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  Overview Vector databases have become popular with the rise of Generative AI . Advanced technologies such as CHAT-G PT  and Gemini rely heavily on vector data. If you want to work with AI, understanding vector data is essential. Embeddings Embeddings are numerical vector representations of unstructured data such as text, images, and audio. They preserve semantic meaning, enabling related content to be located efficiently. Example input: “I love AI”  --->  The sentence is transformed into a vector that captures its semantic intent. Embeddings  are a key technique in AI. They transform text, images, and audio into numerical vectors so that machines can easily process and understand them. Source   How Do Vector Databases Work? User Query - The user enters a question into ChatGPT. Embedding Creation - ChatGPT converts the input data into a vector embedding that represents the core meaning of the question. Database Comparison - This vector em...