How AI Gets Smarter by Focusing on Its Weak Spots
What if your AI could study the same way you do, zeroing in on the topics it still finds tricky? Skill‑Targeted Adaptive Training makes that happen.
A powerful “teacher” AI looks at a math problem set, lists the exact skills needed, and tags each question with those skills.
Then it watches the student AI answer, noting which skills it missed – creating a “missing‑skill profile.
” Think of it like a personal tutor who gives you extra worksheets on the chapters you got wrong.
Using that profile, the teacher either reshuffles existing examples to stress the weak areas (STAT‑Sel) or even writes brand‑new practice problems (STAT‑Syn).
The result? The AI improves by up to 7.
5% on tough math tests and gains a solid boost on fresh challenges it never saw before.
It’s a simple idea with a big impact, showing that teaching AI to fill its own gaps can make it far more capable in everyday tasks.
The future of smarter assistants may just be a little bit more like a good teacher.
Read article comprehensive review in Paperium.net:
Skill-Targeted Adaptive Training
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