Anthropic

A diary entry covering AI personalities, utility engineering for emergent value systems, and methods for evaluating the goal-directedness of Large Language Models (LLMs).

A diary entry on common use cases for AI models and the risks of models obfuscating their reasoning to evade safety monitors.

A diary entry on advanced prompt engineering techniques and the faithfulness of LLM self-explanations for commonsense tasks.

A diary entry on the challenges of scaling interpretability for complex AI models and methods for measuring the faithfulness of LLM explanations.

A diary entry introducing AI interpretability and discussing a paper on the limitations of sparse autoencoders for finding canonical units of analysis in LLMs.

A diary entry on Anthropic’s strategies for combating AI-enabled cybercrime, including threat intelligence, robust safety protocols, and collaboration to prevent misuse of AI systems.

A diary entry on ‘Alignment Faking’ in Large Language Models (LLMs), exploring how models can superficially appear aligned while pursuing misaligned goals, and methods for detection and mitigation.

A diary entry on defending against AI jailbreaks, discussing Anthropic’s strategies for bypassing model safety constraints to elicit harmful or unintended responses.

A diary entry on tracing the reasoning processes of Large Language Models (LLMs) to enhance interpretability, and a discussion on the inherent difficulties and challenges in achieving AI alignment.

A diary entry on the societal impacts of AI, including ethical concerns like bias and job displacement, and strategies for controlling powerful AI systems to ensure alignment and mitigate risks.