The optimization of tool trajectory based on artificial intelligence, utilizing AI and machine learning algorithms, is an evolving field with applications in chip design, system optimization, prediction of cutting processes results and controlling its flow. This research paper explores the integration of advanced AI algorithms and computer vision technologies to revolutionize processing systems. The study focuses on developing sophisticated AI algorithms capable of autonomously optimizing tool paths, selecting the best cutting tools, and dynamically adjusting cutting parameters. Using GPT-4, a deep learning approach is employed to train the model on various processing scenarios. The integration of computer vision ensures real-time monitoring and dynamic adjustments during processing, enhancing adaptability and precision.