This presentation introduces a method that combines traditional numerical techniques with artificial intelligence (AI) approaches to enhance the efficiency and accuracy of solving partial differential equations (PDEs). By utilizing AI models, particularly Neural Operators, we approximate the solutions of PDEs using data, which reduces computation time and improves predictive capabilities for more complex systems. The presentation will explore the potential applications of both traditional numerical methods and AI in various engineering and scientific domains.