This is a report on a survey of core material utilization in management system infrastructure for artificial intelligence and deep learning, conducted as part of the FY2023 Supplementary Global South Future Industry Human Resource Development Project by METI. The survey was conducted by Mizuho Research & Technologies, Ltd.
Background and Purpose of the Survey
This survey aims to analyze the utilization status and future demand of core materials supporting system infrastructure in the industrial application of rapidly developing artificial intelligence (AI) and deep learning technologies. Particularly from the perspective of future industry development and human resource development in Global South countries, detailed research is conducted on securing and efficient utilization of materials and resources necessary for the proliferation of AI and deep learning technologies.
Material Requirements for AI and Deep Learning System Infrastructure
The survey analyzes technical requirements and supply conditions for core materials essential for AI and deep learning system operation, including semiconductors, rare earth elements, lithium, and cobalt. Detailed examination is conducted on technical specifications, quality standards, and cost structures of materials necessary for high-performance computing, identifying materials important from an industrial competitiveness perspective.
Resource Strategy in Global South Expansion
The report analyzes risks where stable procurement of core materials could become a bottleneck in the deployment of AI and deep learning technologies in Global South countries. Specific measures for constructing sustainable resource strategies are presented, including strengthening cooperation with resource-holding countries, promoting development of alternative materials, and utilizing recycling technologies.
Optimization of Management System Infrastructure
To achieve efficient operation of AI and deep learning systems, design of management systems for optimizing core material utilization is examined. An integrated approach considering energy efficiency improvement, waste reduction, and environmental impact reduction throughout the lifecycle is proposed, evaluating implementation feasibility in industry.
Human Resource Development and Technology Transfer
The report points out the importance of understanding core material characteristics and acquiring efficient utilization technologies in developing future industry human resources in Global South countries. Detailed recommendations are made on specific measures for human resource development, including design of technology transfer programs, development of training curricula, and promotion of practical education through industry-academia collaboration.
Policy Recommendations and Future Prospects
Based on survey results, policy recommendations for strengthening core material strategies in international expansion of Japan's AI and deep learning technologies are summarized. Directions are indicated for achieving both securing Japan's technological superiority and international contribution through comprehensive approaches including promoting resource diplomacy, participating in technical standardization, and building international cooperation frameworks.
The article evaluates this as survey research results that clarify the importance of core material strategies supporting sustainable development and international expansion of AI and deep learning technologies, providing valuable knowledge for building future industry ecosystems through cooperation with Global South countries.