Contrastive learning is a method where a computer learns to recognize important differences and similarities between things.
Imagine you have many pictures of cats and dogs. The computer learns which pictures are similar (e.g., two cats) and which are different (cat and dog).
This way, the machine can better understand how things belong together or differ from each other.
This technique helps computers sort and recognize data better without needing many examples with explanations.
Contrastive learning is often used to learn good features from data that can then be used for other tasks.