Harnessing Generative AI for Optimizing Power Generation Innovations and Applications in Energy Efficiency

This article explores modern approaches to the integration of advanced technologies such as generative artificial intelligence (AI), the Internet of Things (IoT), and 5G, aimed at developing digital infrastructure and strategic partnerships with technology companies in the energy sector. The focus is on methods such as the use of generative AI models for big data analysis, failure prediction, and the optimization of energy grid operational processes. Special attention is given to the integration of IoT and 5G to create a flexible and resilient infrastructure capable of adapting to real-time changes. The key conclusions from this work show that these technologies not only reduce operational costs but also significantly enhance environmental sustainability through the integration of renewable energy sources. Furthermore, the analysis indicates that the implementation of Vehicle-to-Grid systems contributes to more efficient energy management, and when combined with IoT and Phasor Measurement Units (PMUs), improves the monitoring and control of electrical networks. The article emphasizes that despite the need for adaptation of existing infrastructure and significant computational resources, the potential of these technologies will continue to grow, offering innovative solutions for reducing energy consumption and enhancing productivity in the long term

Transforming Retail: Elevating Customer Experience and Efficiency with Generative AI Technique

This article examines the impact of generative artificial intelligence (AI) on the transformation of retail in the digital age. The author emphasizes that generative AI, by creating new content and providing personalized experiences, is becoming a key tool for retailers, allowing them not only to understand, but also to anticipate consumer preferences. Special attention is paid to changing the customer experience through innovative solutions such as smart chatbots that are able to adapt to user needs. The article also examines the impact of generative AI on operational efficiency, including inventory management and staff optimization, which helps reduce costs and increase profitability. The financial results of the AI implementation are supported by statistical data showing revenue growth and reduced operating costs. The conclusion emphasizes that generative AI will not only improve existing processes, but also change the very nature of interaction between retailers and consumers, opening up new horizons for business in the future