[barking_biscuit]

It has been amazing to watch the feedback loop with tools like Stable Diffusion where you see two types of strategy for solving problems of missing functionality. The first strategy is coming up with some long winded manual process involving disparate tools and several steps. The other is simply train a model to do what it is you want automatically. It has fast taught me that there is no competing with this new paradigm, and those capable of being able to solve their problems by building models will totally leapfrog those that have to do things the old way.

[Syntonicles]

Could you give me some concrete examples that come to mind? I'm new to Stable Diffusion but have been using it a lot lately.

[barking_biscuit]

ControlNet was a stepwise improvment when in being able to generate a character in a specific pose as compared to trying to coax SD into giving you an approximation of what you wanted through Prompt Engineering.

People training and releasing custom models that can replace entire workflows of disparate steps needed to produce an image that would normally result from that workflow.

There was that video or maybe it was an article where the guy made it so he could just use natural language to describe the edits he wanted made and it would make them etc.