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February 5, 20260 citationsOpen Access

Cloud Computing In Artificial Intelligence and Machine Learning

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P.P Vignesh .SKSribharath K

Key Points

  • To examine the impact of cloud computing on the development and deployment of artificial intelligence and machine learning systems.
  • Analyzed cloud computing architecture and service models
  • Reviewed various cloud platforms and applications
  • Identified benefits and challenges associated with cloud computing in AI/ML
  • Cloud computing reduces costs and increases scalability for AI/ML applications.
  • Provides powerful computing resources like GPUs and TPUs for faster processing.
  • Enables real-time deployment of intelligent applications and services.

Abstract

The rapid growth of Artificial Intelligence (AI) and Machine Learning (ML) has significantly increased the demand for high computational power, massive data storage, and efficient model deployment. Traditional on-premise infrastructures often fail to meet these requirements due to high cost, limited scalability, and maintenance complexity. Cloud computing provides a flexible, scalable, and cost-effective platform that supports the complete lifecycle of AI and ML systems. By offering powerful computing resources such as GPUs, TPUs, distributed storage, and pre-built AI services, cloud computing enables faster innovation and real-time intelligent applications. This paper presents an in-depth study of cloud computing and its role in AI and ML, covering architecture, service models, platforms, applications, benefits, challenges, security concerns, and future scope.

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Cite This Study

. et al. (2026) studied this question.

synapsesocial.com/papers/6984345ff1d9ada3c1fb264chttps://doi.org/10.5281/zenodo.18457305
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