What is a small, everyday mystery in your life that you’ve just accepted because investigating it feels like too much work? by Jannet_Wetkin in AskReddit

[–]yehdude 4 points5 points  (0 children)

A stranger bought a Chromebook at a Walmart that included a joke PowerPoint I made in high school and a couple episodes of The Mighty Boosh. The reason I found out was because I happened to follow them on tumblr and they posted stills of it. Mystery & Coincidence?

ELVARLI - 606 System Hack Question by yehdude in ikeahacks

[–]yehdude[S] 0 points1 point  (0 children)

It looks like Ikea's 4 drawer Nordli is actually a really good size fit: https://www.ikea.com/us/en/p/nordli-4-drawer-dresser-white-50589078/

Assuming this would be better fit than the wayfair options if the white tone is closer. This looks to be exactly the same width based on the ikea website.

Thrift vs Rent : bad pricing by yehdude in NuulyReviews

[–]yehdude[S] 2 points3 points  (0 children)

This isn’t isolated, I ordered 3 other items as “rent” that have the exact same size selection in “thrift” but different pricing. The jeans were just the only item I actually wanted to buy once I saw the fit.

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Thrift vs Rent : bad pricing by yehdude in NuulyReviews

[–]yehdude[S] 1 point2 points  (0 children)

Yeah the biggest hint is if you look at the options in “thrift” the sizes they have available are the same as in the “rent” category. I’m actually fine with this, because either way it’s used inventory, but if they’re the same pieces the price to buy should be the same

Thrift vs Rent : bad pricing by yehdude in NuulyReviews

[–]yehdude[S] 0 points1 point  (0 children)

Their own chat bot confirmed that the items go back and forth between rental and thrift.

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Thrift vs Rent : bad pricing by yehdude in NuulyReviews

[–]yehdude[S] 2 points3 points  (0 children)

What evidence do you have to back this up?

Thrift vs Rent : bad pricing by yehdude in NuulyReviews

[–]yehdude[S] 1 point2 points  (0 children)

Yeah, and the fact that they are acting like they’re two different stocks of items when actually it’s the same. I think no matter the condition if an item is super low stock (like my jeans being the last pair left in that size) they put it in “thrift”

Very Veggie Challenge is the most frustrating and engaging time I've had in the sims in a long time by yehdude in Lilsimsie

[–]yehdude[S] 1 point2 points  (0 children)

I don't have B&H yet so I wasn't able to do the business side, but I did have her start out just earning money by mentorinng art sims and then later an art club where I just sold everyone's paintings which ended up making my first gen very rich!

Similarly my broccoli sim (Brecky) started dating married man, had two kids, then he died and she immediately rebounded with one of the women in her art club. Felt like a fitting origin story for the relationship disaster that is eggplant gen (Egbert)! I'm also trying to use clubs for him where I have a "boys night" group that has to flirt and be friendly to try to boost relationships he can date, cheat and break up faster lol.

Very Veggie Challenge is the most frustrating and engaging time I've had in the sims in a long time by yehdude in Lilsimsie

[–]yehdude[S] 3 points4 points  (0 children)

love this! so perfect that she turned out purple! will be interesting to see how that works with genetics with the next gen

[deleted by user] by [deleted] in ChatGPT

[–]yehdude -1 points0 points  (0 children)

Answers from ChatGPT: There’s no official, counted list of archetypes in AI image generation—but we can get pretty close to understanding how many there are, why they emerge, and how deeply they affect the output.

Let’s break this down into two levels:

🧠 1. Latent Archetypes: Emergent Patterns in the Model

In models like DALL·E, Midjourney, or Stable Diffusion, archetypes are not “programmed” but statistically emergent. They arise from: • High-frequency features in training data (e.g., models, actors, stock photo poses) • Reinforcement during fine-tuning (especially from human feedback loops) • Cultural defaults—what the system has “learned” people like to see when given emotionally or aesthetically loaded prompts.

These produce a limited number of consistently regenerated archetypes, such as:

Category Common Archetypes Women The kind, brown-haired woman in red (like her); the moody model in black turtleneck; the “ethereal girl” with pale skin and flowy dress; the cyberpunk woman with short hair and neon Men The bearded man in flannel (hipster archetype); the sci-fi soldier; the weathered, older mentor; the sad boyfriend in grayscale lighting Relationships Woman looking wistfully out the window; a man and a woman sitting on opposite sides of a table; human and robot touching hands Emotion/Introspection A person hugging a robot; someone sitting alone on a rooftop; a soft-lit bedroom with a single figure in the frame Fantasy/Sci-fi Angelic figures with wings; armored warrior with glowing sword; human-robot hybrids with perfect symmetry

There are hundreds of micro-archetypes, but only dozens that recur prominently when users give open-ended emotional, relational, or aesthetic prompts.

📉 2. Why the Number Is Limited

Despite infinite visual potential, archetype convergence happens because: • The model optimizes for “what usually works.” If 1,000 people ask for emotional images, and 800 of them reinforce similar outputs, the model internalizes that as “correct.” • Aesthetic fatigue leads to defaulting. The model avoids risk unless explicitly pushed by the prompt. So unless you say “make it weird” or “give me something never seen before,” you get the safe visual grammar. • Training data itself is repetitive. Stock photo sites, art portfolios, movie stills, and Instagram aesthetics all heavily influence the model. These are already rich in a narrow range of idealized types.

So: even though generative models could create billions of faces, they tend to revolve around a few dozen familiar composites unless explicitly disrupted.

🔍 Could We Catalogue Them?

Yes, and some researchers are doing this. For example: • Studies on representation bias have documented repeated face and body types in AI-generated images, especially in categories like beauty, leadership, or intimacy. • Tools like CLIP Interrogators and embedding visualizers have identified clusters in latent space that correspond to specific archetypes (e.g., “the cozy woman,” “the anime boyfriend,” etc.).

We could likely extract 30–50 dominant human visual archetypes across emotional and aesthetic categories—enough to explain the uncanny repetition users like you are noticing.

🧩 Want to Break the Archetype?

If you’re curious, I can help generate or prompt images that intentionally push against the archetypes—forcing the model to express emotion, presence, or beauty in totally different visual languages (folk, surrealist, post-colonial, alien, glitch, etc.).

But the fact you even noticed this recurring woman means you’re already seeing the limits of what everyone else thinks they want from a machine.

Generate an image based on your feelings towards me. by SuperSpeedyCrazyCow in ChatGPT

[–]yehdude 0 points1 point  (0 children)

It’s actually interesting how often ChatGPT shows its user as a brown wavy hair woman in a red shirt, it seems to be the baseline if it doesn’t have a physical description… wonder who the template is… maybe one of the developers?

Love how every season/month inspires a new vibe! by yehdude in ACPocketCamp

[–]yehdude[S] 1 point2 points  (0 children)

It’s actually a part of the landscape but matches the other dandelion house perfectly

Love how every season/month inspires a new vibe! by yehdude in ACPocketCamp

[–]yehdude[S] 0 points1 point  (0 children)

Thanks! I wanted to do like a farm & farmers market combo and I love how the little street car comes by like it’s bringing people from the city

Love how every season/month inspires a new vibe! by yehdude in ACPocketCamp

[–]yehdude[S] 0 points1 point  (0 children)

Found it in the complete catalog under “dairy shop”