Nope, not just fluff. New ML model architectures get too much hype, while it's relatively simple tools like this that actually make the difference in whether or not ML can applied to industry problems. The low hanging fruit in the ML industry are in workflow tools rather than novel model architectures. I have a huge amount of respect for the folks at explosion.ai, largely because their solutions are consistently good in practice rather than good in theory.
Exactly. I'm working on something related: building a UI on top of declarative ETL pipelines to drive ML models. I think a lot of time (and big data resources) can be saved.
No, I don't think so. People tend to over-emphasize the latest ML techniques when the greatest improvements right now come from better and cleaner data sets. I am interested in this sort of thing because we were just about to try and build something like it ourselves.
