Exactly. The distinction between the various layers in "AI" systems is pretty vague to the newcomer. What is the "model" vs. the engine "running" it vs. weights?
I don't recall any previous tech stack that was barfed onto the scene with so little background or reference material, going from zero to endless undefined jargon... and no primer in sight.
For people who demand an understanding of their tools, it's a lot of work. I recognize the value of "AI" in performing the tasks I'd have to do manually; for example, keeping the data structures of my front- and back-ends in sync in a project. But do I want to interrupt my development and take weeks off to digest all of these tools?
And if I do, I want to run the show and fully understand it. And like you, I think that's best done locally.
The disturbing thing is that anyone was surprised by this. GPS is very fragile.
This made news in the U.S. a few years ago because Ajit Pai had the brilliant idea to allow so-called "5G" telecom service on frequencies too close to those of GPS. I don't think this case is resolved yet: https://physicstoday.aip.org/news/new-5g-exemption-may-jam-g...