Have you noticed? Now when you generate ten AI images, eight of them look like they were carved out of the same mold.

This isn’t a hallucination—it’s a visual KPI forced out by training data and recommendation algorithms working together.
Tools like GPT and Gemini really have smashed the barriers to the floor, so anyone can generate images.
The result is:
Everyone chases trending prompts, stacks LoRA adapters, and copies the masters’ parameters.
The platforms are happy too, because these highly saturated, cinematic, cyber-neon images are the easiest to retain.
You think you’re creating, but in reality you’re just invoking a set of visual conventions that have been validated by the market.
Stuff like this is like instant noodles—tasty on the first bite, but after you eat too much, you feel like throwing up.
It’s basically the same as before with NFTs: tools lowered the barrier, but what came out was tens of thousands of meaningless visual noise.
Now AI is pushing this whole logic to the extreme again.
It swallows existing styles, then batch-produces the “correct” answer.
The most dangerous thing isn’t that AI draws badly—it’s that it draws so much like the standard answer.
In the future, the contest of aesthetics won’t be about who learns to use AI first, but who can keep their own deviation within the average of AI.
Those clumsy hand-made traces, personal fixations, and regional experiences that can’t be tuned precisely through prompts are the truly valuable things ahead.
In this era of visual oversaturation, making a memorable oddball is far harder—and far more important—than making a perfect standardized part.