AI Demystified: CAE Engineers Decode Neural Networks

This article brilliantly bridges the gap between AI and engineering, making complex neural networks accessible to CAE professionals. It elegantly explains how to understand neural networks using concepts familiar to engineers, turning the seemingly abstract into something concrete and manageable. This approach empowers engineers to leverage AI in their work with greater confidence and understanding.

• •The article translates AI jargon into CAE engineering terms, making neural networks more approachable.
• •It explains neural networks as computational models built from nodes, elements, and non-linear activation functions.
• •The analogy to Finite Element Method (FEM) helps engineers quickly grasp the concepts.