Abstract: Querying relational databases through natural language remains a difficult task, especially for users without knowledge of SQL. Existing Text-to-SQL approaches often face issues of semantic ...

Every data engineering team right now is being asked the same question: "How do we build a chatbot that talks to our data?" The prototypes are deceptively simple. A developer connects GPT-5.1 to a ...

Abstract: Aiming to reduce the learning cost of database operations, Text-to-SQL methods provide a strategy of automatically generating structured query language (SQL), which is an active research ...

Semantic SEO helps search engines understand context. Learn how to use entities, topics, and intent to build richer content that ranks higher. Semantic SEO aims to describe the relationships between ...

Discover how Tinker and Ray are utilized to fine-tune text-to-SQL models, enhancing AI capabilities in generating efficient SQL queries. In an innovative approach to advancing text-to-SQL models, ...

In this tutorial, we build an advanced AI agent using Semantic Kernel combined with Google’s Gemini free model, and we run it seamlessly on Google Colab. We start by wiring Semantic Kernel plugins as ...

A new SQL Server 2025 feature lets organizations run vector-based semantic searches on their own data, connecting to local or cloud-hosted AI models without relying on massive general-purpose LLMs. I ...

In this tutorial, we walk you through the seamless integration of AutoGen and Semantic Kernel with Google’s Gemini Flash model. We begin by setting up our GeminiWrapper and SemanticKernelGeminiPlugin ...