Why RLHF Can't Scale: Understanding the Fundamental Limitations
Examining why RLHF faces fundamental limitations across scalability, human judgment quality, reward models, and governance that constrain the development of more capable AI …
The Economics of Alignment: Why RLAIF Delivers 11x Cost Reduction
A quantitative case study comparing the costs of human preference labeling (RLHF) versus synthetic preference generation (RLAIF), demonstrating how computational approaches …
Synthetic Alignment Research: Key Insights for AI Leaders
This four-part research series examines why RLHF faces fundamental limitations and how synthetic alignment methods are reshaping the field, distilling insights from 20+ recent …