Compiling/creating the Linux kernel or Chromium is no child's dance either, doesn't make them more/less FOSS than other things. Open Source AI gets its name from the license, not how easy/difficult it is to run/produce yourself.
I can compile the Linux kernel on a modest 15 year old laptop. Sure, it took 35 years and thousands of people to build it into what it is today, but anyone with pretty much any computer can meaningfully participate in Linux kernel development, and many Linux contributors have done so using modest hardware. The same is not true of AI. And, the Linux kernel is the biggest open source project, but plenty of small ones with one or two developers are in use on millions of systems.
I have pretty big hardware for local AI, more than most people have (a Strix Halo and a couple of 32GB GPUs in my desktop), but I can barely train anything useful locally; I can do QLoRAs for small models, or LoRAs for very small models, that's about the extent of it. I would need to rent big GPUs to do anything more than an experiment.
That's not comparable.
No, but a small university team with dark time on the state school system's cluster can build a basic, functional LLM.
It will be a few years (or more) until true "open source" LLMs are available and high quality, for sure. But it's not as impenetrable as it seems, IMO.
The free software community complains all the time about binary blobs that are otherwise legal to freely distribute. Like firmwares. But somehow this is all overlooked with these "open weight" models.
And working with the binary weights of a huge pretained model is much easier and cheaper than doing it based on the entirety of its humongous source datasets.
Please tell me this level of obtuseness is deliberate.