👉 Attending engineering, often abbreviated as AE, is a specialized form of machine learning where deep neural networks are trained to perform specific engineering tasks, such as predicting structural failures, optimizing manufacturing processes, or simulating complex physical systems. Unlike traditional machine learning, which might focus on general pattern recognition, attending engineering leverages the power of transformer architectures to understand and generate explanations for engineering decisions. This approach allows models to not only predict outcomes but also provide detailed, interpretable insights into the reasoning behind their predictions, making them particularly valuable in fields where understanding the underlying mechanisms is crucial for safety and reliability.
