How I had a large AI, not people, write the "gold data" that trains a specialist
The "gold data" that trains a specialist AI is something humans write — I threw that assumption out. I had a large AI write it, and a small AI copy it out. Japanese→English, the direction the small model was worst at, jumped 42% → 84% on straight imitation alone. Zero human translators.
The ceiling above that sat not with the teacher but with the student's comprehension capacity (the teacher's own translations passed almost across the board). Lump every ceiling together as "the teacher is bad" and you pick the wrong move.
And one pitfall. Hand the teacher surrounding context with the best of intentions, and the student learns to invent subjects. Build the teacher data under the same input conditions as production — the way kindness backfires only becomes visible once you measure.
Training a small AI into "a specialist at one job" takes a large volume of gold data. A stack of model answers saying "for this input, this translation is the right answer." For translation, that's a pair — the source text and its model translation.
