You are downvoted by fanboys but you are exactly right. I am surrounded by researchers working in DL and I have say at least 40% of them have never heard of FastAI or Jeremy Howard. However folks who are active on Twitter, listening to popular podcasts, popular media, HN etc would be very familiar with name Jeremy Howard and what FastAI is and need no introduction. In research world, an astonishing number of good researchers have little to none online presence. They have little to no time other than keeping track of research papers in their sub-field. It also surprises me when authors sweat for months to churn out 100s of polished pages but couldn’t spend 15 minutes to write a paragraph of introduction in readme.MD.
I guess it depends a bit which field they work in exactly. I'd be rather surprised if rigorous DL researchers in NLP haven't heard of him because I expect "Universal language model fine-tuning for text classification" (and tbh. also "Fine-tuned language models for text classification" due to the universality of the idea) to show up in any half-decent literature review of the field.
Most DL researchers I know also have a pretty good knowledge of available libraries and make it a habit to check them pretty often.
Fast.ai really democratizes the bleeding edge research for the masses, though, that’s why it’s popular among outcasts and outsiders. In general, I would be more wary of people working within closed environments and organizations than people making all they do public and open to review.
fastai is popular among practitioners as well as many researchers rather than just outsiders or outcasts. I've personally learned from it a lot and is amazing contribution. However, there is still a large population that is still unaware and it would be great to have a quick intro paragraph in readme so they know what all the fuzz is about.
