Ragnerock Launches Public Beta of Its Research Intelligence Platform, Making Any Data Source Queryable with standard SQL

Chicago-based startup removes barrier between raw, unstructured data and the tools analysts already use, making every ...

Companies are spending millions on AI, but a flaw in database strategy is eating returns

IEEE research highlights multi-model databases outperform single-model systems, reducing AI costs, latency, and schema issues ...

Databricks research shows multi-step agents consistently outperform single-turn RAG when answers span databases and documents

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 ...
IEEE

CCS-SQL: Enhancing Text-to-SQL Framework for Computational Queries via Large Language Models

Abstract: The Text-to-SQL task is to convert natural language queries into Structured Query Language (SQL) to achieve a natural language interface for database queries. The current research on Text-to ...
ascopubs.org

Development and Assessment of a Pipeline for Extracting Structured Data From Free-Text Medical Reports Using a Large Language Model

Medical free texts such as pathology reports contain valuable clinical data but are challenging to structure at scale. Traditional natural language processing approaches require extensive annotated ...
Frontiers

Large language models for closed-library multi-document query, test generation, and evaluation

Learning complex, detailed, and evolving knowledge is a challenge in multiple technical professions. Relevant source knowledge is contained within many large documents and information sources with ...
University of Vermont

A brief introduction to databases with SQLite

We have seen how to read data from a file, either in unstructured text or CSV format, and how to write data in these formats. We’ve also seen how to read and write JSON. In this chapter we’ll see how ...