> Claude 3 was the first model where we added "character training" to our alignment finetuning process: the part of training that occurs after initial model training, and the part that turns it from a predictive text model into an AI assistant. The goal of character training is to make Claude begin to have more nuanced, richer traits like curiosity, open-mindedness, and thoughtfulness.
What I found particularly interesting is how they implemented this using primarily synthetic data:
> We ask Claude to generate a variety of human messages that are relevant to a character trait—for example, questions about values or questions about Claude itself. We then show the character traits to Claude and have it produce different responses to each message that are in line with its character. Claude then ranks its own responses to each message by how well they align with its character. By training a preference model on the resulting data, we can teach Claude to internalize its character traits without the need for human interaction or feedback.
What I found particularly interesting is how they implemented this using primarily synthetic data:
> We ask Claude to generate a variety of human messages that are relevant to a character trait—for example, questions about values or questions about Claude itself. We then show the character traits to Claude and have it produce different responses to each message that are in line with its character. Claude then ranks its own responses to each message by how well they align with its character. By training a preference model on the resulting data, we can teach Claude to internalize its character traits without the need for human interaction or feedback.