• Journal of the Microelectronics and Packaging Society
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• v.30 no.3
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• pp.11-19
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• 2023

Recently with the rapid advancement of artificial intelligence (AI) technologies such as Chat GPT, AI semiconductors have become important. AI technologies require the ability to process large volumes of data quickly, as they perform tasks such as big data processing, deep learning, and algorithms. However, AI semiconductors encounter challenges with excessive power consumption and data bottlenecks during the processing of large-scale data. Thus, the latest packaging technologies are required for AI semiconductor computations. In this study, the authors have described packaging technologies applicable to AI semiconductors, including interposers, Through-Silicon-Via (TSV), bumping, Chiplet, and hybrid bonding. These technologies are expected to contribute to enhance the power efficiency and processing speed of AI semiconductors.

• Informatization Policy
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• v.31 no.2
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• pp.39-64
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• 2024

This study assesses the national AI competitiveness of 38 OECD countries with focus on AI human capital, AI infrastructure, and AI innovation capacity. Utilizing the fuzzy-set ideal type analysis method, these countries were categorized into eight distinct types based on their national AI competitiveness levels, leading to the derivation of pertinent implications. The analysis identified a category termed "AI Leading Country" consisting of North American, Western European, and Nordic countries, along with several Asian nations including South Korea. Remarkably, the United States demonstrated dominant global national AI competitiveness, achieving the highest fuzzy scores across all three evaluative factors. South Korea was classified as an "AI Leading Country" primarily due to its superior AI infrastructure, but its performance in AI human capital and AI innovation capacity was found to be moderate relative to other analyzed nations; thus highlighting the necessity of sustained focus on the accumulation of AI human capital and bolstering of AI innovation capacity.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.109-115
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• 2020

In this paper, we propose an artificial intelligence(AI) technology analysis using partial least square(PLS) regression model. AI technology is now affecting most areas of our society. So, it is necessary to understand this technology. To analyze the AI technology, we collect the patent documents related to AI from the patent databases in the world. We extract AI technology keywords from the patent documents by text mining techniques. In addition, we analyze the AI keyword data by PLS regression model. This regression model is based on the technique of partial least squares used in the advanced analyses such as bioinformatics, social science, and engineering. To show the performance of our proposed method, we make experiments using AI patent documents, and we illustrate how our research can be applied to real problems. This paper is applicable not only to AI technology but also to other technological fields. This also contributes to understanding other various technologies by PLS regression analysis.

• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.66-85
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• 2020

The purpose of this study is to explain and predict trends the AI development process based on AI technology patents (total) and AI reporting frames in major newspapers. To that end, a summary of South Korean and U.S. technology patents filed over the past nine years and the AI (Artificial Intelligence) news text of major domestic newspapers were analyzed. In this study, Topic Modeling and Time Series Return Analysis using Big Data were used, and additional network agenda correlation and regression analysis techniques were used. First, the results of this study were confirmed in the order of artificial intelligence and algorithm 5G (hot AI technology) in the AI technical patent summary, and in the news report, AI industrial application and data analysis market application were confirmed in the order, indicating the trend of reporting on AI's social culture. Second, as a result of the time series regression analysis, the social and cultural use of AI and the start of industrial application were derived from the rising trend topics. The downward trend was centered on system and hardware technology. Third, QAP analysis using correlation and regression relationship showed a high correlation between AI technology patents and news reporting frames. Through this, AI technology patents and news reporting frames have tended to be socially constructed by the determinants of media discourse in AI development.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1193-1204
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• 2021

In information security, AI technology is used to detect unknown malware. Although AI technology guarantees high accuracy, it inevitably entails false positives, so we are considering introducing XAI to interpret the results predicted by AI. However, XAI evaluation studies that evaluate or verify the interpretation only provide simple interpretation results are lacking. XAI evaluation is essential to ensure safety which technique is more accurate. In this paper, we interpret AI results as features that have significantly contributed to AI prediction in the field of malware, and present an evaluation method for the interpretation of AI results. Interpretation of results is performed using two XAI techniques on a tree-based AI model with an accuracy of about 94%, and interpretation of AI results is evaluated by analyzing descriptive accuracy and sparsity. As a result of the experiment, it was confirmed that the AI result interpretation was properly calculated. In the future, it is expected that the adoption and utilization of XAI will gradually increase due to XAI evaluation, and the reliability and transparency of AI will be greatly improved.

• Smart Media Journal
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• v.10 no.1
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• pp.99-107
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• 2021

In addition to the 4th Industrial Revolution and Industry 4.0, the recent megatrends in the ICT field are Big-data, IoT, Cloud Computing, and Artificial Intelligence. Therefore, rapid digital transformation according to the convergence of various industrial areas and ICT fields is an ongoing trend that is due to the development of technology of AI services suitable for the era of the 4th industrial revolution and the development of subdivided technologies such as (Business Intelligence), IA (Intelligent Analytics, BI + AI), AIoT (Artificial Intelligence of Things), AIOPS (Artificial Intelligence for IT Operations), and RPA 2.0 (Robotic Process Automation + AI). This study aims to integrate and advance various machine learning services of infrastructure-side GPU, CDA (Connected Data Architecture) framework, and AI based on mass distributed Abyss storage in accordance with these technical situations. Also, we want to utilize AI business revenue model in various industries.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.713-722
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• 2024

This study highlights the impact of Artificial Intelligence (AI) technology on journalism, discussing its utility and addressing major ethical concerns. Broadcasting companies and media institutions, such as the Bloomberg, Guardian, WSJ, WP, NYT, globally are utilizing AI for innovation in news production, data analysis, and content generation. Accordingly, the ecosystem of AI journalism will be analyzed in terms of scale, economic feasibility, diversity, and value enhancement of major media AI service types. Through the previous literature review, this study identifies key ethical and social issues in AI journalism as well. It aims to bridge societal and technological concerns by exploring mutual development directions for AI technology and the media industry. Additionally, it advocates for the necessity of integrated guidelines and advanced AI literacy through social consensus in addressing these issues.

• Review of KIISC
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• v.32 no.3
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• pp.57-64
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• 2022

우리 사회에서 AI 활용이 더욱 보편화 되어가고 있는 가운데 AI 신뢰에 대한 사회적 요구도 증가했다. 특히 최근 대화형 인공지능'이루다'사건으로 AI 윤리에 대한 논의가 뜨거워졌다. 금융 분야에서도 로보어드바이저, 보험 심사 등 AI가 다양하게 활용되고 있지만, AI 윤리 문제가 AI 활성화에 큰 걸림돌이 되고 있다. 본 논문에서는 인공지능으로 발생할 수 있는 윤리적 문제를 활용 도메인과 데이터 분석 파이프라인에 따라 나눈다. 금융 AI 기술 분야에 따른 윤리 문제를 분류했으며 각 분야별 윤리사례를 제시했고 윤리 문제 분류에 따른 대응 방안과 해외에서의 대응방식과 우리나라의 대응방식을 소개하며 해결방안을 제시했다. 본 연구를 통해 금융 AI 기술 발전에 더불어 윤리 문제에 대한 경각심을 고취시킬 수 있을 것으로 기대한다. 금융 AI 기술 발전이 AI 윤리와 조화를 이루며 성장하길 바라며, 금융 AI 정책 수립 시에도 AI 윤리적 문제를 염두해 두어 차별, 개인정보유출 등과 같은 AI 윤리 규범 미준수로 파생되는 문제점을 줄이며 금융분야 AI 활용이 더욱 활성화되길 기대한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.597-599
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• 2022

When IoT device performs on-device AI, the device is required to use various AI models selectively according to target service and surrounding environment. Also, AI model can be updated by additional training such as federated learning or adapting the improved technique. Hence, for successful on-device AI, IoT device should acquire various AI models selectively or update previous AI model to new one. In this paper, we propose AI model repository to tackle this issue. The repository supports AI model registration, searching, management, and deployment along with dashboard for practical usage. We implemented it using Node.js and Vue.js to verify it works well.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.87-99
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• 2024

This study aims to identify the competencies required for webtoon artists to survive in the future era of AI commercialization. It explores the current and future use of AI in webtoons, and predicts the role of artists in the future webtoon industry. The study finds that AI will replace human workers in some areas, but human empathy-related fields can be sustained. Artist roles like story projectors, Visual directors, and AI editors were identified as potential models for the changing role of artists. To address terminology ambiguity, a three-step AI categorization mechanical type AI, humanoid type AI, and transcendent type AI was proposed for a more realistic separation of AI capabilities. The researcher suggested these findings as guidelines for developing skills in emerging artists or re-skilling existing ones, emphasizing collaboration with AI for mutual growth rather than a negative acceptance of new technology.