Xi Niu Cai Jing·2025-11-07 08:21Core Insights - The token economy in both China and the U.S. is heavily reliant on electricity, with each country facing unique challenges in this regard [1][3] - The U.S. is experiencing a power shortage due to outdated generation and grid infrastructure, limiting token production [1][2] - In contrast, China faces high token production costs due to relatively low-efficiency hardware, impacting the overall cost of token generation [1][3] Group 1: U.S. Challenges - Microsoft CEO Satya Nadella emphasized that the real issue is not a shortage of GPUs but a lack of electricity, which restricts token production and monetization [1] - Major U.S. tech companies are in a race for AI infrastructure investment, which has turned into a competition for electricity supply [1][2] - The construction of large-scale data centers in the U.S. is progressing from 1GW to 10GW, with companies like Crusoe targeting significant capacity increases [1][2] Group 2: Infrastructure and Policy - Silicon Valley giants are urging the White House for support in developing infrastructure, particularly the power grid, to match the pace of AI innovation [3] - OpenAI has suggested that the U.S. needs to add 100GW of electricity capacity annually to compete effectively in AI against China [3] - The U.S. added 51GW of power capacity last year, while China added 429GW, highlighting a significant "power gap" [3] Group 3: China's Challenges - China's AI infrastructure is built on domestic chips, which currently have lower efficiency, leading to increased demand for computational power [3][4] - ByteDance's daily token calls have surged from 16.4 trillion in May to 30 trillion in September, indicating a rapid increase in computational needs [3] - The cost of electricity for a major cloud provider in China is estimated at 8-9 billion yuan for 1GW annually, reflecting the high operational costs associated with domestic chip usage [5] Group 4: Efficiency and Cost - The competition in the token economy involves not just hardware but also the software, tools, and the electricity and cooling systems required to operate them [4] - Huawei's CloudMatrix 384 has shown a significant increase in total computational power but at a much higher energy cost compared to NVIDIA's latest offerings [5][6] - The average industrial electricity cost in the U.S. is approximately 9.1 cents per kWh, while certain regions in China have reduced costs to below 4 cents per kWh, indicating a competitive advantage for Chinese data centers [6]