A Strategic Direction for Enhancing South Korea's R&D Platform for Science and Technologies
Year: 2024
Type: article
Abstract: This study examines how South Korea's R&D platform can be enhanced by analyzing technology trends and policies from leading international organizations. The study highlights global concerns such as low economic growth, environmental risks, and increase of AI dominance, by particularly introducing ChatGPT. Key technologies identified include AI semiconductors, data-centers, cloud computing, and platform technologies, which are crucial for future R&D platform development. South Korea, striving to strengthen its technological leadership, faces challenges due to its current position as a follower in many strategic areas, except for memory semiconductors, secondary batteries, and 5G. To address this, the country is focusing on 12 essential strategic technologies, including semiconductors and displays. AI semiconductor technology is a priority, viewed as critical for national security, with efforts focused on building a robust ecosystem. The study emphasizes the rapid growth of green data-centers, driven by reducing carbon emissions, and the central role of cloud technology in emerging trends like AI and data analytics. It also highlights the importance of platform technologies that efficiently integrate various resources in a complex and rapidly changing environment. To tackle issues such as demand for cloud computing, AI model efficiency, and hardware limitations, the study suggests focusing on high performance, energy efficiency, and optimization. We propose advancing existing R&D platforms with a cloud-based infrastructure centered on domestic AI semiconductors, and creating specialized AI platforms for scientific applications. In conclusion, the study outlines a strategic direction for advancing South Korea's R&D platform, aligning with cutting-edge technology trends and addressing key challenges.
Author: lee, jong suk
Institution: Korea Institute of Science & Technology Information
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6893235486
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