AI军备竞赛的终点，或是一场关于铀的“全球狩猎”

Group 1 - The article discusses the clash between the rapidly evolving world of artificial intelligence (AI) and the slow-moving, capital-intensive nuclear energy sector, highlighting a structural shift in energy demand driven by AI [1] - A survey of over 600 global investors reveals that 63% view the power demand from AI as a significant change in nuclear energy planning, indicating that this is not a temporary spike but a lasting trend [1] - The traditional narrative around energy efficiency is failing, as advancements in chip efficiency lead to increased resource consumption, exemplified by the Jevons Paradox [2] Group 2 - The uranium market is experiencing a "dual-speed" dynamic, with short-term price volatility contrasting with a long-term supply gap, as current uranium mining can only meet less than 75% of future reactor demands [3] - Over 85% of surveyed investors expect uranium prices to reach between $100 and $120 per pound by 2026, with some predicting a rise to $135 per pound, which reflects a desperate incentive price rather than a healthy market signal [4] - The shift towards private ownership of nuclear energy infrastructure is occurring, as large-scale AI companies secure long-term power purchase agreements, raising questions about who will bear the costs of necessary grid upgrades [6] Group 3 - The geopolitical landscape surrounding uranium supply is critical, with Western nations attempting to rebuild their uranium supply chains while facing significant bottlenecks tied to Russian interests [7] - Emerging markets like China, South Korea, and the UAE are proactively investing in nuclear energy, recognizing its importance for national survival, with China currently constructing more reactors than the rest of the world combined [7] - The article suggests that limited uranium supply could lead to higher prices and a global political scramble for purchase agreements, indicating that control over uranium is essential for maintaining a competitive edge in AI [7]