• 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.

• Korea Information Processing Society Review
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• v.30 no.1
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• pp.26-34
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• 2023

• Proceedings of the Korean Institute of Landscape Architecture Conference
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• 2023.10a
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• pp.42-43
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• 2023

• Magazine of the Korean Society of Agricultural Engineers
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• v.66 no.2
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• pp.2-9
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• 2024

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.13-21
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• 2022

Recent deep learning-based research shows excellent performance in most natural language processing (NLP) fields with pre-trained language models. In particular, the auto-encoder-based language model proves its excellent performance and usefulness in various fields of Korean language understanding. However, the decoder-based Korean generative model even suffers from generating simple sentences. Also, there is few detailed research and data for the field of conversation where generative models are most commonly utilized. Therefore, this paper constructs multi-turn dialogue data for a Korean generative model. In addition, we compare and analyze the performance by improving the dialogue ability of the generative model through transfer learning. In addition, we propose a method of supplementing the insufficient dialogue generation ability of the model by extracting recommended response candidates from external knowledge information through a retrival model.

• Broadcasting and Media Magazine
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• v.26 no.1
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• pp.31-37
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• 2021

코로나로 인해 사회는 급속한 변화를 겪고 있고, 그 변화의 중심에는 온라인 플랫폼 기업과 서비스가 있다. AI 기술의 발전 속도는 여전히 가속되고 있고, 특히 음성 합성과 실시간 동작 인식, 아바타 생성 기술은 콘텐츠 생성 및 비대면 서비스에서 그 활용이 더욱 기대된다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.71-77
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• 2021

Recently, there is a demand for efficient program development of an IoT application support frameworks considering heterogeneous hardware characteristics. In addition, the scope of hardware support is expanding with the development of neuromorphic architecture that mimics the human brain to learn on their own and enables autonomous computing. However, most existing IoT IDE(Integrated Development Environment), it is difficult to support AI(Artificial Intelligence) or to support services combined with various hardware such as neuromorphic architectures. In this paper, we design an AI component abstract model that supports the second-generation ANN(Artificial Neural Network) and the third-generation SNN(Spiking Neural Network), and implemented an autonomous IoT IDE based on the proposed model. IoT developers can automatically create AI components through the proposed technique without knowledge of AI and SNN. The proposed technique is flexible in code conversion according to runtime, so development productivity is high. Through experimentation of the proposed method, it was confirmed that the conversion delay time due to the VCL(Virtual Component Layer) may occur, but the difference is not significant.

• Convergence Security Journal
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• v.23 no.5
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• pp.117-123
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• 2023

Recently, as the demand for Generative Artificial Intelligence (AI) and artificial intelligence has increased, the seriousness of misuse and abuse has emerged. However, intelligent CCTV, which maximizes detection of abnormal behavior, is of great help to prevent crime in the military and police. AI performs learning as taught by humans and then proceeds with self-learning. Since AI makes judgments according to the learned results, it is necessary to clearly understand the characteristics of learning. However, it is often difficult to visually judge strange and abnormal behaviors that are ambiguous even for humans to judge. It is very difficult to learn this with the eyes of artificial intelligence, and the result of learning is very many False Positive, False Negative, and True Negative. In response, this paper presented standards and methods for clarifying the learning of AI's strange and abnormal behaviors, and presented learning measures to maximize the judgment ability of intelligent CCTV's False Positive, False Negative, and True Negative. Through this paper, it is expected that the artificial intelligence engine performance of intelligent CCTV currently in use can be maximized, and the ratio of False Positive and False Negative can be minimized..

• Journal of Internet Computing and Services
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• v.18 no.2
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• pp.43-51
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• 2017

As the game industry is blooming, the generation of contents is far behind the consumption of contents. With this reason, it is necessary to afford the game contents considering level of game player's skill. In order to effectively solve this problem, Procedural Content Generation(PCG) using Artificial Intelligence(AI) is one of the plausible options. This paper proposes the procedural method to generate various monsters considering level of player's skill using genetic algorithm. One gene consists of the properties of a monster and one genome consists of genes for various monsters. A generated monster is evaluated by battle simulation with a player and then goes through selection and crossover steps. Using our proposed scheme, players adaptive monsters are generated procedurally based on genetic algorithm and the variety of monsters which are generated with different number of genome is compared.

• 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.