As AI applications become increasingly sophisticated, they rely on powerful tools to process, store, and query data efficiently. One of the most critical tools in this space is the vector database . If you're working with AI models, especially those involving embeddings , understanding vector databases can significantly improve how you work with large datasets and retrieval tasks. In this article, we’ll explore what vector databases are, their role in AI, and take ChromaDB as an example of how they function in real-world applications. What is a Vector Database? A vector database is a specialized database designed to store, manage, and query vectors – mathematical representations of data. Vectors are often used to represent high-dimensional data like text, images, audio, or even video, which are converted into embeddings (numerical representations generated by AI models). For example: A sentence like "What is AI?" can be converted into a 768-dimensional vector by...
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