To continue reading this content, please enable JavaScript in your browser settings and refresh this page. Preview this article 1 min Plans have been filed for Panda ...

In July and August, 1946, I washed the breakfast, lunch, and dinner dishes of three hundred people. This was at Keewaydin, a summer camp on Lake Dunmore, in Vermont. The kitchen had two notable ...

Data teams building AI agents keep running into the same failure mode. Questions that require joining structured data with unstructured content, sales figures alongside customer reviews or citation ...

A new tool from Google Cloud aims to improve the accuracy of AI agents querying databases in multi-agent systems or applications. However, to create that necessary understanding, enterprise teams ...

Traditional RAG systems struggle bridging structured SQL databases and unstructured document collections (a challenge we call the modality gap), leading to incomplete reasoning and hallucinations.

Timothy Beck Werth is the Tech Editor at Mashable, where he leads coverage and assignments for the Tech and Shopping verticals. Tim has over 15 years of experience as a journalist and editor, and he ...

Building retrieval-augmented generation (RAG) systems for AI agents often involves using multiple layers and technologies for structured data, vectors and graph information. In recent months it has ...

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The query optimizer is a crucial component in a relational database system and is responsible for finding a good execution plan for a SQL query. For cloud database service providers, the importance of ...

This project teaches language models to accurately answer questions about tabular data. The core challenge is that large tables cannot fit into an LLM's context window, yet we need the model to ...

Query groups uses AI to cluster similar search queries. The new card shows total clicks per group and highlights groups trending up or down. Query groups will roll out over the coming weeks to high ...