Question-Answering (QA) has exploded as a subdomain of Natural Language Processing (NLP) in the last few years. QA is a widely applicable use case in NLP yet was out of reach until the introduction of transformer models in 2017.
Without transformer models, the level of language comprehension required to make something as complex as QA work simply was not possible.
This is a companion discussion topic for the original entry at https://www.pinecone.io/learn/haystack-lfqa/