Summary
Knowledge distillation trains a smaller student AI model by using prompts and reasoning outputs from a larger, more advanced teacher model. This process allows the cheaper student model to replicate the expensive teacher's advanced capabilities at a fraction of the computational cost and without accessing its source code.
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