Embeddings are a fundamental concept in machine learning and natural language processing, referring to the representation of complex data, such as words, images, or entities, as dense vectors in a high-dimensional space. By capturing nuanced relationships and patterns in the data, embeddings enable AI models to better understand and process information, driving advancements in applications like text classification, recommender systems, and computer vision, making them a crucial area of research in the tech community.