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Endigest AI Core Summary
This post introduces Google Cloud database labs that demonstrate how to prepare and use data layers for production-ready AI applications.
•Semantic search using text embeddings is covered across AlloyDB, Cloud SQL for PostgreSQL, and Cloud SQL for MySQL as grounding engines for RAG (Retrieval Augmented Generation)
•Multimodal embeddings enable search using both text and images, demonstrated with a product catalog stored in AlloyDB paired with images in Cloud Storage
•AlloyDB AI Functions like AI.IF allow on-the-fly semantic search and sentiment evaluation without prior data preparation
•The alloydb_ai_nl extension supports NL2SQL query generation with custom context, table relations, and metadata derived from real data samples
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These labs are part of the "From Data Foundations to Advanced RAG" module in Google's Production-Ready AI program
This summary was automatically generated by AI based on the original article and may not be fully accurate.
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