This paper, explores the principles and applications of artificial intelligence, with a focus on CUDA technology and the PyTorch framework. The study provides an in-depth analysis of the neural network performance. Key topics include deep neural networks, activation functions, fundamental aspects of building artificial intelligence models, and practical applications of AI across various domains. Furthermore, the paper briefly compares alternatives to CUDA technology and answers the question of why CUDA would be a better option to use at the moment with PyTorch framework for machine learning purposes. By examining the interplay between hardware and software in modern AI workflows, the paper sheds light on the technological advancements driving innovation in the neural network training process. Additionally, the paper examines the growing significance of artificial intelligence in today’s world.