• Title/Summary/Keyword: Generative artificial intelligence (AI)

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Analysis of Key Factors in Corporate Adoption of Generative Artificial Intelligence Based on the UTAUT2 Model

  • Yongfeng Hu;Haojie Jiang;Chi Gong
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.7
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    • pp.53-71
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    • 2024
  • Generative Artificial Intelligence (AI) has become the focus of societal attention due to its wide range of applications and profound impact. This paper constructs a comprehensive theoretical model based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), integrating variables such as Personal Innovativeness and Perceived Risk to study the key factors influencing enterprises' adoption of Generative AI. We employed Structural Equation Modeling (SEM) to verify the hypothesized paths and used the Bootstrapping method to test the mediating effect of Behavioral Intention. Additionally, we explored the moderating effect of Perceived Risk through Hierarchical Regression Analysis. The results indicate that Performance Expectancy, Effort Expectancy, Social Influence, Price Value, and Personal Innovativeness have significant positive impacts on Behavioral Intention. Behavioral Intention plays a significant mediating role between these factors and Use Behavior, while Perceived Risk negatively moderates the relationship between Behavioral Intention and Use Behavior. This study provides theoretical and empirical support for how enterprises can effectively adopt Generative AI, offering important practical implications.

Efficiency Analysis of Integrated Defense System Using Artificial Intelligence (인공지능을 활용한 통합방위체계의 효율성 분석)

  • Yoo Byung Duk;Shin Jin
    • Convergence Security Journal
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    • v.23 no.1
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    • pp.147-159
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    • 2023
  • Recently, Chat GPT artificial intelligence (AI) is of keen interest to all governments, companies, and military sectors around the world. In the existing era of literacy AI, it has entered an era in which communication with humans is possible with generative AI that creates words, writings, and pictures. Due to the complexity of the current laws and ordinances issued during the recent national crisis in Korea and the ambiguity of the timing of application of laws and ordinances, the golden time of situational measures was often missed. For these reasons, it was not able to respond properly to every major disaster and military conflict with North Korea. Therefore, the purpose of this study was to revise the National Crisis Management Basic Act, which can act as a national tower in the event of a national crisis, and to promote artificial intelligence governance by linking artificial intelligence technology with the civil, government, military, and police.

Current Use and Issues of Generative AI in the Film Industry (영화산업의 생성형 인공지능(Generative AI) 활용 현황과 문제점)

  • Jong-Guk Kim
    • Journal of Information Technology Applications and Management
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    • v.31 no.3
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    • pp.181-192
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    • 2024
  • With the introduction of generative artificial intelligence(AI) tools such as OpenAI's Sora into the global film industry, including Hollywood, there has been a simultaneous emergence of innovations in film production as well as various crises. These changes are spreading throughout the entire film production process, including scriptwriting, casting, editing, and acting. This study analyzes the impact of AI on the film industry, particularly Hollywood, and explores how this technology might bring about changes in Korean cinema. AI technologies applied in the film industry offer benefits such as reducing production time and costs. However, they also pose threats to many filmmakers and actors who rely on the traditional production methods, leading to ethical and legal issues. In Hollywood blockbuster films, AI technology is used to create realistic visual effects, analyze scripts, and suggest optimal shooting angles. While these applications improve the qualitative level of films, they also reduce the human resources required in traditional film production processes. The impact on the Korean film industry is also noteworthy. Some Korean film production companies are leveraging AI to create films in a more creative and efficient manner. Efforts are being made to analyze audience data using AI and develop storylines that appeal to a larger audience. However, these technological changes are controversial among many Korean filmmakers who prefer traditional production methods. This study provides an in-depth discussion on whether the adoption of AI in the film industry can bring about positive innovation or inevitably lead to crises. It analyzes how AI technology is transforming traditional roles in the film industry and what new opportunities and challenges this change generates within the industry. Additionally. This study highlights the differences in technology adoption between Hollywood and Korean film industry and explores how each industry is embracing these technological changes.

Utilization Strategies of Generative AI Platforms for CG Education (CG 교육을 위한 생성형 인공지능 플랫폼 활용 방안)

  • Donghee Suh
    • Journal of Practical Engineering Education
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    • v.15 no.2
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    • pp.357-364
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    • 2023
  • Due to the rapid advancement of AI technology, generative artificial intelligence platforms are experiencing innovative applications in various fields. In this paper, it examines research cases involving the utilization of AI in education, explore instances where generative AI platforms are applied in the realm of creative endeavors, and discuss the direction of utilizing generative AI in educational contexts. In the field of computer graphics, this study introduced generative AI platforms that are applicable for image creation, editing, and video editing. It also proposed platforms that can be utilized in the video editing production process. These generative AI platforms not only offer advantages in terms of efficiency, by reducing the efforts of creators and saving time in the production process, but they also present positive aspects in enhancing individual capabilities. It is advocated that their swift integration into education is necessary, considering these benefits. This study aims to provide direction for the expansion of creative education utilizing generative AI platforms.

A Study on the Role of Local Governments in the Era of Generative Artificial Intelligence: Based on Case Studies in Gyeonggi-do Province, Seoul City, and New York City (생성형 인공지능 시대 지방정부의 역할에 대한 연구: 경기도, 서울시, 뉴욕시 사례연구를 바탕으로)

  • S. J. Lee;J. B. Kim
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.3
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    • pp.809-818
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    • 2024
  • This paper proposes an action plan for local governments to safely utilize artificial intelligence technology in various local government policies. The proposed method analyzes cases of application of artificial intelligence-related laws and policies in Gyeonggi Province, Seoul City, and New York City, and then presents matters that local governments should consider when utilizing AI technology in their policies. This paper applies the AILocalism-Korea analysis methodology, which is a modified version of the AILocalsm analysis methodology[1] presented by TheGovLab at New York University. AILocalism-Korea is an analysis methodology created to analyze the current activities of each local government in the fields of legal system, public procurement, mutual cooperation, and citizen participation, and to suggest practical alternatives in each area. In this paper, we use this analysis methodology to present 9 action plans that local governments should take based on safe and reliable use of artificial intelligence. By utilizing various AI technologies through the proposed plan in local government policies, it will be possible to realize reliable public services.

Interaction Between Students and Generative Artificial Intelligence in Critical Mineral Inquiry Using Chatbots (챗봇 활용 핵심광물 탐구에서 나타난 학생과 생성형 인공지능의 상호작용)

  • Sueim Chung;Jeongchan Kim;Donghee Shin
    • Journal of the Korean earth science society
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    • v.44 no.6
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    • pp.675-692
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    • 2023
  • This study used a Chatbot, a generative artificial intelligence (AI), to analyze the interaction between the Chatbot and students when exploring critical minerals from an epistemological aspect. The results, issues to be kept in mind in the teaching and learning process using AI were discussed in terms of the role of the teacher, the goals of education, and the characteristics of knowledge. For this study, we conducted a three-session science education program using a Chatbot for 19 high school students and analyzed the reports written by the students. As a result, in terms of form, the students' questions included search-type questions and non-search-type questions, and in terms of content, in addition to various questions asking about the characteristics of the target, there were also questions requiring a judgment by combining various data. In general, students had a questioning strategy that distinguished what they should aim for and what they should avoid. The Chatbot's answer had a certain form and consisted of three parts: an introduction, a body, and a conclusion. In particular, the conclusion included commentary or opinions with opinions on the content, and in this, value judgments and the nature of science were revealed. The interaction between the Chatbot and the student was clearly evident in the process in which the student organized questions in response to the Chatbot's answers. Depending on whether they were based on the answer, independent or derived questions appeared, and depending on the direction of comprehensiveness and specificity, superordinate, subordinate, or parallel questions appeared. Students also responded to the chatbot's answers with questions that included critical thinking skills. Based on these results, we discovered that there are inherent limitations between Chatbots and students, unlike general classes where teachers and students interact. In other words, there is 'limited interaction' and the teacher's role to complement this was discussed, and the goals of learning using AI and the characteristics of the knowledge they provide were also discussed.

A Research on AI Generated 2D Image to 3D Modeling Technology

  • Ke Ma;Jeanhun Chung
    • International Journal of Internet, Broadcasting and Communication
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    • v.16 no.2
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    • pp.81-86
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    • 2024
  • Advancements in generative AI are reshaping graphic and 3D content design landscapes, where AI not only enriches graphic design but extends its reach to 3D content creation. Though 3D texture mapping through AI is advancing, AI-generated 3D modeling technology in this realm remains nascent. This paper presents AI 2D image-driven 3D modeling techniques, assessing their viability in 3D content design by scrutinizing various algorithms. Initially, four OBJ model-exporting AI algorithms are screened, and two are further evaluated. Results indicate that while AI-generated 3D models may not be directly usable, they effectively capture reference object structures, offering substantial time savings and enhanced design efficiency through manual refinements. This endeavor pioneers new avenues for 3D content creators, anticipating a dynamic fusion of AI and 3D design.

Reference-based Utterance Generation Model using Multi-turn Dialogue (멀티턴 대화를 활용한 레퍼런스 기반의 발화 생성 모델)

  • Sangmin Park;Yuri Son;Bitna Keum;Hongjin Kim;Harksoo Kim;Jaieun Kim
    • Annual Conference on Human and Language Technology
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    • 2022.10a
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    • pp.88-91
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    • 2022
  • 디지털 휴먼, 민원 상담, ARS 등 칫챗의 활용과 수요가 증가함에 따라 칫챗의 성능 향상을 위한 다양한 연구가 진행되고 있다. 특히, 오토 인코더(Auto-encoder) 기반의 생성 모델(Generative Model)은 높은 성능을 보이며 지속적인 연구가 이루어지고 있으나, 이전 대화들에 대한 충분한 문맥 정보의 반영이 어렵고 문법적으로 부적절한 답변을 생성하는 문제가 있다. 이를 개선하기 위해 검색 기반의 생성 모델과 관련된 연구가 진행되고 있으나, 현재 시점의 문장이 유사해도 이전 문장들에 따라 의도와 답변이 달라지는 멀티턴 대화 특징을 반영하여 대화를 검색하는 연구가 부족하다. 본 논문에서는 이와 같은 멀티턴 대화의 특징이 고려된 검색 방법을 제안하고 검색된 레퍼런스(준정답 문장)를 멀티턴 대화와 함께 생성 모델의 입력으로 활용하여 학습시키는 방안을 제안한다. 제안 방안으로 학습된 발화 생성 모델은 기존 모델과 비교 평가를 수행하며 Rouge-1 스코어에서 13.11점, Rouge-2 스코어에서 10.09점 Rouge-L 스코어에서 13.2점 향상된 성능을 보였고 이를 통해 제안 방안의 우수성을 입증하였다.

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Comparison of online video(OTT) content production technology based on artificial intelligence customized recommendation service (인공지능 맞춤 추천서비스 기반 온라인 동영상(OTT) 콘텐츠 제작 기술 비교)

  • CHUN, Sanghun;SHIN, Seoung-Jung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.3
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    • pp.99-105
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    • 2021
  • In addition to the OTT video production service represented by Nexflix and YouTube, a personalized recommendation system for content with artificial intelligence has become common. YouTube's personalized recommendation service system consists of two neural networks, one neural network consisting of a recommendation candidate generation model and the other consisting of a ranking network. Netflix's video recommendation system consists of two data classification systems, divided into content-based filtering and collaborative filtering. As the online platform-led content production is activated by the Corona Pandemic, the field of virtual influencers using artificial intelligence is emerging. Virtual influencers are produced with GAN (Generative Adversarial Networks) artificial intelligence, and are unsupervised learning algorithms in which two opposing systems compete with each other. This study also researched the possibility of developing AI platform based on individual recommendation and virtual influencer (metabus) as a core content of OTT in the future.

An Analysis of Artificial Intelligence Education Research Trends Based on Topic Modeling

  • You-Jung Ko
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.2
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    • pp.197-209
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    • 2024
  • This study aimed to analyze recent research trends in Artificial Intelligence (AI) education within South Korea with the overarching objective of exploring the future direction of AI education. For this purpose, an analysis of 697 papers related to AI education published in Research Information Sharing Service (RISS) from 2016 to November 2023 were analyzed using word cloud and Latent Dirichlet Allocation (LDA) topic modeling technique. As a result of the analysis, six major topics were identified: generative AI utilization education, AI ethics education, AI convergence education, teacher perceptions and roles in AI utilization, AI literacy development in university education, and AI-based education and research directions. Based on these findings, I proposed several suggestions, (1) including expanding the use of generative AI in various subjects, (2) establishing ethical guidelines for AI use, (3) evaluating the long-term impact of AI education, (4) enhancing teachers' ability to use AI in higher education, (5) diversifying the curriculum of AI education in universities, (6) analyzing the trend of AI research, and developing an educational platform.