I share your excitement for this tool that assists artists. However, I don't share the same disdain for prompt generators.
I find it enlightening to view it in the context of coding.
GitHub Copilot assists programmers, while ChatGPT replaces the entire process. There are pros and cons though:
GitHub Copilot is hard to use for non-programmers, but can be used to assist in the creation of complex programs.
ChatGPT is easy to use for non-programmers, but is usually restricted to making simple scripts.
However, this doesn't mean that ChatGPT is useless for professional programmers either, if you just need to make something simple.
I think a similar dynamic happens in art. Both types of tools are awesome, they're just for different demographics and have different limitations.
For example, using the coding analogy: MidJourney is like ChatGPT. Easy to use, but hard to control. Good for random people. InvokeAI, Generative Fill and this new tool is like Copilot. Hard to use for non-artists, but easier to control and customise. Good for artists.
However, I do find it frustrating how most of the funding in AI art tools goes towards the easy-to-use side, instead of the easy-to-control side (this doesn't seem to be shared by coding, where Copilot is more well-developed than ChatGPT coding). More funding and development to the easy-to-control type would be very welcome indeed!
(Note, ControlNet is probably a good example as easy-to-control. There's a very high skill ceiling in using Stable Diffusion right now.)
Good analogy. Yes, controllability is severely lacking, which is what makes diffusion models a very bad tool for artists. The current tools, even Photoshop's best attempt to implement them as a tool (smart infill), are situational at best. Artists need controllable specialized tools that simplify annoying operations, not prompt generators.
As a programmer, I find copilot a pretty decent tool, thanks to its good controllability. ChatGPT is less so, but it is decent for finding the right keywords or libraries i can look up later.
I find it enlightening to view it in the context of coding.
GitHub Copilot assists programmers, while ChatGPT replaces the entire process. There are pros and cons though:
GitHub Copilot is hard to use for non-programmers, but can be used to assist in the creation of complex programs.
ChatGPT is easy to use for non-programmers, but is usually restricted to making simple scripts.
However, this doesn't mean that ChatGPT is useless for professional programmers either, if you just need to make something simple.
I think a similar dynamic happens in art. Both types of tools are awesome, they're just for different demographics and have different limitations.
For example, using the coding analogy: MidJourney is like ChatGPT. Easy to use, but hard to control. Good for random people. InvokeAI, Generative Fill and this new tool is like Copilot. Hard to use for non-artists, but easier to control and customise. Good for artists.
However, I do find it frustrating how most of the funding in AI art tools goes towards the easy-to-use side, instead of the easy-to-control side (this doesn't seem to be shared by coding, where Copilot is more well-developed than ChatGPT coding). More funding and development to the easy-to-control type would be very welcome indeed!
(Note, ControlNet is probably a good example as easy-to-control. There's a very high skill ceiling in using Stable Diffusion right now.)