IDEAS home Printed from https://ideas.repec.org/a/abz/journl/y2017id92.html
   My bibliography  Save this article

Technologies Of Artificial Intelligence As The Factor Of Digitalization Of Economy In Russia And In The World

Author

Listed:
  • L. A. Tsvetkova

Abstract

The growth rates of the market for high-tech goods and services based on deep learning technologies are estimated. Key investors and beneficiaries in the development of deep learning technologies were identified. The patent activity in the world is analyzed and the place of Russia in the patent landscape in the field of deep learning is determined. It is shown that most of the patent documents are concentrated in the portfolios of major US corporations, which are headed by Microsoft, IBM, Google, Yahoo. Among the leaders of the rating of patent holders are also the corporations of Japan and the Republic of Korea. High rates of growth of patent activity in China are noted. The prospects of the development of artificial intelligence technologies and deep learning in Russia are estimated. Special attention is paid to the fact that most of the research and development in this area is carried out in public research institutes and universities, while in the countries – technological leaders the driver of development of the direction is the business sector.

Suggested Citation

  • L. A. Tsvetkova, 2017. "Technologies Of Artificial Intelligence As The Factor Of Digitalization Of Economy In Russia And In The World," Economics of Science, Delo Publishing house, vol. 3(2).
  • Handle: RePEc:abz:journl:y:2017:id:92
    DOI: 10.22394/2410-132X-2017-3-2-126-144
    as

    Download full text from publisher

    File URL: https://ecna.elpub.ru/jour/article/viewFile/92/89
    Download Restriction: no

    File URL: https://libkey.io/10.22394/2410-132X-2017-3-2-126-144?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    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:abz:journl:y:2017:id:92. 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: Кочетков Дмитрий Михайлович (email available below). General contact details of provider: https://delo.ranepa.ru/ .

    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.