• 제목/요약/키워드: Generative artificial intelligence (AI)

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A Study on the Understanding and Effective Use of Generative Artificial Intelligence

  • Ju Hyun Jeon
    • International journal of advanced smart convergence
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    • 제12권3호
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    • pp.186-191
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    • 2023
  • This study would investigate the generative AIs currently in service in the era of hyperscale AIs and explore measures for the use of generative AIs, focusing on 'ChatGPT,' which has received attention as a leader of generative AIs. Among the various generative AIs, this study selected ChatGPT, which has rich application cases to conduct research, investigation, and use. This study investigated the concept, learning principle, and features of ChatGPT, identified the algorithm of conversational AI as one of the specific cases and checked how it is used. In addition, by comparing various cases of the application of conversational AIs such as Google's Bard and MS's NewBing, this study sought efficient ways to utilize them through the collected cases and conducted research on the limitations of conversational AI and precautions for its use. If connected to city-related databases, it can provide information on city infrastructure, transportation systems, and public services, so residents can easily get the information they need. We want to apply this research to enrich the lives of our citizens.

Analysis of perceptions and needs of generative AI for work-related use in elementary and secondary education

  • Hye Jin Yun;Kwihoon Kim
    • 한국컴퓨터정보학회논문지
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    • 제29권7호
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    • pp.231-243
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    • 2024
  • 생성형 AI 서비스의 다각화로 다양한 분야와 연령대에서 사용됨에 따라, 교육 분야에서도 활용 시도와 논의가 활발해지고 있다. 본 연구에서는 충청북도 지역 초·중등 교직원 934명 대상의 설문 조사를 통해 생성형 AI에 대한 일반적 및 업무 영역에서의 인식과 활용도, 요구 사항을 조사·분석했다. 주요 연구 결과로, 첫째, 교직원의 생성형 AI 활용 경험은 일반적 사용 대비 업무 목적 사용 경험이 적었고, 월 1회 이상의 주기적 빈도를 고려하면 훨씬 적은 비율로 나타났다. 둘째, 생성형 AI의 업무 활용 시 업무 효율 향상에 대한 기대가 가장 높은 것으로 나타났다. 셋째, 직위와 직종에 따라 생성형 AI의 활용 방안별 유용성 인식차가 두드러졌지만, 다양한 문서 처리 도움에 대한 유용성 인식 정도가 공통으로 높은 것으로 나타났다. 초·중등 교직원의 생성형 AI 업무 활용을 위해 생성형 AI 사용 관련 부작용 및 유의점에 대한 안전장치 마련과 촉진 환경 조성 등의 사항에 대한 개선이 필요하고 직위와 직종에 따라 요구 사항과 필요성이 고려되어야 할 것이다.

우울증 환자의 자살 위험 평가의 훈련을 위한 생성형 인공지능 챗봇의 의학적 교육 활용 사례: 일개 한의과대학 학생을 중심으로 (Utilization of Generative Artificial Intelligence Chatbot for Training in Suicide Risk Assessment of Depressed Patients: Focusing on Students at a College of Korean Medicine)

  • 권찬영
    • 동의신경정신과학회지
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    • 제35권2호
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    • pp.153-162
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    • 2024
  • Objectives: Among OECD countries, South Korea has been having the highest suicide rate since 2018, with 24.1 deaths per 100,000 people reported in 2020. The objectie of this study was to examine the use of generative artificial intellicence (AI) chatbots to train third-year Korean medicine (KM) students in conducting suicide risk assessments for patients with depressive disorders to train students for their clinical practice skills. Methods: The Claude 3 Sonnet model was utilized for chatbot simulations. Students performed mock consultations using standardized suicide risk assessment tools including Ask Suicide-Screening Questions (ASQ) tool and ASQ Brief Suicide Safety Assessment. Experiences and attitudes were collected through an anonymous online survey. Responses were rated on a 1~5 Likert scale. Results: Thirty-six students aged 22~30 years participated in this study. Their scores for interest and appropriateness (4.66±0.57), usefulness (4.60±0.61), and overall experience (4.63±0.60) were high. Their evaluation of the usability of artificial intelligence chatbot was also high at 4.58±0.70 points. However, their trust in chatbot responses (Q12) was lower (3.86±0.99). Common issues related to dissatisfaction included conversation disruptions due to token limits and inadequate chatbot responses. Conclusions: This is the first study investigating generative AI chatbots for suicide risk assessment training in KM education. Students reported high satisfaction, although their trust in chatbot accuracy was moderate. Technical limitations affected their experience. These preliminary findings suggest that generative AI chatbots hold promise for clinical training, particularly for education in psychiatry. However, improvements in response accuracy and conversation continuity are needed.

기업 내 생성형 AI 시스템의 보안 위협과 대응 방안 (Security Threats to Enterprise Generative AI Systems and Countermeasures)

  • 최정완
    • 융합보안논문지
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    • 제24권2호
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    • pp.9-17
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    • 2024
  • 본 논문은 기업 내 생성형 AI(Generative Artificial Intelligence) 시스템의 보안 위협과 대응 방안을 제시한다. AI 시스템이 방대한 데이터를 다루면서 기업의 핵심 경쟁력을 확보하는 한편, AI 시스템을 표적으로 하는 보안 위협에 대비해야 한다. AI 보안 위협은 기존 사람을 타겟으로 하는 사이버 보안 위협과 차별화된 특징을 가지므로, AI에 특화된 대응 체계 구축이 시급하다. 본 연구는 AI 시스템 보안의 중요성과 주요 위협 요인을 분석하고, 기술적/관리적 대응 방안을 제시한다. 먼저 AI 시스템이 구동되는 IT 인프라 보안을 강화하고, AI 모델 자체의 견고성을 높이기 위해 적대적 학습 (adversarial learning), 모델 경량화(model quantization) 등 방어 기술을 활용할 것을 제안한다. 아울러 내부자 위협을 감지하기 위해, AI 질의응답 과정에서 발생하는 이상 징후를 탐지할 수 있는 AI 보안 체계 설계 방안을 제시한다. 또한 사이버 킬 체인 개념을 도입하여 AI 모델 유출을 방지하기 위한 변경 통제와 감사 체계 확립을 강조한다. AI 기술이 빠르게 발전하는 만큼 AI 모델 및 데이터 보안, 내부 위협 탐지, 전문 인력 육성 등에 역량을 집중함으로써 기업은 안전하고 신뢰할 수 있는 AI 활용을 통해 디지털 경쟁력을 제고할 수 있을 것이다.

Research on AI Painting Generation Technology Based on the [Stable Diffusion]

  • Chenghao Wang;Jeanhun Chung
    • International journal of advanced smart convergence
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    • 제12권2호
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    • pp.90-95
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    • 2023
  • With the rapid development of deep learning and artificial intelligence, generative models have achieved remarkable success in the field of image generation. By combining the stable diffusion method with Web UI technology, a novel solution is provided for the application of AI painting generation. The application prospects of this technology are very broad and can be applied to multiple fields, such as digital art, concept design, game development, and more. Furthermore, the platform based on Web UI facilitates user operations, making the technology more easily applicable to practical scenarios. This paper introduces the basic principles of Stable Diffusion Web UI technology. This technique utilizes the stability of diffusion processes to improve the output quality of generative models. By gradually introducing noise during the generation process, the model can generate smoother and more coherent images. Additionally, the analysis of different model types and applications within Stable Diffusion Web UI provides creators with a more comprehensive understanding, offering valuable insights for fields such as artistic creation and design.

University Faculty's Perspectives on Implementing ChatGPT in their Teaching

  • Pyong Ho Kim;Ji Won Yoon;Hye Yoon Kim
    • International Journal of Advanced Culture Technology
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    • 제11권4호
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    • pp.56-61
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    • 2023
  • The present study explored a comprehensive investigation of university professors' perspectives on the implementation of ChatGPT - an artificial intelligence-powered language model - in their teaching practices. A diverse group of 30 university professors responded to a questionnaire about the level of their interest in implementing the tool, willingness to apply it, and concerns they have regarding the intervention of ChatGPT in higher education setting. The results showed that the participants are highly interested in employing the tool into their teaching practice, and find that the students are likely to benefit from using ChatGPT in classroom settings. On the other hand, they displayed concerns regarding high depandency on data, privacy-related issues, lack of supports required, and technical contraints. In today's fast-paced society, educators are urged to mindfully apply this inevitable generative AI means with thoughtfulness and ethical considerations to and for their learners. Relevant topics are discussed to successfully intervene AI tools in teaching practices in higher education.

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

  • 이기석;이승욱;윤민성;유정재;오아름;최인문;김대욱
    • 전자통신동향분석
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    • 제39권2호
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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.

AI 기반 지능형 CCTV 이상행위 탐지 성능 개선 방안 (AI-Based Intelligent CCTV Detection Performance Improvement)

  • 류동주;김승희
    • 융합보안논문지
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    • 제23권5호
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    • pp.117-123
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    • 2023
  • 최근 생성형 Artificial Intelligence(이하 AI)와 인공지능에 대한 수요가 높아짐에 따라, 오남용에 대한 심각성이 대두되고 있다. 그러나, 이상행위 탐지를 극대화한 지능형 CCTV는 군과 경찰에서 범죄 예방에 큰 도움이 되고 있다. AI는 인간이 가르쳐준 대로 학습을 수행한 후, 자가 학습을 진행한다. AI는 학습된 결과에 따라 판단을 하기 때문에, 학습 시 특징을 명확하게 이해해야만 한다. 그러나, 인간이 판단하기에도 모호한 이상한 행위와 비정상 행위의 시각적 판단이 어려운 경우가 많다. 이것을 인공지능의 눈으로 학습하기란 매우 어렵고, 학습을 한 결과는 오탐, 미탐 그리고 과탐이 매우 많아진다. 이에 대해 본 논문에서는 AI의 이상한 행위와 비정상 행위의 학습을 명확하게 하기 위한 기준과 방법을 제시하고, 지능형 CCTV의 오탐, 미탐 그리고 과탐에 대한 판단 능력을 최대화 하기 위한 학습 방안을 제시하였다. 본 논문을 통해, 현재 활용 중인 지능형 CCTV의 인공지능 엔진 성능을 극대화가 가능하고, 오탐율과 미탐율의 최소화가 가능할 것으로 기대된다.

인공지능으로 작성된 논문의 처리 방안 (How to Review a Paper Written by Artificial Intelligence)

  • 신동우;문성훈
    • Journal of Digestive Cancer Research
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    • 제12권1호
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    • pp.38-43
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    • 2024
  • Artificial Intelligence (AI) is the intelligence of machines or software, in contrast to human intelligence. Generative AI technologies, such as ChatGPT, have emerged as valuable research tools that facilitate brainstorming ideas for research, analyzing data, and writing papers. However, their application has raised concerns regarding authorship, copyright, and ethical considerations. Many organizations of medical journal editors, including the International Committee of Medical Journal Editors and the World Association of Medical Editors, do not recognize AI technology as an author. Instead, they recommend that researchers explicitly acknowledge the use of AI tools in their research methods or acknowledgments. Similarly, international journals do not recognize AI tools as authors and insist that human authors should be accountable for the research findings. Therefore, when integrating AI-generated content into papers, it should be disclosed under the responsibility of human authors, and the details of the AI tools employed should be specified to ensure transparency and reliability.

Potential role of artificial intelligence in craniofacial surgery

  • Ryu, Jeong Yeop;Chung, Ho Yun;Choi, Kang Young
    • 대한두개안면성형외과학회지
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    • 제22권5호
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    • pp.223-231
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    • 2021
  • The field of artificial intelligence (AI) is rapidly advancing, and AI models are increasingly applied in the medical field, especially in medical imaging, pathology, natural language processing, and biosignal analysis. On the basis of these advances, telemedicine, which allows people to receive medical services outside of hospitals or clinics, is also developing in many countries. The mechanisms of deep learning used in medical AI include convolutional neural networks, residual neural networks, and generative adversarial networks. Herein, we investigate the possibility of using these AI methods in the field of craniofacial surgery, with potential applications including craniofacial trauma, congenital anomalies, and cosmetic surgery.