There are researchers who have discovered ways to leverage machine learning to optimize hyperparameter selection, as well as neural network design, such as mentioned here: Using Machine Learning to Optimize Machine Learning - AutoML.
Additional detail is provided in the links:
Large-Scale Evolution of Image Classifiers (2017)
and
Neural Architecture Search With Reinforcement Learning (2017)
Is there any interest in adopting these methods?