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.

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    6 天前

    Ollama for text and multimodal (image to text). It supports structured JSON responses you can tie un to cool flows.

    ComfyUI for image/audio/video/3d model generation. Use a docker image because installing and configuring it raw is a nightmare.

    Huggingface is a good spot for the models. Ollama has its own library. There are several others.

    You can get basic text interactions and small images on a typical office PC. You can make nice enough stuff with a typical gaming PC. More power definitely means better results though

    *CivitAI also great for models, and they have a .ted domain too