Advanced Integration of Generative AI into AWS Cloud Computing Ecosystems: Frameworks for Scalable Machine Learning Models and Automated Decision-Making

Shivendra Pratap P Singh

Authors

Shivendra Pratap P Singh Independent Researcher and IT Expert, India. Author

Keywords:

Generative AI, AWS Cloud Computing, Machine Learning, Automated Decision-Making, Scalability, Frameworks

Abstract

The intersection of generative artificial intelligence (AI) and cloud computing frameworks has catalyzed a transformative shift in scalable machine learning (ML) model deployment and automated decision-making. Leveraging Amazon Web Services (AWS) as a dynamic ecosystem, this study explores advanced strategies to integrate generative AI into AWS's infrastructure. It investigates the architectural frameworks, scalability techniques, and automation paradigms that enable seamless operationalization of ML models. Through empirical analysis and theoretical exploration, this paper elucidates the role of generative AI in enhancing computational efficiency, reducing costs, and accelerating decision-making in real-world applications.

References

Goodfellow, I., Pouget-Abadie, J., Mirza, M., et al. (2014). "Generative Adversarial Networks." Communications of the ACM, 63(3), pp. 139-144.

Hazelwood, K., Bird, S., Brooks, D., et al. (2018). "Applied Machine Learning at Facebook: A Datacenter Infrastructure Perspective." ACM SIGARCH Computer Architecture News, 46(3), pp. 620-629.

Gogula, L. S. R. (2024). SAP Business Integration Builder (BIB): A Technical Deep Dive. International Journal of Research in Computer Applications and Information Technology, 7(2), 736–746.

Nguyen, T., Tran, M., & Goyal, R. (2019). "AI-Based Decision Support in Cloud Computing." Decision Support Systems, 121(2), pp. 55-72.

Gogula, L. S. R. (2024). Exploring the Transformative Power of SAP BTP: A Comprehensive Comparison with Traditional ABAP. International Journal of Computer Engineering and Technology (IJCET), 15(5), 494–504.

Huang, G., Liu, Z., Van Der Maaten, L., & Weinberger, K. Q. (2017). "Densely Connected Convolutional Networks." IEEE CVPR, pp. 2261-2269.

Gogula, L. S. R. (2024). Modernizing Enterprise Development: Harnessing SAP CAPM and OData for Cloud-Native and Microservices Architectures. International Journal for Multidisciplinary Research (IJFMR), 6(6), November-December.

Brown, T., Mann, B., Ryder, N., et al. (2020). "Language Models are Few-Shot Learners." Advances in Neural Information Processing Systems, 33(1), pp. 1877-1901.

Hochreiter, S., & Schmidhuber, J. (1997). "Long Short-Term Memory." Neural Computation, 9(8), pp. 1735-1780.

Gogula, L. S. R. (2024). Harnessing the Power of Secure and Scalable Generative AI: A Deep Dive into AWS and SAP's Cutting-Edge Collaboration. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 10(5), 221–232.

Karpathy, A., & Fei-Fei, L. (2015). "Deep Visual-Semantic Alignments for Generating Image Descriptions." IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(4), pp. 664-676.

Bengio, Y., Courville, A., & Vincent, P. (2013). "Representation Learning: A Review and New Perspectives." IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(8), pp. 1798-1828.

He, K., Zhang, X., Ren, S., & Sun, J. (2016). "Deep Residual Learning for Image Recognition." IEEE CVPR, pp. 770-778.

Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016). "You Only Look Once: Unified, Real-Time Object Detection." IEEE CVPR, pp. 779-788.

Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012). "ImageNet Classification with Deep Convolutional Neural Networks." Advances in Neural Information Processing Systems, 25(2), pp. 1106-1114.

Simonyan, K., & Zisserman, A. (2015). "Very Deep Convolutional Networks for Large-Scale Image Recognition." ICLR.

LeCun, Y., Bengio, Y., & Hinton, G. (2015). "Deep Learning." Nature, 521(7553), pp. 436-444.

Silver, D., Huang, A., Maddison, C. J., et al. (2016). "Mastering the Game of Go with Deep Neural Networks and Tree Search." Nature, 529(7587), pp. 484-489.

Vaswani, A., Shazeer, N., Parmar, N., et al. (2017). "Attention Is All You Need." Advances in Neural Information Processing Systems, 30(4), pp. 5998-6008.