Lesson 1524 of 2116
Model distillation fundamentals: smaller, faster, mostly as good
Distill larger models into smaller ones for cost, latency, or deployment — accepting the trade-offs you choose.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2teacher model
- 3student model
- 4knowledge transfer
Concept cluster
Terms to connect while reading
Section 1
The premise
Distillation captures most of a teacher model's behavior in a smaller student; what is lost is rarely uniform across tasks.
What AI does well here
- Sketch a distillation pipeline from teacher outputs to student training.
- Estimate per-task capability gap from teacher to student.
What AI cannot do
- Guarantee the student matches teacher on rare or hardest cases.
- Replace task-specific evaluation.
Key terms in this lesson
End-of-lesson quiz
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