IDEAS home Printed from https://ideas.repec.org/a/bhx/ojijce/v7y2025i14p24-37id3004.html
   My bibliography  Save this article

Cloud-Powered Neural Networks: The Democratization of Deep Learning through Cloud Computing

Author

Listed:
  • Vimal Pradeep Venugopal

Abstract

The democratization of deep learning through cloud computing represents a transformative shift in artificial intelligence accessibility, breaking down traditional barriers that once limited participation to well-funded institutions. This article explores how cloud platforms have revolutionized access to specialized computing infrastructure, reduced financial obstacles through flexible pricing models, and introduced technical enablers that simplify AI implementation. The emergence of collaborative ecosystems and knowledge sharing mechanisms has fostered global research communities that transcend geographical and institutional boundaries. These developments have catalyzed real-world applications across consumer technologies, business operations, and scientific research, particularly in healthcare. Looking ahead, the continuing co-evolution of cloud services and AI capabilities promises further advancements in accessibility while presenting new challenges related to skills gaps, economic disparities, and regulatory frameworks. This article examines both the technological innovations driving AI democratization and their broader societal implications.

Suggested Citation

  • Vimal Pradeep Venugopal, 2025. "Cloud-Powered Neural Networks: The Democratization of Deep Learning through Cloud Computing," International Journal of Computing and Engineering, CARI Journals Limited, vol. 7(14), pages 24-37.
  • Handle: RePEc:bhx:ojijce:v:7:y:2025:i:14:p:24-37:id:3004
    as

    Download full text from publisher

    File URL: https://carijournals.org/journals/index.php/IJCE/article/view/3004
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bhx:ojijce:v:7:y:2025:i:14:p:24-37:id:3004. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chief Editor (email available below). General contact details of provider: https://www.carijournals.org/journals/index.php/IJCE/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.