Knowledge distillation transfers capabilities from large teacher models to smaller student models.
- True
- False
Answer: True
Knowledge distillation trains compact models to mimic large teacher outputs, enabling efficient deployment on edge devices with minimal accuracy loss. Critical for scalable AI systems.