International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

The GenAI Code: Cracking the Genetic Blueprint of Artificial Creativity

Ravi ShawStudent, Department of Computer Application, Narula Institute of Technology, Kolkata, IndiaPranoy PatraStudent, Department of Computer Application, Narula Institute of Technology, Kolkata, IndiaMadhura SarkarStudent, Department of Computer Application, Narula Institute of Technology, Kolkata, IndiaRupa SahaAssistant Professor, Department of Computer Application, Narula Institute of Technology, Kolkata, India

Vol 7 No 10 (2023): Volume 7, Issue 10, October 2023 | Pages: 688-691

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 09-11-2023

doi Logo doi.org/10.47001/IRJIET/2023.710090

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Abstract

Generative Artificial Intelligence (AI) has emerged as a transformative technology with wide-ranging applications in fields such as natural language processing, computer vision, and creative content generation. This research paper provides a comprehensive review of recent advancements in generative AI, highlighting key methodologies, breakthroughs, and their impact on various domains.

The paper begins by discussing the evolution of generative AI, tracing its roots from early neural network models to the current state-of-the-art deep learning techniques. It explores the fundamental concepts behind generative models, including Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Transformers, which have revolutionized the field.

In conclusion, this research paper provides a holistic overview of generative AI's progression, current capabilities, and future potential. As generative AI continues to evolve, it offers new opportunities for innovation, while also raising critical questions about ethics, privacy, and security that necessitate ongoing research and discussion.

Keywords

GenAI, Machine learning, Neural networks, Genetic encoding, Evolutionary innovation, Generative Models


Citation of this Article

Ravi Shaw, Pranoy Patra, Madhura Sarkar, Rupa Saha, “The GenAI Code: Cracking the Genetic Blueprint of Artificial Creativity” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 7, Issue 10, pp 688-691, October 2023. Article DOI https://doi.org/10.47001/IRJIET/2023.710090

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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