principles.fyi · the brain · concept

model alignment

Adjusting a model so its behaviour matches what people actually want.

Alignment is the goal that post-training serves: nudging an LLM toward being helpful (it does what you asked), honest (it does not make things up or mislead), and harmless (it refuses to cause damage). A pretrained base model has none of this on purpose — it just predicts likely text — so alignment is the work of layering human intent on top, usually through instruction tuning followed by preference-alignment methods like RLHF or DPO. It is a direction to steer toward, not a fixed recipe, which is why different labs reach it by different combinations of techniques.