What is Natural Language Processing?

It's easy to understand the importance of NLP given the number of applications for it--question-and-answer (Q&A) systems, translation of text from one language to another, automatic summarization (of long texts into short summaries), grammar analysis and recommendation, sentiment analysis, and much more. This technology is even more important today given the massive amount of unstructured data generated daily in the context of news, social media, scientific and technical papers, and the variety of other sources in our connected world. Today, when we ask Alexa or Siri a question, we don't think about the complexity involved in recognizing speech, understanding the meaning of the question, and ultimately providing a response. Recent advances in state-of-the-art NLP models, BERT, and BERT's lighter successor ALBERT from Google is setting new benchmarks in the industry and allowing researchers to increase training speed of the models. In the mid-1950s, IBM sparked tremendous excitement for language understanding through what was called the Georgetown experiment, a joint development project between IBM and Georgetown University.