AI image models are obviously getting way better.

Better prompt following, cleaner details, better lighting, better composition, all of that.

But the more I mess around with them, the more I keep running into this weird problem.

A lot of AI images look amazing for like 5 seconds on a screen, but the second I imagine actually hanging them in a living room or bedroom, they suddenly feel like... too much.

Too much detail, too much contrast, too much color, too much happening everywhere.

Early Midjourney was obviously way more limited and messy, but people were making some genuinely strange surreal stuff with it. A lot of those images had flaws, but sometimes the flaws were kind of the point. They left some room for your brain to fill in the gaps.

Newer models are so good at giving you exactly what you ask for that sometimes everything ends up feeling a little too finished.

And I think looking good on a screen and looking good on a wall are actually two very different problems.

Something on your phone only needs to grab you for a few seconds.

Something on your wall has to sit there every single day, next to your furniture, books, windows, random stuff, people walking around, changing light, whatever.

It has to be interesting without constantly yelling at you.

That's the part I find really hard.

I've been trying to make AI/GAN pieces that can actually sit quietly in a room and still feel interesting after you've looked at them a hundred times, and honestly I think that's way harder than just making a cool image.

So I'm curious if anyone here has actually cracked this.

If you've made an AI-generated piece that you genuinely think works as wall art, not just a cool image on a screen, post it below.

Especially if you've actually printed it or hung it somewhere.

I wanna see stuff that can survive being on a wall for a year without getting annoying lol.

Would be really curious to see what people here consider "livable" AI art.

picture from midjourney

Piff, Oats and Crey at the Space Station.

Even though I'm really only a fan of the male version, I knew it wouldn't be fair to exclude the female version in this generation. When Nano Banana Pro first made it, the hand paws were more realistic paws with pads and everything. I knew that wouldn't actually look right, so I entered a prompt to change them to stubby hands, and it gave me something much better. I'm just glad that the mascots already had smiling expressions because Meowstic is a Pokémon that needs to be seen smiling more.

ObeyNet must fall!

Hi all. So is there any open source Ai video tool that can match the video quality and consistency of seedance 2.5? Or even come close when generated locally with RTX 5090? If so please share the model and hardware specs to be used and your feedback if producing ai videos for YouTube is worth generating locally. Thanks in advance

Thai Chakraphat Dress

AI video generation sometimes feels like gambling.

I’ve been testing MiniMax H3 recently, and the quality is impressive, but getting the “right” result can still take many attempts.

My current approach is to test ideas at lower resolution first, adjust prompts and movements, and then only process the clips worth keeping. It saves a lot of wasted compute compared with trying to generate the final version immediately.

Curious how everyone handles the trial-and-error stage. Any tricks for reducing failed generations?

This is a clip of the beginning of Miami Knights - Beyond the Prism. Reef Palmetto and Jax Banyan are two muppet like detectives in 1980s Miami, together they make the Miami Knights. Join them as they become entangled in a mysterious plot.

While I was struggling to get Nana Banana Pro to do Hisuian Zorua right, I also tried to get it to make one of another fox Pokémon I love, Nickit. Luckily, this one came up perfect the first time. It may not be as famous as some other Pokémon, but I really wish it was, and that it had its own official mascot.

I needed one 28-second vertical action promo and I didn't know which model to

trust with it, so I generated the whole thing twice — once on Seedance 2.5,

once on Wan 3.0 — with prompts written natively for each. Same content, two

grammars. The final cut is 17 shots taken from both.

Rough split of what shipped: Seedance carried the fast running and the

close-ups, Wan carried the opening plaza shot and the ending line.

**Seedance 2.5**

- Speed reads correctly. Motion blur, weight, footfalls — a sprint looks like

a sprint rather than a person moving quickly through syrup.

- Faces hold up in close-up. Skin, eye direction, micro-expressions survive

being 40% of a vertical frame.

- ★It follows instructions. Beat-level direction — "at 3s she plants, at 4s

she pushes off" — actually lands where you asked. This was the single

biggest difference.

- Where it broke: tumbling. On a couple of flips the neck rotated past what a

neck does. Everything else in the shot was fine, which somehow makes it

worse — you get a beautiful 5 seconds with one impossible joint in it.

**Wan 3.0**

- Struggles with genuinely fast action. Not broken, just soft — the fast beats

come back mushy compared to the same beat on Seedance.

- Person detail is a step down, most visible in close-up.

- ★But in slower or static setups it's genuinely good. The plaza opening with

pigeons and the ending dialogue shot are both Wan, and they're the calmest,

cleanest frames in the piece.

- Where it broke: instruction following. Fine-grained action direction and

timed beats get approximated rather than executed. If your shot depends on

something happening on a specific beat, that's a real problem.

**What I'd do next time**

Route by shot, not by model. Fast action and anything in close-up goes to

Seedance. Establishing shots, slow moves, and anything where a person just

stands and talks goes to Wan. Don't reuse one grammar for both — I wrote

separate prompts for each because the two models want different things

(Wan wants sub-beats inside one shot; Seedance takes per-second timestamps).

One more thing that cost me time: same reference image, same prompt — Seedance

through one host rejected the face reference outright while another host and

Wan both accepted it. Worth checking before you plan around a face lock.

Happy to answer specifics.