This paper is proposing alternative to common practices in machine learning: Softmax Policy Gradient for RL and softmax parameterization in classification when minimizing cross-entropy loss. The limitation of softmax in these two cases are well explained, and the paper will be interesting for a wide range of the NeurIPS community.