Of course, I’m not in favor of this “AI slop” that we’re having in this century (although I admit that it has some good legitimate uses but greed always speaks louder) but I wonder if it will suffer some kind of piracy, if it is already suffering or people simple are not interested in “pirated AI”
I’m pretty sure those things are trained on content which was obtained without paying royalties to the creators, hence by definition pirated content - so that would count as “piracy around them”.
On the opposite side, as far as I know the things created with Generative AI so far can’t be copyrighted, hence by definition can’t be pirated as they’ve always belonged to the Public Domain.
As for the engines themselves, there are good fully open source options out there which can be locally installed (if you have enough memory in your graphics card) and there seem to be thriving communities around it (at least it looks like it from what bit I dipped into that stuff so far). I’m not sure if it’s at all possible to pirate the closed source engines since I expect those things are designed to be deployed to very specific server farm architectures.
There are quite a few options for running your own LLM. Ollama makes it fairly easy to run (with a big selection of models - there’s also Hugging Face with even more models to suit various use cases) and OpenWebUI makes it easy to operate.
Some self-hosting experience doesn’t hurt, but it’s pretty straightforward to configure if you follow along with Networkchuck in this video.
Training is transformative use. Sluicing data through a pile of linear algebra, to mechanically distill the essence of words like “fantasy,” is not what copyright protects against.
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I’m pretty sure those things are trained on content which was obtained without paying royalties to the creators, hence by definition pirated content - so that would count as “piracy around them”.
On the opposite side, as far as I know the things created with Generative AI so far can’t be copyrighted, hence by definition can’t be pirated as they’ve always belonged to the Public Domain.
As for the engines themselves, there are good fully open source options out there which can be locally installed (if you have enough memory in your graphics card) and there seem to be thriving communities around it (at least it looks like it from what bit I dipped into that stuff so far). I’m not sure if it’s at all possible to pirate the closed source engines since I expect those things are designed to be deployed to very specific server farm architectures.
There are quite a few options for running your own LLM. Ollama makes it fairly easy to run (with a big selection of models - there’s also Hugging Face with even more models to suit various use cases) and OpenWebUI makes it easy to operate.
Some self-hosting experience doesn’t hurt, but it’s pretty straightforward to configure if you follow along with Networkchuck in this video.
Any that are easier to set up on a phone? I tried something before but had trouble despite having enough RAM.
Not that I’m familiar with. I would guess that the limited processing power of a phone would bring a pretty poor experience though.
Training is transformative use. Sluicing data through a pile of linear algebra, to mechanically distill the essence of words like “fantasy,” is not what copyright protects against.