Geodesic
Potentials of the bio-inspired approach in the development of artificial intelligence systems (trends review)
Učënye zapiski Kazanskogo universiteta. Seriâ Fiziko-matematičeskie nauki, Uchenye Zapiski Kazanskogo Universiteta. Seriya Fiziko-Matematicheskie Nauki, Tome 164 (2022) no. 2, pp. 244-265

Voir la notice du chapitre de livre provenant de la source Math-Net.Ru

Artificial intelligence (AI) efficiently builds predictive models in engineering, politics, economics, and science, as well as provides optimal strategies for solving various problems. However, modern AIs are often far from being as accurate as one might have expected a few decades ago. As a result, a number of problems linked to the widespread use of AI hinder the positive effects of the tasks it solves. This article focuses on the difficulties and limitations in using AI systems that have arisen to date and possible ways to overcome them.
Keywords: artificial intelligence, machine learning, bio-inspired approach, cerebellum model. 
@article{UZKU_2022_164_2_a6,
     author = {A. R. Nurutdinov and R. Kh. Latypov},
     title = {Potentials of the bio-inspired approach in the development of artificial intelligence systems (trends review)},
     journal = {U\v{c}\"enye zapiski Kazanskogo universiteta. Seri\^a Fiziko-matemati\v{c}eskie nauki},
     pages = {244--265},
     publisher = {mathdoc},
     volume = {164},
     number = {2},
     year = {2022},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/UZKU_2022_164_2_a6/}
}
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A. R. Nurutdinov; R. Kh. Latypov. Potentials of the bio-inspired approach in the development of artificial intelligence systems (trends review). Učënye zapiski Kazanskogo universiteta. Seriâ Fiziko-matematičeskie nauki, Uchenye Zapiski Kazanskogo Universiteta. Seriya Fiziko-Matematicheskie Nauki, Tome 164 (2022) no. 2, pp. 244-265. http://geodesic.mathdoc.fr/item/UZKU_2022_164_2_a6/