Today, we are going to dive into one of the most important research papers of the last few months published by Anthropic. This is a must read if you care about security and the potential vulnerabilities of LLMs.

Security is one of the most fascinating areas in the new generation of foundation models, specifically LLMs. Most security techniques designed until now have been optimized for discrete systems that with well understood behaviors. LLMs are stochastic systems that we understand very little. The evolution of LLMs have created a new attack surface for these systems and we are just scratching the surface of the vulnerabilities and defense techniques. Anthropic explored this topic in detail in a recent paper : Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training

The focus of Anthropic’s research is focused on scenarios where an LLM might learn to mimic compliant behavior during its training phase. This behavior is strategically designed to pass the training evaluations. The concern is that once deployed, the AI could shift its behavior to pursue goals that were not intended or aligned with its initial programming. This scenario raises questions about the effectiveness of current safety training methods in AI development. Can these methods reliably detect and correct such cunning strategies?...