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 ...

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 ...

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 ...

How to use knowledge graphs to improve customer experience — digging into the healthcare example. Knowledge graphs are well known to the Pharma industry, and their power has been utilized for many ...

Ever since the introduction of the Google Knowledge Graph, a growing number of organizations have adopted this powerful technology to drive efficiency and effectiveness in their data management.

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 ...

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 ...