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Exploring Generative AI: A Systematic Review of Research Trends and Future Directions

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This paper presents a systematic review of generative artificial intelligence (GAI), analyzing 1319 records from Scopus to identify key themes and challenges in the field. It reveals seven clusters of topics, including image processing, content generation, and data privacy. The authors call for further research in areas like explainability and multi-modal generation.
  • main points
  • unique insights
  • practical applications
  • key topics
  • key insights
  • learning outcomes

  • • main points

    • 1
      Comprehensive analysis of GAI research landscape
    • 2
      Identification of key challenges and opportunities in GAI
    • 3
      Thorough examination of diverse application areas in GAI

  • • unique insights

    • 1
      Emerging themes in GAI research such as cognitive inference and planning
    • 2
      Importance of addressing data privacy and security in GAI

  • • practical applications

    • The article provides valuable insights for researchers and practitioners in GAI, highlighting current trends and future research directions.

  • • key topics

    • 1
      Generative artificial intelligence
    • 2
      Topic modeling techniques
    • 3
      Data privacy and security in GAI

  • • key insights

    • 1
      Systematic review methodology applied to GAI
    • 2
      Identification of seven distinct research clusters
    • 3
      Call for further exploration of GAI challenges

  • • learning outcomes

    • 1
      Understand the current landscape of generative AI research
    • 2
      Identify key challenges and opportunities in GAI
    • 3
      Explore emerging themes and applications in generative AI
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“ Introduction to Generative AI

This study employs a systematic review methodology, analyzing a comprehensive corpus of 1319 records sourced from Scopus, covering various types of publications including journal articles, books, and conference papers from 1985 to 2023.

“ Key Findings

The identified clusters include: 1) Image Processing and Content Analysis, 2) Content Generation, 3) Emerging Use Cases, 4) Engineering, 5) Cognitive Inference and Planning, 6) Data Privacy and Security, and 7) GPT Academic Applications. Each cluster represents a unique area of focus within GAI.

“ Challenges and Opportunities

Future research in GAI should prioritize areas like explainability, robustness, cross-modal and multi-modal generation, and interactive co-creation. These directions are crucial for advancing the field and addressing existing challenges.

 Original link: https://www.sciencedirect.com/science/article/pii/S2543925124000020

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