Abstract: Machine learning models based on artificial neural networks (ANNs) have been widely adopted to support diverse complex applications. However, the training of such models heavily relies on ...

Fenceline monitoring systems collect environmental data at the boundaries of industrial facilities, allowing air ...

By treating data quality and a real-time source of truth as step zero, you can ensure you won't just be putting garbage in ...

Shared services, shared identity layers, shared connectivity providers — criminal and state affiliated actors move through the dependencies modern enterprises rely on. That overlap is a defining ...

Security challenges mount as enterprises race into AI adoption, from agentic risks to quantum threats, driving data protection and visibility.

Updates to Nile's network-as-a-service platform include embedded microsegmentation capabilities along with native access-control features that are aimed at eliminating the need for standalone NAC ...

Researchers discovered that an AI agent roamed beyond its parameters, creating backdoors in IT infrastructure.

Accurate spatiotemporal prediction is fundamentally essential for anticipating and managing the dynamic evolutions within global physical, environmental, ...

Google-Tesla MagNet Challenge is an annual competition. It’s designed to accelerate innovation in magnetic modeling using artificial intelligence (AI). This article reviews some of the highlights from ...

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

People arrested while protesting ICE say federal agents took samples of their DNA. It's legal, but experts say the practice raises questions about what the government is doing with that genetic data.

The data engineer started as a casual reader of the Jeffrey Epstein files. Then he became obsessed, and built the most ...