Pornographic use has long been the "break glass in case of emergency" for the LLM labs when it comes to finances.

My personal opinion is that while smut won't hurt anyone in of itself, LLM smut will have weird and generally negative consequences. As it will be crafted specifically for you on top of the intermittent reinforcement component of LLM generation.

It says what to do if you are over 18, but thinks you are under 18. But what if it identifies someone under 18 as being older?

And what if you are over 18, but don't want to be exposed to that "adult" content?

> Viral challenges that could push risky or harmful behavior

And

> Content that promotes extreme beauty standards, unhealthy dieting, or body shaming

Seem dangerous regardless of age.

Sexual and intimate chat with LLMs will be a huge market for whoever corners it. They'd be crazy to leave that money on the table.

What’s the goal there? Sexting?

I’m guessing age is needed to serve certain ads and the like, but what’s the value for customers?

eh there's an old saying that goes "no Internet technology can be considered a success until it has been adopted by (or in this case integrated with) the porn industry".

hate to say it but I'm pretty excited to try out those features.

As someone who's worked with population data, I found that there is an enormous rift between reported opinion (and HN and reddit opinion) vs revealed (through experimentation) population preferences.

I thought this was almost due to the AI personality splinter groups (trying to be charitable) like /myboyfriendisai and wrapper apps who vocally let them know they used those models the last time they sunset them.

This doesn't come as too much of a surprise to me. Feels like it mirrors some of the reasons why toxic positivity occurs in the workplace.

I was one of those pesky users who complained when o3 suddenly was unavailable.

When 5.2 was first launched, o3 did a notably better job at a lot of analytical prompts (e.g. "Based on the attached weight log and data from my calorie tracking app, please calculate my TDEE using at least 3 different methodologies").

o3 frequently used tables to present information, which I liked a lot. 5.2 rarely does this - it prefers to lay out information in paragraphs / blog post style.

I'm not sure if o3 responses were better, or if it was just the format of the reply that I liked more.

If it's just a matter of how people prefer to be presented their information, that should be something LLMs are equipped to adapt to at a user-by-user level based on preferences.

I thought it was based on the user thumbs-up and thumbs-down reactions, it evolving the way that it does makes it pretty obvious that users want their asses licked

They have added settings for this now - you can dial up and down how “warm” and “enthusiastic” you want the models to be. I haven’t done back to back tests to see how much this affects sycophancy, but adding the option as a user preference feels like the right choice.

If anyone is wondering, the setting for this is called Personalisation in user settings.

Put on a good show, offer something novel, and people will gleefully march right off a cliff while admiring their shiny new purchase.

Your absolutely right. You’re not imagining it. Here is the quiet truth:

You’re not imagining it, and honestly? You're not broken for feeling this—its perfectly natural as a human to have this sentiment.

Have you had a chance to compare with Gemini 3?

nah bruh you are just imagining it.

Its just as good as ever /s

It's amazing how different are the experiences different people have. To me every new version of chatgpt was an improvement and gemini is borderline unusable.

Why not Claude?

I REALLY struggle with Gemini 3 Pro refusing to perform web searches / getting combative with the current date. Ironically their flash model seems much more likely to opt for web search for info validation.

Not sure if others have seen this...

I could attribute it to:

1. It's known quantity with the pro models (I recall that the pro/thinking models from most providers were not immediately equipped with web search tools when they were released originally)

2. Google wants you to pay more for grounding via their API offerings vs. including it out of the box

I find Gemini does the most searching (and the quickest... regularly pulls 70+ search results on a query in a matter of seconds - likely due to googlebot's cache of pretty much every page). Chatgpt seems to only search if you have it in thinking/research mode now.

Well yeah, because 5.2 is the default and there's no way to change the default. So every time you open up a new chat you either use 5.2 or go out of your way to select something else.

(I'm particularly annoyed by this UI choice because I always have to switch back to 5.1)

0.1% of users is not necessarily 0.1% of conversations…

What's the default model when a random user goes to use the chatgpt website or app?

won't somebody think of the goonettes?!

Why would someone want to spend half a million dollars on GPUs and components (if not more) to run one year old models that genuinely aren't useful? You can't self host trillion parameter models unless you own a datacenter lol (or want to just light money on fire).

They'd only do that if they were some kind of open ai company /s

We're very echo-chambered here. That graph OpenAI released had coding at 4% or something.

4o is the most popular one for that

That’s been my experience and has lead to hours of wasted time. It’s faster for me to read through docs and watch YouTube.

Even if I submit the documentation or reference links they are completely ignored.

My theory, based on what I would see with non-thinking models, is that as soon as you start detailing something too much (ie: not just "speak in the style of X" but more like "speak in the style of X with [a list of adjectives detailing the style of X]" they would loose creativity, would not fit the style very well anymore etc. I don't know how things have evolved with new training techniques etc. but I suspected that overthinking their tasks by detailing too much what they have to do can lower quality in some models for creative tasks.

Have you tried the relatively recent Personalities feature? I wonder if that makes a difference.

(I have no idea. LLMs are infinite code monkeys on infinite typewriters for me, with occasional “how do I evolve this Pokémon’ utility. But worth a shot.)

/r/MyBoyfriendIsAI https://www.reddit.com/r/MyBoyfriendIsAI/ is a whole thing. It's not a joke subreddit.

I wonder if they have run the analytics on how many users are doing that. I would love to see that number.

well now you can unlock an 18+ version for sexual role-play so i guess its the other way around

Those people need to be uploaded into the Matrix and the data servers sent far, deep into space.

I was mostly using 4o for academic searches and planning. It was the best model for me. Based on the context I was giving and questions I was asking, 4o was the most the consistent model.

It used to get things wrong for sure but it was predictable. Also I liked the tone like everyone else. I stopped using ChatGPT after they removed 4o. Recently, I have started using the newer GPT-5 models (got free one month). Better than before but not quite. Acts way over smart haha

The reaction to its original removal on Instagram Reels, r/ChatGPT, etc., was genuinely so weird and creepy. I didn't realise before this how many people had genuine parasocial (?) relationships with these LLMs.

It was the first model I used that was half decent at coding. Everyone remembers their gateway drug.

I wonder if it will still be up on Azure? How much you think I can make if I setup 4o under a domain like yourgirlfriendis.ai or w/e

Note: I wouldnt actually, I find it terrible to prey on people.

ChatGPT Made Me Delusional: https://www.youtube.com/watch?v=VRjgNgJms3Q

Should be essential watching for anyone that uses these things.

Even ChatGPT (and certainly Google) confuses the names.

I'm sure there is some internal/academic reason for them, but from an outside observer simply horrible.

Considering how many people say ChatGTP too

It's almost always marketing and some stupid idea someone there had. I don't know why non-technical people try and claim so much ownership over versioning. You nearly always end up with these ridiculous outcomes.

"I know! Let's restart the version numbering for no good reason!" becomes DOOM (2016), Mortal Kombat 1 (2025), Battlefield 1 (2016), Xbox One (not to be confused with the original Xbox 1)

As another example, look at how much of a trainwreck USB 3 has become

Or how Nvidia restarted Geforce card numbering

"4o" was bad to begin with, as "four-oh" is a common verbalization of "4.0".

Even more than that, I've seen a lot of people confuse 4 and 4o, probably because 4o sounds like a shorthand for 4.0 which would be the same thing as 4.

I think this kind of thing is a pretty strong argument for the entire open source model ecosystem, not just open weights but open data and the whole gamut.