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SQL Server gains local AI and secure RAG integration options

SQL Server 2025 is introducing AI-native capabilities alongside new approaches for secure integration with large language models. Enterprises can now run local AI models such as Llama 3 via Ollama for ...
VentureBeat

Table-augmented generation shows promise for complex dataset querying, outperforms text-to-SQL

AI has transformed the way companies work and interact with data. A few years ago, teams had to write SQL queries and code to extract useful information from large swathes of data. Today, all they ...

The RAG era is ending for agentic AI — a new compilation-stage knowledge layer is what comes next

Vector database pioneer Pinecone recognizes this and is pivoting to meet the specific needs of agentic AI. The company today ...
dbta

RESEARCH@DBTA: Survey: RAG Emerges as the Connective Tissue of Enterprise AI

While the generative AI (GenAI) revolution is rolling forward at full steam, it’s not without its share of fear, uncertainty, and doubt. The great promises that can be delivered through large language ...
dbta

A Deep Dive into RAG Adoption and Optimization with Elastic

Retrieval-augmented generation—or RAG—is an AI strategy that supplements text generation with information from private or proprietary data sources, according to Elastic, the search AI company. RAG ...
InfoWorld

What is retrieval-augmented generation? More accurate and reliable LLMs

Retrieval-augmented generation, or RAG, integrates external data sources to reduce hallucinations and improve the response accuracy of large language models. Retrieval-augmented generation (RAG) is a ...
CIO

Vector Database vs. Knowledge Graph: Making the Right Choice When Implementing RAG

Whether IT leaders opt for the precision of a Knowledge Graph or the efficiency of a Vector DB, the goal remains clear—to harness the power of RAG systems and drive innovation, productivity, and ...