Abstract: The Text-to-SQL task has significant application prospects in automating relational database query interfaces. It can reduce user learning costs and improve data query efficiency. However, ...

Abstract: Generating accurate SQL from users' natural language questions (text-to-SQL) remains a long-standing challenge due to the complexities involved in user question understanding, database ...

The first release candidate (RC0) of SQL Server 2025 is now available. As we move toward general availability, our focus shifts to delivering enhanced stability, performance, and product improvements ...

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 ...

Snowflake has thousands of enterprise customers who use the company's data and AI technologies. Though many issues with generative AI are solved, there is still lots of room for improvement. Two such ...

As developers look to harness the power of AI in their applications, one of the most exciting advancements is the ability to enrich existing databases with semantic understanding through vector search ...

Organizations are using generative AI to stay ahead of the competition, but the real advantage lies in harnessing the power of your own data securely and at scale. One of the most exciting new ...

The United Nations Security Council adopted its first resolution, S/RES/1(1946), on 25 January 1946 – long before the current modes of online distribution of documents. As of 30 November 2024, the ...

Security researchers have found a vulnerability in a key air transport security system that allowed unauthorized individuals to potentially bypass airport security screenings and gain access to ...

Oracle SQL Developer is a great tool for managing Oracle Databases. It has a user-friendly interface that makes it easier to handle database tasks. The software offers features to simplify workflows ...

Current methodologies for Text-to-SQL primarily rely on deep learning models, particularly Sequence-to-Sequence (Seq2Seq) models, which have become mainstream due to their ability to map natural ...