As developers look to harness the power of AI in their applications, one of the most exciting advancements is the ability to enrich existing databases with semantic understanding through vector search ...
DataHub's Context Intelligence mines validated SQL query history to build a semantic index for AI agents. At Miro, agents hit ...
Microsoft has found a new use for natural language processing capabilities in machine learning large language models (LLMs): SQL queries. The company has set up a sandbox for developers and data pros ...
Modern semantic search does not have to require a separate vector database. Data architects, database engineers, developers, or platform leaders can integrate Vertex AI and Cloud SQL vector indexes ...
The standard architecture — chunking documents, embedding them into a vector database, and retrieving top-k results via cosine similarity — is effective for unstructured semantic search. However, for ...
With an emphasis on AI-first strategy and improving Google Cloud databases' capability to support GenAI applications, Google announced developments in the integration of generative AI with databases.
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