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 neural ...

Bob van Luijt's career in technology started at age 15, building websites to help people sell toothbrushes online. Not many 15 year-olds do that. Apparently, this gave van Luijt enough of a head start ...

Since the birth of artificial intelligence (AI), the journey of understanding human intelligence in neuroscience is on the same path as the pursuit of machine intelligence for graph learning in AI.

Crystal structures have a decisive impact on the properties of materials, and research on crystal structures often serves as a starting point for material studies. Crystal structure prediction is a ...

Science and data are interwoven in many ways. The scientific method has lent a good part of its overall approach and practices to data-driven analytics, software development, and data science. Now ...

Flooding is the deadliest natural disaster in India and accounts for over 40% of all fatalities caused by catastrophic weather events. River channels lose part of their carrying capacity due to ...

Bringing knowledge graph and machine learning technology together can improve the accuracy of the outcomes and augment the potential of machine learning approaches. With knowledge graphs, AI language ...

There’s been a debate of sorts in AI circles about which database is more important in finding truthful information in generative AI applications: graph or vector databases. AWS decided to leave the ...

Kicking off on Tuesday, the Google I/O developer conference tends to be more than just an extravaganza for the techie set. It’s also a spotlight for the company’s vision and priorities — and shopping ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...