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Title: explainable ai: current status and future directions.
Abstract: Explainable Artificial Intelligence (XAI) is an emerging area of research in the field of Artificial Intelligence (AI). XAI can explain how AI obtained a particular solution (e.g., classification or object detection) and can also answer other "wh" questions. This explainability is not possible in traditional AI. Explainability is essential for critical applications, such as defense, health care, law and order, and autonomous driving vehicles, etc, where the know-how is required for trust and transparency. A number of XAI techniques so far have been purposed for such applications. This paper provides an overview of these techniques from a multimedia (i.e., text, image, audio, and video) point of view. The advantages and shortcomings of these techniques have been discussed, and pointers to some future directions have also been provided.
Subjects: | Machine Learning (cs.LG); Artificial Intelligence (cs.AI) |
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Frontiers in Sport Research , 2024, 6(5); doi: 10.25236/FSR.2024.060508 .
Research on the Path of Artificial Intelligence Enabling Free Diving Training
Zhang Zhenyu
School of Sports Science, Lingnan Normal University, Zhanjiang City, 524048, China
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With the integration of artificial intelligence (AI) technology, its value in the field of sports training has become increasingly prominent. Specifically in the extreme sport of free diving, the involvement of AI has opened up new horizons for the innovation and upgrading of training methods. This article explores the potential of AI in free diving training and constructs a framework for AI-based free diving training. The framework is grounded in the theory of digital intelligence empowerment, leveraging data collection, processing, and in-depth analysis to accurately grasp the athlete's status and provide personalized guidance and real-time feedback. Additionally, the integration of virtual reality technology creates an immersive training environment, enhancing the authenticity and sense of participation. AI enables free diving training to reach new heights, improving efficiency and safety. In the future, AI will continue to play a role in the field of sports training, bringing more possibilities to athletes. This research first explores the inherent logic of AI-enabled free diving training, clarifying the core elements such as data-driven, personalized guidance, intelligent monitoring, and interactive experiences. Secondly, by referring to international successful cases and experiences, this study proposes a localized practical framework, encompassing the construction of technical systems, organizational systems, and environmental spaces. The technical system is responsible for data collection, processing, and analysis, providing scientific and precise training guidance for athletes. The organizational system ensures the smooth implementation and effective management of the project. Meanwhile, the environmental space provides necessary physical and virtual training spaces for athletes. Through empirical research, this article validates the effectiveness and practicality of the framework, providing new ideas and methods for the innovation and development of free diving training. This research not only enriches the application research of AI in the field of sports training, but also provides strong support for the sustainable development of free diving. In the future, with the continuous advancement of technology and the expansion of application scenarios, the application of AI in free diving training will become more extensive and in-depth.
Artificial Intelligence; Free Diving Training; Digital Intelligence Empowerment
Cite This Paper
Zhang Zhenyu. Research on the Path of Artificial Intelligence Enabling Free Diving Training. Frontiers in Sport Research (2024) Vol. 6, Issue 5: 48-54. https://doi.org/10.25236/FSR.2024.060508.
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The International Journal of Indian Psychȯlogy
Sociological Analysis of Artificial Intelligence, Benefits, Concerns and it’s Future Implications
| Published: September 05, 2024
This paper conducts a sociological analysis of artificial intelligence (AI), examining its benefits, concerns, and future implications for society. Through a multidimensional lens, it explores how AI technologies shape social structures, relationships, and cultural norms. The study highlights the potential benefits of AI, including increased efficiency, innovation, and accessibility across various sectors such as healthcare, education, and transportation. However, it also addresses significant concerns such as job displacement, privacy infringement, and bias in AI algorithms, which have profound societal implications. Drawing on sociological theories and empirical research, this paper investigates how AI influences social dynamics, power structures, and identity formation, as well as its impact on labor markets, inequality, and human-machine interactions. Additionally, it examines the ethical, legal, and regulatory challenges posed by AI and explores strategies to address these issues while fostering responsible AI development and deployment. By synthesizing existing literature, case studies, and sociological insights, this paper provides a comprehensive understanding of the sociocultural dimensions of AI and offers recommendations for policymakers, technologists, and communities to navigate the complex interplay between AI and society in the future. This paper is totally based on secondary sources of data and not any test has been utilized to carry out the research.
Sociological Analysis , Artificial Intelligence , Benefits , Concerns , Future Implications
This is an Open Access Research distributed under the terms of the Creative Commons Attribution License (www.creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any Medium, provided the original work is properly cited.
© 2024, Warr, M.A. & Rather, M.S.
Received: August 26, 2024; Revision Received: September 01, 2024; Accepted: September 05, 2024
Dr. Mohd Sultan Rather @ [email protected]
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Published in Volume 12, Issue 3, July-September, 2024
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