Data/ML guy here, also founder of frame.ai -- we're a NYC-based startup that helps customer-facing team categorize and analyze their conversations. There are a

Data/ML guy here, also founder of frame.ai -- we're a NYC-based startup that helps customer-facing team categorize and analyze their conversations. There are a lot of factors contributing to widespread adoption of NLP -- certainly the availability of great tools like PyTorch/Keras, SpaCy, and Gensim, and more broadly growing technical competence and awareness among teams that traditionally handle text. But the single biggest factor is that people are generating massively more purpose-driven text in interactive channels. A generation that grew up texting their friends is becoming core consumers and workers in every industry. People drop text in team chat, in project management tickets and pull requests, when contacting support, and more. Plus, we break our text into meaningful snippets and add our own metadata to make them more readable (and usable) for other people. Language and tools are co-evolving very rapidly in ways that make them more accessible. As a human-and-organization-augmentation nerd, I'm incredibly excited. We are seeing so much more about how groups of people self-organize than we ever used to, and at the same time that our tools are starting to become capable of understanding us in the ways that we communicate most conveniently.