The article presents work on developing a software application for test creation using artificial intelligence and large language models. Its main goal is to optimize the educators’ work by automating the process of test generation and evaluation, with the tests being stored for subsequent analysis and use. The application can generate test questions based on specified criteria such as difficulty level, Bloom’s taxonomy level, question type, style and format, feedback inclusion, and more, thereby providing opportunities to enhance the adaptability and efficiency of the learning process. It is developed on the Google Firebase platform, utilizing the ChatGPT API, and also incorporates cloud computing to ensure scalability and data reliability.

This study explores the integration of artificial intelligence (AI) in education, focusing on its potential benefits and challenges. Through an in-depth analysis of contemporary AI platforms and software technologies, it examines their suitability for educational environments. The study highlights AI's capacity to enhance personalized learning experiences, facilitate educational gaming and simulations, and support teachers in various tasks. However, ethical considerations regarding data privacy and algorithmic bias, as well as technical challenges related to software reliability, require careful attention. By providing insights into the transformative potential of AI in education, this research aims to inform stakeholders about the opportunities and risks associated with its implementation.

This research analyzes the application of modern methods for energy consumption forecasting in the residential sector. Traditional statistical models show limitations in modeling complex consumer behaviors, while technologies based on machine learning (ML) and artificial intelligence (AI) demonstrate significantly improved accuracy and adaptability. The study encompasses a wide spectrum of methodologies – from conventional statistical approaches to cutting-edge generative algorithms, evaluating their applicability for personalized household solutions. Comparative analysis highlights the advantages of AI-based technologies in terms of precision and adaptability, positioning them as optimal for integration into intelligent energy consumption management systems. The results provide a foundation for improving energy efficiency and resource optimization in the context of the growing application of smart technologies in the residential sector.

Artificial intelligence has rapidly entered people's daily lives and has innovated many traditional models by integrating AI technologies. The need for changes in educational practices has come to the forefront. This article outlines various possibilities for using generative artificial intelligence in programming education. Different examples are presented, including code generation, debugging and optimization, documentation and commenting, automated testing, conversion between different programming languages, and more. Additionally, some risks and limitations are discussed.