There is a massive shift coming to market of asset creation that I'd like to address or at least start outlining here. This is not a blog post, nor an advertisement of the methods described below. The purpose of this thread is to gage the position on the subject as it relates to Unv and strategize about our approach(if any) to the whole thing.
Some applications recent GAI advancements made feasible come to mind:
Texture work
upscaling (img2img) legacy textures
text2img for generating textures from prompts
inpainting customizations (cracks, rust, vines, smears etc.) on tile images
creating textures from images, including normal/relief/spect/pbr sets
making textures tileable with inpainting
3d model creation
text-to-3d and img-to-3d for low priority/background prop generation
3d model generation as a base for finished 3d assets
Concept art
concept iteration using img2img over 3d, photos, and drawings
concept initialization using text2img
Definitely not an exhaustive list and one that completely sidelines sound and text generation, but I wanted show how fundamental shift this is and just get some opinions. I'd like to also point out that above are some of the lowest hanging fruits available today. We could actually be using these today!
Here are some issues I foresee coming with using GAI technology:
Legality - works created even partially with GAI have unclear copyright status, it's not even clear to me if a CC license can be applied to derivative works. Some platforms like Steam require apps to disclose all GAI content used, a temporary solution in my opinion, giving them an out if copyright law cracks down on generated content.
I should note here that not all models are created equal and a lot of questions of legality/morality depend on contents of training set for given model.Ethics - other then law, some people, especially in art scene have very heavily condemn the practice
Quality and taste - cheap and easy solutions have their price.
Easy creation hides the artistic technical debt. Just because you can create something appealing doesn't mean you can make it fit with other things in some consistent way. You may not understand what makes it appealing in the first place. As an analogy, you can allow llm write you some code, but you would have no idea why it works, how you can change it and if perhaps it is broken in some way if you couldn't write it yourself in the first place.
AI generation is likely not create value on it's own, unassisted. It's likely to create contextless noise, with no profundity, no 'uh-huh' moment, just ceaseless steam of "Oh! This looks interesting... nope, it's nothing" experiences, which not only undermine the enjoyment of watching a piece of content, but teaches viewer to become disengaged. Which can be very bad for things with actual depth in it.