Reverse-engineering LLMs

In a recent video, Discover AI delves into groundbreaking research from MIT on reverse-engineering large language models (LLMs) through conditional queries and barycentric spanners. The study outlines a novel method for efficiently learning from low-rank distributions, highlighting potential security threats to proprietary models. By leveraging mathematical techniques, the researchers present a framework for approximating the behavior of LLMs without direct access to their internal parameters, raising critical questions about data privacy and cybersecurity in AI.