YOLO (You Only Look Once) is a real-time object detection system that can detect multiple objects in an image or video with high accuracy and speed. It uses a single neural network to predict bounding boxes and class probabilities directly from full images in one evaluation, making it highly efficient for real-time applications. YOLO is widely used in tasks like surveillance, autonomous driving, and video analysis. The model's speed and accuracy make it suitable for applications that require fast processing, such as in embedded systems or mobile devices. Over time, newer versions of YOLO have continuously improved its accuracy and reduced latency, solidifying its place as a top choice for object detection tasks.