On October 26, the “Report on Mineral Resources Investment in the New Era of AI” was released in Guangzhou. The report suggests that as the AI industry moves towards large-scale application, the importance of energy supply, computing power infrastructure, and upstream mineral resources is becoming more and more prominent. The report systematically studies the relationship between the AI industry and mineral resources at five levels: energy layer, chip layer, infrastructure layer, model layer, and application layer. According to the statistical caliber of classifying rare earths as a mineral type, the report sorts out 46 major mineral resources involved in the AI industry chain, including 5 types of energy minerals, 32 types of metal minerals, 8 types of non-metallic minerals, and 1 type of hydrogas mineral. These minerals include coal, petroleum, natural gas, copper, iron, aluminum, nickel, cobalt, lithium, niobium, tantalum, gallium, germanium, high-purity quartz, rare earth and helium, etc., and are used in energy supply, semiconductor manufacturing, computing power equipment, data centers and related terminal products.

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