Anchors

Anchors are predefined reference points or targets used in machine learning models to improve accuracy during training. They serve as known benchmarks that guide the model’s understanding, helping it learn more effectively by providing context or specific examples. For example, in facial recognition, an anchor might be a verified image of a person’s face, which the system uses to compare and identify other images. Essentially, anchors help models focus on important features and improve their ability to make accurate predictions by anchoring their learning process around reliable reference points.