• Title/Summary/Keyword: chatGPT

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Design to Improve Educational Competency Using ChatGPT

  • Choong Hyong LEE
    • International Journal of Internet, Broadcasting and Communication
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    • v.16 no.1
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    • pp.182-190
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    • 2024
  • Various artificial intelligence neural network models that have emerged since 2014 enable the creation of new content beyond the existing level of information discrimination and withdrawal, and the recent generative artificial intelligences such as ChatGPT and Gall-E2 create and present new information similar to actual data, enabling natural interaction because they create and provide verbal expressions similar to humans, unlike existing chatbots that simply present input content or search results. This study aims to present a model that can improve the ChatGPT communication skills of university students through curriculum research on ChatGPT, which can be participated by students from all departments, including engineering, humanities, society, health, welfare, art, tourism, management, and liberal arts. It is intended to design a way to strengthen competitiveness to embody the practical ability to solve problems through ethical attitudes, AI-related technologies, data management, and composition processes as knowledge necessary to perform tasks in the artificial intelligence era, away from simple use capabilities. It is believed that through creative education methods, it is possible to improve university awareness in companies and to seek industry-academia self-reliant courses.

The Role of Functional and Playful Experiential Value on the Intention to Use ChatGPT (사용자가 인지하는 기능적, 유희적 경험가치가 챗GPT의 재사용 의도에 미치는 영향)

  • Hyun Ju Suh;Jumin Lee;Jounghae Bang
    • Journal of Information Technology Services
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    • v.23 no.1
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    • pp.81-95
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    • 2024
  • ChatGPT, a generative artificial intelligence(AI) technology that analyzes conversations to identify users' intentions and generates responses in consideration of the context of the conversation, is attracting attention from a user interface (UI) perspective that it can provide information through natural conversations with users. This study examined the effect of functional and playful values experienced by early users of ChatGPT on reuse intention and verified the structural relationship between technological efficacy, experiential values, and reuse intention. To verify the research model and hypotheses, a survey was conducted on college students who used ChatGPT for the first time. A total of 156 responses were received and 154 responses were used for analysis. As a result, both the functional experiential value and playful experiential value in the initial use process had significant effects on the intention to use ChatGPT. In addition, it was found that technological efficiency had a significant effect on functional and playful experiential values.

Empathetic Dialogue Generation based on User Emotion Recognition: A Comparison between ChatGPT and SLM (사용자 감정 인식과 공감적 대화 생성: ChatGPT와 소형 언어 모델 비교)

  • Seunghun Heo;Jeongmin Lee;Minsoo Cho;Oh-Woog Kwon;Jinxia Huang
    • Proceedings of the Korea Information Processing Society Conference
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    • 2024.05a
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    • pp.570-573
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    • 2024
  • 본 연구는 대형 언어 모델 (LLM) 시대에 공감적 대화 생성을 위한 감정 인식의 필요성을 확인하고 소형 언어 모델 (SLM)을 통한 미세 조정 학습이 고비용 LLM, 특히 ChatGPT의 대안이 될 수 있는지를 탐구한다. 이를 위해 KoBERT 미세 조정 모델과 ChatGPT를 사용하여 사용자 감정을 인식하고, Polyglot-Ko 미세 조정 모델 및 ChatGPT를 활용하여 공감적 응답을 생성하는 비교 실험을 진행하였다. 실험 결과, KoBERT 기반의 감정 분류기는 ChatGPT의 zero-shot 접근 방식보다 뛰어난 성능을 보였으며, 정확한 감정 분류가 공감적 대화의 질을 개선하는 데 기여함을 확인하였다. 이는 공감적 대화 생성을 위해 감정 인식이 여전히 필요하며, SLM의 미세 조정이 고비용 LLM의 실용적 대체 수단이 될 수 있음을 시사한다.

A Study on Active Senior Travel Recognition Using ChatGPT (ChatGPT를 활용한 액티브 시니어 여행 인식 탐색 연구)

  • Han Jangheon
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.20 no.3
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    • pp.25-35
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    • 2024
  • ChatGPT, a leading example of generative AI, is expanding the use of its LLM (Large Language Model) from traditional academic fields such as literature and creative writing to practical areas like management, tourism, and media. This study was conducted with active seniors to analyze their perceptions of travel and tourism, identifying key areas of interest and specific details. ChatGPT was utilized as an analytical tool in major areas of the study, providing suggestions for key findings.The research findings are as follows: First, terms closely associated with active senior travel include retirement, together, service, consumption, leisure, health, life, hobby, culture, generation, platform, wellness, and program. Second, centrality analysis showed that words like service, leisure, and together had high degrees of centrality and closeness centrality, while terms such as health, domestic, culture, activity, program, and life had high closeness centrality. Third, based on the CONCOR analysis with suggestions from ChatGPT, two clusters were identified: 'Retirement and Lifestyle' and 'Senior Services and Platforms'. Based on the research findings, practical implications for active senior travel were identified, along with academic implications for the field of tourism studies.

Analysis of Prompt Engineering Methodologies and Research Status to Improve Inference Capability of ChatGPT and Other Large Language Models (ChatGPT 및 거대언어모델의 추론 능력 향상을 위한 프롬프트 엔지니어링 방법론 및 연구 현황 분석)

  • Sangun Park;Juyoung Kang
    • Journal of Intelligence and Information Systems
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    • v.29 no.4
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    • pp.287-308
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    • 2023
  • After launching its service in November 2022, ChatGPT has rapidly increased the number of users and is having a significant impact on all aspects of society, bringing a major turning point in the history of artificial intelligence. In particular, the inference ability of large language models such as ChatGPT is improving at a rapid pace through prompt engineering techniques. This reasoning ability can be considered as an important factor for companies that want to adopt artificial intelligence into their workflows or for individuals looking to utilize it. In this paper, we begin with an understanding of in-context learning that enables inference in large language models, explain the concept of prompt engineering, inference with in-context learning, and benchmark data. Moreover, we investigate the prompt engineering techniques that have rapidly improved the inference performance of large language models, and the relationship between the techniques.

Applications and Concerns of Generative AI: ChatGPT in the Field of Occupational Health (산업보건분야에서의 생성형 AI: ChatGPT 활용과 우려)

  • Ju Hong Park;Seunghon Ham
    • Journal of Korean Society of Occupational and Environmental Hygiene
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    • v.33 no.4
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    • pp.412-418
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    • 2023
  • As advances in artificial intelligence (AI) increasingly approach areas once relegated to the realm of science fiction, there is growing public interest in using these technologies for practical everyday tasks in both the home and the workplace. This paper explores the applications of and implications for of using ChatGPT, a conversational AI model based on GPT-3.5 and GPT-4.0, in the field of occupational health and safety. After gaining over one million users within five days of its launch, ChatGPT has shown promise in addressing issues ranging from emergency response to chemical exposure to recommending personal protective equipment. However, despite its potential usefulness, the integration of AI into scientific work and professional settings raises several concerns. These concerns include the ethical dimensions of recognizing AI as a co-author in academic publications, the limitations and biases inherent in the data used to train these models, legal responsibilities in professional contexts, and potential shifts in employment following technological advances. This paper aims to provide a comprehensive overview of these issues and to contribute to the ongoing dialogue on the responsible use of AI in occupational health and safety.

A Case Study on Metadata Extractionfor Records Management Using ChatGPT (챗GPT를 활용한 기록관리 메타데이터 추출 사례연구)

  • Minji Kim;Sunghee Kang;Hae-young Rieh
    • Journal of Korean Society of Archives and Records Management
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    • v.24 no.2
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    • pp.89-112
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    • 2024
  • Metadata is a crucial component of record management, playing a vital role in properly managing and understanding the record. In cases where automatic metadata assignment is not feasible, manual input by records professionals becomes necessary. This study aims to alleviate the challenges associated with manual entry by proposing a method that harnesses ChatGPT technology for extracting records management metadata elements. To employ ChatGPT technology, a Python program utilizing the LangChain library was developed. This program was designed to analyze PDF documents and extract metadata from records through questions, both with a locally installed instance of ChatGPT and the ChatGPT online service. Multiple PDF documents were subjected to this process to test the effectiveness of metadata extraction. The results revealed that while using LangChain with ChatGPT-3.5 turbo provided a secure environment, it exhibited some limitations in accurately retrieving metadata elements. Conversely, the ChatGPT-4 online service yielded relatively accurate results despite being unable to handle sensitive documents for security reasons. This exploration underscores the potential of utilizing ChatGPT technology to extract metadata in records management. With advancements in ChatGPT-related technologies, safer and more accurate results are expected to be achieved. Leveraging these advantages can significantly enhance the efficiency and productivity of tasks associated with managing records and metadata in archives.

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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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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    • v.12 no.3
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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.

Evaluating the Current State of ChatGPT and Its Disruptive Potential: An Empirical Study of Korean Users

  • Jiwoong Choi;Jinsoo Park;Jihae Suh
    • Asia pacific journal of information systems
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    • v.33 no.4
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    • pp.1058-1092
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    • 2023
  • This study investigates the perception and adoption of ChatGPT (a large language model (LLM)-based chatbot created by OpenAI) among Korean users and assesses its potential as the next disruptive innovation. Drawing on previous literature, the study proposes perceived intelligence and perceived anthropomorphism as key differentiating factors of ChatGPT from earlier AI-based chatbots. Four individual motives (i.e., perceived usefulness, ease of use, enjoyment, and trust) and two societal motives (social influence and AI anxiety) were identified as antecedents of ChatGPT acceptance. A survey was conducted within two Korean online communities related to artificial intelligence, the findings of which confirm that ChatGPT is being used for both utilitarian and hedonic purposes, and that perceived usefulness and enjoyment positively impact the behavioral intention to adopt the chatbot. However, unlike prior expectations, perceived ease-of-use was not shown to exert significant influence on behavioral intention. Moreover, trust was not found to be a significant influencer to behavioral intention, and while social influence played a substantial role in adoption intention and perceived usefulness, AI anxiety did not show a significant effect. The study confirmed that perceived intelligence and perceived anthropomorphism are constructs that influence the individual factors that influence behavioral intention to adopt and highlights the need for future research to deconstruct and explore the factors that make ChatGPT "enjoyable" and "easy to use" and to better understand its potential as a disruptive technology. Service developers and LLM providers are advised to design user-centric applications, focus on user-friendliness, acknowledge that building trust takes time, and recognize the role of social influence in adoption.