Both are valid points. And no, there's currently no programmatic access to machines - but that's high on the roadmap.

Regarding environments, it's funny, when I was starting out I would kill for a pre-configured instance because I wanted to focus on modeling and didn't care if package X was version x.x.y or x.x.z. But as you grow as an ML engineer and develop your own toolkit these things start to matter.

So when creating a machine on gpu.land you have the choice of going pre-configured or just having a clean Ubuntu image. The former is meant for newcommers while the latter for pros. That was my thingking!