Model3h ago
Fundamental Flaw Leaves LLMs Vulnerable To Attack
Researchers at the International Conference on Machine Learning claim LLMs cannot be fully secured against hacks. This vulnerability stems from a core architectural flaw in how these models process information. Developers must now weigh the trade-off between model utility and inherent security risks. The finding suggests a ceiling on current safety measures.