人工智能投资减少了对关键矿物供应的风险
Joaquin Vespignani1,2, Russell Smyth3
1Tasmanian School of Business and Economics, University of Tasmania, Sandy Bay, TAS, Australia. Joaquin.Vespignani@utas.edu.au.
Nature communications
|August 24, 2024
概括
关键矿产项目面临"背后风险溢价",增加资本成本并可能阻碍投资. 人工智能 (AI) 可以减轻这种风险,支持能源转型.
科学领域:
- 地球科学 地球科学
- 经济学 经济学 经济学
- 金融风险分析 金融风险分析
背景情况:
- 对于能源转型至关重要的重要矿产项目,面临着巨大的财务风险.
- 项目中未解决的技术和非技术障碍 (例如,) 创造了独特的投资挑战.
研究的目的:
- 提出关键矿物质的经济理论,结合地球科学对项目开发风险的见解.
- 引入和定义"世界"的概念.
- 背后的风险溢价是背后的风险溢价.
- 对于关键矿产项目而言.
- 分析这种溢价对投资的影响以及人工智能 (AI) 的潜在作用.
主要方法:
- 经济理论的发展.
- 在项目开发中分析财务风险.
- 评估技术和非技术障碍对投资的影响.
主要成果:
- 提出了关键矿物质的新经济理论.
- "后期风险溢价"被认为是提高关键矿产项目的资本成本的关键因素.
- 这种溢价可能会减少人工智能在采矿中的投资和生产率增长.
结论:
- 政府对人工智能采矿技术和研究的投资至关重要.
- 人工智能进步可能通过缩短项目持续时间和降低投资风险来降低"后期风险溢价".
- 对人工智能的战略投资对于降低能源转型成本至关重要.
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