• Title/Summary/Keyword: Generative AI Content

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Generative AI Technology Trends and Development Prospects for Digital Asset Creation (디지털 에셋 창작을 위한 생성형 AI 기술 동향 및 발전 전망)

  • K.S. Lee;S.W. Lee;M.S. Yoon;J.J. Yu;A.R. Oh;I.M. Choi;D.W. Kim
    • Electronics and Telecommunications Trends
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    • v.39 no.2
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    • pp.33-42
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    • 2024
  • With the recent rapid development of artificial intelligence (AI) technology, its use is gradually expanding to include creative areas and building new content using generative AI solutions, reaching beyond existing data analysis and reasoning applications. Content creation using generative AI faces challenges owing to technical limitations and other aspects such as copyright compliance. Nevertheless, generative AI may increase the productivity of experts and overcome barriers to creative work by allowing users to easily express their ideas as digital content. Thus, various types of applications will continue to emerge. As images and videos can be created using text input on a prompt, generative AI allows to create and edit digital assets quickly. We present trends in generative AI technology for images, videos, three-dimensional (3D) assets and scenes, digital humans, interactive content, and interfaces. In addition, the prospects for future technological development in this field are discussed.

Children's Perception of Generative AI : Focusing on Type and Attribute Classification (생성형 AI에 대한 아동들의 인식 연구 : 유형과 속성 분류를 중심으로)

  • Suyong Jang;Jisu Han;Hyorim Shin;Changhoon Oh
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.1
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    • pp.591-601
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    • 2024
  • As generative AI-based educational content and services targeting child users rapidly increase, the need for research related to children's perception of generative AI is increasing. Accordingly, this study sought to determine the type of generative AI recognized by children and whether cognitive, behavioral, and emotional properties were assigned to it. To understand this, we collected responses through workshop activities to create storybooks with children, semi-structured interviews, and drawing. As a result, children viewed generative AI as an artifact with a high cognitive level, but it was not a type of existing artifact.

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.

Transforming Text into Video: A Proposed Methodology for Video Production Using the VQGAN-CLIP Image Generative AI Model

  • SukChang Lee
    • International Journal of Advanced Culture Technology
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    • v.11 no.3
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    • pp.225-230
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    • 2023
  • With the development of AI technology, there is a growing discussion about Text-to-Image Generative AI. We presented a Generative AI video production method and delineated a methodology for the production of personalized AI-generated videos with the objective of broadening the landscape of the video domain. And we meticulously examined the procedural steps involved in AI-driven video production and directly implemented a video creation approach utilizing the VQGAN-CLIP model. The outcomes produced by the VQGAN-CLIP model exhibited a relatively moderate resolution and frame rate, and predominantly manifested as abstract images. Such characteristics indicated potential applicability in OTT-based video content or the realm of visual arts. It is anticipated that AI-driven video production techniques will see heightened utilization in forthcoming endeavors.

Methodology for Visual Communication Design Based on Generative AI

  • Younjung Hwang;Yi Wu
    • International journal of advanced smart convergence
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    • v.13 no.3
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    • pp.170-175
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    • 2024
  • The field of Generative AI(Artificial Intelligence) involves a technology that autonomously comprehends user intentions through commands and learns from provided data to generate new content, such as images or text. This capability, which allows autonomous creativity even with design keywords, is anticipated to play a significant role in the domain of visual communication design. This article delves into the tools of generative AI applicable to visual design and the methodology for design creation using these tools. Furthermore, it discusses how designers can interact visually with AI technology in the era of generative AI.

Secure Coding for SQL Injection Prevention Using Generative AI

  • Young-Bok Cho
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.9
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    • pp.61-68
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    • 2024
  • In this paper, Generative AI is a technology that creates various forms of content such as text, images, and music, and is being utilized across different fields. In the security sector, generative AI is poised to open up new possibilities in various areas including security vulnerability analysis, malware detection and analysis, and the creation and improvement of security policies. This paper presents a guide for identifying vulnerabilities and secure coding using ChatGPT for security vulnerability analysis and prediction, considering the application of generative AI in the security domain. While generative AI offers innovative possibilities in the security field, it is essential to continuously pursue research and development to ensure safe and effective utilization of generative AI through in-depth consideration of ethical and legal issues accompanying technological advancements.

The effect of generative AIintervention level on webtoon content quality perceptions:focusing on the moderating effect of the presence or absence of AI-enabled labels (생성형 AI 개입 수준이 웹툰 콘텐츠 품질 인식에 미치는 영향: AI 활용 표기 문구 유무에 따른 조절효과를 중심으로)

  • Lee, Min chae;Lee, Sang Woo
    • The Journal of Information Systems
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    • v.33 no.3
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    • pp.123-145
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    • 2024
  • Purpose The purpose of this study was twofold. First, we wanted to understand the degree of AI involvement that users find objectionable by examining whether there is a difference in the quality of webtoon content perceived by users depending on the level of AI involvement in the creative process. Secondly, we wanted to find out how users evaluate the quality of webtoon content based on the presence or absence of an AI disclosure statement, and provide implications for the need for AI disclosure statements in the webtoon industry. Design/methodology/approach This study validated the research model by creating a 2 (generative AI intervention level: low/high) X 2 (AI utilisation notation: present/absent) experimental group and conducting an experiment in an online environment. Findings First, we found that the higher the level of AI involvement in webtoon creation, the lower the fun and artistic quality. Second, we found that webtoon content quality depends on the presence or absence of AI disclosure messages. In particular, the higher the level of AI involvement in webtoon creation, the more positive the effect of disclosing the use of creative AI on user perceptions. Third, we found that fun and artistic quality are the main variables that significantly affect webtoon satisfaction. This study can contribute to considering the scope of AI in webtoon creation in the future, and provides new implications by identifying differences in user perceptions based on whether AI is disclosed or not.

Analysis of the Impact of Generative AI based on Crunchbase: Before and After the Emergence of ChatGPT (Crunchbase를 바탕으로 한 Generative AI 영향 분석: ChatGPT 등장 전·후를 중심으로)

  • Nayun Kim;Youngjung Geum
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.19 no.3
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    • pp.53-68
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    • 2024
  • Generative AI is receiving a lot of attention around the world, and ways to effectively utilize it in the business environment are being explored. In particular, since the public release of the ChatGPT service, which applies the GPT-3.5 model, a large language model developed by OpenAI, it has attracted more attention and has had a significant impact on the entire industry. This study focuses on the emergence of Generative AI, especially ChatGPT, which applies OpenAI's GPT-3.5 model, to investigate its impact on the startup industry and compare the changes that occurred before and after its emergence. This study aims to shed light on the actual application and impact of generative AI in the business environment by examining in detail how generative AI is being used in the startup industry and analyzing the impact of ChatGPT's emergence on the industry. To this end, we collected company information of generative AI-related startups that appeared before and after the ChatGPT announcement and analyzed changes in industry, business content, and investment information. Through keyword analysis, topic modeling, and network analysis, we identified trends in the startup industry and how the introduction of generative AI has revolutionized the startup industry. As a result of the study, we found that the number of startups related to Generative AI has increased since the emergence of ChatGPT, and in particular, the total and average amount of funding for Generative AI-related startups has increased significantly. We also found that various industries are attempting to apply Generative AI technology, and the development of services and products such as enterprise applications and SaaS using Generative AI has been actively promoted, influencing the emergence of new business models. The findings of this study confirm the impact of Generative AI on the startup industry and contribute to our understanding of how the emergence of this innovative new technology can change the business ecosystem.

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Job Counselor's Experience and Perception of Generative AI (직업상담사의 생성형 AI 활용경험 및 인식)

  • Sang-ho Bae;Hye-young Kang
    • Journal of Practical Engineering Education
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    • v.16 no.4
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    • pp.567-575
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    • 2024
  • This study was conducted to provide basic data on how to use Generative AI and education to strengthen Generative AI competency in vocational counseling by confirming the experience and perception of job counselors' use of Generative AI. A questionnaire was produced based on literature research and FGI preliminary surveys, and the main contents of the questionnaire were 'experience in using Generative AI (whether to have experience, type of tool, job, educational experience, etc.) and Generative AI recognition (recognition level, usefulness, availability, educational needs, etc.). An online survey was conducted for vocational counselors, and a total of 293 data were analyzed. As a result of major research, first, there were many counselors who had no experience in using Generative AI(60%), and the response that the reason for not using it was because they did not feel the need(28%). Second, the 'degree of recognition' in the Generative AI was somewhat low (M=2.77), and 'Generative AI usefulness' was found to be at a normal level (M=3.32), and it was recognized that it would be necessary mainly for jobs related to 'vocational information'. Third, 'tool (computer use, etc.) competency' (26%) was the highest as the competency required for future vocational counselors, and 'how to use Generative AI' (57%) accounted for a high proportion of the educational content necessary to improve these competencies.

Comparative Study of 3D Gen-AI Platform for Spatial Computing (공간 컴퓨팅 적용을 위한 3D 생성 AI 플랫폼 비교 연구)

  • Donghee Suh
    • Journal of Industrial Convergence
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    • v.22 no.10
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    • pp.37-45
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    • 2024
  • This study aims to compare and analyze the functionality and efficiency of 3D generation AI platforms to evaluate their practical applicability in the 3D content creation process and suggest improvement directions. A total of nine platforms were researched using search, and four platforms were selected based on their utilization of the latest technology, compatibility, and user accessibility. We used the same prompts to create 3D objects on each platform and analyzed the results, focusing on whether they were customizable, beneficial for creating immersive content, efficient in production, free to test, or good value for money. The results showed that Meshy and Tripo performed well with fast generation speeds and efficient polygon optimization, while Spline offered a wide range of media application capabilities but was limited in quality. We found that different 3D generation AI platforms are suitable for different production pipelines and user needs. This study provides practitioners interested in 3D content creation with a practical guide for platform selection and provides insights into the future direction of 3D generative AI technology, which will contribute to future research and industrial applications.