What?
So far most generative QA models were not really useful in practice, because they could only answer very generic questions that were included in their "wiki + web" training corpora. For use cases in the industry we mostly want to:

• ask domain-specific questions
• get the answer from a specified, reliable corpus
• have a possibility to check the answer (e.g. by inspecting the document / context where it came from)

Pure generative models don't fulfill these requirements. However, recent retrieval-augmented approaches could be interesting to test.

How?

The latest transformers release comes with the RAG model from Facebook (https://ai.facebook.com/blog/retrieval-augmented-generation-streamlining-the-creation-of-intelligent-natural-language-processing-models). We could add a "TransformersGenerator" class in Haystack that gets documents from the retriever and generates the answer conditioned on those.