HN user
My university best friend's dad was a cop. They were a middle class family and it was a relatively good paying / benefits job. He was a really nice guy. I never had the impression he was passionate about law enforcement, nor on a power trip, just a normal guy who got a job after high school. He would have become a cop in the 70s - what you say may be more relevant now.
I definitely buy that there is a use case for this kernel. Whenever I see this kind of optimization, I feel like it's at least flirting with classical feature engineering. Not that there's necessarily anything wrong with that. You could probably say the same thing about Relu if you wanted. I just think the "it responds better to certain features" argument, which is how I'm understanding this, can quickly throw you back into some classical computer vision work where you're trying to hand optimize instead of relying on gradient descent to find your features
I think you mean the package management rather than the ecosystem. For all its failings, the python ecosystem (for machine learning / data science in particular) is unmatched, which is why python is so popular.
As a "professional" python user (who got there in a roundabout way), I'd say the biggest problem with package management is all the conflicting advice and different ways to accomplish the same thing (there are other problems, but they are surmountable). Once you get a workflow down, it ends up being pretty easy to set up and manage an environment for a given project. Not that it's perfect, but I think a lot of the stereotypes about how bad it is come from how bad it appears as you try to converge on a setup that works for you.