The Rise of Generative AI: Transforming Industries with Large Language Models and Deep Learning

Naga Surya Teja Thallam

The Rise of Generative AI: Transforming Industries with Large Language Models and Deep Learning

Author(s)	Naga Surya Teja Thallam
Country	United States
Abstract	The development of Generative AI (GenAI) with large language models (LLMs) and deep learning has been so rapid that is changing many industries ranging from healthcare, finance, education, media to cybersecurity. Transformer based AI systems like GPT, BERT and T5 are quite impressive in being able to generate human like text and images and other media. In this work, we look into the genesis of Generative AI, how it is constructed from the technological perspective and what are the business implications, as well as the ethical, security and computation implications which arise. While Generative AI has great potential, it has the ability to be biased, deliver misinformation, be an adversarial threat and come at high levels of computational costs. The paper discusses different strategies for reducing algorithmic bias, increasing the model interpretability, and optimizing the energy efficiency through quantization, knowledge distillation, federated learning, etc.. In addition, the research stresses the importance of ethical AI governance, regulatory framework development, and making security improvements to mitigate potential abuse, like the deepfake alterations and adversarial attacks. In this paper, the paper shows how Generative AI boosts automation, decision making and personalization in real – world applications and case studies. Future research will have to concentrate on improving the model efficiency, ensuring fairness, and improving the AI security so it can deploy the responsible AI. Generative AI can be used as a force for economic growth, societal benefits and for developing a more sustainable AI future if innovation doesn’t outweigh ethical responsibility.
Keywords	Generative AI, Large Language Models, Deep Learning, Transformer Networks, Ethical AI, Bias Mitigation, Explainable AI, Security Risks, Computational Efficiency, AI Regulation, Adversarial Attacks, AI Governance, Responsible AI Deployment.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 15, Issue 4, October-December 2024
Published On	2024-12-12

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The Rise of Generative AI: Transforming Industries with Large Language Models and Deep Learning

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