Transforming language models into effective red teamers is not without its challenges. Modern large language models have transformed the way we interact with technology, yet they still struggle with preventing the generation of harmful content. Efforts such as refusal training help these models deny risky requests, but even these safeguards can be bypassed with carefully… →

Artificial intelligence in multi-agent environments has made significant strides, particularly in reinforcement learning. One of the core challenges in this domain is developing AI agents capable of communicating effectively through natural language. This is particularly critical in settings where each agent has only partial visibility of the environment, making knowledge-sharing essential for achieving collective goals.… →

Recent discussions on AI safety increasingly link it to existential risks posed by advanced AI, suggesting that addressing safety inherently involves considering catastrophic scenarios. However, this perspective has drawbacks: it may exclude researchers with different approaches, mislead the public into thinking AI safety is solely about existential threats, and create resistance among skeptics. As AI… →