Oracle announces agentic AI capabilities for Oracle AI Database, including Private Agent Factory, Deep Data Security, and ...

Neo4j Aura Agent is an end-to-end platform for creating agents, connecting them to knowledge graphs, and deploying to ...

AI data curation will hit $253B by 2030. As "dirty data" costs firms $12.9M , shifting to agentic memory and synthetic ...

Google’s generative AI tool can quickly surface trends in your data, generate charts and formulas, clean up your data, and ...

The latest GPT-5.4 mini model delivers benchmark results surprisingly close to the full GPT-5.4 model while running much ...

The next phase of blockchain adoption will not be defined by blockspace alone. It will be defined by data. As onchain finance, tokenization, AI agents, and institutional workflows scale, the demand ...

Have you ever gone to sleep with visions of gelatin bubbles dancing in your head? What about information on 70 million financial securities and 40,000 data fields? Marvin Ward knows what both are like ...

Abstract: Various graph models have emerged to meet diverse application needs, each with unique characteristics and specialties. Managing and analyzing graph data inevitably requires interactions ...

Abstract: Graph matching, as an important query technology, has been widely applied in various fields. With the increasing of graph data, users choose to encrypt a large number of graphs and store ...

An explosion of user-generated data from online social networks motivates analysis to extract deep insights from this data’s graph at scale, even of social, temporal, spatial, and topical connections.

I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...