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How has John Mosquera utilized vector databases and search technologies in his AI projects?
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John has explored various vector databases and search technologies to enhance his AI projects. He's used MongoDB, PostgreSQL (with pgvector), Elasticsearch, Weaviate, Redis (with Redis-Search and Redis-VSS), and Pinecone to implement efficient vector search capabilities. These technologies allow him to handle large-scale vector data and perform similarity searches, which are crucial for applications like recommendation systems and semantic search. John Mosquera has utilized MongoDB, PostgreSQL (pgvector), Elasticsearch, Weaviate, Redis (Redis-Search and Redis-VSS), and Pinecone for vector search capabilities in his AI projects.