Part 2/8:
Unlike conventional training approaches that focus solely on whether the final answer is correct, process supervision evaluates every reasoning step the AI takes toward solving a problem. Essentially, instead of waiting for the AI to produce an answer and then checking its correctness, this method provides real-time feedback at each step, guiding the AI to think more logically and systematically.
For example, in mathematical problem solving, process supervision trains AI to follow a chain of reasoning—adding, subtracting, or solving for variables step-by-step—and receives feedback on each. Correct steps are rewarded, while mistakes are penalized, enabling the AI to learn from its reasoning process as it occurs.