I'm sorry but this is not a good enough argument for gutting science. You need to justify that capacity and coverage increase is required.
The companies trying to make these plans are just looking for money. It's not for some noble goal for progress. If you fail to see that, I'm sorry for you.
Yes, I can do most of the things now because enough is already up there. Can you elaborate why do you want more? Like a million more as these companies are planning?
That's an insane take. Do you actually understand what is being argued? It's an threat to ground based telescopes in the name of more slop-generating infrastructure.
The issue at hand is with the ground based telescopes. We need both ground-based and space-based telescopes because with ground based telescopes you can create arrays and interferometers enabling a much larger baseline (in layman terms this means much higher angular resolution)
It depends on the kind of people. Most normal people don't do that, it's not a reddit-like platform after all.
But most researchers and grad students (like me) often subscribe to daily mailing list of the papers dropping that day from their particular field. Having a cursory read at the paper titles and then opening the papers further relevant to you is a morning ritual for many.
For something more rigorous, I would like to take this opportunity to share rebound[1], something we use for n-body simulations in our field (planet formation). Perhaps few people here are already familiar with it. It has a Python interface but the C interface is very easy to use as well and has plethora of pre-set examples which can be visualized using GLFW. It's very very cool!
I have never understood this way of approaching programming. I feel the best way to learn a language is solving a problem you have in that language.
Figure out an actual real problem you have which you can solve with programming and just implement it in a language you're thinking about learning. This way there's nothing to invest in because you're solving a problem instead of approaching programming as if it was some coursework. It is not.