Ever since large language models (LLMs) exploded onto the scene, executives have felt the urgency to apply them enterprise-wide. Successful use cases such as expedited insurance claims, enhanced ...

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In the realm of Artificial Intelligence (AI), knowledge graphs stand as a crucial innovation, particularly influential in areas like machine learning and natural language processing (NLP). These ...

While Large Language Models (LLMs) like LLama 2 have shown remarkable prowess in understanding and generating text, they have a critical limitation: They can only answer questions based on single ...

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 ...

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 ...

What if you could transform overwhelming, disconnected datasets into a living, breathing map of relationships, one that not only organizes your data but also reveals insights you didn’t even know you ...

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 ...

Discover what context graphs are, why they're revolutionizing AI systems, and who's building this trillion-dollar technology ...

Debate and discussion around data management, analytics, BI and information governance. This is a guest blogpost by Jim Webber, Chief Scientist at graph database provider Neo4j. It discusses Knowledge ...