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Weirdly, I think the biggest non-Google winner is OEMs that make widgets that need some UI. I'm thinking of the infotainment systems in cars, thermostats, all of the IoT randomness that's around. It's a lot easier to start with a base that at least has a head start on drawing to a screen and accepting inputs than from base Linux. Even if you start with a Raspberry Pi, you still have a bunch more work to do if you want to not only output bitmaps, but also accept user input.
I'm in basically the same boat as you are. But I'm mostly commenting on the "normal" people using Android.
My stance is that the base OS itself, Linux, is open. AOSP is a pretty thin veneer on top. It's helpful for some OEMs, phone and otherwise.
I totally agree on everything else. Having toyed with the idea of procuring chips, then looking at the lead times of some unique ones... I didn't really go too far on that side other than buying way too many USB jacks that I doubt I'll ever use.
But the last bit is kind of interesting. AI is going to be replacing things that, up until now, humans were uniquely suited for.
I'll use a present project as an example. I'm working on a side project that is heavily reliant on AI. Without getting too far into the weeds, it's a system to allow "smart" replaying of sets of related API calls to enable better testing. I could get 90% of the way to success pretty easily without any AI help. Sure, things like variables would get named "var1," "var2," etc., but it worked. Then there's weirder cases where you need to be able to take some context cues to figure out how to select the right value to use in a replay.
On a subsequent call, we need to find the ticket number, but it might not be in the same place every time. (The API I'm working with is... meh.) You may have multiple documents and they may not be in the same order (think JSONPath selectors to get the document's number where the type is "ticket").
Now, I can, in lieu of AI, present that to a human to make that decision. The end result is the same. I have the inputs that went to either the AI or the human, and I have the answer provided. In neither case do I have an audit trail of how the answer was arrived at. I would argue that you might be able to get more of an audit trail from the AI because there may be logged "reasoning" ideas used in the process. I know I can't audit what I did to come to the answer other than "it felt right."
My prediction: even in OSS, there will be an increasing reliance on AI -- both in the generation of the code itself, as well as the actual invocation of services from that code.
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