Patterns are recurring structures or sequences that an
AI model learns to identify during its
training with
datasets. They enable the recognition of regularities, the making of predictions, and decision-making when analyzing new information.
Patterns can be found in any type of data: numbers, text, images, or sound.
AI models learn to detect anything from simple relationships to complex features that repeat in data, similar to how humans recognize faces through the unique combination of traits.
For example, a model can identify patterns in shopping behavior (which products are often purchased together), in medical images (disease indicators), or in urban traffic (predicting traffic jams based on schedules and events).
The ability to recognize increasingly complex patterns is what enables modern AI to perform advanced tasks like language translation, fraud detection, or personalized recommendations in streaming services.