I usually don’t even understand the lingo they use. “Open-weighted” is the most recent one, then it usually goes down to specific “models” that everybody is supposed to know about.

These are my thoughts (I will stick to the vague “it” for now, but of course therein lies another question: “and how does all this apply to various specialised AIs”):

  • Is it really feasible to run it 100% locally? I know there’s plenty of people with very powerful rigs indeed, but still. Or are 99% of these people really saying “it would, in theory, be possible to run that locally, therefore your concerns are invalid”?
  • If yes to the previous: the software doesn’t come from nowhere and ultimately still relies on gas-turbine-powered datacenters and stolen IP and stolen personal data, no?

If what I wrote above is true, what exactly are people arguing when they say it’s still possible to use LLMs ethically or true to FOSS philosophy, because … ???


edit

Thanks to all who answered.

I guess it’s my fault for asking several questions in one, but this thread has attracted exactly the type of people I’m writing about; several even used the term “open-weighted models” without explaining it.

Asking to get arguments explained, I got more arguments instead.

  • Wildmimic@anarchist.nexus
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    4 hours ago

    You can also train your own local models with license free material if you wish! I think one of the easiest ways to get into that is by using software like unsloth (that’s the one i am using), an open source no-code tool which can be both used to train models on whatever data you wish and to run models either locally or using an inference provider.

    Quick example for something like that which is also not dependent on copyrighted material is RAG, where you can provide the 400-page manual for something and then can chat with “the document” to get explanations, ask quick questions without searching for possibly multiple occurrences of a specific term and similar stuff. I love this for technical documents like mainboard manuals!