Ha, it reminds me of what Andrej Karpathy said "Kaggle competitions need some kind of complexity/compute penalty. I imagine I must be at least the millionth person who has said this." It would be interesting to collaborate/compete on more creative tasks and have different metrics for success.
So true. Another reason to put constraints in Kaggle competition is due to production environment. How many winner models have been used in production? I suspect this number is near zero. High accuracy with a delayed time makes a ML/DL artefact not usable in production, because from users point of view speed is much more valuable than the difference between 97% and 98% in accuracy.
[1] https://twitter.com/karpathy/status/913619934575390720