As we know, there are a variety of Neural Network tools out there - and of course some are better than others. One issue with NNs is that by nature, they are a "black box" technology - its not an easy task to conjure causal factors out of a proprietary tool - whether the output be on target or way off the mark. By capturing how the training (and later, validation) goes in a localized and "query able" data model, the door opens to using this potentially valuable metadata in a variety of creative ways in a much broader data model if the results warrant, not to mention being able to benchmark your own implementation in comparison with other implementations you might try. Looking forward to your next post, Sylvia!