What is an embedding model?

Embedding models are a type of tool used in machine learning and artificial intelligence that simplifies large and complex data into a more manageable form. This process, known as embedding, involves reducing the data’s dimensions.

Imagine going from a detailed world map with highways, railroads, rivers, trails, and so on, to a simpler, summarized version with only country boundaries and capital cities. This not only makes computation faster and less resource-intensive, but also helps identify and understand relationships within the data. Because embedding models streamline the processing and analyzing of large datasets, they are particularly useful in areas of language (text) processing, image and sound recognition, and recommendation systems.

Consider a vast library where each book stands for one point in high dimensions. Embedding models can help reorganize the library to improve ease of navigation, such as by grouping the books on related...