The Future of AI-Generated Content（AIGC）
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: 15 February 2025 | Viewed by 354
Special Issue Editor
Special Issue Information
Dear Colleagues,
Due to the exponential increase in AI-generated content (AIGC) in various industrial applications, this Special Issue aims to explore the current state and future potential of AIGC. It collects high-quality literature reviews, mapping studies, technical, multidisciplinary, and cross-disciplinary advancements in AI content generation.
The Special Issue on “The Future of AI-Generated Content (AIGC)” invites contributions on a variety of topics related to advancements in AI content generation. This includes novel algorithms and models for generating text, images, audio, and video, as well as improvements in natural language processing and understanding for content creation. Submissions may include case studies and applications of AI in content creation across different industries. We also seek papers that discuss methods for assessing the quality and authenticity of AI-generated content, explore human–AI collaboration in content creation, and present comparative studies between human-generated and AI-generated content.
Future directions and emerging trends in AI content generation are also of great interest. Papers that provide predictions for the future development of AI-generated content, cross-disciplinary perspectives on its impact, and innovative uses of AI in generating interactive and immersive content are encouraged. This Special Issue aims to provide a comprehensive overview of the current state and future potential of AI-generated content, fostering a deeper understanding of its possibilities, applications in various domains, and challenges.
The topics include, but are not limited to, the following:
- Prompt engineering;
- Prompt effectiveness methods;
- Algorithms for AIGC for various input and output formats;
- Quality assessments for AIGC;
- Metrics for evaluation of AIGC;
- User interfaces for AIGC;
- User experience and human factors in AIGC;
- Security and privacy issues in AIGC;
- Identifying deepfake content;
- Fake news identification;
- AIGC chatbots;
- Retrieval augmented generation (RAG);
- Future challenges.
Dr. Ajay Bandi
Guest Editor
Manuscript Submission Information
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Keywords
- AIGC
- generative AI
- prompt engineering
- fake news identification
- AIGC chatbots
- retrieval augmented generation (RAG)
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