Graph-based metamaterial modeling and construction principles have been introduced, including the set up. By using this strategy, the authors have demonstrated how to obtain beam-like and plane wave ...

Alongside text-based large language models (LLMs), including ChatGPT in industrial fields, GNN (Graph Neural Network)-based graph AI models that analyze unstructured data such as financial ...

A graph model has exactly as much semantic meaning as you want, with no normalization and no waste. Additionally, the graph model supports object-oriented thinking, as clear, explicit semantics are ...

TigerGraph, maker of a graph analytics platform for data scientists, during its Graph & AI Summit event today introduced its TigerGraph ML (Machine Learning) Workbench, a new-gen toolkit that ...

The core of this patent lies in utilizing large models to optimize the summarized Q&A capabilities of private domain ...

A sui generis, multi-model open source database, designed from the ground up to be distributed. ArangoDB keeps up with the times and uses graph, and machine learning, as the entry points for its ...

Graph analysis is not a new technology, but many analytics professionals remain unfamiliar with it. One reason for this is that most people learn to associate data modeling with only one structure ...

As graph database adoption accelerates, new data infrastructures will emerge to eliminate many of the scale struggles of graph database models.