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).

The paper elaborates on a technique for using knowledge graphs with machine learning; specifically, a branch of machine learning called reinforcement learning. This is something that holds great ...

and machine learning. According to Communications of the ACM (hereafter referred to as ACM), knowledge graphs are important for deepening understanding of ideas and technologies in a variety of ...

You can even generate embeddings from this graph (encompassing both its data and its structure) that can be used in machine learning pipelines or as an integration point to LLMs. But a knowledge ...

the industry’s first knowledge graph coprocessor for the data cloud. Nikolaos has over 20 years of experience implementing high-value machine learning and AI solutions across various industries.

Before gen AI, companies used to try to create knowledge graphs with machine learning. “We used to use natural language processing to create knowledge graphs, using name entity recognition and ...

A knowledge graph is an information-rich structure that provides a ... You can even generate embeddings from this graph (both its data and its structure) which can be used in machine learning ...

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization ...