Yes, vector search powers search engines for text and images by encoding their semantic meaning into vectors, allowing for deeper understanding and relevance in search results. Unlike traditional keyword-based searches, vector search retrieves results based on the context and meaning of the query, even when exact terms aren't used.
In text search, vector-based engines can handle queries like “affordable beach vacations” by retrieving results related to inexpensive coastal trips without requiring an exact match. Similarly, these engines improve search results in legal or academic domains by identifying contextually relevant documents based on complex queries.
For image search, vector search compares visual features extracted from an image query to those in a database. For instance, uploading a photo of a shoe might retrieve similar shoe designs or colors, aiding fashion retailers. Additionally, multi-modal search—where text and image inputs are combined—enhances user experience by linking different media types semantically.