The article explores the concept of Large Language Model (LLM) red teaming, a practice where practitioners provide inputs to LLMs to test their boundaries and assess risks. It discusses the characteristics of LLM red teaming, including its manual, collaborative, and exploratory nature. The article also delves into the motivations behind red teaming, the strategies employed, and how the findings contribute to model security and safety.
An article discussing ten predictions for the future of data science and artificial intelligence in 2025, covering topics such as AI agents, open-source models, safety, and governance.
The article discusses how open-source Large Language Models (LLMs) are helping security teams to better detect and mitigate evolving cyber threats.
AI Risk Database is a tool for discovering and reporting the risks associated with public machine learning models. It provides a comprehensive overview of risks and vulnerabilities associated with publicly available models.
