中英双语|吕国博士深度解读AI找矿技术对资源评估与规划的革新优势
北京阳光创译语言翻译有限公司是一家在翻译领域实力出众的专业机构，同时也是具备矿业领域实战经验的咨询服务商。我们的专业团队深谙矿产资源勘探、资源评估、采矿工艺等全流程环节，在与客户的合作中，始终致力于为客户提供全方位矿业咨询服务，助力客户在矿业项目的策划、管理与优化中实现更高价值与更优成效。作为矿业咨询领域的领军力量，我们的团队由深耕行业多年的专业人士构成，兼具深厚的矿业实战经验与敏锐的行业洞察力。Beijing Suntrans Language Translation Co.,Ltd. is a professional institution that excels in translation services, as well as a consulting service provider with practical experience in the mining sector. Our professional team is familiar with various aspects of mineral resource exploration, resource assessment, and mining processes. In our partnerships with clients, we remain dedicated to delivering comprehensive mining consulting services, empowering them to realize higher value and better outcomes in the planning, management, and optimization of mining projects. As a leading force in the mining consulting field, our team comprises seasoned professionals with years of deep engagement in the industry, who possess both profound practical mining experience and sharp industry insights.
我们的董事长吕国博士，是地质矿业领域的资深专家，深耕行业多年，兼具扎实的矿业专业知识与深厚的实践经验。他在中国地质大学（北京）获得矿物学、岩石学、矿床学博士学位，后以博士公派身份赴美国迈阿密大学深造，学成归国后又于北京大学开展地质学领域博士后研究工作。吕国博士曾任职于全球最大矿业公司之一的必和必拓（BHP Billiton），以及中国地质调查局境外矿产战略研究室，在实战中积累了极为丰富的行业经验。
Dr. Lyu Guo, our chairman, is a seasoned expert in the field of geological mining. With years of dedicated engagement in the industry, he possesses solid professional knowledge and profound practical experience in mining. He earned his Doctor’s degree in Mineralogy, Petrology, and Ore Deposit Geology from China University of Geosciences (Beijing), then pursued advanced studies as a government-sponsored doctoral scholar at Miami University (USA). After returning to China, he subsequently conducted postdoctoral research in geology at Peking University. Dr. Lyu once held positions at BHP Billiton (one of the world’s largest mining companies) and the Overseas Mineral Strategy Research Office of the China Geological Survey, accumulating extremely extensive industry experience through practical work.
AI 找矿技术的重要研究成果
Important Research Achievements of AI Prospecting Technology
近年来，AI找矿技术如同一颗耀眼的新星，在矿业领域取得了突破性的进展。2024年，KoBold Metals公司运用 AI 技术在赞比亚Mingomba 项目中取得了惊人的发现——高品位世界级铜矿，其铜矿品位超5%，且预计10年内即可投产。该公司通过巧妙整合地质卫星图片、激光雷达扫描及地震波等多源异构数据，成功创建了高效的矿藏分布预测模型，这一创新举措极大地提升了找矿效率，为全球矿业勘探树立了新的标杆。
In recent years, AI prospecting technology has emerged as a dazzling new star and made breakthrough progress in the mining industry. In 2024, KoBold Metals used AI technology to make an amazing discovery in the Mingomba project in Zambia—a high-grade world-class copper deposit with a copper grade exceeding 5%, and it is expected to be put into production within 10 years. By deeply integrating multi-source heterogeneous data such as geological satellite remote sensing imagery, LiDAR scanning data, and seismic wave information, the company successfully created an efficient mineral deposit distribution prediction model. This innovative measure has greatly improved prospecting efficiency and set a new benchmark for global mining exploration.
2023年，美国卡内基科学院和印度理工学院孟买分校团队强强联合，利用包含29.6万个矿物地点和 5478 种矿物种类的庞大数据库，建立了先进的AI模型。借助这一模型，他们成功在莫哈韦沙漠特科帕盆地预测出铀矿和稀土元素位置，为稀土矿勘探开辟了全新的路径。
In 2023, a joint team from the Carnegie Institution for Science (USA) and the Indian Institute of Technology Bombay (India) joined forces to establish an advanced AI model using a large database containing 296,000 mineral locations and 5,478 mineral species. With the help of this model, they successfully predicted the locations of uranium deposits and rare earth elements in the Tecoma Basin of the Mojave Desert, opening up a new path for rare earth mineral exploration.
《全球矿业发展报告2024》明确指出，AI技术正引领着矿产勘查向高效、智能、高精度和低碳化的方向转变。如今，全球近百家AI找矿初创企业如雨后春笋般兴起，AI技术的数据处理优势使得找矿效率相较于传统方法提高了约10倍，彻底改变了矿业勘探的格局。
The Global Mining Development Report 2024 clearly points out that AI technology is leading the transformation of mineral exploration towards efficiency, intelligence, high precision, and low carbon. Today, nearly 100 AI prospecting startups around the world have sprung up like mushrooms. The data processing advantage of AI technology has increased prospecting efficiency by approximately 10 times compared with traditional methods, completely changing the pattern of mining exploration.
阳光创译吕国博士在《2024（第四届）矿业投融资大会》的圆桌对话环节中与大冶有色金属集团控股有限公司张金钟总助、澳大利亚励万律师事务所孙颖律师、印度尼西亚鑫兴大型有限责任公司张晓旺董事长、地心互动联合创始人/CEO 中国矿业联合会张鑫伟理事、北京固废通固废资源化利用有限公司杜根杰总经理进行交谈
吕国博士在解读这些成果时，凭借其对行业的深入理解和敏锐洞察，详细分析了背后的技术原理和发展趋势，为在场嘉宾提供了专业且独到的见解。
When interpreting these achievements, Dr. Lyu Guo, relying on his in-depth understanding and keen insight into the industry, analyzed the underlying technical principles and development trends in detail, providing professional and unique insights for the on-site guests.
阳光创译吕国博士在《2024（第四届）矿业投融资大会》的圆桌对话环节中与大冶有色金属集团控股有限公司张金钟总助、澳大利亚励万律师事务所孙颖律师、印度尼西亚鑫兴大型有限责任公司张晓旺董事长、地心互动联合创始人/CEO 中国矿业联合会张鑫伟理事以及北京固废通固废资源化利用有限公司杜根杰总经理进行交谈。
Dr. Lyu Guo from Suntrans had a conversation with Zhang Jinzhong (Assistant General Manager of Daye Non-Ferrous Metals Group Holdings Co., Ltd.), Sun Ying (Lawyer of Australia Liwan Law Firm), Zhang Xiaowang (Chairman of Indonesia Xinxing Large-Scale Co., Ltd.), Zhang Xinwei (Co-founder/CEO of Dixin Interaction and Director of China Mining Association), and Du Genjie (General Manager of Beijing Solid Waste Tong Solid Waste Resource Utilization Co., Ltd.) in the roundtable dialogue session of the “2024 (4th) Mining Investment and Financing Conference” to discuss.
AI找矿技术相较于传统找矿技术在资源评估与规划方面的显著优势
The Significant Advantages of AI Prospecting Technology over Traditional Prospecting Technology in Resource Assessment and Planning
吕国博士在大会上进一步深入剖析了AI找矿技术相较于传统找矿技术在资源评估与规划方面的显著优势。
At the conference, Dr. Lyu Guo further analyzed in depth the significant advantages of AI prospecting technology over traditional prospecting technology in resource assessment and planning.
数据处理与分析能力
Data Processing and Analysis Capability
AI 具备强大的数据处理与分析能力，能够迅速整合海量的多源异构数据，涵盖地质调查、卫星影像、地球物理和地球化学等各个方面的数据。与传统技术在处理大规模数据时效率低下且难以综合分析的困境相比，AI 能够挖掘数据中的非线性关系和隐藏信息，精准地识别潜在矿化异常区域。而传统技术主要依赖人工经验和简单统计方法，很容易遗漏复杂数据之间的内在联系。
AI has strong data processing and analysis capabilities, and can quickly integrate massive multi-source heterogeneous data, covering data in various aspects such as geological surveys, satellite images, geophysics, and geochemistry. Compared with the dilemma of traditional technologies, which are inefficient and difficult to conduct comprehensive analysis when processing large-scale data, AI can mine non-linear relationships and hidden information in data, and accurately identify potential mineralization anomaly areas. However, traditional technologies mainly rely on manual experience and simple statistical methods, which easily miss the internal connections between complex data.
资源评估准确性与效率
Accuracy and Efficiency of Resource Assessment
借助先进的地质模型和算法，AI能够精确估算矿产储量和品位。以 KoBold Metals公司为例，其利用AI技术精确计算矿脉储量，这一成果是传统方法难以企及的。同时，AI凭借其快速的数据处理能力，能够在短时间内完成大面积的资源评估工作，准确确定资源的潜在价值和开发可行性，有效缩短项目周期。相比之下，传统技术的评估效率则显得相对较低。
With the help of advanced geological models and algorithms, AI can accurately estimate mineral reserves and grades. Taking KoBold Metals as an example, it uses AI technology to accurately calculate vein reserves, an achievement that is difficult for traditional methods to match. At the same time, relying on its fast data processing capability, AI can complete large-area resource assessment work in a short time, accurately determine the potential value and development feasibility of resources, and effectively shorten the project cycle. In contrast, the assessment efficiency of traditional technologies is relatively low.
规划科学性
Scientific Nature of Planning
AI通过深入分析历史和地质数据，能够精准预测开采过程中可能面临的风险，为矿山规划提供科学、可靠的依据。而传统技术在风险预测方面能力有限，难以做到如此精准的分析。此外，AI还能够根据资源分布与开采条件，对开采方案进行优化，从而提高资源回收率和开采效率，降低开采成本。传统的开采方案在精准度和优化程度上则明显不足。
By in-depth analyzing historical and geological data, AI can accurately predict the risks that may be encountered in the mining process, providing a scientific and reliable basis for mine planning. However, traditional technologies have limited capabilities in risk prediction and are difficult to achieve such accurate analysis. In addition, AI can optimize mining plans according to resource distribution and mining conditions, thereby improving resource recovery rate and mining efficiency, and reducing mining costs. Traditional mining plans are obviously insufficient in terms of accuracy and optimization.
可视化与交互性Visualization and Interactivity
AI以三维可视化模型的形式展示评估规划结果，能够直观、清晰地呈现地质和矿体信息，为决策者提供有力的辅助。与之相比，传统技术多以二维图纸和报告的形式展示，效果远不如AI技术直观。而且，AI支持实时交互功能，能够依据新的数据即时调整规划，具有很强的灵活性。而传统技术在修改规划时往往耗时费力，难以满足实际需求。
AI displays assessment and planning results in the form of 3D visualization models, which can present geological and ore body information intuitively and clearly, providing strong support for decision-makers. In contrast, traditional technologies mostly display information in the form of 2D drawings and reports, whose effect is far less intuitive than that of AI technology. Moreover, AI supports real-time interactive functions and can adjust plans in real time based on new data, featuring strong flexibility. However, traditional technologies are often time-consuming and labor-intensive when modifying plans, making it difficult to meet actual needs.
吕国博士通过详实的案例和数据对比，深入浅出地阐述了这些优势，让与会者对AI 找矿技术有了更为清晰和深刻的认识。
Through detailed cases and data comparisons, Dr. Lyu Guo explained these advantages in a simple and in-depth manner, enabling the participants to have a clearer and deeper understanding of AI prospecting technology.
AI 找矿技术的应用案例与创新应用领域
Application Cases and Innovative Application Fields of AI Prospecting Technology
资源评估与规划应用案例：在资源评估与规划方面，AI找矿技术已经有了诸多成功的应用案例。KoBold Metals在赞比亚铜矿勘探中，充分利用AI技术分析多源数据，创建了精准的模型，不仅精确计算了储量、评估了资源，还成功签订了开采合同并规划了产量。美印合作项目借助矿物演化数据库建立 AI模型，在莫哈韦沙漠成功预测潜在矿产位置，为资源评估规划提供了全新的方法。华为为Codelco提供的解决方案，融合AI与行业数据，有力地推动了矿山数字化转型，实现了科学的资源评估与开采规划。
Resource Assessment and Planning Application Cases: In terms of resource assessment and planning, AI prospecting technology has many successful application cases. In copper ore exploration in Zambia, KoBold Metals made full use of AI technology to analyze multi-source data and create an accurate model. It not only accurately calculated reserves and assessed resources, but also successfully signed mining contracts and planned production volume. The US-India cooperative project established an AI model with the help of a mineral evolution database, successfully predicting the locations of potential minerals in the Mojave Desert and providing a new method for resource assessment and planning. The solution provided by Huawei for Codelco integrates AI and industry data, which has strongly promoted the digital transformation of mines and realized scientific resource assessment and mining planning.
矿业创新应用：在矿业创新应用领域，AI 找矿技术同样展现出了巨大的潜力。在找矿勘查方面，AI 能够高效处理地质数据，挖掘其中的关键信息，如 KoBold Metals 公司的找矿效率因此大幅提升。通过解析数据建立可视化地质矿山模型，为地质人员的决策提供了有力支持。在采矿过程中，AI 实现了对设备的智能化控制，例如 AI 配煤技术的应用，不仅降低了成本，还优化了生产管理，有效提升了生产效率和资源利用率。
Innovative Mining Applications: In the field of innovative mining applications, AI prospecting technology also shows great potential. In prospecting and exploration, AI can efficiently process geological data and mine key information from it—for example, KoBold Metals has significantly improved its prospecting efficiency. By analyzing data to establish a visual geological mine model, it provides strong support for geologists' decision-making. In the mining process, AI has realized intelligent control of equipment; for instance, the application of AI coal blending technology not only reduces costs, but also optimizes production management, effectively improving production efficiency and resource utilization.
此外，AI 技术结合遥感和物联网，能够实时监测地质环境，及时预警灾害，为矿山安全提供了可靠保障。通过综合多维度数据，AI 能够科学评估矿产资源，助力企业合理规划开发，提高经济效益。同时，AI 技术还有助于开发低品位难选冶矿产，降低对环境的影响，推动矿业可持续发展。在全球矿业治理方面，AI 技术率先整合地质数据和成矿模型，提升了全球矿业治理的话语权。
In addition, AI technology combined with remote sensing and the Internet of Things (IoT) can monitor the geological environment in real time and provide timely disaster early warnings, offering reliable guarantees for mine safety. By integrating multi-dimensional data, AI can scientifically assess mineral resources, help enterprises reasonably plan development, and improve economic benefits. At the same time, AI technology also helps develop low-grade and refractory minerals, reduces environmental impact, and promotes the sustainable development of the mining industry. In terms of global mining governance, AI technology takes the lead in integrating geological data and mineralization models, enhancing the right to speak in global mining governance.
吕国博士对这些应用案例和创新领域进行了详细解读，分享了自己在实践中的经验和见解，让与会者深刻感受到AI找矿技术在矿业领域的广泛应用和巨大潜力。
Dr. Lyu Guo gave a detailed interpretation of these application cases and innovative fields, shared his practical experience and insights, and made the participants deeply feel the wide application and great potential of AI prospecting technology in the mining industry.
降低成本的应用案例与技术优势体现
Application Cases of Cost Reduction and Reflection of Technical Advantages
AI 找矿技术在降低成本方面也有着显著的成效。Earth AI公司助力传奇矿产公司在澳大利亚找矿，仅投资50万澳元就获得了重大发现，而传统方法则需要耗费1亿澳元，成本差距一目了然。盘古矿山大模型在山东能源的应用，不仅缩短了软件开发周期，降低了研发成本，其 AI 配煤技术还节省了大量煤炭成本。Kobold公司在赞比亚铜矿的发现成本仅为传统方法的四分之一，并且能够快速收回研发成本。美印合作找稀土矿项目也节省了大量的人力、物力和时间成本。
AI prospecting technology also has significant effects in reducing costs. Earth AI helped Legendary Minerals make a major discovery in Australia with an investment of only 500,000 Australian dollars, while traditional methods would cost 100 million Australian dollars—the cost gap is obvious. The application of the Pangu Mine Large Model in Shandong Energy not only shortened the software development cycle and reduced R&D costs, but also saved a lot of coal costs through its AI coal blending technology. The discovery cost of Kobold’s copper mine in Zambia was only a quarter of that of traditional methods, and it could quickly recover R&D costs. The US-India cooperative project for rare earth mineral prospecting also saved a lot of labor, material, and time costs.
AI之所以能够实现如此显著的成本降低，得益于其高效的计算和信息处理能力。它可以自动进行数据处理和建模，实现设备的智能化控制，从而减少人力和时间成本，提高生产效率和资源利用率。此外，AI 在找矿范围上不受地理和勘探手段的限制，能够分析全球地质数据，大大增加了发现新矿种和矿床的机会。同时，AI还能整合专家知识经验，建立更可靠的找矿模型。
The reason why AI can achieve such a significant cost reduction lies in its efficient computing and information processing capabilities. It can automatically perform data processing and modeling, and realize intelligent control of equipment, thereby reducing labor and time costs and improving production efficiency and resource utilization. In addition, AI is not limited by geography and exploration methods in terms of prospecting scope, and can analyze global geological data, greatly increasing the chances of discovering new mineral species and deposits. At the same time, AI can also integrate expert knowledge and experience to establish a more reliable prospecting model.
吕国博士对这些降低成本的应用案例进行了深入剖析，详细阐述了AI 技术优势在其中的具体体现，为矿业企业在成本控制方面提供了新的思路和方法。
Dr. Lyu Guo conducted an in-depth analysis of these cost-reduction application cases, elaborated on the specific reflection of AI technical advantages in them, and provided new ideas and methods for mining enterprises in cost control.
阳光创译吕国博士在《2024（第四届）矿业投融资大会》的投资人与矿权人项目面对面对接会中担任主持人
Dr. Lyu Guo from Suntrans served as the host in the Investor-Mining Right Holder Project Face-to-Face Matching Meeting of the 2024 (4th) Mining Investment and Financing Conference
紫金矿业及相关软件的情况
紫金矿业的AI找矿应用与研究进展
Application and Research Progress of AI Prospecting in Zijin Mining
虽然公开资料尚未明确紫金矿业AI找矿技术的具体应用地区，但从一些相关信息可以看出其在该领域的积极探索。塞尔维亚的相关技术应用为紫金矿业提供了重要的数据支持，国内及海外部分地区的AI罐笼识别服务项目也在稳步推进。
Although public information has not yet clearly specified the specific application areas of Zijin Mining's AI prospecting technology, some relevant information shows its active exploration in this field. The relevant technical applications in Serbia have provided important data support for Zijin Mining, and the AI cage recognition service projects in some domestic and overseas regions are also advancing steadily.
2024年，紫金矿业在AI找矿领域动作频频。5月，与华为签署战略合作协议，共同开发人工智能解决方案；11月，与成都理工大学进行交流合作；旗下威海晶合公司积极开展应用实践探索。6月，旗下铜矿资源储量增长，尽管目前尚不确定是否完全归因于 AI 技术，但新技术的应用无疑可能发挥了重要作用。此外，紫金矿业组建了科技公司，储备了340多名专业人才，为 AI 找矿技术的深入研究和应用提供了坚实的保障。
In 2024, Zijin Mining took frequent actions in the field of AI prospecting. In May, it signed a strategic cooperation agreement with Huawei to jointly develop artificial intelligence solutions; in November, it conducted exchanges and cooperation with Chengdu University of Technology; its subsidiary Weihai Jinghe Company actively carried out application practice and exploration. In June, the reserves of its copper ore resources increased—although it is not yet certain whether this is completely attributed to AI technology, the application of new technology has undoubtedly played an important role. In addition, Zijin Mining has established a technology company and reserved more than 340 professional talents, providing a solid guarantee for the in-depth research and application of AI prospecting technology.
吕国博士对紫金矿业在AI找矿领域的布局和进展进行了专业解读，分析了其潜在的发展趋势和对行业的影响。
Dr. Lyu Guo gave a professional interpretation of Zijin Mining’s layout and progress in the field of AI prospecting, and analyzed its potential development trends and impact on the industry.
探矿者软件（MRAS3.0）的相关信息
Relevant Information about Prospector Software (MRAS3.0)
探矿者软件（MRAS3.0）由中国地质科学院资源所研发，是一款在地质找矿领域具有重要影响力的专业软件。该软件的安装需要专业知识和合法授权，操作相对复杂，对使用者的专业素养要求较高。
Prospector Software (MRAS3.0) is developed by the Institute of Mineral Resources, Chinese Academy of Geological Sciences, and is a professional software with important influence in the field of geological prospecting. The installation of this software requires professional knowledge and legal authorization; its operation is relatively complex, and it has high requirements for the professional quality of users.
在实际应用中，探矿者软件（MRAS3.0）展现出了强大的功能。在河南地质找矿和昆明自然资源调查中心等项目中，它涵盖了空间数据管理、地质勘查制图、三维地质建模、资源量估算和大数据立体预测等多个功能模块，为地质工作提供了有力的技术支持。
In practical application, Prospector Software (MRAS3.0) has shown powerful functions. In projects such as geological prospecting in Henan and the Kunming Natural Resources Survey Center, it covers multiple functional modules including spatial data management, geological exploration mapping, 3D geological modeling, resource estimation, and big data three-dimensional prediction, providing strong technical support for geological work.
吕国博士对探矿者软件（MRAS3.0）的特点和应用进行了详细介绍，使与会者对这款专业软件有了更全面的了解。
Dr. Lyu Guo provided a detailed overview of the features and applications of Prospector Software (MRAS3.0), helping the attendees gain a more comprehensive understanding of this professional software.
中国在AI找矿领域的整体进展与杰出团队
China’s Overall Progress and Outstanding Teams in the Field of AI Prospecting
中国在AI找矿领域取得了令人瞩目的进展。中国地质科学院矿产资源研究所肖克炎团队总结的矿产预测 5 大基本理论，为 AI 找矿技术提供了坚实的理论支撑，有力地推动了技术攻关。
China has made remarkable progress in the field of AI prospecting. The five basic theories of mineral prediction summarized by the Xiao Keyan Team from the Institute of Mineral Resources, Chinese Academy of Geological Sciences have provided solid theoretical support for AI prospecting technology and strongly promoted technological breakthroughs.
在技术应用方面，AI算法能够高效处理地质数据，实现对稀土矿床的精准定位以及矿物分选等功能。研发的探矿者软件（MRAS3.0），实现了地质勘探数据的管理和可视化表达等功能，为地质工作者提供了便捷的工具。2024年11月，全国首个AI地矿研究院的成立，标志着中国在AI找矿领域的研究进入了一个新的阶段。同时，国家出台的一系列政策，也为智能矿山建设和AI模型优化提供了有力的支持。
In terms of technical application, AI algorithms can efficiently process geological data and realize functions such as accurate positioning of rare earth deposits and mineral separation. The developed Prospector Software (MRAS3.0) has realized functions such as the management and visual expression of geological exploration data, providing a convenient tool for geologists. In November 2024, the establishment of China’s first AI Geology and Mining Research Institute marked that China’s research in the field of AI prospecting has entered a new stage. At the same time, a series of policies issued by the state have also provided strong support for the construction of smart mines and the optimization of AI models.
杰出团队介绍
Introduction to Outstanding Teams
中国在AI找矿领域涌现出了许多杰出的团队。中国地质科学院矿产资源研究所肖克炎团队在软件研发和找矿实践方面成果显著，为行业发展做出了重要贡献。武汉地质实验室团队凭借其精湛的技术，精准定位稀土矿床，展现了强大的科研实力。中国地质调查局大数据团队在西秦岭研究金矿取得了重要成果，为金矿勘探提供了新的思路和方法。中国矿业大学团队创新煤炭分选技术，提升了煤炭资源的利用效率。辽宁工程技术大学团队优化岩性识别技术，有效降低了成本。
Many outstanding teams have emerged in China in the field of AI prospecting. The Xiao Keyan Team from the Institute of Mineral Resources, Chinese Academy of Geological Sciences has achieved remarkable results in software R&D and prospecting practice, making important contributions to the development of the industry. The Wuhan Geological Laboratory Team has accurately positioned rare earth deposits with its exquisite technology, demonstrating strong scientific research capabilities. The Big Data Team of China Geological Survey has achieved important results in gold deposit research in the West Qinling Mountains, providing new ideas and methods for gold deposit exploration. The China University of Mining and Technology Team has innovated coal separation technology, improving the utilization efficiency of coal resources. The Liaoning Technical University Team has optimized lithology identification technology, effectively reducing costs.
此外，美国KoBold Metals 团队在全球矿业领域也有着重要影响力，他们发现巨型铜矿并积极拓展全球项目，为 AI 找矿技术的推广和应用起到了示范作用。
In addition, the KoBold Metals Team (USA) also has an important influence in the global mining field. They have discovered giant copper deposits and actively expanded global projects, playing a demonstration role in the promotion and application of AI prospecting technology.
这些团队在不同方面共同推动了AI找矿技术的发展，在全球矿业领域发挥着重要作用。未来，他们有望持续取得新突破，进一步提升矿产勘探与开发的效率和效益，促进矿业的可持续发展。
These teams have jointly promoted the development of AI prospecting technology in different aspects and played an important role in the global mining field. In the future, they are expected to continue to make new breakthroughs, further improve the efficiency and benefits of mineral exploration and development, and promote the sustainable development of the mining industry.
吕国博士对中国在AI 找矿领域的整体进展和杰出团队进行了全面的梳理和介绍，强调了中国在该领域的重要地位和贡献，激发了与会者对中国矿业科技创新的信心和期待。
Dr. Lyu Guo comprehensively sorted out and introduced China’s overall progress and outstanding teams in the field of AI prospecting, emphasized China's important position and contributions in this field, and inspired the participants' confidence and expectations for China’s mining science and technology innovation.
在本次大会的投资人与矿权人项目面对面对接会中，吕国博士担任主持人，凭借其丰富的行业经验和专业素养，为项目对接提供了有力的支持和引导，促进了矿业领域的投资与合作。
In the Investor-Mining Right Holder Project Face-to-Face Matching Meeting of this conference, Dr. Lyu Guo served as the host. Relying on his rich industry experience and professional quality, he provided strong support and guidance for project matching, and promoted investment and cooperation in the mining field.
总之，在本次《2024（第四届）矿业投融资大会》上，吕国博士对AI找矿技术的深入解读和专业分享，为矿业企业指明了方向。矿业企业若能紧跟这一科技浪潮，精准布局海外市场，必将在未来的发展中收获满满，开启全新的辉煌篇章。让我们携手共进，迎着矿业投资的新风向砥砺前行，共同推动全球矿业的繁荣与发展！
In short, at the 2024 (4th) Mining Investment and Financing Conference, Dr. Lyu Guo’s in-depth interpretation and professional sharing of AI prospecting technology pointed out the direction for mining enterprises. If mining enterprises can keep up with this technological wave and accurately layout the overseas market, they will surely gain a lot in future development and open a new brilliant chapter. Let us work hand in hand, forge ahead in the new trend of mining investment, and jointly promote the prosperity and development of the global mining industry!