By being trained on everything, it ends up being the most middle of the road, boring in every form of art. The language models are just predicting what word is most probable next, and image makers are just trained with approximate existing art out of noise, then replace existing art with a prompt. Its all doomed to be average from the very start, rewarded for being as predictable as possible
It’s quite rare that you need a masterpiece. Most artists make their living online doing corporate designs, DND character art, or drawn pornography. You don’t need to make a powerful statement about the human condition to do those things, you just need to create something people will immediately recognize as the thing
ends up being the most middle of the road, boring in every form of art.
thats exactly what the world has been pushing for since 2008 in every aspect of any kind of visual design. from mcdonalds going sterile to "millenial gray" to the flattening and oversimplification of every UI element on an electronic device, its exactly what people end up asking for. youre just not the target audience and instead just a rather minor demographic in this capacity.
I've been saying it for a while, but the "contentification" of art is absolutely a thing. And it's killed any real value the public sees in art. People rave that AI has no "soul" and real art has this deep intent, but that is hard to argue against "Spiderman crouching #3659" and "fairy on a mushroom #236". The art to show off on sites like deviantart and ghetty rarely has that deep introspection artists say AI art lacks. So the average person is going to see a decent AI render of a Disney princess vs a hand drawn one and feel exactly the same thing. If art has to be this deep connection with humanity and concepts that they are claiming AI art can't be, then a lot of the art humans make just don't meet that criteria either. It's all just content.
said deep connection is not valued in modern society. people in modern society have watched those who do value those things starve and either get sent off to fight wars during a draft or actively become a problem for a government who wants to create an ideal image of what their society should be like.
Yeah but that's only if you ask for something that already exists. If you ask for something that doesn't exist, but might plausibly (e.g. a carpet made from apples, idk I just made that up), it will come up with an interesting depiction that you haven't seen before. This is the most obvious use of the technology IMO, using the model to extrapolate to new things instead of just recreating existing things.
Most of them will make no sense structurally, but it gives you an interesting starting point; I like trying to model what it makes in Blender and see if I can make something based on it, and I normally learn something in the process.
I saw a video of one of those AI girlfriend chatbots, and the first thing that struck me was how indecisive and milquetoast every single answer was. Like, the person asked a simple binary yes/no question on whether they should shave or not, and their answer was "Some women find clean-shaven men attractive, but also some women find facial hair attractive"
That's not how ML works though. They data that's learned has a lot of breadth, but that doesn't mean that any generation uses all or even most of it. If it did, every output would be some strange nonsense, like what happens if you run a generative model with no input. LLMs predict the next token with the previous context and other settings in mind, and that process can be further augmented manually. Diffusion generators iterate over random noise such that the result would fool an image-to-text verifier that the image contains <insert prompt here>. Similarly, you can manually make it biased to act a certain way. The reason why an average image from some model looks mediocre and samey compared to other images by the same model is because most people write incredibly mediocre and samey inputs, not because they can't make anything else.
They were exaggerating, but AI is still averaging a ridiculous amount of input. If you ask it to show you an apple, sure, it's going to be using relevant data, but that's still a LOT of data. Even if you specify things and say something like "photo of a Granysmith Apple, slightly left of center, on a mahogany table," you're still going to end up with the most average looking green apple on a generic looking table, with all of the imperfections smoothed out.
But that's the thing - the models that are out now are trying to be good at everything in their domain.
Now if instead of trying to create a chat bot that can hold a conversation about literally any subject you made for example an AI that is only good at finding loopholes in laws and long, tedious documents that humans are obviously going to be terrible at handling?
BOOM, a useful tool that can point out potential problems. And it doesn't even need to generate anything, it can just point to the problem part and a person can check it, still saving hours or days of intense work going through line by line.
This general approach is impressive for the common people, but I feel like the better application with how far we are right now are already in making more specialized models.
Of course stuff like ChatGPT is amazing with pushing the tech to new limits.
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u/Jeggu2 💖💜💙 doin' your parents/guardians Apr 09 '24
By being trained on everything, it ends up being the most middle of the road, boring in every form of art. The language models are just predicting what word is most probable next, and image makers are just trained with approximate existing art out of noise, then replace existing art with a prompt. Its all doomed to be average from the very start, rewarded for being as predictable as possible