Generative AI systems operate differently enough that some assumptions underpinning today's governance approaches warrant ...

Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper appearing in Patterns. Though large language models ...

As technology and regulations evolve, enterprises need to address data governance throughout pipelines, models, and AI agents ...

Scaling agentic AI demands a strong data foundation - 4 steps to take first ...

In the past 18 months, the FDA has outlined clear guidelines for designing, documenting, updating, and monitoring AI-powered ...

Intelligence without integrity is just sophisticated risk. To build AI that lasts, you have to apply zero-trust principles to ...

The limitation for many companies investing in AI is not the sophistication of the models being deployed, but the lack of AI-ready data.

In 2026, AI threats shift from data leaks to operational chaos. Shadow agents with high-privilege access risk enterprise ...

They also let users adopt tiered approaches with containerized software at the edge-computing layer.” To connect legacy PLCs ...

Born in Rizhao, China, Qin overcame early hardships during the Cultural Revolution to pursue higher education at Tsinghua ...

Tungsten's superior performance in extreme environments makes it a leading candidate for plasma-facing components (PFCs) in ...

The SIGMOD community honors the research of BIFOLD researchers Arnab Phani and Matthias Böhm. Their work on eliminating the inefficient reuse of intermediate computations across multi-backend machine ...