Have you ever wondered why all the flyers you see on Facebook look exactly the same these days? It's because they're generated by large language models.
That's an important part of this point: they're not called "large design models," or "large art models" — they're called "large language models" — or, more succinctly, "LLMs," or for the purposes of our discussion, simply "AI."
You see, what AI excels at is finding the average. When you ask it "what color is the sky?" it can't see the sky to answer you. Instead, it will find all the ways that question has been answered by humans in its vast set of training data and see that the phrase "the sky is" most often ends with the word "blue," and therefore conclude that's the answer you want. It's an oversimplification, to be sure, but it's the truth.
What AI can't do — and what I excel at — is find a photograph of a tree stump covered in snow while out walking its dog in 2019, and then wait six years to put it through a series of layered filters, coming up with something novel while trying to incite a new version of digital impressionism.
That's what this is ... and I don't think it's particularly aggressive to say that it's never been done before. But that's exactly why AI can't do it. Sure, you could spend your human energy directing it to do exactly this. But why would you? I'm certainly not going to.
I may not be putting charcoal hand prints on cave walls, or even painting, but I don't think it's wrong to say that I prefer to make my art the old-fashioned way: by doing it myself. Like all the other artists that came before me, I enjoy wrestling with difficult ideas and complicated processes, seeing the novel results that come out of them, and sharing them with you.
If you want to read more about this, read my statement on AI and art.
If you want to support me, you can send me an encouraging message or check out my store and buy a print or two:
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But more than anything: thanks for being here, fellow human.