Abstract Big Data, machine learning, and neural networks have taken NLP by storm. This talk evaluates these approaches from a critical perspective. I argue that in particular for customer-facing applications, these techniques do not perform as well as one would hope once one goes beyond purely quantitative evaluation metrics. Traditional approaches still offer significant advantages that have not been fully harnessed yet.