The road to competitive advantage and differentiation based on learning to think in graphs is going to be different for each company. But it is a road worth traveling.

Graph database developer Neo4j Inc. is upping its machine learning game today with a new release of Neo4j for Graph Data Science framework that leverages deep learning and graph convolutional ...

Graph-structured data are pervasive in the real-world such as social networks, molecular graphs and transaction networks. Graph neural networks (GNNs) have achieved great success in representation ...

This article explores what knowledge graphs are, why they are becoming a favourable data storage format, and discusses their potential to improve artificial intelligence and machine learning ...

Google DeepMind and Intrinsic developed AI that uses graph neural networks and reinforcement learning to automate multi-robot ...

Lead author Matthew Lai, a PhD researcher at UCL and Google DeepMind, said, “RoboBallet transforms industrial robotics into a choreographed dance, where each arm moves with precision, purpose, and ...

As 2022 dawns, knowledge graphs bear the dubious distinction of being at the epicenter of AI and machine learning for two reasons. One is that, unassisted, they are one of the myriad manifestations of ...