1) the lower rate per piece enabled by higher productivity unlocks a much larger market for commissioned work. No one has to lose their job, people make up the price difference in volume.
2) there is not a much larger market waiting for cheaper art. The existing pool of artists is too big, and some of them need to find new work.
My guess is lowering the price does grow the market some, but not enough to avoid displacing at least some of the artists. Whether that’s 10% or 99% depends on how good these tools ultimately end up being.
If you want something a diffusion model can produce, you can get it for nearly free. If you want something significantly better, you have to pay an artist significant money for it.
1) Quick, low quality sketch
2) Generate detailed scene based on that sketch
3) Fix obvious errors by re-generating specific parts of the image
I also have questions, what is the "Generate detailed scene based on that sketch" process? Can an algorithm do this? Can a person easily do this? I'd be more impressed than with the raw pictures. Similarly with your #3.
[1]: https://www.reddit.com/r/ProgrammerHumor/comments/u8j3lf/i_n...
I can immediately recognize (as I did for this post) when art is AI generated right now. I've spent a lot of time playing with SD and while it's been a blast as a toy, the vast majority of the outputs are 'meh' and even the best still have those weird artifacts that stick out like a sore thumb.
Just like the clip art ascetic quickly becomes recognizable and somewhat nauseating, so too is AI generated art already starting to feel that way.
As far as aiding experts I don't imagine synthetic art will be nearly as game changing as the Adobe suite. I do a fair bit of writing and find GPT-3 to be completely unnecessary for "quickly generating a bunch of concepts". I assume that visual arts, like writers, already have a bunch of ideas in their head for what to do. That's never the bottle neck. Writers block happens but it's not because you can't think of a general concept, it's because implementing that specific concept into text is what's hard.
The output between all the major AI image synthesis tools, while impressive, is quite clearly very high dimensional interpolation, and it shares the same limitations in that space as it does the 2d space. We've already thrown insane amounts of data and compute resources at the problem and it's made the things that were done well in the past even better but doesn't move us towards solving the hard parts.
Particularly as one deals with the world of atoms, where the cost of a mistake is much higher.
There are already models that work to “aesthetically” rate images, and the results are quite promising.
To think we won’t see leaps in quality over the coming months/years is narrow sighted.
Though it's more likely in a the coming months/years people's ability ignore reality will just become stronger and we'll all believe that a person waving their 4 wiggly fingers and staring at you with strange fish eyes is hyper realism at it's finest.
We've entered the "emperor's new clothes" reality at this point, so nothing would surprise me.
But they haven't plateaued. I can go take a trip in a self-driving Cruise in San Francisco right now. I couldn't do that last year.
There's certainly a lot of room for them to improve, but the self-driving car industry is making progress.
Not happening.
A force multiplier, allowing existing professionals to generate more art.
The creation of a new profession. Digital artists are already doing a very different job with very different tools. These tools will be another step and there will be demand for human and generated art in different applications.
The empowerment of non artists. Same as how digital art democratized art. This will let people without hours of skill generate images of their liking with relatively minimal effort. Anyone can generate scenarios or images, even if they aren't perfect.
These aren't exclusive and will probably all happen at the same time. It will also 100 percent devalue artists work since it's now easier to meet people's needs. This won't make them obsolete, but it'll reduce demand and put people out of business.
- Instead of video advertising with a handful of regional variations, hundreds or thousands of variants tweaked for specific preferences, target profiles, as part of A/B testing, etc. Changes to accent, emphasis, copy, maybe even which parts of the product being advertised are focused on.
- Increasing variation in open world game locations and interactions, with AI able to insert much more meaningful distinction between instances of a template (as compared with recent Assassins Creed games, where identical towns and forts are copy-pasted dozens of times all over the map).
- Much greater accessibility of visual art as an accent for other kinds of creators— illustrations to accompany poetry, blog posts, fanfic, etc.
- Increasing ability for AI to do first-cut assembly of video content, particularly review-type YouTubers (think: SkillUp, Critical Drinker) where the video is kind of secondary and the majority of the audience may even be listening to it as a podcast anyway. The AI being able to understand from the script what is under discussion and select matching clips would likely match or approach what
This is far from a sure thing— sometimes people really are the buggy-whip manufacturers in a situation and technology completely displaces them. But other times (as with software development), the market and use-cases have expanded considerably faster than the efficiency gains made by better tooling.
Not saying this is bad, or that typesetters or illustrators deserve a living. I am saying that being able to draw used to require being able to draw, and that instead being a fan of drawings, being good at describing imaginary ones to a computer and iterating them into a finished product is a mostly, if not entirely, different skill.
Right now naively generated AI images are having their day, but I expect we'll soon get over that. I think the real future is in visual artists who closely collaborate with future generations of ML systems that are much more tractable and responsive. I expect a lot of that iteration will involve pretty traditional art skills, because those are time-tested ways to convey visual information.
So basically, you read over a book(with amazing art) over, know your terms(or maybe know how to use a neat visual dictionary), and now you can paint in many art styles.
Of course there will be some more learning while playing with stable diffusion and getting a feel how to talk to it.
But it's very far from the old skill of neing an artist, not much knowledge will transfer.
Inevitably they started on the lower rungs and worked their way up.
If these tools displace the need for lower level/apprenticeship like work, then it won’t be a surprise if later on we have less quality artists who weren’t able to get the necessary experience early on.
I think of it more like, If an artist can support themselves doing commissions of low quality art so they can support their high quality art, that’s better than if they had to drive Uber.
https://mobile.twitter.com/xsteenbrugge/status/1558508866463...