representations in artificial intelligence

In artificial intelligence, representations are ways of organizing and encoding information so that computers can understand and manipulate it. Think of it as how concepts, data, or patterns are stored internally—like language, images, or numerical data—so the AI can analyze, learn from, and make decisions about them. Good representations capture essential features while filtering out irrelevant details, enabling AI systems to perform tasks such as recognizing objects in photos, understanding language, or predicting outcomes effectively. Essentially, representations are the internal maps that allow AI to interpret and work with complex information efficiently.