Google Lens uses Vector Similarity Search (VSS), an AI-powered method to measure similarity between data, including images, to enable "visual search" or "semantic similarity" features in applications with just a few lines of code. VSS is particularly useful for comparing similarity in unstructured data such as images and long pieces of text. Pre-trained machine learning models like Hugging Face's and Torchvision's can be used to generate vector embeddings from unstructured data, which can then be stored in a database like Redis for efficient search capabilities. Redis Vector Similarity Search is a new feature that enables developers to store and query vector data with advanced indexing and search capabilities, turning Redis into a powerful real-time, in-memory vector database.