• Title/Summary/Keyword: AI characteristics

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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.

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

  • Jong-woan Choi
    • Convergence Security Journal
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    • v.24 no.2
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    • pp.9-17
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    • 2024
  • This paper examines the security threats to enterprise Generative Artificial Intelligence systems and proposes countermeasures. As AI systems handle vast amounts of data to gain a competitive edge, security threats targeting AI systems are rapidly increasing. Since AI security threats have distinct characteristics compared to traditional human-oriented cybersecurity threats, establishing an AI-specific response system is urgent. This study analyzes the importance of AI system security, identifies key threat factors, and suggests technical and managerial countermeasures. Firstly, it proposes strengthening the security of IT infrastructure where AI systems operate and enhancing AI model robustness by utilizing defensive techniques such as adversarial learning and model quantization. Additionally, it presents an AI security system design that detects anomalies in AI query-response processes to identify insider threats. Furthermore, it emphasizes the establishment of change control and audit frameworks to prevent AI model leakage by adopting the cyber kill chain concept. As AI technology evolves rapidly, by focusing on AI model and data security, insider threat detection, and professional workforce development, companies can improve their digital competitiveness through secure and reliable AI utilization.

Perceptions of Benefits and Risks of AI, Attitudes toward AI, and Support for AI Policies (AI의 혜택 및 위험성 인식과 AI에 대한 태도, 정책 지지의 관계)

  • Lee, Jayeon
    • The Journal of the Korea Contents Association
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    • v.21 no.4
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    • pp.193-204
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    • 2021
  • Based on risk-benefit theory, this study examined a structural equation model accounting for the mechanisms through which affective perceptions of AI predicting individuals' support for the government's Ai policies. Four perceived characteristics of AI (i.e., usefulness, entertainment value, privacy concern, threat of human replacement) were investigated in relation to perceived benefits/risks, attitudes toward AI, and AI policy support, based on a nationwide sample of South Korea (N=352). The hypothesized model was well supported by the data: Perceived usefulness was a strong predictor of perceived benefit, which in turn predicted attitude and support. Perceived benefit and attitude played significant roles as mediators. Perceived entertainment value along with perceived usefulness and privacy concern predicted attitude, not perceived benefit. Neither attitude nor support was significantly associated with perceived risk which was predicted by privacy concern. Theoretical and practical implications of the results are discussed.

A Case Study of Creative Art Based on AI Generation Technology

  • Qianqian Jiang;Jeanhun Chung
    • International journal of advanced smart convergence
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    • v.12 no.2
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    • pp.84-89
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    • 2023
  • In recent years, with the breakthrough of Artificial Intelligence (AI) technology in deep learning algorithms such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAE), AI generation technology has rapidly expanded in various sub-sectors in the art field. 2022 as the explosive year of AI-generated art, especially in the creation of AI-generated art creative design, many excellent works have been born, which has improved the work efficiency of art design. This study analyzed the application design characteristics of AI generation technology in two sub fields of artistic creative design of AI painting and AI animation production , and compares the differences between traditional painting and AI painting in the field of painting. Through the research of this paper, the advantages and problems in the process of AI creative design are summarized. Although AI art designs are affected by technical limitations, there are still flaws in artworks and practical problems such as copyright and income, but it provides a strong technical guarantee in the expansion of subdivisions of artistic innovation and technology integration, and has extremely high research value.

A study of Artificial Intelligence (AI) Speaker's Development Process in Terms of Social Constructivism: Focused on the Products and Periodic Co-revolution Process (인공지능(AI) 스피커에 대한 사회구성 차원의 발달과정 연구: 제품과 시기별 공진화 과정을 중심으로)

  • Cha, Hyeon-ju;Kweon, Sang-hee
    • Journal of Internet Computing and Services
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    • v.22 no.1
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    • pp.109-135
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    • 2021
  • his study classified the development process of artificial intelligence (AI) speakers through analysis of the news text of artificial intelligence (AI) speakers shown in traditional news reports, and identified the characteristics of each product by period. The theoretical background used in the analysis are news frames and topic frames. As analysis methods, topic modeling and semantic network analysis using the LDA method were used. The research method was a content analysis method. From 2014 to 2019, 2710 news related to AI speakers were first collected, and secondly, topic frames were analyzed using Nodexl algorithm. The result of this study is that, first, the trend of topic frames by AI speaker provider type was different according to the characteristics of the four operators (communication service provider, online platform, OS provider, and IT device manufacturer). Specifically, online platform operators (Google, Naver, Amazon, Kakao) appeared as a frame that uses AI speakers as'search or input devices'. On the other hand, telecommunications operators (SKT, KT) showed prominent frames for IPTV, which is the parent company's flagship business, and 'auxiliary device' of the telecommunication business. Furthermore, the frame of "personalization of products and voice service" was remarkable for OS operators (MS, Apple), and the frame for IT device manufacturers (Samsung) was "Internet of Things (IoT) Integrated Intelligence System". The econd, result id that the trend of the topic frame by AI speaker development period (by year) showed a tendency to develop around AI technology in the first phase (2014-2016), and in the second phase (2017-2018), the social relationship between AI technology and users It was related to interaction, and in the third phase (2019), there was a trend of shifting from AI technology-centered to user-centered. As a result of QAP analysis, it was found that news frames by business operator and development period in AI speaker development are socially constituted by determinants of media discourse. The implication of this study was that the evolution of AI speakers was found by the characteristics of the parent company and the process of co-evolution due to interactions between users by business operator and development period. The implications of this study are that the results of this study are important indicators for predicting the future prospects of AI speakers and presenting directions accordingly.

A Methodology for SDLC of AI-based Defense Information System (AI 기반 국방정보시스템 개발 생명주기 단계별 보안 활동 수행 방안)

  • Gyu-do Park;Young-ran Lee
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.3
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    • pp.577-589
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    • 2023
  • Ministry of National Defense plans to harness AI as a key technology to bolster overall defense capability for cultivation of an advanced strong military based on science and technology based on Defense Innovation 4.0 Plan. However, security threats due to the characteristics of AI can be a real threat to AI-based defense information system. In order to solve them, systematic security activities must be carried out from the development stage. This paper proposes security activities and considerations that must be carried out at each stage of AI-based defense information system. Through this, It is expected to contribute to preventing security threats caused by the application of AI technology to the defense field and securing the safety and reliability of defense information system.

AB9: A neural processor for inference acceleration

  • Cho, Yong Cheol Peter;Chung, Jaehoon;Yang, Jeongmin;Lyuh, Chun-Gi;Kim, HyunMi;Kim, Chan;Ham, Je-seok;Choi, Minseok;Shin, Kyoungseon;Han, Jinho;Kwon, Youngsu
    • ETRI Journal
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    • v.42 no.4
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    • pp.491-504
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    • 2020
  • We present AB9, a neural processor for inference acceleration. AB9 consists of a systolic tensor core (STC) neural network accelerator designed to accelerate artificial intelligence applications by exploiting the data reuse and parallelism characteristics inherent in neural networks while providing fast access to large on-chip memory. Complementing the hardware is an intuitive and user-friendly development environment that includes a simulator and an implementation flow that provides a high degree of programmability with a short development time. Along with a 40-TFLOP STC that includes 32k arithmetic units and over 36 MB of on-chip SRAM, our baseline implementation of AB9 consists of a 1-GHz quad-core setup with other various industry-standard peripheral intellectual properties. The acceleration performance and power efficiency were evaluated using YOLOv2, and the results show that AB9 has superior performance and power efficiency to that of a general-purpose graphics processing unit implementation. AB9 has been taped out in the TSMC 28-nm process with a chip size of 17 × 23 ㎟. Delivery is expected later this year.

A Study on the Factors Affecting Continuous Use of AI Speaker Using SNA (SNA를 이용한 AI 스피커 지속적 사용에 영향을 미치는 요인 분석 연구: 아마존 에코 리뷰 중심으로)

  • Kim, Young Bum;Cha, Kyung Jin
    • The Journal of Society for e-Business Studies
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    • v.26 no.4
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    • pp.95-118
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    • 2021
  • As the AI speaker business has risen significantly in recent years, the potential for numerous uses of AI speakers has gotten a lot of attention. Consumers have created an environment in which they can express and share their experiences with products through various channels, resulting in a large number of reviews that leave consumers with a variety of candid opinions about their experiences, which can be said to be very useful in analyzing consumers' thoughts. Using this review data, this study aimed to examine the factors driving the continued use of AI speakers. Above all, it was determined whether the seven characteristics associated with the intention to adopt AI identified in prior studies appear in consumer reviews. Based on customer review data on Amazon.com, text mining and social network analysis were utilized to examine Amazon eco-products. CONCOR analysis was used to classify words with similar connectivity locations, and Connection centrality analysis was used to classify the factors influencing the continuous use of AI speakers, focusing on the connectivity between words derived by classifying review data into positive and negative reviews. Consumers regarded personality and closeness as the most essential characteristics impacting the continued usage of AI speakers as a result of the favorable review survey. These two parameters had a strong correlation with other variables, and connectedness, in addition to the components established from prior studies, was a significant factor. Furthermore, additional negative review research revealed that recognition failures and compatibility are important problems that deter consumers from utilizing AI speakers. This study will give specific solutions for consumers to continue to utilize Amazon eco products based on the findings of the research.

A Study on the ${AI_2}{O_3}$/ and ${SnO_2}-{AI_2}{O_3}$/AI Thin Film Humidity Sensors (${AI_2}{O_3}$/ AI 및 ${SnO_2}-{AI_2}{O_3}$/AI박막습도 센서에 관한 연구)

  • Jeon, Chun-Saeng
    • Korean Journal of Materials Research
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    • v.4 no.2
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    • pp.159-165
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    • 1994
  • Two kinds of humidity sensor are made, one by anodizing pure aluminum and the other by evaporation Sn02 on the anodized pure alumia film, and their electrical characteristics are investigated in various humidity atmosphere. The change of surface resistance with humidity of $AI_2O_3/AI$ and $SnO_2-AI_2O_3/Al$ sensors are found to be $1.40 \times 10^{-2}\Omega$/RH and $1.56 \times 10^{-2}\Omega$/RH, respectively. The hysteresis phenomena associated with the irreversibility of surface resistance-humidity is less in $SnO_2-AI_2O_3/Al$ sensor than in $AI_2O_3/AI$. It is concluded that $SnO_2-AI_2O_3/Al$ film can be used as humidity sensor in room temperature region because temperature dependence of surface resistance of the film is found to be as $0.56 \times 10^{-2} \Omega /^{\circ}C$ in O~ $20^{\circ}C$ range, where as $2.50 \times 10^{-2} \Omega /^{\circ}C$ in 40-$50^{\circ}C$.

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Analysis of User Experience and Usage Behavior of Consumers Using Artificial Intelligence(AI) Devices (인공지능(AI) 디바이스 이용 소비자의 사용행태 및 사용자 경험 분석)

  • Kim, Joon-Hwan
    • Journal of Digital Convergence
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    • v.19 no.6
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    • pp.1-9
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    • 2021
  • Artificial intelligence (AI) devices are rapidly emerging as a core platform of next-generation information and communication technology (ICT), this study investigated consumer usage behavior and user experience through AI devices that are widely applied to consumers' daily lives. To this end, data was collected from 600 consumers with experience in using AI devices were derived to recognize the attributes and behavior of AI devices. The analysis results are as follows. First, music listening was the most used among various attributes and it was found that simple functions such as providing weather information were usefully recognized. Second, the main devices used by AI device users were identified as AI speakers, smartphone, PC and laptops. Third, associative images of AI devices appeared in the order of fun, useful, novel, smart, innovative, and friendly. Therefore, practical implications are suggested to contribute to provision of user services using AI devices in the future by analyzing usage behaviors that reflect the characteristics of AI devices.