A practical overview of security architectures, threat models, and controls for protecting proprietary enterprise data in retrieval-augmented generation (RAG) systems.

Alternatively, data from all transducers can be used while limiting the focal depth, allowing more transmit-receive pulses to ...

The HOLiFOOD consortium is reimagining food safety risk assessment for the benefit of all stakeholders in the food chain ...

Aramco has been one of the safety pioneers in the oil and gas industry since its inception, more than 90 years ago. The ...

While AI models may exhibit addiction-like behaviors, the technology is also proving to be a powerful ally in combating real ...

Galantas Gold Corporation (TSX-V: GAL | AIM: GAL) ("Galantas" or the "Company") is pleased to announce that on January 6, 2026 it has entered into a share purchase ...

Also featuring deep dives into rampant worker injuries in automobile factories, health hazards from imported scrap tires, and ...

Learn how to implement algorithmic agility and post-quantum cryptography in MCP server-client negotiations to secure AI infrastructure against future threats.

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data ...

O n Tuesday, researchers at Stanford and Yale revealed something that AI companies would prefer to keep hidden. Four popular ...

New research shows that AI doesn’t need endless training data to start acting more like a human brain. When researchers ...