Model1h ago
Fundamental Flaw Makes LLMs Permanently Vulnerable
Researchers at the International Conference on Machine Learning argue that large language models cannot be fully secured against hacks. This vulnerability stems from the core architecture of how these models process information. Developers cannot patch this flaw with traditional security layers. It forces a rethink of how LLMs are deployed in high-stakes environments.