Aligned Model

Aligned models aim to create artificial intelligence systems whose behavior and internal representations closely match human preferences and understanding. Current research focuses on improving alignment through iterative self-evaluation, efficient extrapolation techniques from pre-trained models, and bootstrapping methods to reduce reliance on expensive human annotation. These advancements are crucial for enhancing the safety, robustness, and generalizability of AI, particularly in applications involving complex tasks and limited data.