美媒直言：中美AI竞争，美国已经输在了电力上！

Group 1 - The core argument of the articles highlights that the disparity in electricity supply is a critical factor determining the future competitiveness of AI technology, with the U.S. facing significant challenges due to its weak power grid [1] - AI models like GPT-3 consume substantial amounts of electricity, with a single training session equivalent to the annual electricity usage of 120 American households, and daily operations consuming 500,000 kWh, enough to power 20,000 households for a day [4] - High-end AI chips, such as NVIDIA's H100, have a significant energy footprint, with each chip consuming approximately the annual electricity of three households, and projected sales of 4-5 million units in 2024 could lead to an annual consumption equivalent to that of 12 million households [4] Group 2 - The U.S. power grid operates with only 15% reserve capacity, leading to shortages and outages, particularly in states like Texas and California, which hampers the ability of AI companies to secure sufficient energy for their data centers [5] - In contrast, China excels in energy production and transmission, with diverse sources including wind, hydro, nuclear, and solar power, and is currently constructing 42 nuclear power plants, with the Yalong River Hydropower Station expected to generate 300 billion kWh annually, three times that of the Three Gorges Dam [7] - China's unique ultra-high voltage transmission technology allows for significantly lower industrial electricity prices, with rates as low as 0.3 yuan per kWh compared to California's 1.2 yuan, providing a substantial competitive advantage in the AI technology race [7]