| Autor: |
Zhukov Aleksandr, Saveliev Anton, Zhurenkov Denis, Khachaturyan Suren, Kartsan Igor |
| Jazyk: |
English<br />French |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
E3S Web of Conferences, Vol 531, p 03010 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2267-1242 |
| DOI: |
10.1051/e3sconf/202453103010 |
| Popis: |
The article systematizes theoretical and methodological provisions on the international experience of the formation of machine learning in interests of economic development and strengthening of defense capabilities on the example of the USA and China. On the basis of official documents and statistical data the state strategies, the strategy of machine learning formation for dual-use technology and the methodology of state regulation of machine learning in the countries under consideration are analysed. Increasing complexity of modern digital technologies is compensated by their growing interoperability - their readiness to integrate into various heterogeneous spheres of state development without the need for costly adaptation measures. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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