While retrieval-augmented generation is effective for simpler queries, advanced reasoning questions require deeper connections between information that exist across documents. They require a knowledge ...

In the quest to teach software to understand language, scientists have mainly focused on text as a source of data to help train their algorithms. Among other things, text is used to populate a ...

Understand the building blocks of knowledge graphs – entities, relationships and attributes – and how they relate to information retrieval. Knowledge graphs are reshaping how we organize and make ...

Generative AI depends on data to build responses to user queries. Training large language models (LLMs) uses huge volumes of data—for example, OpenAI’s GPT-3 used the CommonCrawl data set, which stood ...

At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...

Google introduced the Knowledge Graph in 2012 to help searchers discover new information quicker. Essentially, users can search for places, people, companies, and products and find instant results ...

The unprecedented explosion in the amount of information we are generating and collecting, thanks to the arrival of the internet and the always-online society, powers all the incredible advances we ...

This may come as a shock if you've first encountered knowledge graphs in Gartner's hype cycles and trends, or in the extensive coverage they are getting lately. But here it is: Knowledge graph ...