A Theoretical and Practical Exploration of Generative AI in AWS Architectures Enhancing Cloud-Based Data Processing and Intelligent Service Deployment
Keywords:
Generative AI, AWS, Cloud Computing, Data Processing, Intelligent Services, Serverless Architectures, Machine LearningAbstract
Generative AI has revolutionized intelligent service deployment in cloud computing, offering scalable solutions for data processing and analytics. This paper explores theoretical underpinnings and practical applications of generative AI within Amazon Web Services (AWS) architectures, focusing on optimizing cloud-based workflows. The study systematically reviews prior works and examines key AWS services that integrate AI, such as SageMaker and Lambda, evaluating their role in automated decision-making and real-time processing. The research highlights challenges in latency, security, and scalability, proposing frameworks for effective implementation. Theoretical models, comparative analysis, and case studies substantiate the discussion.
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Copyright (c) 2025 Asama Kulvanitchaiyanunt A (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
