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The paper titled "Artificial Intelligence-Based Cloud Planning and Migration to Cut the Cost of Cloud" aims at examining how AI can be implemented to improve cloud planning and migration in a bid to reduce their costs. The proposal is concerned with the utilization of multiple AI techniques such as machine learning models, natural language processing and reinforcement learning to manage the migration process in the cloud. In incorporating AI within the transitions, the paper establishes how organizations improve organizational resource allocation, productivity stability, and security during Cloud transitions. It provides detailed pseudocode of the scenario, making the content sufficiently intelligible to the IT professionals who wish to implement these AI algorithms. In this regard, this paper helps to fill the gap that has been demonstrated in the current literature regarding the link between theoretical uses of AI and its application in cloud migration towards enhancing the deployment efficacy and cost-efficiency of cloud services.
Sasibhushan Rao Chanthati (Tue,) studied this question.
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