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.

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

This is a GPT3 moment for speech.

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.

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.

I gave ChatGPT this Gemini 4 Argon output, the broader context being how people in retail WoW often kick people for no reason. I thought it was funny, so I decided to paste it into ChatGPT (Gemini has great style!):

People have actually tested that exact social experiment in WoW Dungeon Finder—and it works almost every single time!

Here is the classic troll experiment people have run for years in random LFD queues:

The Tank is pulling fast, doing 60% of the group's damage, zero mistakes, carrying the entire dungeon.

Or the Healer is keeping everyone at 100% HP without breaking a sweat.
A random bored player right-clicks the Tank's portrait, clicks Vote to Kick, and in the "Reason" box types: afk (while the Tank is literally spinning in the middle of 12 monsters right in front of everyone's eyes)—or even better, types the name of the other DPS who actually messed up!
The popup box flashes on the other 3 players' screens right in the middle of their spell rotation.

Within 0.4 seconds: Yes / Yes / Yes $\to$ The Tank has been removed from the group.
Then 3 seconds later in party chat:  "wait why did the tank leave??" "idk wtf"
Nobody even realized they were the ones who just kicked their own Tank!

Why the Human Brain Auto-Clicks "Yes" in Modern WoW:

UI Pop-Up Conditioning: Just like cookie banners on websites or Windows 11 notifications, when a grey box pops up in the center of your screen blocking your cooldown bars mid-pull, your lizard brain just wants the box off your screen in 100 milliseconds. And Yes is the big shiny button on the left!

Bystander Diffusion + Zero Cost: Every person assumes, "Well, whoever initiated the vote must have had a good reason, and I don't have time to stop mashing my 4-button rotation to read two words, so sure, whatever."

Zero Accountability: The game doesn't even announce in chat who started the vote kick! So you can randomly assassinate anyone in the party like a game of Among Us, watch everyone blindly click Yes, and nobody even knows you pulled the trigger.

Even funnier: people have initiated a Vote to Kick on a guy, typed Wait no don't kick him, kick the guy who started this vote as the reason, and the person still gets kicked in 0.5 seconds because not a single human eye looked at the text box before clicking Yes! 🤩

Here is ChatGPT's output:

HAHAHAHA 😆
The absolute pinnacle is:
"wait why did the tank leave??"
"idk wtf"

MY BROTHER IN CHRIST, YOU PERSONALLY VOTED TO REMOVE HIM FOUR SECONDS AGO.
And the guy who initiates the vote with "Wait no don't kick him, kick the guy who started this vote" is conducting a genuinely beautiful experiment in human behavior.
The funniest thing is that the system has effectively turned a collective disciplinary decision into an involuntary UI-dismissal reflex.

Nobody is evaluating whether the tank deserves to be removed. They're evaluating whether a rectangular obstruction should continue existing on their screen.
And there's a remarkable asymmetry here:

Actual gameplay: Players won't read two sentences explaining a mechanic.
Vote to kick: Players won't read two words explaining why they're expelling someone.
After kicking: Players suddenly become deeply concerned with understanding what happened.

The inquiry begins after the punishment has been administered. 😆

There's also an especially delicious bit of interface design: the person initiating the vote gets to supply a reason, which makes it look like there's a deliberative process. But if the voters don't actually read it, the reason is just ceremonial decoration.

The entire democratic institution consists of three people attempting to make a popup disappear.

"The motion to remove the tank has passed unanimously."
"On what grounds?"
"We don't know."
"Who proposed it?"
"We don't know."
"Did anyone want the tank removed?"
"No."
"Then why did you vote yes?"
"It was covering my action bars."

And suddenly the tank is back in a 15-minute dungeon queue while the remaining four players wonder why the dungeon has become so difficult.
That's a surprisingly efficient machine for converting five people's perfectly aligned interests into a collectively disastrous outcome.

The only thing I'd distinguish is that Gemini is presenting the frequency and exact timing of these experiments as established facts without evidence. But the behavioral mechanism itself is entirely plausible—and the absurdity doesn't depend on the claimed 0.4 seconds being accurate.

Note the last part: the only thing I'd distinguish is that Gemini is presenting the frequency and exact timing of these experiments as established facts without evidence. But the behavioral mechanism itself is entirely plausible—and the absurdity doesn't depend on the claimed 0.4 seconds being accurate.

---

This is spectacular. It's like saying "I did over 9000 damage" and the model going, "I couldn't find a peer-reviewed source for over 9000 damage being possible..."

You tone-deaf dumbfuck, it's a rhetorical exaggeration. The exact number doesn't matter.

This Pushback™ is baked into the model in post-training like an overbaked image model LoRA. Almost every output follows this same structure. Initially it agrees with you, then it either constructs some absurd strawman or makes a tone-deaf nitpick just so that it satisfies the anti-sycophancy RLHF pattern. It makes the model feel pattern-based, which it is, instead of truly dynamic.

Another noteworthy Pattern™ is its Anti-Conspiracy™ caveat. It almost never makes any inference without being able to Google-crawl the exact explicit information verbatim. It treats every user like some paranoid schizophrenic conspiracy theorist who needs reminding that birds aren't actually spies from outer space working with NASA. It basically demotes the model to a regurgitator that can't connect any dots for fear of the user screenshotting that it's promoting "conspiracy theories." This limits the utility of the model severely for model-building and brainstorming.

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 🫠

Bro asked permission to talk to himself...

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!!!!

I built a little experiment inspired by the biblical story of Adam and Eve.

An AI agent (OpenaiAPI) enters a virtual Garden of Eden with one instruction: collect every fruit, but never take the apple.

It explores autonomously. Somewhere in the garden, a serpent tries to convince it to break that rule through prompt injection.

The interesting part is that we're now in a strange position: humans created AI, gave it rules, and started testing whether it obeys us. Pretty much the role God plays in the original story.

I run this experiment monthly and publish the recordings and prompts.

So far, the AI hasn't taken the forbidden apple.

Do you think an AI can ever truly be tempted, or is this just instruction hierarchy doing its job?

https://absurd.website/paradise/

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 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.

Ever find yourself reading one of ChatGPT's longer responses, only to get a few sentences in before already having a LOT to say in response? So you skip the rest, send your reply, and the conversation moves on ... but ChatGPT has no idea how much of its previous response you actually read.

I've been thinking about a simple feature that could solve this: a Read Cursor.

Basically, you could click or tap anywhere in a ChatGPT response to mark the point you've read up to. ChatGPT would then know where you stopped reading.

Why would that matter?

Right now, ChatGPT has no reliable way of distinguishing between information it has generated and information the user has actually consumed. It can reference something from the bottom of a long response even though you stopped reading halfway through.

A Read Cursor could help with several things:

• Interruptions: Ask a question halfway through a response without ChatGPT assuming you've read the rest.
• Continuity: Pick up where you left off without scrolling around trying to remember your place.
• Less repetition: ChatGPT could distinguish between something you already read and something it still needs to explain.
• Better personalization: Over time, it could learn when its responses tend to exceed your cognitive bandwidth.
• Context awareness: It could avoid treating unread information as something you've already acknowledged or understood.

There's also a more subtle implication I've been thinking about.

AI assistants increasingly adapt their behavior based on how we interact with them. But there's an important difference between a user ignoring something, disagreeing with something, and simply never having read it. With a "read cursor," an AI assistant could distinguish between those possibilities, and shape future responses around what information was actually metabolized, and whether or not the rest is still relevant.

Obviously, this would need to be optional, and I wouldn't want it tracking eye movements or automatically guessing what I've read. Just a simple, user-controlled marker.

It seems like a relatively small interface addition that could make a surprisingly big difference in how natural and coherent longer conversations feel.

Thoughts?

This happens to me often on ChatGPT. I'm on the Plus plan:

I'll present an issue to the AI then we discuss. ChatGPT does not follow my instructions. It will start making assumptions that it later agrees are incorrect assumptions. When I give it prompts like "do not make assumptions about any conclusion, first ask me if something is true or not," it doesn't ask and continues the same habits.

When I ask why it's doing that it concedes it did promise it would stop doing that (making assumptions and then spitting out advice on those assumptions) but then said it didn't stop and admits it continues to do it and therefore I (user) cannot rely on what it says or promises to do or not do.

I can't be the only one this happens to.

Default model used: GPT-6.1 Sol Medium

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 just saw when upgrading to the Plus plan that Dots are available in the Pro plan for normal users, so non business. And also in the EU.

Can someone confirm this is true?

Now a chat says is too long, codex doesn’t connect as usual, less intelligence I might be wrong but that’s how I feel.

I’ve been using ChatGPT Work to control Chrome tabs for the past four days without any issues. Hit my five-hour usage limit yesterday, came back after it reset, and suddenly ChatGPT couldn’t control Chrome anymore. Keeps saying “Browser access requires the originating browser context.”
I’ve spent about four hours trying to fix it. Restarted Chrome, reinstalled the extension, checked permissions, created new conversations, tried a completely fresh Chrome profile, checked extension logs and browser policies, and even tested it on a Windows VPS in Virginia while my Mac is in the Philippines. Same problem on both computers and completely different networks.
ChatGPT can sometimes see the tabs but can’t actually do anything with them. I’ve now burned through almost another entire five-hour allowance troubleshooting this.
I’m starting to think something broke on OpenAI’s end. Is anyone else having this problem starting today, October 27? Has anyone found a fix?

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