Dessa is a full-duplex speech-to-speech model that you can run on consumer GPUs.

This is a GPT3 moment for speech.

Think about it.

The French have spent centuries treating their language like a sacred artifact. The Académie Française exists specifically to protect French from “pollution.” They invent official replacements for every English tech word (courriel, logiciel, etc.). They’re extremely proud of how elegant and precise French is supposed to be.

Then along comes the most culturally dominant AI product of the decade and they call it… **ChatGPT**.

In French, “j’ai pété” literally means “I farted.”

So every single time a French person says the name of the tool out loud, they are forced to announce that they just farted.

This cannot be a coincidence. Sam Altman is not that careless with branding. They could have called it ChatAI, OpenChat, Athena, Hermes, literally anything else. Instead they chose the one combination of syllables that forces the most linguistically proud nation on Earth to repeatedly say “I farted” in polite company.

Still think it's just a coincidence? That one language was just an oversight? Consider this: French is the 4th most widely spoken language in the world!

It’s not about the technology. It’s a precision strike against French linguistic arrogance, executed with surgical cruelty and zero actual stakes.

Prompt: Please could you create me a realistic horse model and walking animation in 3js

Used Terra 6.1 max. This took around 15 minutes and used 30% of my 5H limit (plus).

I first noticed it was going to find horse models online so told it to stop and that it must generate the model itself.

Cool that it made shadows but I probably should have prompted it to be photo realistic

I’ve been experimenting with AI image generation, trying to figure out why so much of the artwork has that instantly recognizable AI look.

You know what I mean. The excessive glowing edges, bizarrely detailed textures, unnecessarily dramatic lighting, overcrowded compositions, and typography that seems designed to be impressive rather than readable.

I have a background in art and design, so I started treating ChatGPT like a junior designer. Instead of just generating new images when something looked wrong, I critiqued specific problems and developed a set of principles to address them.

One of the biggest discoveries was that reducing clutter isn’t the same as changing styles. When I criticized a neon-heavy poster, AI would often replace it with an equally cluttered vintage poster. Different aesthetic, same underlying problems.

Eventually, we developed 43 principles across composition, typography, texture, lighting, and artistic direction.

I’m sharing them because I think they could be useful for anyone working with AI-generated images, whether you’re an artist, designer, or just someone tired of everything looking like the same over-processed fantasy illustration.

The overarching philosophy: Design should look intentional, not merely impressive.

Composition & Visual Hierarchy
Restraint over spectacle. Don’t add elements just to make an image look impressive.
One dominant focal point. Give the viewer something obvious to look at first.
Negative space matters. Empty space isn’t a problem that needs fixing.
Remove unnecessary elements. If something isn’t contributing to the design, get rid of it.
Complexity needs a purpose. Intricate artwork is fine. An uncontrolled composition isn’t.

Typography
Legibility comes first. Don’t sacrifice readable letters for decorative effects.
Integrate typography into the composition. Text shouldn’t look randomly pasted over an illustration.
Limit competing type treatments. Not everything needs outlines, shadows, gradients, and a different font.
Create a clear reading order. Title first, essential information second.

Content & Communication
Stop adding lists to every flyer. Unless specifically requested, avoid cramming in lists of attractions, features, or activities.
Use only necessary copy. AI loves inventing taglines and promotional filler. Most designs don’t need them.
Show rather than explain. Let the artwork communicate the concept.
Don’t invent details. Fake addresses, dates, prices, and QR codes aren’t useful design elements.

Avoiding Generic AI Aesthetics
Stop defaulting to AI clichés. Neon, glowing particles, lens flares, excessive gradients, and dramatic lighting shouldn’t be automatic.
Polish isn’t originality. An elaborate image can still be completely generic.
Avoid stock-image thinking. Develop imagery around an actual concept.
Not everything needs to be cinematic, mystical, or ornate. Sometimes a simple illustration is more interesting.
Choose a coherent visual direction. Color, imagery, typography, and texture should feel like parts of the same design.

Working With AI as an Art Director
Treat criticism as art direction. Fix the underlying problem instead of making cosmetic adjustments.
Don’t replace one cliché with another. Switching neon clutter for vintage clutter isn’t an improvement.
Preserve what already works. When revising, don’t randomly change successful elements.
Critique the result before presenting it. Check hierarchy, legibility, unnecessary details, and visual coherence.
Don’t automatically agree with every criticism. Good creative collaboration includes independent judgment.
Material Authenticity & Texture
This was probably the most interesting part of the experiment.
There’s a particular texture that seems to appear in an enormous amount of AI-generated art. Everything looks simultaneously painterly, photographic, grainy, and digitally sharpened.
The stone, clouds, fabric, skin, and foliage somehow all share the same artificial surface quality.
These principles specifically target that problem.
Texture needs a reason to exist. It should come from the material, artistic technique, or environment.
Materials should look different. Stone shouldn’t have the same surface treatment as fabric or skin.
Avoid universal grain and distressing. Don’t coat the entire image in the same scratches, speckles, or artificial noise.
Choose a coherent artistic medium. Photography, illustration, painting, printmaking, and 3D rendering have different visual languages.
Avoid accidental medium mixing. Photographic anatomy combined with painted clouds and digitally rendered architecture can create an inconsistent result.

Detail & Visual Information
Establish a hierarchy of detail. The focal point can be highly resolved while secondary elements remain simple.
Allow quiet surfaces. Not every shadow, wall, or patch of sky needs intricate texture.
Avoid artificial microdetail. Tiny scratches, pores, and surface patterns don’t automatically make an image better.
Focus on large shapes first. Silhouette, proportion, and value structure matter more than decorative detail.
Use selective sharpness. Everything doesn’t need to be equally crisp.
Stop faking craftsmanship with texture. Random distressing isn’t a substitute for deliberate mark-making.
Lighting & Tonal Control
Lighting needs consistent logic. Highlights and shadows should follow a believable or intentionally stylized lighting scheme.
Stop outlining everything with glowing rim lights. It’s one of the most recognizable AI habits.
Let shadows stay dark. Not every dark surface needs artificially revealed detail.
Control microcontrast. Excessive local contrast makes everything look hyper-sharpened, metallic, or wet.
Use atmospheric effects selectively. Fog, bloom, haze, glowing particles, and light rays should exist for a reason.
Artistic Process & Authenticity
Design for a believable production method. The artwork should feel like something that could have been photographed, illustrated, painted, printed, or otherwise intentionally created.
Respect the limitations of the medium. If you’re imitating screen printing or lithography, the textures and color separations should make sense.
Imperfections should be intentional. Random scratches and distressed surfaces don’t automatically make something feel handmade.
Actively look for the AI texture signature. Check for repetitive detail, inconsistent materials, overprocessed surfaces, and grain that doesn’t belong. Fix the underlying image rather than hiding it with filters.

The two biggest takeaways
1. Design should look intentional, not merely impressive.
2. Detail should reveal the nature of the subject, not advertise the sophistication of the image generator.
I’m not advocating that every AI-generated image should be minimalist, photorealistic, or resemble traditional artwork. I actually love elaborate, theatrical, and highly stylized imagery.

What I want is intentional complexity rather than visual noise.

One practical technique that helped was evaluating designs at two sizes. At thumbnail scale, look at composition, silhouette, and hierarchy. At full resolution, inspect texture, lighting, edges, and material consistency.
And perhaps most importantly, stop treating image generation as a slot machine. Generating another image isn’t the same thing as improving the design.
These principles don’t magically fix every generation. Even with detailed instructions, the model sometimes repeats exactly the mistake it was told to avoid. But they’ve given me a much better vocabulary for directing and critiquing the results.

I’m curious whether other designers have noticed that distinctive AI surface texture, and whether you’ve found reliable ways to get rid of it.

Also, what principles would you add?

EDIT: Examples added.

Bro asked permission to talk to himself...

I’ve noticed ChatGPT offering worse and worse code recently, getting confused about what I’m asking it and seemingly less efficient at solving issues.

Am I imagining this or is something going on? I did read that there’s a point of diminishing returns where adding more data eventually decreases performance.

Everyone’s talking about AI becoming more and more intelligent but I swear it’s getting worse.

Hello everyone. I do reverse engineering, but what I do is always personal, so I don't work for someone or a company to do RE. The problem I have is the unnecessary safeguards on mainstream AIs, Gemini is the worst in this case, and then it is chatGPT and then Claude in my experience.

Is there any way to fix this issue or any alternative? I really don't have powerful hardware; I have 12th Gen Intel CPU with iGPU. I can't locally host a model, and I don't know what to do.

For example, I have a VM and inside of that I was testing a sketchy "antivirus". it wasn't nod32 or Kaspersky or anything mainstream, it is from an unknown origin, and I wanted to know how it works and what it does, I noticed that virtual memory page exhaustion shuts it down and I figured it out by accident.

Now since I'm working on an "antivirus" and I want to find a way to replicate the same shutdown, AI just freaks out and refuses to help because it is "deactivating a security product". changing the wordings didn't help either.

Either I get "This answer cannot be shown" banner in chatGPT, when I give my IDA output to it, or I get "I'm sorry I can't do X" from Gemini.

I'm tired of wrestling with them

Frequently:

• The answer is obvious from the conversation.

• It offers a choice of two answers that mean the exact same thing.

• It claims the answer is somehow relevant to the advice when it's not.

And of course I keep falling for it and polluting the context with details that have nothing to do with my question. Really frustrating.

I've been using ChatGPT to generate images for a while, and until October it worked really well. But lately instruction-following seem to have gotten significantly worse.

My biggest issue is that when I ask for six separate images it keeps generating a single collage containing all six, despite explicitly telling it NOT to make a collage. Even after acknowledging the mistake and promising to fix it, it does the exact same thing again. And it keeps apologizing.

It swears up and down the image model hasn't changed recently.

Do you have any insights?

I said LETS GO GAMBLING when I learned about Tibo's challenge thing (very new pro 100 user) and it seems to have picked this up without looking up the reference i was making. Was fun to see.

BULLSHITE?!

UTTER bullshite. I don't feel like fully going into what I was talking to it about, but let's pick something similar.

Neither the Hiroshima bomb nor the Nagasaki bomb were very efficient fissioning only an extremely small portion of the fissionables aboard each.

"yes, but with an important clarification"

No there is no "clarification" to what I said UNLESS you are going to introduce, for instance, actual percentages.

It did something similar to saying

"There is no way to determine exactly how efficient either device was".

Uhmm yeah...yeah there is. It's called E=MC2.

Now as I said that isnt' what we were talking about but I said something equally obvious and it argued with me. Repeatedly. Despite the fact the logic was as simple as if A=B and B=C then C=A.

"yes, but with an important clarification".

Grrrrrrrr!!!!

TL;DR: The official Sora export appears incomplete, but the old Library is gone, so I cannot even identify what is missing.
OpenAI Support has told me they cannot verify the export against the former Library and cannot confirm that the export is complete.
For three months, I have been asking for one temporary read-only preservation window, or at least a verified inventory or manifest, before historical Sora data is permanently deleted.

I’ve been trying to handle this privately with OpenAI Support for about three months, but at this point I think other former Sora users should know what has been happening.

I’m not asking OpenAI to bring Sora generation back.

My problem is much more basic than that: I still cannot reliably determine whether my historical Sora data has actually been preserved in the official export, because the old Library is gone and the export itself appears incomplete.

Before Sora became inaccessible, I remember having roughly around 4,000 historical items or records associated with my use of Sora.

I can’t verify that exact historical number anymore, and that is part of the problem. What I can currently account for through the export appears to be substantially less than what I remember having, possibly around half.

I’ve run the official Sora export multiple times and the same basic problem remains.

Some of my own historical creations appear to be missing, and former Library areas such as Likes, Favorites, My Media, and other account-linked history can no longer be opened at all.

So I have no reliable way to identify what is missing.

The interface that would have allowed me to compare my historical account against the export is no longer available.

That puts me in a ridiculous situation: I have reason to believe historical data is missing, but I no longer have access to the very interface I would need to identify and verify those missing items.

After months of Support conversations, OpenAI Support eventually gave me a clear written answer.

They told me that Support currently cannot compare my exported files against the former Sora Library, cannot confirm whether all historical content was included, and does not have another method to retrieve, verify, or preserve historical Sora content beyond the existing export.

They also explicitly told me that this does not mean my exports have been confirmed as complete.

That is the part I find most troubling.

The only preservation mechanism users are being given cannot be independently verified.

The original Library is inaccessible.

Support cannot verify it either.

And according to the official discontinuation process, historical Sora data may eventually be permanently deleted.

Since July, I have been asking OpenAI for what I think is a very reasonable preservation solution: give former Sora users a temporary, authenticated, strictly read-only Library before final deletion.

I am not asking for generation to come back.

Generation could stay disabled. Uploads could stay disabled. Editing, publishing, Likes, Saves, deletion, and every other write action could stay disabled.

I only want a way to search, review, verify, preserve, and download eligible historical material that is still associated with my account.

If even a limited read-only Library is not practical, then an equivalent verified inventory, manifest, historical item list, or another verification mechanism would also help.

I first raised this issue in July.

I even asked for a temporary read-only period before the remaining Sora API shutdown on September 24.

Nothing like that was provided.

It is now late October.

For roughly three months I have gone through Support cases, AI-assisted replies, duplicate closures, escalations, and human reviews.

The Support staff I spoke with were generally polite, and I do appreciate that.

But politeness does not solve the underlying problem.

One human Support specialist eventually told me directly that they cannot verify the export against the old Library, cannot provide another preservation method, and cannot confirm from the available case history that my proposal was ever forwarded to Product or Engineering.

That has been incredibly frustrating.

There is also a personal reason this matters so much to me.

I lost my local Sora backup after an unexpected hard-drive failure in July.

That accident was not OpenAI’s fault, and I have never claimed that it was.

But that accident exposed a much broader problem.

What happens when the official export appears incomplete or questionable, while the original service has already removed the only interface that could be used to verify what is missing?

A backup mechanism without a verification mechanism is not enough once the original inventory has disappeared.

I have also seen other former Sora users on Reddit and X complaining about incomplete exports, missing material, differing export results, and the loss of access to historical Sora content.

Those posts do not prove that every Sora user is affected or that there is a platform-wide export bug.

But they do show that I am not the only person frustrated by the way Sora’s history has been handled.

I think OpenAI should take that seriously.

Sora may be EOL, but that should not make our history disposable.

How a company retires a product matters just as much as how it launches one.

After three months, I’m exhausted.

I’ve tried being patient. I’ve tried Support. I’ve tried escalation. I’ve explained the same verification problem over and over.

I’m posting this publicly now because I honestly do not know what other path is left.

OpenAI, please give former Sora users one final meaningful opportunity to verify and preserve their history before historical data is permanently deleted.

A temporary read-only Library would help.

A verified inventory would help.

A complete preservation export would help.

Any practical mechanism that allows us to know what we actually had and preserve what is still eligible and retained would help.

That is all I am asking.

If you used Sora and experienced missing exports, inconsistent export counts, inaccessible Likes/Favorites/Collections, or other preservation problems, please share what happened, especially if you still have screenshots, export dates, approximate counts, or other evidence.

I genuinely want to know whether this is only my experience or whether other former Sora users are dealing with the same thing.

Since this morning, I’ve been experiencing several issues with ChatGPT (Plus €24/month).

Chats have become incredibly slow, it has suddenly started addressing me by name (wtf ?!) and using weird emojis (which it had never done before), and overall, it feels like its personality has completely changed. The way it responds is noticeably different from usual.
I’ve also tried generating a render several times. Each time, it appeared to be ready and available, but I was never actually able to view or download it.

Most importantly, it seems to have lost access to my memory.

Is anyone else experiencing these issues?

Edit:
I just tested it, and I can confirm that GPT-6 is the main issue. Sol 5.6 seems to be working normally 🫠

I've been experimenting with using ChatGPT to help make a bit of extra pocket money and wondered whether anyone else has done something similar.

One thing I've been using it for recently is matched betting. I started with very little knowledge of how it worked, but ChatGPT has been surprisingly useful in guiding me through the process.

It's helped me:

• Understand bookmaker welcome offers and their terms and conditions.
• Work out back and lay bets, including stakes, liabilities and potential profits.
• Identify suitable betting markets and compare odds.
• Keep track of deposits, withdrawals, free bets and overall profit or loss.
• Understand the risks and avoid making expensive mistakes.

Obviously, it isn't infallible, so I double-check the figures and offers before placing anything. But it's been a useful tool for learning something I probably wouldn't have attempted otherwise.

I'm not talking about making a fortune or replacing my income, just using AI to help generate a little extra spending money.

Has anyone else used ChatGPT to help make money in a similar way?

I'd be particularly interested in hearing about other genuine, practical ways people have used it to earn a bit of extra cash, ideally without needing specialist skills or a big initial investment.

Not looking for get-rich-quick schemes, just real experiences of things that have actually worked.

A clock tower and a fountain make this town feel familiar. The people flying above the rooftops give it a different set of possibilities. The complete Ling-3.1-flash scene brings those ideas together with market stalls, clustered houses and a warm evening sky.

The shared build used the model through the API with high thinking. Its scene request was a stylized village at sunset with flying people. A useful way to expand that idea is to describe the place and its movement in the same brief.

Here is a suggested version to adapt:

Create a stylized 3D village on a small island at sunset. Arrange houses and market stalls around a fountain plaza, with a clock tower as the main landmark. Add people flying above the rooftops. Use warm light and long shadows. Deliver a complete browser scene and a camera tour that shows the whole island, the streets and the people in flight.

The familiar village layout gives the flying figures a world to belong to.

My assistant has a distinct way of talking with me and suddenly it has been starting new chats with 0 memory context, referring to me as my account's fake name and it didn't remember itself at all.