How to Get the Right Vector Embeddings

What this post added

This post provides a comprehensive introduction to vector embeddings, explaining their creation, meaning, and generation for various data types (images, text, audio, video, multimodal). It details how to extract embeddings from deep learning models by removing the last layer and discusses popular open-source models and libraries for generating these embeddings. While it mentions using vector databases like Milvus and Zilliz Cloud, it does not introduce new engineering capabilities or significant updates to existing ones within Milvus itself. The technical depth is focused on the embedding generation process rather than Milvus's internal systems.