Agentic AI that can plan and execute complex scientific work using natural language, configure the platform itself, and ...

Objective: Our objective was to evaluate employing Large Language Models (LLMs) to systematically transform the rich, unstructured textual data from AskDocs into a structured dataset, an approach that ...

SQM (Structured Query Model) is a Java framework for representing SQL as a typed immutable model and running end-to-end SQL pipelines. It supports parse, validate, transform/rewrite, render, serialize ...

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 ...

Abstract: Text-to-SQL systems facilitate smooth interaction with databases by translating natural language queries into Structured Query Language (SQL), bridging the gap between non-technical users ...

At its Cloud Next conference, Google is showing off a new AI engine for AlloyDB that enables developers to embed natural language questions in SQL queries. Google is enhancing AlloyDB, its fully ...

Large Language Models (LLMs) have become crucial in customer support, automated content creation, and data retrieval. However, their effectiveness is often hindered by their inability to follow ...

pySQLY is a Python library that enables developers to write database queries using YAML syntax instead of traditional SQL. This approach simplifies database interactions, enhances readability, and ...

Natural Language to SQL (NL2SQL) technology has emerged as a transformative aspect of natural language processing (NLP), enabling users to convert human language queries into Structured Query Language ...

Background: Using Electronic Health Record (EHR) data to accurately phenotype patients for atherosclerotic cardiovascular disease (ASCVD) is crucial for clinical decision-making and research.