I wouldn't say that "the opportunity all seems to be on the front end". Specifically for stable diffusion, there are a lot of different ways to use the model. I think we're just starting to scratch the surface of what SD can do, so there is some value in tinkering with different ways to use and apply the model.
Example 2: you can merge different dreambooth models together to varying degrees of success (the idea being, you train model A on subject A, model B on subject B, and now you want to generate pictures of A and B together). My understanding is that this doesn't work too well at the moment, but it's possible that a different interpolation algorithm can yield better results.
I do agree with the general sentiment that you wouldn't necessarily be training your own models or creating your own architecture, just want to provide the perspective that understanding the AI side is valuable because it can lead to different capabilities and products.
I'd say the "opportunity" is primarily in creating business models with these new AIs. The AI field is going to be innovating on them regardless what any individual chooses to do. Discussions about viable applications of these new capabilities are scant, beyond reducing existing technical artist head counts I see little to no discussion about new capabilities and new applications not possible before. Sure, we're developers, but we're also supposed to be entrepreneurs and this lack of creative discussion about what can be done that was not possible before is curious in itself.
Guess based on historical anecdata: I think that is because it looks like the current gen AI:s will help automating lot of stuff, but wont enable anything new. I would say we are at the analogous point where ’computer’ no longer meant a chain of humans with calculators. First the automation needs to become entrenched, then new innovations can emerge.
Can I future quote your "current gen AI's will help automating lot of stuff, but won't enable anything new" when that "something new" tears a new economic hole in our global economy?
Personally, I see this tech capable of destroying and recreating the advertising industry completely via inserting everyday consumers into ad media, depicting them as happy consumers of a product they've not used yet - while celebrity spokespeople, appearing as their personal friend, inform them how much the celebrity idolizes them for using said product. This is an obvious non-subtle application. There will be many, many more.
Current gen is not ready for that. It's ready soon enough for sure. When I said "gen" I meant "not currently" but with this speed of development I'm not ready to bet if the scenario you described is 3 months of 5 years away.
I agree that the current produced images by say SD, are more of a curiosity than true art. Give it a year or so, I would say, and we will change our mind. Remember the early VR models? Not comparable with the quality you have now in real time. Only AI seems to increase in quality of output at a much faster pace.
Example 1: have a look through here: http://synapticpaint.com/dreambooth/browse/ for some examples of dreambooth models people have created
Example 2: you can merge different dreambooth models together to varying degrees of success (the idea being, you train model A on subject A, model B on subject B, and now you want to generate pictures of A and B together). My understanding is that this doesn't work too well at the moment, but it's possible that a different interpolation algorithm can yield better results.
I do agree with the general sentiment that you wouldn't necessarily be training your own models or creating your own architecture, just want to provide the perspective that understanding the AI side is valuable because it can lead to different capabilities and products.