distilling education

Distilling education involves training a smaller, efficient model—called a "student"—to learn from a larger, more complex "teacher" model. The teacher has learned extensive knowledge, and its predictions guide the student to acquire similar capabilities. This process makes the student model faster and less resource-intensive while preserving much of the teacher’s accuracy. Essentially, it’s like learning from an expert teacher in a condensed form, enabling effective deployment of sophisticated AI in environments with limited computing power.