas. He highlights China's superior electricity generation and urges building data centers near fuel supplies in regions like the Shale Crescent. Without such measures, the US risks falling behind in the global AI competition.

Nathan Lord, president of the non-profit Shale Crescent USA, contends that the race for artificial intelligence dominance hinges not just on technological innovation but on energy infrastructure. Writing in The Daily Wire, Lord emphasizes that AI requires massive, continuous electricity, and nations providing power at scale, low cost, and high reliability will prevail in AI, manufacturing, and national security.

Lord points to China's advantage, noting that it generates more than twice the electricity of the United States and expands infrastructure faster than the US has in years. In contrast, US electricity demand is rising at a sustained rate for the first time in over 50 years. The Department of Energy projects a need for 50 to 150 gigawatts of new capacity in the next decade, likening it to the Manhattan Project.

Data centers, likened by Lord to 24/7 industrial factories, consume as much power as heavy facilities and demand uninterrupted baseload supply. He advocates prioritizing natural gas as the deployable, scalable, affordable fuel. More than 80% of US natural gas comes from the Gulf Coast and Shale Crescent—Ohio, West Virginia, and Pennsylvania—which together produce about one-third of the nation's gas and would rank as the world's third-largest producer if considered a single country.

Gas in the Shale Crescent is three to four times cheaper than in Europe or Asia. Lord warns that data centers face power shortages nationwide, with utilities imposing moratoria and queues extending a decade. He recommends siting new infrastructure atop fuel sources to cut costs, losses, and delays from long transmission lines.

"America cannot out-AI China if China out-powers the United States," Lord writes, calling natural gas a strategic asset requiring political will. The views are his own, not necessarily those of the publisher.

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Utah Gov. Spencer Cox advocating for states' control of AI regulation, linking it to energy demands and nuclear power expansion.
AI에 의해 생성된 이미지

Utah governor urges states to retain authority over AI regulation

AI에 의해 보고됨 AI에 의해 생성된 이미지 사실 확인됨

In a recent NPR video interview, Utah Governor Spencer Cox argued that states should keep primary authority to regulate artificial intelligence, warning against broad federal intervention. He also linked AI’s rapid growth to surging energy demands, backing expanded nuclear power and calling for a "human-flourishing" approach to technology.

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AI에 의해 보고됨

A new analysis warns that surging energy demands from data centers will significantly boost US power plant emissions over the next decade. However, shifting to renewables could reduce these emissions while stabilizing electricity prices. Simple policy measures might help address both environmental and economic concerns.

China's total electricity consumption reached a record 10.4 trillion kilowatt-hours in 2025, driven by AI services and electric vehicle charging, widening the energy gap with the US and other major economies. The National Energy Administration announced this on Saturday, marking the first time annual usage exceeded 10 trillion kWh in China's history. Growth was primarily fueled by the tertiary sector and residential demand.

AI에 의해 보고됨

Germany-based Siemens Energy has committed $1 billion to bolster America's power infrastructure, expanding manufacturing across multiple states. The move, announced on Tuesday, is expected to create 1,500 skilled jobs amid rising energy demands from artificial intelligence. Company leaders credit the Trump administration's policies for enabling this growth.

Researchers from Purdue University and the Georgia Institute of Technology have proposed a new computer architecture for AI models inspired by the human brain. This approach aims to address the energy-intensive 'memory wall' problem in current systems. The study, published in Frontiers in Science, highlights potential for more efficient AI in everyday devices.

AI에 의해 보고됨

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