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 ...

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

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

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

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

With data quality and governance key to AI success, IT leaders — and their CEOs — can no longer overlook data debt. Experts ...

AI governance is not merely a regulatory requirement, but also the strategic infrastructure that enables sustainable ...

A robust and quantitative map links chromatin modification and gene expression of cells during zebrafish embryogenesis.

Coding errors or data poisoning can create security challenges in the AI supply chain. Here's how to prevent that from ...

As AI accelerates across biopharma and other science-driven industries, organizations are encountering a critical bottleneck: advanced technologies fall short without proper scientific context. In a ...

Protein engineering is a field primed for artificial intelligence research. Each protein is made up of amino acids; to ...