Solving the Human Training Data Problem

A graduate student discovered that without access to past exam papers for practice, studying effectively becomes a significant hurdle, a situation he terms the "Human Training Data Problem." To overcome this lack of "training data," he turned to large language models to generate synthetic practice exams tailored to his courses. By feeding an AI all available course materials, from lecture slides to vague hints from Q&A sessions, he was able to create realistic and challenging mock tests. This novel approach of creating synthetic study materials successfully bridged the gap between theoretical knowledge and the practical problem-solving skills needed to pass his finals.