it sounds like people who don't work with machine learning asked that question. People who do work with machine learning should see the difference. Besides what is mentioned in the blog post, OpenAI is a research effort for moving start of the art, while fast.ai is for teaching students in a non math heavy way.
We also do research and try to move the state of the art. Although we share our results and methods largely through courses rather than academic papers.
Our plan is to teach more material each year, in less time, with less prerequisites, by both curating the best practice techniques and adding our own.
So far we've spent much more time on education than research since that's the highest leverage activity right now (helping create more world class practitioners helps move the field forward). And most of the research is more curation and meta-analysis to figure out what really works in practice.
Didn't realize you are doing research as well. I love what you have done with the courses and look forward to seeing how the linear algebra computational course does.
anyway I could contact you to ask you more questions? My email is in my profile
If you published your research in peer-reviewed venues, it would help your democratization ambitions. Few people can pay attention to original research that is buried into teaching material.
