Goal
OpenAI researchers conducted this study to compare the effectiveness of outcome supervision and process supervision in training AI models to solve complex math problems. The research was motivated by the need to improve the reliability of large language models in multi-step reasoning tasks, as even state-of-the-art models still regularly produce logical mistakes.
![Minerva: Solving Quantitative Reasoning Problems with Language Models](https://storage.googleapis.com/gweb-research2023-media/original_images/9028529d0c2385dae8ae28c6af30335a-image5.png)
Methodology
![Supervised and Unsupervised learning - GeeksforGeeks](https://media.geeksforgeeks.org/wp-content/uploads/20231121154747/Supervised-learning.png)
Key findings
Recommendations
![Supervised learning - Wikipedia](https://upload.wikimedia.org/wikipedia/commons/9/90/Task-guidance.png)
Implications
Alternative perspectives
AI predictions
![Google's Minerva, Solving Math Problems with AI | by Salvatore ...](https://miro.medium.com/v2/resize:fit:1400/1*rMKWYS2DzJbZkaPm_DZJsA.png)
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