Annotation: Main problem: the most key issue of Kazakhstan is its unpreparedness for the latest technologies. The introduction of artificial intelligence in medicine in Kazakhstan, which has both positive and negative sides, falls into this category. To start working with them, it is necessary to determine the attitude of citizens to them, especially if it concerns social activities. The work has social and scientific significance. The work highlights the main positive aspects of reducing the workload in the workplace, as well as the positive results of the active use of artificial intelligence in other countries. Methods: Three methods were used for detailed analysis: interviews, content analysis and survey. All methods of obtaining information were used in further analyzing the problem and identifying the results. Purpose: the main objective of the study is to find the existing practices for using AI in Kazakhstan. Moreover, the possible opportunities to develop AI implementation in medicine and how it can upgrade internal procedures in the medical field. Results and their significance: At the end of the article, it is clearly seen that more and more people are exposed to AI technology on a daily basis, but its implementation in Kazakhstan remains relatively low, indicating that Kazakhstan is lagging behind other countries and that people are unaware of all the advantages of AI. It can also be noted that the introduction of AI in medicine can help remote areas in transmitting patient data.

Annotation: Over the past decades, efforts have been made to develop irrigation and pasture infrastructure across significant areas of seasonal pastures within the state land fund of the Republic of Kazakhstan. However, the current level of fodder base development remains insufficient to fully meet the needs of the livestock sector, thereby limiting the growth potential of agricultural production. A key strategy for intensifying pasture management lies in the efficient use of pasture and fodder resources through the implementation of rotational grazing systems that prevent land degradation. Within the framework of the Agro-Industrial Complex Development Concept, a central objective is the restoration and preservation of the productivity of agricultural landscapes, many of which are affected by various forms of land degradation. Currently, the region is experiencing a decline in both the qualitative and quantitative characteristics of agricultural land, including a 6-27 % decrease in humus content on irrigated lands, wind erosion across 2.4 million hectares of farmland, and an increase of 1.4 million hectares in degraded pasture areas. These processes have led to substantial income losses among agricultural producers, largely due to water scarcity and the deterioration of agricultural landscapesincluding irrigated lands, hayfields, and pastures. Consequently, the region is facing growing socioeconomic tensions, marked by declining rural living standards and reduced volumes of agricultural output.

Annotation: In the context of a rapidly growing elderly population, one of the key priorities is the development of specialized food products that support health maintenance, prevent age-related diseases, and provide physiologically adequate nutrition. The aim of this study was to develop a gerodietetic meat semi-finished product technology using plant-based ingredients-bulgur flour and zucchini-known for their high nutritional and biological value. Three formulation variants were developed, differing in the percentage ratio of animal and plant-based raw materials. The samples were evaluated by sensory analysis using a scoring system (appearance, color, smell, taste, texture) and by determining the chemical composition of the optimal variant. The results showed that the inclusion of plant ingredients improves the sensory qualities of the product, reduces fat content, and increases the levels of dietary fiber, vitamins, and minerals. The best performance was observed in sample No. 2, containing approximately 20 % plant additives. The proposed formulation offers an optimal balance of sensory and nutritional properties, making it suitable for implementation in the production of gerodietetic meat products. Given its balanced composition and high consumer appeal, it is also appropriate for use in institutional catering systems and in the production of functional foods targeted at elderly nutrition.

Annotation: Although Kazakhstan increases the area under soybean cultivation annually, its production remains challenging in the northern and eastern regions due to the limited number of varieties adapted to climatic conditions. Traditional methods of selecting parental forms for the creation of new ultraearly and early soybean varieties require significant time and resource investments, so modern breeding technologies are aimed at increasing the accuracy and efficiency of hybridization. In the context of agricultural intensification and the need to adapt soybean varieties to specific agroecological conditions, cluster analysis has proven to be an effective tool for evaluating and selecting varietal material. Its application made it possible not only to structure the studied soybean accessions by economically important traits, but also to identify the most promising forms for subsequent use in breeding programs. The article presents the results of a study of 102 collection soybean accessions of various ecological and geographical origins, evaluated by the main economically important traits in order to define criteria for selecting sources and donors for breeding for high productivity, early maturity, and high biochemical performance, using cluster analysis via Ward’s method with the Statistica v.13 software. To conduct a cluster analysis of 102 collection soybean accessions for systematization based on economically important traits and to identify genetically promising parental forms to improve the efficiency of the breeding process and accelerate the development of new varieties adapted to the conditions of the northern and eastern regions of Kazakhstan. The study was conducted using the hierarchical clustering method based on Ward’s method. Statistical analysis was carried out using Statistica v.13. As a result of studying 102 collection soybean accessions using cluster analysis, five clusters were identified that differed in sets of economically important traits. From the first cluster, four accessions were identified as sources and donors of high yield and high protein content in seeds. From the second cluster, six accessions were identified as sources and donors of early maturity, and five as sources of high protein content. From the third cluster, four early maturing accessions, three highyielding accessions, five with high protein content, and three with high fat content were identified. From the fourth cluster, three accessions were identified by yield level, two by 1000 seed weight, two by protein content, and four by pod insertion height. In the fifth cluster, seven soybean accessions stood out for yield and three for pod insertion height. Cluster analysis has proven its effectiveness as a digital breeding tool, facilitating the accelerated development of adapted soybean varieties and the expansion of soybean cultivation in Kazakhstan.

Annotation: The article is devoted to the development of technology for the production of cottage cheese based on goat's milk for functional nutrition. The authors have considered the nutrition structure of the population of the Republic of Kazakhstan, which is characterized by a continuing decrease in consumption of the most biologically valuable food products. The authors noted that one of the problems of violation of the nutritional status of the population is associated with a deficiency in the diet of biologically active components, including animal proteins, reaching from 15 % to 20 % of the recommended rational consumption standards. Cottage cheese and cottage cheese products are considered essential food products for all age groups of the population, due to their significant content of high–grade proteins, minerals – calcium, phosphorus, magnesium, iron, sulfur-containing compounds - methionine, lysine, choline and other substances that cause its high nutritional and biological value. The authors argued for the choice of Bifilact PRO starter cultures, Sweet Jam functional ingredients and flavor fillers, and developed a new technology for the production of a curd product based on goat's milk. Pasteurization of dairy raw materials is carried out at t = (71 ± 2) °C, homogenization of milk mixture 10-12 Mpa t = (45 ± 1) °C. Comprehensive studies of the organoleptic, physico-chemical, and microbiological parameters of the new product, as well as safety indicators, have been conducted. The authors have proved that the developed technology for the production of cottage cheese is based on the use of high–quality raw materials - goat's milk, the use of new methods of its processing, and the use of high-tech equipment.

Annotation: In the context of the digital transformation of sports, there is an increasing need for systematic use of data and artificial intelligence (AI) technologies to support decision-making at all levels – from individual athlete training to the management of sports infrastructure. The aim of this paper is to justify a conceptual architecture of a digital sports platform based on the integration of data analytics and AI methods and adapted to the conditions of the Republic of Kazakhstan. The study employs content analysis of scientific and applied publications, a comparative analysis of the functionality of existing foreign and Russian software solutions for sports, as well as an expert assessment of their applicability in the national context. Based on the analysis, a set of requirements for a digital sports platform is formulated, including the integration of heterogeneous data sources, support for different levels of sports training, adaptive AI-driven analytics, scalability and openness of the architecture. A conceptual architecture of the platform is proposed, comprising data sources, data storage and processing, AI-based analytical modules, user services and integration with external information systems, while ensuring information security. The implementation of such a digital platform can enhance the efficiency of the training process, support the development of mass sports and enable more evidence-based sports policy planning in Kazakhstan.

Annotation: In arid regions, food security is constrained by land degradation, unstable water resources, and localized environmental pollution, which reduce the resilience of agri-food systems and negatively affect product quality and processing potential. The purpose of the study was to assess the impact of environmental factors on food security in the Zhambyl region and to substantiate the role of food technologies in improving product quality and safety. The study applies a systems approach, comparative geographical analysis, and environmental monitoring data on soils, air, and surface waters for 2023-2024, followed by scientific interpretation of the results. Land degradation, including humus decline and deflation processes, is identified as the main limiting factor for agricultural productivity. Heavy metal concentrations in soils remain within permissible limits. Air quality is generally characterized by low pollution levels, although local exceedances of maximum allowable concentrations are observed. Surface water quality shows a positive trend with no cases of extreme pollution. The findings emphasize the importance of implementing resource-efficient and treatment technologies and can be used in developing regional food security policies.

Annotation: Today, access control systems that rely only on passwords and PIN codes can no longer keep up with growing security requirements. These traditional methods are easy to steal, guess, or share with someone else, which turns them into the weakest link in the protection chain. In this context, solutions that use biometrics and can also “understand” user behavior, rather than just verify entered data, are becoming especially relevant. This study develops a software system that makes decisions not only based on a person’s biometric features, but also on how they behave when trying to log in. The aim is to obtain a tool that can detect suspicious activity in time and automatically strengthen access restrictions when necessary. As a technical foundation, computer vision and deep learning methods are used to recognize faces in a video stream. In addition, a behavioral analysis module is implemented that tracks the sequence and frequency of login attempts, as well as the time and context of access. The system is structured into several interconnected modules: face recognition, time- and zone-based access verification, and risk level assessment. The prototype shows that combining biometric and behavioral features can significantly improve the quality of access control. When the number of errors or atypical actions exceeds a predefined threshold, the system automatically blocks the user and triggers an alarm scenario. In this way, the probability of unauthorized access is reduced, while part of the routine work of the security administrator is offloaded to the system itself. The scientific novelty of the proposed approach lies in integrating face recognition and behavioral analysis not as two separate layers of protection, but as components of a single decision-making architecture. This makes it possible to consider both the user’s biometric characteristics and the context of their actions-such as time, location, and patterns of failed attemptssimultaneously when deciding whether to grant access. Compared to classical single-factor solutions, such an integrated approach forms a more flexible and intelligent security perimeter

Annotation: The rapid development of digital technologies has significantly increased the importance of ensuring data security. In this context, the study of the interaction between cryptography and artificial intelligence has become one of the most relevant research areas. This article examines the opportunities, risks, and future prospects of applying artificial intelligence technologies in cryptographic systems. The main objective of the study is to perform a comparative analysis of the efficiency of traditional cryptographic algorithms and algorithms optimized using artificial intelligence techniques. The research is based on experimental modeling, during which the encryption time for different data volumes was measured. The obtained results demonstrate that AI-optimized algorithms provide higher performance compared to traditional methods. In addition, artificial intelligence can automate the process of identifying vulnerabilities in cryptographic systems and improve the adaptability of security mechanisms. The findings indicate that the integration of cryptography and artificial intelligence has significant potential for enhancing modern information security systems.