What’s the Magic Word? A Control Theory of LLM Prompting.

This article discusses a research paper that applies control theory to understand and improve Large Language Models (LLMs). The researchers, Aman Bhargava and Cameron Witkowski, frame LLMs as discrete stochastic dynamical systems, exploring the 'reachable set' of outputs. Their work emphasizes the importance of prompt engineering in influencing LLM outputs and suggests that control theory can lead to more reliable and capable language models. The article also promotes the ML Street Talk Pod and provides links to the Patreon and YouTube versions.

• •The research applies control theory to understand and improve LLMs.
• •Prompt engineering is crucial for influencing LLM outputs.
• •Control theory concepts could lead to more reliable and capable language models.