Ai Alignment

Draws parallels between AI ‘scheming’ and ape language experiments, exploring deceptive tendencies in LLMs and the need for advanced monitoring for AI safety.

Examines the challenges of predicting AI agent behavior from observed actions and its implications for AI safety, alignment, and the need for robust monitoring.

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 Unit 1 of the BlueDot AI Alignment course, covering foundational concepts like neural networks, gradient descent, transformers, and the future impacts of AI.