This document discusses different computational methodologies for solving problems, including hard computing and soft computing. Hard computing uses certain methods to solve problems, while soft computing uses approximate methods to find implicit solutions. Artificial intelligence (AI) derivatives are similar to soft computing methods. The document also describes white, black, and grey box models for mathematical modeling, where white box models are based on first principles, black box models explore input-output relationships without structure, and grey box models identify patterns and provide structure. Finally, it mentions AI learning methods and structural optimization techniques for finding optimal designs that meet criteria like strength, stiffness, weight, and cost.