The article shows how machine learning can help designers extract important information from design documents more quickly and accurately. By using a type of machine learning called Natural Language Processing, a computer program was trained to find functional requirements in written documents. This can save designers time and make their work more efficient. The study used a language model called BERT to identify these requirements in design documents. The researchers found that this approach could be a useful tool for designers, allowing them to learn from past designs more easily.