The success of AI governance is intertwined with strong data governance. By reliably automating routine tasks and freeing human resources for more strategic work, AI can revolutionise data governance.

However, this growth has amplified the risk of sensitive information leaks within source code, exposing organizations to data breaches, regulatory penalties, and reputational damage. Hardcoded ...

The basic version of S2S AI uses the properties of the sense space to determine the meaning of the analyzed text as a single sentence, or, for example ... own anthological database, which is ...

Context engineering—the art of shaping the data, metadata, and relationships that feed AI—may become the most critical ...

Microsoft is aiming to make the search process more natural with the introduction of NLWeb, or natural language Web. NLWeb ...

Though Retrieval-Augmented Generation has been hailed — and hyped — as the answer to generative AI's hallucinations and ...

Having begun in the 1990s, the digitization of the property cadastre in Switzerland has now nearly been completed. At the same time, the ...

I've issued three monster articles (and four podcasts) about SAP Sapphire - but it wasn't enough. To kick off my spring event ...

The ETL architecture Saurabh developed incorporated robust error handling, data validation rules, and performance ...

This article explores the current applications of artificial intelligence (AI) in chromatography. It anticipates AI’s ...

NAB has detailed its 2023 Teradata decommissioning publicly for the first time, revealing how the data team rebuffed pressure ...

AI is poised to revolutionize UI/UX design by streamlining the design process, enhancing user experiences, and unlocking new ...