Artists have for the longest time used our brains ability to upscale. Many paintings, even ones that seem super detailed like those by James Gurney in his Dinotopia series, will have blobs in the background. Our brain will recognize based on silhouette and shape an extraordinary amount of detail that isn’t actually there. Detail such as the type of clothing and the action of a person. But if you look closer it’s a rectangular blob with a triangular blob within it to indicate clothes.
The difference between AI art and actual human art is the level of intention one can detect in it. When I look at human art I absolutely marvel at the cleverness of the artist to convey something that still looks like what I was imagining even when I look closer at it.
With AI art I look closer and realize that the blob presents more confusion the closer I look at it.
I’ve been telling anyone who will listen that AI art isn’t stealing much lunch when it comes to professional art. But it may very well be a powerful tool to artists to speed up their workflows and artists who refuse to use the tool stand a chance at being left behind the same way some artists got left behind in the illustration industry world once digital tools showed up.
I’ve been telling anyone who will listen that AI art isn’t stealing much lunch when it comes to professional art.
Yet. These models have been out for only a matter of months. Just last year the state of the art was DALL-e v1, which is a toy in comparison[0] to DALL-e 2/imagen/SD.
Making predictions is perilous but it would be surprising to me if computers did not have fully super-human artistic ability in the next 5 years.
I mean for sure. I’m not going to make any predictions about the future when the field is so young. It’s only related to the current generation. Honestly though, art isn’t the field to look at for seeing when the jump is coming. It’s in AI actually being able to recognize relationships between things. Basic stuff like looking at enough pictures of horses and recognizing what the leg is and how many legs a normal horse will have. Even stable diffusion which has some of the best generation will still give me 5 legs or two legs coming out of the same side. These kinds of images are a boon to artists who will need to do all the final corrections.
Relationships between things is complicated. Someone resting their face on a fence is going to have a huge number of effects on the deformations of the face, especially the eyes and hair depending on how they are resting. It’s not enough for AI to have seen enough pictures of faces on fences to be able to apply that in an image. It needs to understand what pressure and gravity is doing to the underlying structures. That’s how human artists study at least. It’s why they can take that lesson and apply it to learnings about how skin behaves depending on the age of a person. They aren’t copying. They are solving problems by thinking about muscles underneath and how they change depending on any number of factors.
None of this even touches on lighting and colours.
If there’s one prediction of the future I’m willing to make, it’s that until research progresses on teaching computers to apply actual knowledge, AI within the creative space will remain assistive instead of replacing.
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Artists have for the longest time used our brains ability to upscale. Many paintings, even ones that seem super detailed like those by James Gurney in his Dinotopia series, will have blobs in the background. Our brain will recognize based on silhouette and shape an extraordinary amount of detail that isn’t actually there. Detail such as the type of clothing and the action of a person. But if you look closer it’s a rectangular blob with a triangular blob within it to indicate clothes.
The difference between AI art and actual human art is the level of intention one can detect in it. When I look at human art I absolutely marvel at the cleverness of the artist to convey something that still looks like what I was imagining even when I look closer at it.
With AI art I look closer and realize that the blob presents more confusion the closer I look at it.
I’ve been telling anyone who will listen that AI art isn’t stealing much lunch when it comes to professional art. But it may very well be a powerful tool to artists to speed up their workflows and artists who refuse to use the tool stand a chance at being left behind the same way some artists got left behind in the illustration industry world once digital tools showed up.
Yet. These models have been out for only a matter of months. Just last year the state of the art was DALL-e v1, which is a toy in comparison[0] to DALL-e 2/imagen/SD.
Making predictions is perilous but it would be surprising to me if computers did not have fully super-human artistic ability in the next 5 years.
[0] https://openai.com/blog/dall-e/
I mean for sure. I’m not going to make any predictions about the future when the field is so young. It’s only related to the current generation. Honestly though, art isn’t the field to look at for seeing when the jump is coming. It’s in AI actually being able to recognize relationships between things. Basic stuff like looking at enough pictures of horses and recognizing what the leg is and how many legs a normal horse will have. Even stable diffusion which has some of the best generation will still give me 5 legs or two legs coming out of the same side. These kinds of images are a boon to artists who will need to do all the final corrections.
Relationships between things is complicated. Someone resting their face on a fence is going to have a huge number of effects on the deformations of the face, especially the eyes and hair depending on how they are resting. It’s not enough for AI to have seen enough pictures of faces on fences to be able to apply that in an image. It needs to understand what pressure and gravity is doing to the underlying structures. That’s how human artists study at least. It’s why they can take that lesson and apply it to learnings about how skin behaves depending on the age of a person. They aren’t copying. They are solving problems by thinking about muscles underneath and how they change depending on any number of factors.
None of this even touches on lighting and colours.
If there’s one prediction of the future I’m willing to make, it’s that until research progresses on teaching computers to apply actual knowledge, AI within the creative space will remain assistive instead of replacing.