Generating some non-throwaway images seems better when I’m making a bunch of model API cost classification calls about this undocumented indeterminate black box.
For you seven-petal lovers.
Wow, not gonna even try to remake it!
Thanks! (Not to that you not trying to remake it, you absolutely can) I got that result on the first go and so beautiful, I love mermaids! This is same prompt, but quality: medium and quality: high (which took forever to generate, almost thought the generator went to fetch a real mermaid). I actually think quality: low gave the best output.
(medium)
(high)
Here’s the quote of the day, my own words:
The prompt itself doesn’t matter; what matters is arriving at the ideas and realizing them. Without an idea, all you do is simplify what you don’t understand. Try to understand it, maybe even emulate it—but never expect to equal it
This applies here! 
And that is why AI is so empowering.
Observatory, Floating Market…
These are recursive nonsense/filler subjects of some high value within the system
I’ve got some filler subjects, quite an extensive list actually
And this one was the first i got from my ‘randomize’
It’s usually within the first 5 clicks.
I think if we want to begin to understand nonsense within the system, in order to harness it for any purpose…
We have to understand where it comes from…
And I don’t know that.
completely unexpected behavior from ‘floating market’ as a prompt
no image request, but it’s automated directly to one
didn’t ask for an image but it associates it with one.
i wager that’s they’re wearing actual lamp shades with the metal bracket still on the inside - holding all the hats so high.
It’s wormhole right back to … the system’s trolling
BUT IT IS, PRODUCING NONSENSE…
@_j
oh that might be a clue to understanding?
Extremely Brief Semantic mapping of “Nonsense“ to “Floating Market“.
The overlap is weak directly, but not zero.
“Floating market” primarily belongs to clusters around:
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commerce
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boats and waterways
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Southeast Asia
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tourism
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produce and street food
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crowded canal scenes
“Nonsense” primarily belongs to clusters around:
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absurdity
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incoherence
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illogic
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randomness
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gibberish
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surreal or impossible combinations
They touch through a few semantic bridges:
1. “Floating” can become physically absurd
A model may interpret “floating market” literally rather than idiomatically:
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stalls floating in the sky
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merchandise levitating
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a marketplace on clouds
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boats suspended without water
That creates contact with nonsense through impossible spatial logic.
2. Dense markets resemble controlled visual chaos
Floating markets contain many boats, people, signs, foods, colors, and overlapping activities. That density can drift toward:
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clutter
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randomness
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incoherent object placement
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unreadable signage
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malformed interactions
This is not semantic nonsense in the strict sense, but image models often produce visual nonsense when resolving highly crowded scenes.
3. “Nonsense market” is a plausible surreal compound
Both words can meet inside broader clusters such as:
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surrealism
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whimsical fantasy
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dream logic
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absurdist illustration
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impossible commerce
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marketplaces selling concepts, memories, words, or emotions
For example, “a floating market selling forgotten thoughts” strongly activates both clusters.
4. Generated text creates an accidental bridge
Market scenes invite signs, labels, prices, and advertisements. Image generators frequently produce:
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pseudo-language
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malformed lettering
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invented alphabets
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semantically meaningless signage
So the “market” cluster often creates literal textual nonsense, even when the requested scene is realistic.
Practical estimate
In a generic semantic embedding space:
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Direct conceptual overlap: very low
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Shared visual-chaos overlap: moderate
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Surreal-prompt overlap: potentially high
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Accidental image-generation overlap: moderate to high
The image you received shows that last category. It contains a coherent floating-market scene, but the signage and some micro-details drift into generated nonsense because the prompt activated a dense commercial environment where text and many small object relationships had to be synthesized simultaneously.
and 5.3 (unless group model access had been updated)
treats the floating market prompt quite a bit differently:
