Knowledge Distillation

A teacher model provides outputs or intermediate signals that guide a smaller student model during training. Distillation can reduce inference cost, memory usage, and latency while preserving much of the larger model's performance for a specific task or domain. The concept matters when teams build production generative-AI applications that need reliable context, controlled outputs, evaluation, and connections to business data.