Deep Learning and Machine Learning has made breakthroughs in recent years. There is tens of billions of dollars going into development of the new AI.

Rebooting AI: Deep learning, meet knowledge graphs Gary Marcus, a prominent figure in AI, is on a mission to instill a breath of fresh air to a discipline he sees as in danger of stagnating.

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 ...

As Toon reminds The Next Platform, deep learning frameworks are capturing a knowledge model from data and the best way to represent those features and represents is via a computational graph. At their ...

A graph approach leaves machine learning users with a structure that can expose a huge amount of parallelism (each of the vertexes might have, for example, 25 million parameters) and that is a lot of ...

A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

TigerGraph, provider of a leading graph analytics platform, is introducing the TigerGraph ML (Machine Learning) Workbench-a powerful toolkit that enables data scientists to significantly improve ML ...

A research team from Kumamoto University has developed a promising deep learning model that significantly enhances the accuracy of subgraph matching—a critical task in fields ranging from drug ...