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1

Yoon, Young Hyun, Dong Hyun Hwang, Jun Hyeok Yang, and Seung Eun Lee. "Intellino: Processor for Embedded Artificial Intelligence." Electronics 9, no. 7 (2020): 1169. http://dx.doi.org/10.3390/electronics9071169.

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The development of computation technology and artificial intelligence (AI) field brings about AI to be applied to various system. In addition, the research on hardware-based AI processors leads to the minimization of AI devices. By adapting the AI device to the edge of internet of things (IoT), the system can perform AI operation promptly on the edge and reduce the workload of the system core. As the edge is influenced by the characteristics of the embedded system, implementing hardware which operates with low power in restricted resources on a processor is necessary. In this paper, we propose
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2

Ortmeyer, Cliff. "AI Options for Embedded Systems." New Electronics 52, no. 3 (2019): 26–27. http://dx.doi.org/10.12968/s0047-9624(22)60909-x.

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3

Zhang, Zhaoyun, and Jingpeng Li. "A Review of Artificial Intelligence in Embedded Systems." Micromachines 14, no. 5 (2023): 897. http://dx.doi.org/10.3390/mi14050897.

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Advancements in artificial intelligence algorithms and models, along with embedded device support, have resulted in the issue of high energy consumption and poor compatibility when deploying artificial intelligence models and networks on embedded devices becoming solvable. In response to these problems, this paper introduces three aspects of methods and applications for deploying artificial intelligence technologies on embedded devices, including artificial intelligence algorithms and models on resource-constrained hardware, acceleration methods for embedded devices, neural network compression
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4

Gusti, Wahyu Ramadhani. "Embedded System Training Kit for Artificial Intelligence." International Journal of Information and Education Technology 14, no. 1 (2024): 72–80. http://dx.doi.org/10.18178/ijiet.2024.14.1.2026.

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Ever-developing science and technology require us always to be ready to adapt. The current challenging era is Society 5.0, which places a strong emphasis on harnessing human potential to overcome diverse challenges, including the development of Artificial Intelligence (AI) technology. Therefore, to improve the quality of human resources, this paper proposes the development of an artificial intelligence training kit based on embedded systems according to industry needs. The development of a training kit utilizing the RnD method was accomplished through the use of the ADDIE (analysis design, dev
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5

Hwang, Dong Hyun, Chang Yeop Han, Hyun Woo Oh, and Seung Eun Lee. "ASimOV: A Framework for Simulation and Optimization of an Embedded AI Accelerator." Micromachines 12, no. 7 (2021): 838. http://dx.doi.org/10.3390/mi12070838.

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Artificial intelligence algorithms need an external computing device such as a graphics processing unit (GPU) due to computational complexity. For running artificial intelligence algorithms in an embedded device, many studies proposed light-weighted artificial intelligence algorithms and artificial intelligence accelerators. In this paper, we propose the ASimOV framework, which optimizes artificial intelligence algorithms and generates Verilog hardware description language (HDL) code for executing intelligence algorithms in field programmable gate array (FPGA). To verify ASimOV, we explore the
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6

Choudhury, Avishek, and Onur Asan. "Human factors: bridging artificial intelligence and patient safety." Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care 9, no. 1 (2020): 211–15. http://dx.doi.org/10.1177/2327857920091007.

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The recent launch of complex artificial intelligence (AI) in the domain of healthcare has embedded perplexities within patients, clinicians, and policymakers. The opaque and complex nature of artificial intelligence makes it challenging for clinicians to interpret its outcome. Incorrect interpretation and poor utilization of AI might hamper patient safety. The principles of human factors and ergonomics (HFE) can assist in simplifying AI design and consecutively optimize human performance ensuring better understanding of AI outcome, their interaction with the clinical workflow. In this paper, w
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7

Yeo, K. K. "Artificial intelligence in cardiology: did it take off?" Russian Journal for Personalized Medicine 2, no. 6 (2023): 16–22. http://dx.doi.org/10.18705/2782-3806-2022-2-6-16-22.

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Artificial intelligence (AI) has been touted as a paradigm shifting, game-changing development in medicine. Did AI in cardiology take off? In this paper, we discuss some areas within cardiology in which there has some been progress in the implementation of AI technologies. Despite the promise of AI, challenges remain including cybersecurity, implementation and change management difficulties. This paper discusses the use of AI embedded as a ‘black box’ technology in existing diagnostic and interventional tools, AI as an adjunct to diagnostic tools such as echo or CT or MRI scans, AI in commerci
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8

Azizah, Desi, Aji Wibawa, and Laksono Budiarto. "Hakikat Epistemologi Artificial Intelligence." Jurnal Inovasi Teknologi dan Edukasi Teknik 1, no. 8 (2021): 592–98. http://dx.doi.org/10.17977/um068v1i82021p592-598.

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Artificial Intelligence, commonly abbreviated as AI, is a scientifically intelligent entity created by humans. The entity is embedded into a machine, thus making the machine seem capable of thinking on its own to decide. The definition of AI can be viewed from two approaches, namely a scientific approach (A Scientific Approach) and an engineering approach (An Engineering Approach). The way artificial intelligence works is by combining a large amount of data, with a process that is fast, iterative and has an intelligent algorithm. Artificial intelligence is closely related to philosophy because
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9

Almusaed, Amjad, Ibrahim Yitmen, and Asaad Almssad. "Enhancing Smart Home Design with AI Models: A Case Study of Living Spaces Implementation Review." Energies 16, no. 6 (2023): 2636. http://dx.doi.org/10.3390/en16062636.

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The normal development of “smart buildings,” which calls for integrating sensors, rich data, and artificial intelligence (AI) simulation models, promises to usher in a new era of architectural concepts. AI simulation models can improve home functions and users’ comfort and significantly cut energy consumption through better control, increased reliability, and automation. This article highlights the potential of using artificial intelligence (AI) models to improve the design and functionality of smart houses, especially in implementing living spaces. This case study provides examples of how art
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10

Marcinowski, Maciej. "Artificial Intelligence or the Ultimate Tool for Conservatism." DANUBE 13, no. 1 (2022): 1–12. http://dx.doi.org/10.2478/danb-2022-0001.

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Abstract Artificial intelligence (AI) is foremost viewed as a technologically revolutionary tool, however, the author discusses here whether it is in fact a tool for socio-economic and legal conservatism, because its training data is always embedded in the past. The aim of this paper is to explain, exemplify and predict – whether and how – AI could cause discrimination, stagnation and uniformization by conserving what is relayed even by the most representative data. Furthermore, the author aims to propose possible legal barriers to these phenomena. The presented hypotheses are based upon empir
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11

Antonov, Alexander. "Managing complexity: the EU’s contribution to artificial intelligence governance." Revista CIDOB d'Afers Internacionals, no. 131 (September 22, 2022): 41–65. http://dx.doi.org/10.24241/rcai.2022.131.2.41/en.

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With digital ecosystems being questioned around the world, this paper examines the EU’s role in and contribution to the emerging concept of artificial intelligence (AI) governance. Seen by the EU as the key ingredient for innovation, the adoption of AI systems has altered our understanding of governance. Framing AI as an autonomous digital technology embedded in social structures, this paper argues that EU citizens' trust in AI can be increased if the innovation it entails is grounded in a fundamental rights-based approach. This is assessed based on the work of the High-Level Expert Group on A
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12

Tarozzi, Martina Elena. "Artificial intelligence for Next generation sequencing data analysis." Science Reviews. Biology 3, no. 1 (2024): 9–15. http://dx.doi.org/10.57098/scirevs.biology.3.1.2.

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In the rapidly evolving field of genomics, our capacity to decipher genetic data encoded in DNA has been transformed by Next Generation Sequencing (NGS) technologies. These advanced technologies produce an enormous volume of data, posing substantial challenges in extracting meaningful biological insights. Artificial intelligence (AI) algorithms offer distinctive possibilities to unravel the biological information embedded in such extensive and intricate datasets. This review offers a synopsis of AI classifications and algorithms, elucidating how these techniques can be employed on sequencing d
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13

Chu, Charlene, Kathleen Leslie, Shehroz Khan, Rune Nyrup, and Amanda Grenier. "AGEISM IN ARTIFICIAL INTELLIGENCE: A REVIEW." Innovation in Aging 6, Supplement_1 (2022): 663. http://dx.doi.org/10.1093/geroni/igac059.2446.

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Abstract Background Artificial intelligence (AI) has emerged as a major driver of technological development in the 21st century, yet little attention has been paid to algorithmic biases towards older adults. "Digital ageism" is a new form of ageism that is embedded into technology and AI systems. Aim: This review aimed to explore how age-related bias is encoded in AI systems to better understand digital ageism. Methods The scoping review follows a six-stage methodology framework developed by Arksey and O'Malley. The search strategy has been established in six databases and we will investigate
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14

Tkachev, Andrey N. "About the unconscious and the possibility of creativity in artificial intelligence." Digital Scholar: Philosopher`s Lab 7, no. 1 (2024): 56–61. https://doi.org/10.32326/2618-9267-2024-7-1-56-61.

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The article defines the role of the unconscious when considering the possibility of artificial intelligence (AI) creativity. The author proposes a comparison between the work of the unconscious and artificial intelligence. He suggests understanding the volumes of data embedded in AI as an artificial unconscious. Often critics of the creative abilities of AI point to the need for AI programming as an argument. The author criticizes this position because human creativity also requires a certain program. The article also raises the problem of ontology in connection with AI and the controversial l
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15

Krishna, Anirudh. "Will AI Slay the Poverty Dragon?" Current History 123, no. 849 (2024): 37–39. http://dx.doi.org/10.1525/curh.2024.123.849.37.

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The rise of artificial intelligence and other new technologies has raised hopes that they might contribute to reducing poverty. History suggests that they need to be embedded in broader frameworks of institutions, regulations, and training.
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16

Ebule, Amejuma Emmanuel. "Leveraging Artificial Intelligence in Business Intelligence Systems for Predictive Analytics." International Journal of Scientific Research and Management (IJSRM) 13, no. 01 (2025): 1862–79. https://doi.org/10.18535/ijsrm/v13i01.ec02.

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Artificial Intelligence (AI) and Business Intelligence (BI) are rapidly emerging as the next big things for organizations to analyze data and gain insights. As this article will go on to examine, the concept of using AI for BI is one that has significant implications about the possible integration of AI into various Business Intelligence systems examined in this article will focus on the application of AI for BI in the use of predicting analytics. When integrating Machine learning, natural language processing, and intelligent automation, these AI-Advanced BI systems assist organizations to go
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17

Fadillah, Jihan Trie. "Artificial Intelligence In The Electric Vehicle Ecosystem: Adoption; Impact; And Future Prospect." International Student Conference on Business, Education, Economics, Accounting, and Management (ISC-BEAM) 2, no. 1 (2024): 2573–79. http://dx.doi.org/10.21009/isc-beam.012.187.

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Artificial Intelligence (AI) has been around since 1940, namely the first digital computer called Atanasoff Berry Computer (ABC) which aroused the enthusiasm of scientists to develop the idea of making an "electronic brain" or hiding electronic devices in the human brain . With Artificial Intelligence (AI) that can work efficiently, of course, work can be done more easily. The purpose of writing this scientific paper is to explain the use of Artificial Intelligence (AI) in the automotive industry which can make it easier for humans in the future. The method taken by the author is through obser
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18

Nwozor, Blessing U., and Happy Faotu. "Artificial Intelligence and SaaS Embedded System: Enhancing Content Creation Through Contextual Language." International Journal of Research and Innovation in Applied Science IX, no. XI (2024): 161–73. https://doi.org/10.51584/ijrias.2024.911013.

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Artificial Intelligence (AI) has been advancing rapidly, allowing machines to perform tasks commonly done by humans, such as writing, coding, diagnosing diseases, predicting weather patterns, translating languages, providing customer support, etc. As AI becomes more sophisticated, its integration into Software as a Service (SaaS) platforms holds significant potential to enhance productivity for individuals and businesses. The application of AI within SaaS can extend across a wide array of domains, including entertainment, academia, finance, content creation, mathematics, and more. This paper e
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19

Hong, Sungcheol. "Wireless Optogenetic Microsystems Accelerate Artificial Intelligence–Neuroscience Coevolution Through Embedded Closed-Loop System." Micromachines 16, no. 5 (2025): 557. https://doi.org/10.3390/mi16050557.

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Brain-inspired models in artificial intelligence (AI) originated from foundational insights in neuroscience. In recent years, this relationship has been moving toward a mutually reinforcing feedback loop. Currently, AI is significantly contributing to advancing our understanding of neuroscience. In particular, when combined with wireless optogenetics, AI enables experiments without physical constraints. Furthermore, AI-driven real-time analysis facilitates closed-loop control, allowing experimental setups across a diverse range of scenarios. And a deeper understanding of these neural networks
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20

Tyagi, Mukund, Dr Nikhil Sirohi, Dr Pallavi Tyagi, and Kajal Yadav. "Future Trends of B2C Marketing with Artificial Intelligence." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 07 (2025): 1–9. https://doi.org/10.55041/ijsrem51309.

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Artificial Intelligence (AI) is fundamentally transforming business-to-consumer (B2C) marketing by enhancing the ability of brands to understand, engage, and retain customers. This paper investigates the emerging trends shaping the future of B2C marketing through the integration of advanced AI technologies. Key developments such as generative AI, conversational interfaces, emotion AI, and ethical personalization are enabling hyper-personalized content, real-time customer interactions, and deeper emotional engagement. These innovations are not only optimizing marketing strategies but also resha
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21

Jaber, Tanya Abdulsattar. "Artificial intelligence in computer networks." Periodicals of Engineering and Natural Sciences (PEN) 10, no. 1 (2022): 309–22. https://doi.org/10.21533/pen.v10.i1.539.

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Artificial Intelligence (AI) has been defined as a modern and intense scientific topic that enables computer-based systems or embedded systems to divide and solve problems by simulating complex biological procedures that are represented by specific algorithms along with (learning, reasoning, as well as self-correction). The present study provides a detailed assessment and review of applications of various artificial intelligence approaches for the purpose of improving the general efficiency of optical communication structures and networks and network systems in general. Using the AI-based appr
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22

Davenport, Thomas, Abhijit Guha, Dhruv Grewal, and Timna Bressgott. "How artificial intelligence will change the future of marketing." Journal of the Academy of Marketing Science 48, no. 1 (2019): 24–42. http://dx.doi.org/10.1007/s11747-019-00696-0.

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Abstract In the future, artificial intelligence (AI) is likely to substantially change both marketing strategies and customer behaviors. Building from not only extant research but also extensive interactions with practice, the authors propose a multidimensional framework for understanding the impact of AI involving intelligence levels, task types, and whether AI is embedded in a robot. Prior research typically addresses a subset of these dimensions; this paper integrates all three into a single framework. Next, the authors propose a research agenda that addresses not only how marketing strateg
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Karampelas, Konstantinos. "Integration of artificial intelligence in national science curricula." Contemporary Mathematics and Science Education 6, no. 1 (2025): ep25002. https://doi.org/10.30935/conmaths/15883.

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This study investigates the integration of artificial intelligence (AI) in national science curricula across 21 countries, including Australia, Cyprus, Estonia, France, Finland, Greece, Hong Kong, India, Iceland, Ireland, Nepal, New Zealand, Norway, Ontario (Canada), Poland, Singapore, South Africa, South Korea, Sweden, the United Kingdom, and the United States. By analyzing these curricula, the research identifies the presence of AI-related knowledge, skills, and attitudes, providing a comprehensive understanding of how AI is embedded in educational frameworks. The findings reveal a strong em
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Adams, BS, James, Mahmud Hasan, PhD, MS, MEng, and Jacob Thorp, BS. "AI (artificial intelligence)-assisted planning within emergency management operations." Journal of Emergency Management 20, no. 1 (2022): 41–52. http://dx.doi.org/10.5055/jem.0622.

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There is a demand for future technologies to be embedded within emergency management operations. Artificial intelligence (AI) can help save lives and create more efficient systems for emergency management operators to prepare, design, develop, and execute responses to disasters and catastrophes. This study intends to provide insight into how AI can integrate with climate modeling and traffic management systems in response to natural disasters. Research with supporting evidence implies that current technology and frameworks can coexist inside the existing infrastructure and emergency management
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25

Zhang, Xiaojuan, Yongheng Zhang, Feng Zhang, and Xiuyun Yang. "Research of Schema Evolution and Implementation Scheme Optimization in AI-Enabled Embedded Systems." Wireless Communications and Mobile Computing 2021 (August 14, 2021): 1–10. http://dx.doi.org/10.1155/2021/3591427.

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The demand of embedded artificial intelligence system for powerful computing power and diversified application scenarios will inevitably bring some new problems. This paper builds the system dynamics model of embedded system based on artificial intelligence (AI). By analyzing the causal relationship between the elements of the system dynamics model, the state equation is established, and the parameters are estimated and tested. At the same time, the influence of the model simulation experiment on the relevant factors is evaluated. The simulation results show that the proposed model is effectiv
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26

Helanski Cardoso, Juliane Cristina. "Digital images generated by Artificial Intelligence as ethnographic experimentation." Desde el Sur 16, no. 2 (2024): e0023. http://dx.doi.org/10.21142/des-1602-2024-0023.

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The article discusses the role of images produced by artificial intelligence (AI) in visual anthropology, highlighting their ability to represent identity and experience. It also addresses the technical and ethical challenges of AI data classification and its interaction with socio-technical networks, questioning technological neutrality. Technical implications include data categorization that can perpetuate biases and power relations. The simplification and distortion of representations by AI is highlighted, requiring a critical analysis of the stories embedded in the categorizations. It is p
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27

Jinglu, Zhang, and Wang Linna. "Research on Ai Technology of Intelligent Information Visualization Based on Rtos System Service." Journal of Physics: Conference Series 2717, no. 1 (2024): 012018. http://dx.doi.org/10.1088/1742-6596/2717/1/012018.

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Abstract In order to improve the visual interaction ability of intelligent information, an intelligent information visualization artificial intelligence technology based on RTOS system service is proposed in this paper. Based on embedded integrated control, this paper constructs the system design scheme, client and host system of intelligent information visualization artificial intelligence RTOS service system. The information monitoring module, artificial intelligence programmable logic control module, artificial intelligence processing module and human-computer interaction module of intellig
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28

Labayen, Mikel, Laura Medina, Fernando Eizaguirre, José Flich, and Naiara Aginako. "HPC Platform for Railway Safety-Critical Functionalities Based on Artificial Intelligence." Applied Sciences 13, no. 15 (2023): 9017. http://dx.doi.org/10.3390/app13159017.

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The automation of railroad operations is a rapidly growing industry. In 2023, a new European standard for the automated Grade of Automation (GoA) 2 over European Train Control System (ETCS) driving is anticipated. Meanwhile, railway stakeholders are already planning their research initiatives for driverless and unattended autonomous driving systems. As a result, the industry is particularly active in research regarding perception technologies based on Computer Vision (CV) and Artificial Intelligence (AI), with outstanding results at the application level. However, executing high-performance an
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Shadbolt, Nigel. "“From So Simple a Beginning”: Species of Artificial Intelligence." Daedalus 151, no. 2 (2022): 28–42. http://dx.doi.org/10.1162/daed_a_01898.

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Abstract Artificial intelligence has a decades-long history that exhibits alternating enthusiasm and disillusionment for the field's scientific insights, technical accomplishments, and socioeconomic impact. Recent achievements have seen renewed claims for the transformative and disruptive effects of AI. Reviewing the history and current state of the art reveals a broad repertoire of methods and techniques developed by AI researchers. In particular, modern machine learning methods have enabled a series of AI systems to achieve superhuman performance. The exponential increases in computing power
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Shadbolt, Nigel. "“From So Simple a Beginning”: Species of Artificial Intelligence." Daedalus 151, no. 2 (2022): 28–42. http://dx.doi.org/10.1162/daed_a_01898.

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Abstract Artificial intelligence has a decades-long history that exhibits alternating enthusiasm and disillusionment for the field's scientific insights, technical accomplishments, and socioeconomic impact. Recent achievements have seen renewed claims for the transformative and disruptive effects of AI. Reviewing the history and current state of the art reveals a broad repertoire of methods and techniques developed by AI researchers. In particular, modern machine learning methods have enabled a series of AI systems to achieve superhuman performance. The exponential increases in computing power
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31

Garcia-Perez, Asier, Raúl Miñón, Ana I. Torre-Bastida, and Ekaitz Zulueta-Guerrero. "Analysing Edge Computing Devices for the Deployment of Embedded AI." Sensors 23, no. 23 (2023): 9495. http://dx.doi.org/10.3390/s23239495.

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In recent years, more and more devices are connected to the network, generating an overwhelming amount of data. This term that is booming today is known as the Internet of Things. In order to deal with these data close to the source, the term Edge Computing arises. The main objective is to address the limitations of cloud processing and satisfy the growing demand for applications and services that require low latency, greater efficiency and real-time response capabilities. Furthermore, it is essential to underscore the intrinsic connection between artificial intelligence and edge computing wit
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Ko, Ga Eun. "Artificial Intelligence and Your Life: The Problems We Must Face." Science Insights 46, no. 4 (2025): 1799–803. https://doi.org/10.15354/si.25.pe211.

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Artificial intelligence (AI) is transforming human life at an unprecedented pace. From revolutionizing industries and improving health outcomes to shaping how we interact with the world and each other, AI technologies are deeply embedded in modern life. While these systems bring powerful benefits, they also pose serious problems that demand urgent attention. This essay explores key issues related to algorithmic bias, loss of privacy, job displacement, psychological impacts, social inequality, environmental concerns, and inadequate governance. It highlights that as AI continues to evolve, socie
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Songlin Chen, Songlin Chen, Hong Wen Songlin Chen, and Jinsong Wu Hong Wen. "Artificial Intelligence Based Traffic Control for Edge Computing Assisted Vehicle Networks." 網際網路技術學刊 23, no. 5 (2022): 989–96. http://dx.doi.org/10.53106/160792642022092305007.

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<p>Edge computing supported vehicle networks have attracted considerable attention in recent years both from industry and academia due to their extensive applications in urban traffic control systems. We present a general overview of Artificial Intelligence (AI)-based traffic control approaches which focuses mainly on dynamic traffic control via edge computing devices. A collaborative edge computing network embedded in the AI-based traffic control system is proposed to process the massive data from roadside sensors to shorten the real-time response time, which supports efficient traffic
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Ihor, HUNKO. "Adaptive Approaches to Software Testing with Embedded Artificial Intelligence in Dynamic Environments." International Journal of Current Science Research and Review 08, no. 05 (2025): 2036–51. https://doi.org/10.5281/zenodo.15344813.

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Abstract : Artificial intelligence (AI) is rapidly being integrated into application domains such as autonomous vehicles, health care, and cybersecurity; therefore, the requirements for dependable and robust AI-embedded systems are more pressing in these dynamic environments characterized by unpredictable variations in operational conditions. The traditional software testing methodologies that depend on static test cases and a predetermined set of scenarios usually fail to tackle the complexity of modern AI applications, resulting in undetected defects and security vulnerabilities. This study
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Jovanović, Sonja, Lazar Dražeta, Bogdan Dražeta, and Aleksandar Petrović. "Business perspective on exploring the intriguing vistas of artificial intelligence." European Journal of Applied Economics 22, no. 1 (2025): 1–17. https://doi.org/10.5937/ejae22-55443.

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Although the use of artificial intelligence (AI) in everyday life is increasing, the complex nature of AI still prevents its full adoption. The potential of AI is boundless, and it will reshape the reality. How humans perceive the world will forever change with AI tools implemented in embedded devices. Apart from the possibility of changing human perception through augmented reality (AR), AI is also applied in 3D-printing, art, and decoding of ancient communication systems. Moreover, the most important role AI has today is in healthcare. The use of AI tools can contribute to improving the way
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Nugroho, Oktian Fajar, Lisna Hikmawaty, and Silvia Ratna Juwita. "Artificial Intelligence Technology Embedded in High School Science Learning: A Study of Teacher Perception." Pedagonal : Jurnal Ilmiah Pendidikan 8, no. 2 (2024): 132–43. http://dx.doi.org/10.55215/pedagonal.v8i2.16.

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This study examines teachers' perceptions and acceptance of using artificial intelligence (AI) technology in the teaching of Sciences (IPA) in Vocational High Schools (SMK). Based on quantitative and qualitative data, the results indicate that the understanding and use of AI in teaching are still limited. Quantitative data were collected through a structured questionnaire to assess teachers' knowledge, confidence, and AI usage frequency, while qualitative data were obtained through in-depth interviews exploring their views and challenges. Although some teachers see the great potential of AI in
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Podile, Dr Venkateswararao, Kovvuri Priyanka Reddy, Vemareddy Nikhil Sai Reddy, Mekala Surendra Babu, and Adusumalli Karthik Phani. "Artificial Intelligence and Corporate Social Responsibility: Synergies, Challenges, and Future Directions." International Journal of Advanced Multidisciplinary Research and Studies 4, no. 6 (2024): 95–99. http://dx.doi.org/10.62225/2583049x.2024.4.6.3399.

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Corporate social responsibility, or CSR, has been the subject of an increasing amount of interest with the infusion of artificial intelligence or AI. AI may open up much-needed improvements in CSR practice, including better decision-making, transparency, and sustainable benefits, but it also poses challenges related to the ethical concerns of data privacy, bias, and accountability. This paper focuses on how an AI-based approach enhances CSR activities and identifies risks embedded in AI adoption in approaches to CSR. The study combines qualitative interviews with industry experts and quantitat
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Thi Minh, Pham Trang. "The Protection of Human Rights Under the Artificial Intelligence Act." Közigazgatási és Infokommunikációs Jogi PhD Tanulmányok 6, no. 1 (2025): 22–37. https://doi.org/10.47272/kikphd.2025.1.2.

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Artificial intelligence (AI) has developed rapidly and is having a profound impact on society as a whole. AI-driven technologies are now present in sectors such as healthcare, agriculture, food safety, education, media, sports, and culture, where they have the potential to optimize human time and enhance work efficiency. However, the social prospects of AI are both alluring and alarming; its promises and perils are difficult to disentangle. The risks to users have become an increasing concern as AI technologies are embedded in everyday products and services. Furthermore, AI can influence human
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39

Das, Sumit, Manas Kumar Sanyal, and Debamoy Datta. "Artificial Intelligent Embedded Doctor (AIEDr.)." International Journal of Big Data and Analytics in Healthcare 4, no. 2 (2019): 34–56. http://dx.doi.org/10.4018/ijbdah.2019070103.

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This article focuses on the development of a diagnostic model for low back pain management, a mathematical model describing the cause of the disease and an inclusive hardware implementation with artificial intelligence (AI). It has been observed that the greater part of the people in developing countries cannot afford the cost of this treatment due to low financial status. Moreover, a continuous assessment is not made for continuous monitoring of the patient's status. The problem of back pain develops slowly and if some early assessments can be made, then the treatment becomes effective. The p
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40

Humr, Scott, and Mustafa Canan. "Intermediate Judgments and Trust in Artificial Intelligence-Supported Decision-Making." Entropy 26, no. 6 (2024): 500. http://dx.doi.org/10.3390/e26060500.

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Human decision-making is increasingly supported by artificial intelligence (AI) systems. From medical imaging analysis to self-driving vehicles, AI systems are becoming organically embedded in a host of different technologies. However, incorporating such advice into decision-making entails a human rationalization of AI outputs for supporting beneficial outcomes. Recent research suggests intermediate judgments in the first stage of a decision process can interfere with decisions in subsequent stages. For this reason, we extend this research to AI-supported decision-making to investigate how int
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41

Garg, Puru, and Binayak Dutta. "Impact of Artificial Intelligence on Everyday Life." International Journal of Innovative Research in Science,Engineering and Technology 13, no. 05 (2024): 9972–79. http://dx.doi.org/10.15680/ijirset.2024.1305567.

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This research paper will tell you about how the AI is helping us in our daily lives. How it is making not only our lives. Have you ever thought about how artificial intelligence (AI) is changing the game in our daily lives? From smart home appliances to virtual assistants, artificial intelligence tools are used in many areas of our daily lives. This what I mean is a game changer. That's the beauty of artificial intelligence; It makes life easier by taking control of all those annoying tasks and programs. Plus, isn't it amazing how chatbots and translation tools are changing the way we communic
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42

Luo, Man, and Xuan Xiao. "THE IMPACT OF AI-EMBEDDED ENTERPRISE SOCIAL MEDIA USAGE ON EMPLOYEES' KNOWLEDGE SHARING BEHAVIOR." EUrASEANs: journal on global socio-economic dynamics, no. 6(49) (December 1, 2024): 589–602. https://doi.org/10.35678/2539-5645.6(49).2024.589-602.

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With the rapid advancement of artificial intelligence (AI) technology, embedding AI into enterprise social media has become a common practice for employees in online work, exerting a profound influence on their psychology and behavior. However, how AI-embedded enterprise social media (AI-embedded ESM) affects employees' knowledge sharing remains unclear. Based on the theory of psychological empowerment (PE), this paper constructs two types of AI-embedded enterprise social media usage—Task-Oriented and Social-Oriented -and examines their impact on employees' willingness to engage in knowledge-s
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43

Blackledge, Jonathan, and Napo Mosola. "Applications of Artificial Intelligence to Cryptography." Transactions on Machine Learning and Artificial Intelligence 8, no. 3 (2020): 21–60. http://dx.doi.org/10.14738/tmlai.83.8219.

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This paper considers some recent advances in the field of Cryptography using Artificial Intelligence (AI) It specifically considers the applications of Machine Learning (ML) and Evolutionary Computing (EC) concepts used to generate ciphers. A short overview is given on Artificial Neural Networks (ANNs) and the principles of Deep Learning (DL) using Deep ANNs. In this context, the paper considers: (i) the implementation of EC and ANNs to generate unique and unclonable ciphers; (ii) ML strategies for detecting the genuine randomness (or otherwise) of binary streams for applications in Cryptanaly
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44

Gnacy-Gajdzik, Anna, and Piotr Przystałka. "Automating the Analysis of Negative Test Verdicts: A Future-Forward Approach Supported by Augmented Intelligence Algorithms." Applied Sciences 14, no. 6 (2024): 2304. http://dx.doi.org/10.3390/app14062304.

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In the epoch characterized by the anticipation of autonomous vehicles, the quality of the embedded system software, its reliability, safety, and security is significant. The testing of embedded software is an increasingly significant element of the development process. The application of artificial intelligence (AI) algorithms in the process of testing embedded software in vehicles constitutes a significant area of both research and practical consideration, arising from the escalating complexity of these systems. This paper presents the preliminary development of the AVESYS framework which fac
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45

Gembaczka, Pierre, Burkhard Heidemann, Bernhard Bennertz, Wolfgang Groeting, Thomas Norgall, and Karsten Seidl. "Combination of sensor-embedded and secure server-distributed artificial intelligence for healthcare applications." Current Directions in Biomedical Engineering 5, no. 1 (2019): 29–32. http://dx.doi.org/10.1515/cdbme-2019-0008.

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AbstractThe application of artificial intelligence (AI) in the areas of health, care and social participation offers great opportunities but also involves great challenges. Extensive regulatory, ethical and data-security related requirements exist for data recording, storage and processing of respective personalized and patient-related data. “Artificial Intelligence as a Service” (AIaaS) is pushed for consumer applications by global players, which implies data storage on external database server. However, the available solutions do not meet the requirements. Moreover, small and medium-sized en
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46

Suleiman, Dawud Adaviruku, Tahir Mumtaz Awan, and Maria Javed. "Enhancing digital marketing performance through usage intention of AI-powered websites." IAES International Journal of Artificial Intelligence (IJ-AI) 10, no. 4 (2021): 810. http://dx.doi.org/10.11591/ijai.v10.i4.pp810-817.

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<p><span>Digital and wireless technology are a crucial part of today’s modern life. Artificial intelligence (AI) uses different technologies and systems for speech recognition, visual perception and decision making to mimic human functions. This study explores the impact of AI on website interactivity and the ease of use for enhancing digital marketing performance. The methodology used is qualitative with structured interviews, using three artificial intelligence-powered websites (Amazon, Alibaba, and Uber) as reference. The participants' structured interview responses were grouped
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47

Rodrigues, Leonel Cezar, Reziere Dagobi da Silva, Simone Maria Espinosa, and Valeria Riscarolli. "Artificial Intelligence, Ethics and Speed Processing in the Law System." Journal of Law and Corruption Review 6 (August 30, 2024): e084. http://dx.doi.org/10.37497/corruptionreview.6.2024.84.

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Objective: This study aims to demonstrate how the use of generative Artificial Intelligence (AI) fosters innovation within the Judiciary by enhancing the operational performance of the legal system. Methodology: The research adopts an explanatory qualitative approach with a theoretical foundation. It relies on secondary data and documentary evidence sourced from specialized literature. Results: The findings suggest that generative AI significantly expands the operational capacity of judges and legal professionals by automating repetitive tasks and facilitating the generation of legal sentences
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48

Rodrigues, Leonel Cezar, da Silva Reziere Dagobi, Simone Maria Espinosa, and Valeria Riscarolli. "Artificial Intelligence, Ethics and Speed Processing in the Law System." Journal of Law and Corruption Review 6 (October 16, 2024): 01–19. https://doi.org/10.37497/CorruptionReview.6.2024.84.

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<strong>Objective:</strong> This study aims to demonstrate how the use of generative Artificial Intelligence (AI) fosters innovation within the Judiciary by enhancing the operational performance of the legal system. <strong>Methodology:</strong> The research adopts an explanatory qualitative approach with a theoretical foundation. It relies on secondary data and documentary evidence sourced from specialized literature. <strong>Results:</strong> The findings suggest that generative AI significantly expands the operational capacity of judges and legal professionals by automating repetitive tasks
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49

Schwabe, Nils, Yexu Zhou, Leon Hielscher, Tobias Röddiger, Till Riedel, and Sebastian Reiter. "Tools and methods for Edge-AI-systems." at - Automatisierungstechnik 70, no. 9 (2022): 767–76. http://dx.doi.org/10.1515/auto-2022-0023.

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Abstract The enormous potential of artificial intelligence, especially artificial neural networks, when used for edge computing applications in cars, traffic lights or smart watches, has not yet been fully exploited today. The reasons for this are the computing, energy and memory requirements of modern neural networks, which typically cannot be met by embedded devices. This article provides a detailed summary of today’s challenges and gives a deeper insight into existing solutions that enable neural network performance with modern HW/SW co-design techniques.
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50

Bavli, Itai, and Sandro Galea. "Key considerations in the adoption of Artificial Intelligence in public health." PLOS Digital Health 3, no. 7 (2024): e0000540. http://dx.doi.org/10.1371/journal.pdig.0000540.

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The integration of Artificial Intelligence (AI) into public health has the potential to transform the field, influencing healthcare at the population level. AI can aid in disease surveillance, diagnosis, and treatment decisions, impacting how healthcare professionals deliver care. However, it raises critical questions about inputs, values, and biases that must be addressed to ensure its effectiveness. This article investigates the factors influencing the values guiding AI technology and the potential consequences for public health. It outlines four key considerations that should shape discussi
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