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Journal of Information and Optimization Sciences cover
Open Access ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667

WoS  JIF 2026 : 0.4 (Q4)

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Monthly Journal: Publishes theoretical and applied research on topics in information and optimization sciences.

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Open Access Research Article

State-of-the-art review and critical analysis of emerging trends in generative artificial intelligence

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pp. 1691–1704Vol. 46Issue 5July 2025DOI: 10.47974/JIOS-1945XML
Received:
07 Aug 2024
Published Online:
16 Jul 2025
Article type:
Research Article
Language:
EN
Article no.:
JIOS-1945
Pages:
1691–1704

Abstract

Generative AI technology now leads the way as a transformative innovation that produces diverse, realistic content across various content modalities. This research extensively reviews generative AI by examining its core mechanisms, architectural improvements, and current breakthroughs in making images, text, audio, and videos. The paper discusses three main generative models, GANs, VAEs and diffusion models, to explain their distinctive advantages and technical constraints. The document demonstrates industrial uses in different sectors yet focuses on essential issues connected to biased data, unintelligible model configurations, and efficiency constraints. The paper focuses on upcoming developments of multimodal systems and environmentally friendly AI practices. The main emphasis lies in building generative models that demonstrate robustness, interpretability, and sustainability across the environment. The paper explores research directions for the future with a specific focus on integrating multiple modalities and establishing ethical practices during model design. Researchers, practitioners, and policymakers will find this review highly helpful in their tasks related to understanding and developing generative AI technologies.

Keywords

Subject Classifications

68T05

References

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