According to Gartner, supervised learning "works by feeding known historical input and output data into ML algorithms. In each step, after processing each input-output pair, the algorithm alters the model to create an output that is as close as possible to the desired result." [...] "Input and output data can be derived from historical data, through simulations or through human data labeling. In cases involving unstructured data, like images, video, audio or text, certain properties or categorizations can serve as output data. Supervised learning can be used to make predictions, recognize data or classify it."
Amelia is provided with a company's back-end data in order to help her form her responses to users' questions. This provides her with context, while observational learning helps her to continually advance her capabilities.