The article discusses key aspects of the implementation of artificial intelligence in the educational process. Using the example of developing an online course on databases, the practical application of artificial intelligence is shown: material generation, automatic checking of assignments, chatbot, etc. Particular attention is paid to the role of artificial intelligence as a support tool for teaching.

This article examines the role of algorithms in solving artificial intelligence (Al) problems and ways to increase their effectiveness. The main algorithmic approaches used in systems (Al) will be analyzed, as well as their advantages and limitations will be highlighted. The article uses advanced literature that will help to study the theoretical and practical aspects of artificial intelligence algorithms.

Artificial intelligence (Al) is becoming an integral part of everyday life, actively influencing many aspects of human activity. Al technologies are used to automate routine tasks, improve the quality of service and enhance convenience in various fields, such as medicine, education, transportation, finance and entertainment. For example, voice assistants, recommendation systems, smart homes and chatbots significantly simplify the performance of daily tasks. However, along with the benefits, Al raises questions related to ethics, privacy and data security. The impact of artificial intelligence on the labor market raises concerns about replacing human labor, while the rapid development of technology generates the need to adapt to new conditions. This topic emphasizes the importance of studying the benefits and risks associated with the implementation of Al, as well as developing strategics for its effective use to improve the quality of life and minimize possible threats. Keywords: Artificial intelligence (Al), machine learning, deep learning, automation, smart devices, robotics, data analysis, computer vision, chatbots, digital transformation, social networks and algorithms.

The article provides methodological recommendations on the use of the concept of artificial intelligence and its essence in education when teaching robotics to schoolchildren. During the lesson, the concept of artificial intelligence and effective aspects of using its essence were studied.

The article examines the role of digital technologies and artificial intelligence in the modem world, especially in the context of their impact on the global economy. Theoretical aspects of the use of artificial intelligence in science, education and industry are discussed, as well as practical examples of successful implementation of digital technologies in economic processes.

Accurate assessment of athletes’ physical condition, including fatigue level, is essential for optimal training planning, achieving high performance, and reducing the risk of injury. Muscle biosignals, in particular electromyography (EMG), provide valuable information about muscle activity and fatigue. In recent years, artificial intelligence (Al) methods have become a powerful tool for analyzing these biosignals and automatically assessing fatigue. This article aims to analyze the effectiveness of various Al algorithms in assessing athlete fatigue based on EMG signals.

The article is devoted to the study of the impact of digital transformation and artificial intelligence on the formation of sustainable ecosystems in higher education. The paper discusses theoretical and practical aspects of the implementation of advanced digital technologies such as cloud services, big data, artificial intelligence and machine learning, which provide new opportunities for optimizing the educational process and management of educational institutions.

This work analyzes the historical development, operating principles, and modem approaches of X-ray imaging technologies. It mainly considers technologies ranging from traditional X-ray imaging methods to advanced systems integrated with artificial intelligence. The work also analyzes the advantages and disadvantages of X-ray systems, which will serve as an important source of information for medical professionals and researchers.

This article examines the impact of digital technologies and artificial intelligence on logistics between Russia, China and Uzbekistan. The theoretical and practical aspects of Al application in logistics systems are described, as well as the possibilities of optimizing processes, increasing efficiency and reducing costs are analyzed. The strategic importance of logistics for the development of the economics of these countries in the context of globalization is emphasized.

This article analyzes the challenges encountered in the digital processing of images of human internal organs obtained through video endoscopy, as well as methods for addressing them. Although video endoscopic images are widely used in medicine for diagnostics and surgical planning, their quality can be degraded by factors such as insufficient lighting, noise, geometric distortions, and variations in color balance. Moreover, the biological variability of the human body and pathological differences in disease manifestation adversely affect the accuracy of artificial intelligence models. The article substantiates the relevance of applying modem algorithmic approaches, including deep learning technologies, to improve image quality and enhance diagnostic efficiency.

This article analyzes the possibilities of artificial intelligence technologies in digitization, systematization and analysis of scientific and historical heritage. Using the example of archival materials from the Institute of Physics and Technology, the methodology and software tools of the digital platform created on the basis of practical experience are considered. The article analyzes such areas as digitization of archival documents using OCR technologies, semantic analysis, automatic classification and graphing of scientific knowledge.

The use of artificial intelligence technologies in teaching mathematics and probability theory improves the quality of education, making it more accessible and engaging for students. The application of a personalized approach, interactive methods, and gamification contributes to the development of analytical thinking and independent learning skills.

The purpose of this study is to analyze the important role that artificial intelligence (Al) plays in the educational process. The article explores how modem Al technologies can solve a number of problems in the field of education, such as barriers to access to educational materials, learning difficulties and a shortage of educational resources.

This article examines the role and importance of artificial intelligence (Al) technologies in the digitization process of archival documents in Uzbekistan. Digitizing archival records ensures their preservation, facilitates their processing, and enhances public accessibility. The article provides an overview of the information systems introduced by the “Uzarchiv” Agency and explores how Al technologies are being applied within these systems. It also presents a comparative analysis of advanced international practices in countries such as the United States, the United Kingdom, South Korea, China, and other European nations, focusing on legal frameworks, digital infrastructure, and the integration of Al in archival management. The article concludes with practical recommendations for the development of the archival digitization system in Uzbekistan.

This article proposes a deep learning-based model for extracting key entities from texts and creating a knowledge base. The Long Short-Term Memory (LSTM) model is used for the Named Entity Recognition (NER) task. The data is preproccssed and converted into a digital format using tokenization and one-hot encoding. The model is trained and evaluated to extract various types of entities (e.g., person names, dates, and location names). Experimental results demonstrate the model’s effectiveness, and the impact of different parameters is analyzed.

This article analyzes the processes of analyzing and classifying textual data, considers the types of textual data, namely structured, unstructured and semi-structured data, and presents their characteristics. In addition, special attention is paid to the existing opportunities and problems in processing textual data in the Uzbek language. In particular, the achievements and shortcomings of analyzing textual data in the Uzbek language using the example of the "Tahrirchi" system are presented.

This article analyzes the role of digital technologies and artificial intelligence in modern society, especially their application in science, education, and industry. The paper highlights practical uses of Al technologies, their impact on human activity, efficiency, and development prospects.

Nowadays, systems ensuring natural interaction between humans and machines are rapidly evolving. Among them, the task of identifying the user’s language holds particular importance. This article analyzes the problem of language identification (LID) based on speech signals, its application areas, challenges, and modem approaches. It compares traditional machine learning methods (GMM, SVM, i-vcctor) with deep neural network-based approaches (CNN, RNN, Transformer) for language recognition. Additionally, the paper discusses key evaluation metrics such as Accuracy, Precision, Fl-score, and Equal Error Rate (EER) for assessing system performance. Advanced methods for handling complex scenarios like code-switching and openset LID are reviewed, with a focus on practical perspectives for under-resourced languages like Uzbek. The results of the study provide a solid theoretical and practical foundation for developing multilingual interactive voice systems.

This article discusses the increasing role of Artificial Intelligence (Al) in English language education, highlighting its benefits and potential drawbacks. Three main purposes of Al in education have been outlined. Moreover, practical examples such as ChatGPT, Mentimeter, Gencraft, and Aspose Grade calculator are used to illustrate how Al is transforming teaching and learning processes. While acknowledging the advantages of Al in providing personalized learning, creating engaging materials, and automating assessment, the text also emphasizes the importance of critical thinking, teacher guidance, and responsible Al use. The conclusion stresses that Al is no longer a futuristic tool but a present-day resource, and educators must equip students to use it wisely and ethically.

This paper investigates the role of digital models and metadata-based systems in analyzing and optimizing technological processes in the machining industry. Using cylindrical plunge grinding as an example, modeled in the software environment, the study provides a step-by-step analysis of the dynamic system involved.

This study analyzes various types of the IDEF methodology, examining the most suitable methodologies for modeling speech-to-text (STT) and text-to-speech (TTS) conversion processes, as well as translation systems from Uzbek to Russian and English. Based on the research findings, IDEFO and IDEF3 were selected as the most optimal methodologies for STT and TTS processes, while IDEF IX was chosen for translation systems. Based on this model, a web application was developed for processing users’ speech and text data.

Artificial intelligence (Al) models arc creating numerous opportunities for the intelligent analysis of medical images. However, the effective performance of these models requires large and high-quality labeled datasets. Since collecting such data in the medical field is challenging and costly, data augmentation methods play a crucial role.

The paper presents a mathematical model and the results of numerical calculations designed to analyze and predict the distribution of pollutants in the atmospheric surface layer. The model accounts for the dynamics of pollutant concentration reduction due to their natural decomposition and photochemical transformation, the influence of changes in wind patterns and terrain topography, and variations in diffusion and turbulent mixing coefficients depending on the stability of atmospheric stratification. High accuracy and stability of results arc achieved through the use of a semi-implicit finite-difference scheme and the method of lines for solving the specified problems.

This research paper is devoted to the problem of classifying pathologies in renal computed tomography images using deep neural networks, where not only binary classification such as «normal/pathological» but also complex differential diagnosis issues between pathologies arc analyzed. The paper also proposes a combinatorial approach to classifying pathologies, in which it is shown that initially making a general diagnosis using a four-class classification model, and in doubtful cases, additional examination using binary or ternary models is acceptable for clinical practice.

This paper examines modem algorithms used for the intelligent analysis of speech signals and their scientific and practical significance. The development of artificial intelligence and machine learning technologies has expanded the capabilities of automatic speech signal processing, feature extraction, and recognition. The study analyzes modeling processes based on advanced methods such as MFCC, CNN, and RNN. It also explores algorithms used for spccch-to-tcxt conversion, speaker identification, and context understanding. The results may be applied in intelligent voice interfaces, security systems, and linguistic applications.