  It is beneficial to develop an efficient machine-learning based method for
addition using embedded hexadecimal digits. Through a comparison between
human-developed machine learning model and models sampled through Neural
Architecture Search (NAS) we determine an efficient approach to solve this
problem with a final testing loss of 0.2937 for a human-developed model.
