Build your first fully functional, Java-based AI agent using familiar Spring conventions and built-in tools from Spring AI.

The purpose of the Text-to-SQL task is to bridge the gap between natural language and SQL queries. Current approaches mainly rely on large language models (LLMs), but employing them for Text-to-SQL ha ...

Abstract: The increasing reliance on data-driven decision making has made database interaction a critical component in many domains. However, writing Structured Query Language (SQL) queries requires ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. This voice experience is generated by AI. Learn more. This ...

With new updates in the search world stacking up in 2026, content teams are trying a new strategy to rank: LLM pages. They’re building pages that no human will ever see: markdown files, stripped-down ...

QuantLens converts natural language into SQL using a local LLM. Your data never leaves your machine. ┌─────────────────────────────────────────────────────────────────┐ │ │ │ "What are the top 5 ...

From the recent momentum behind translating natural language to SQL (nl2sql), to commercial product offerings such as Co-Pilot for Microsoft Fabric, Large Language Models (LLMs) are poised to have a ...

Semantic caching in LLM (Large Language Model) applications optimizes performance by storing and reusing responses based on semantic similarity rather than exact text matches. When a new query arrives ...

In most enterprises, data access still feels like a locked room with SQL as the only key. Business teams depend on data engineers for every report, dashboard, or metric tweak. Even in the age of ...