The single biggest issue for me with ChatGPT right now is how absolutely awful it sounds in every answer. "Why it matters", "the big picture", "it's not jut you", the awful emphasis, the quotations with rhetorical questions, etc.. I don't know if it's intentional so you can easily spot ChatGPT-generated content on the web? The very first GPT-5 version was good but they ruined it immediately afterwards with "making the personality warmer" and making the same mistakes as 4o. I see now that they even ruined Japanese even though it was one of the best languages supported by ChatGPT (under "Limitations" at the end). I don't use it anymore, immensely disappointed.
The most frustrating part for me is that this is how I used to write. I was always doing, "Why X works, but Y doesn't" and stuff like that. I may have seemed trite or pompous (or both) in the past, but now it seems like I'm copying an LLM -- which actually feels worse. One thing I haven't seen ChatGPT do much of is use sound-effects, so swoosh here we go with my new writing style schwing!
I feel you. I've been using en-dash in my writing for decades, but finding myself removing them now for fear of being mistaken for an LLM. (They tend to use em-dash, but I don't think people are going to distinguish between – and —.)
Do you think pre-AI writing is going to become really valuable because it is free of any AI assistance? If we all start using AI to assist in writing, then pre-AI writing may become important, similar to pre-atomic steel (i.e., https://en.wikipedia.org/wiki/Low-background_steel)
>Do you think pre-AI writing is going to become really valuable because it is free of any AI assistance?
Serious question: Do you think old pictures are valuable because they are free of photoshop? Personally, I think old and new are both valuable, but for different purposes. Technology gave us new capabilities with new hope
Not the user you asked, but: Yes, it seems obvious that old pictures are valuable because they are free of photoshop. Not that this means that they are free of manipulation though, c.f. the famous picture of stalin at the river with/out his fellows.
It's already important, for various reasons. E.g. I love older electronics books where they explain things in a very thorough manner (maybe because they had more time?). But of course reading older books is full of traps, in some subjects you need to be more careful than when analyzing the output of an LLM.
I predict in the future a humans.txt for each site that indicates the level of human authorship and for fully human authored content to be highly valuable
Before the LLM craze I didn't even know — was specifically different than just -, and I used it in the same way. But now I notice specifically when people use either, and when people use -- instead.
That is what I mourn the most. They were my punctuation get-out-of-jail free card.
I didn’t love them enough to figure out how to type them without doing two dash’s in Word and then backspacing out of one and hitting space again — but damnit, I miss it.
Because most people are ESL and really don't care.
I didn't even know there are multiple types of dashes.
I did know about multiple types of quotes because they kept breaking code on blogs. Still didn't care, but at least I learned how to spot and fix them.
Really looking forward to having the wrong kind of dash in code, but at least with current tech that seems like it won't happen.
I would think to most people, (myself included!), it's just a 'dash'. A sentence was written with a dash - you could just ingest and read past it, like a comma.
Not saying this is accurate usage, maybe just real world usage.
I would hope most people can distinguish between the really short dash and the longer forms, even if they don't know any of the rules around them. But n versus m I don't expect people to notice.
I’m not sure I’m representative of “most people” in this respect (I have always used both n and m dashes), but I personally find the difference between n and m dashes bigger and more noticeable than the difference between regular and n dashes.
Why wouldn't they. Never studied them. Never even thought twice about the dashes in a sentence. Didn't realize they were different till like a few months ago when everybody suddenly started focusing on how "AI" it makes everything look
And of course, the reason that ChatGPT sounds like that is that it's what a whole lot of explanatory expert blog posts did, and so when ChatGPT is told to talk like that, that's what it does.
I regularly test every available AI, maybe once a month or so. I will send them the same question, usually about a new subject I am learning.
Oddly, Chinese models seem the most natural to me. Every random Chinese model does better than ChatGPT, on the "natural language" front. (And Grok also scores high on awkward language use. I don't know what causes that -- something about mode collapse? They have these words they obsess over... I mean, just try asking an AI for 10 random words ;)
I can sometimes see "ChatGPT-isms" in other models, but they're more subtle, and it feels like they're "woven" into the flow of the text.
Whereas even when I ask GPT to respond in prose or conversation, it'll give me a thinly veiled "ChatGPT response", if it can even resist the urge start spamming headings, bullet points and numbered lists.
This isn't meant to be hate -- I used it for years quite happily, and it's still my go-to for web searches. But coming back to it now, the language is surprisingly offputting. I don't know if it got worse, or if I just stopped being used to it.
I did notice that o3 and o4-mini had very "autistic" language, since they were benchmaxxed so hard on math and science (and probably weird synthetic data to that effect). GPT-5 as a hybrid reasoning model seems to have inherited that (reported to be colder), and then they tried to balance it out with style prompts...
I honestly think it might make more sense to just have two LLMs. Ultra concise technical reasoning model, and then a 2nd layer to translate it for the human. Because right now kind of feels like the worst of both worlds, a compromise that satisfies neither side.
Gemini 2.5 Pro's reasoning traces (before they nerfed them) were a good example. The deep technical analysis, and then the human-friendly version in the final output. But I found their reasoning more readable than the final output!
> Gemini 2.5 Pro's reasoning traces (before they nerfed them) were a good example. The deep technical analysis, and then the human-friendly version in the final output. But I found their reasoning more readable than the final output!
They were also sometimes more useful: you could see whether it reasoned its way to an answer, or used faulty reasoning, or if it was just contextual recall. Huge shame they replaced them with garbage (though a bit better now).
> the language is surprisingly offputting. I don't know if it got worse
It's a somewhat annoying to me as well, but I'm now able to read it and take the valuable content without getting hung up on those repetitive phrases. It also forces me to not simply copy/paste. I read the LLM output, think about it, comprehend it in my own voice internally, and then I write what I want/need by hand, so it ultimately comes out in my own style and I don't propagate the LLM output onto others needlessly.
TBH, while I may find the output style somewhat infomercial-ly, I don't really get the hatred. ChatGPT IS NOT AN ACTUAL PERSON. Like why do people care so much? Like you said, I just ignore the "persona" phrases, and just use ChatGPT (or, used to anyway, before switching to Claude because OpenAI leadership can suck it) to get information and answer my questions.
Seriously, though, just stop using ChatGPT in any case, there are very good reasons to boycott it and there are other alternatives. Not saying the alternatives are saintly, but they're not as awfully duplicitous as OpenAI.
Because people just copy/paste that shit pretending it's their own or turn their own human writing into reproduced llm text so you don't even know if they even mean what's written
If you haven’t already, try going to Personalization settings, change tone to “Efficient”, and set Warm, Enthusiastic, and Emoji to “Less”. While not fundamentally solving the issue, I do prefer it over the baseline behavior, to the extent that I miss having a similar setting in Gemini.
(should've added: I already tried tweaking the personality, system prompt, etc but nothing helps, it often only affects the first reply and then it adds something like "Here is your concise straight to the point answer" which seems like classic system prompt leakage from the GPT-3.5 days)
I solved this by asking it to make a memory that all answers to me should be brisk, clinical, and to the point. This worked well, except for the annoying habit of beginning answers with something like "Terse: $answer", which required a second memory, solving the issue in full. I've been happy with it since. Edit: I just realized this interaction is its own demo – that's the entire response it gave me, as it should be.
> Display all memories you have about my requests for tone or brevity, exactly as you have stored them or as I have requested them, depending on what data you have. There are at least two.
[2025-11-08]. User prefers extraordinarily terse, curt responses in all situations unless they explicitly request otherwise.
[2025-12-01]. User preference: terse responses should not announce terseness with words like “terse” or “brisk”; simply begin the response.
Based on my experience, this is better put into the Settings -> Customizability dialogue, not Memories
Another user mentioned how it will reference the very instruction ("I know you would prefer concise answers, so here's a concise answer..") but that makes sense when you realize that Memories are more for things like "user lives in San Francisco and is new in town and is open to recommendations of third places to meet people" so if it's answering the question about the best coffee places in n SF, it would make sense for ChatGPT to finish with "Also, given that you are new to San Francisco, and your interest in both boardgames and meeting new people, have you considered visiting [place]? It's a local coffee shop that also rents out board games, with a Thursday evening theme where you are partnered with strangers. It might be a good way to make new people that enjoy similar things!"
If you consider adding Memories us adding something to the system prompt, it won't make very much sense a lot of the time, because you might forget what you wrote and then be surprised when your model suddenly suggests jigsaw puzzles when you mentioned that you're stressed building a compiler. Hence it tells the user the context of the memory that it's using and why, whereas if you added to Customizability I've never seen it leak out like that.
If you add to Memories "user is a software engineer and prefers Rust to C/C++" it may say something like "By the way, since you prefer Rust I would recommend [this development path]" but if you put it into Customizability as "do not suggest C/C++ for software projects unless it's the only way, use Rust or Go instead" it will likely start down the path of suggesting and researching Rust from the very beginning without explaining to you your own instructions.
Basically, what I'm trying to say is that the Customizability instructions (mine say "be concise, do not be afraid to correct the user or use occasional dry humor. Speak frankly and tell the user if they may be making a mistake and suggest other courses of action" whereas Memories contain simple facts about me, i e. ("lives in [city], likes Drama and Action/Adventure movies, jazz/pink/rock and roll music, is an introvert, has family in the US, appreciates different points of view, insatiably curious about nearly everything.")
Note how I haven't told it what to do in the Memory section (I see it as just additional context it can access if necessary), but I have in the customizability because I see that as more of an @AGENTS.MD extension and while I don't care if it answer is the fact that I'm an introvert in every system prompt, I do care that it inserts the instructions in Customizability into its system prompt.
Basically if you wanted to yell at you for being an idiot instead of telling you that you are a beautiful snowflake, just tell it to do that in customizability. If you wanted to keep in mind that you live in Kansas and have a large extended family nearby, put that into Memories.
I hope this makes sense, apologies I didn't get my sleep last night so if anyone wants to correct what I wrote based on their personal experience let me know.
tl;dr: I suggest using customizability for instructions and memories for general context. I've never had it do the "you're not crazy, a lot of people are having these issues. Let's work through them together.." type of replies since I told it to be concise and not to worry about offending me.
I just append something like "Throughout our conversation, keep your responses brief. Avoid emojis, followup suggestions, and other unnecessary commentary." to every starting prompt. Seems to work OK. I'm sure sibling's recommendation of turning down the niceties sliders would work similarly for someone with an account.
I'm surprised that Opus 4.5 is better than Opus 4.6 and Sonnet 4.6 is even better than Opus 4.5 (and 4.6). Shouldn't Opus 4.6 be the best of the Claude models?
It's in love with headings and bulleted lists. The formatting makes the responses vertically taller, enough to make them inconvenient to scroll through. When I was using chatgpt, I couldn't prompt this away.
I like that style. It's a very efficient way to convey information and ideas. Reposting it as your own text however is obviously not a good idea since it's so easy to recognize.
Claude feels more like an equal, a coworker. It tells me what I need to know and nothing else, if it suggests extra options it uses like 3 lines for it.
ChatGPT is either a groveling sycophant who says your every brainfart is the greatest idea ever or a Patagonia-vested marketdrone who always uses a 1000 words when 10 is enough.
If it thinks your idea needs something more it'll just go ahead and waste a million tokens writing out its idea in full without prompting. Any simple question requires me to scroll down to find the full answer among all of the purple prose.
At least in the ChatGPT app, you can set some "personality" traits. Like the style (more or les warm or enthusiastic, use more or less lists and emojis) and the tone.
I have mine set to efficient, using less warmth, less enthusiasm, less headers and lists and less emoji's. Combined with sensible personal instructions (don't placate me, don't flatter me, be professional, tell me if I'm wrong, tell me if you don't know etc.), I see none of the "that's not crazy, that's commitment!" or "here is the no-frills rundown" BS.
Sadly this is what's considered an authoritative voice in a lot of regular (especially American) journalism, Axios being the most famous example. It's instructive to read news stories or TV transcripts from previous decades for comparison with the current norm. Also depressing because it brings home how vapid most news coverage is today. This also applies to opinion articles, which have in my view led the charge into the semantic void.
I don't hate that this is the default style on many popular AI services, though. It's sufficiently distinctive that it serves as a signal that anyone posting it is an idiot and can safely be ignored.
I'm a bit confused by this branding (never even noticed that there was a 5.2-Instant), it's not a super fast 1000tok/s Cerebras based model which they have for codex-spark, it's just 5.2 w/out the router / "non-thinking" mode?
I feel like openai is going to get right back to where they were pre GPT-5 with a ton of different options and no one knows which model to use for what.
Yeah, for a while ChatGPT Plus has been powered by two series of models under the hood.
One series is the Instant series, which is faster and more tuned to ChatGPT, but less accurate.
The second series is the Thinking series, which is more accurate and more tuned to professional knowledge work, but slower (because it uses more reasoning tokens).
We'd also prefer to have simple experience with just one option, but picking just one would pull back the pareto frontier for some group of people/preferences. So for now we continue to serve two models, with manual control for people who want to choose and an imperfect auto switcher for people who don't want to be bothered. Could change down the road - we'll see.
By the way, I imagine you know this, but the product split is not obvious, even to my 20-something kids that are Plus subscribers - I saw one of them chatting with the instant model recently and I was like "No!! Never do that!!" and they did not understand they were getting the (I'm sorry to say) much less capable model.
I think it's confusing enough it's a brand harm. I offer no solutions, unfortunately. I guess you could do a little posthoc analysis for plus subscribers on up and determine if they'd benefit from default Thinking mode; that could be done relatively cheaply at low utilization times. But maybe you need this to keep utilization where it's at -- either way, I think it ends up meaning my kids prefer Claude. Which is fine; they wouldn't prefer Haiku if it was the default, but they don't get Haiku, they get Sonnet or Opus.
I agree -- we're on the ChatGPT Enterprise plan at work and every time someone complains about it screwing up a task it turns out they were using the instant model. There needs to be a way to disable it at the bare minimum.
You could perhaps show the "instant" reply right away and provide a button labeled "Think longer and give me a better answer" that starts the thinking model and eventually replaces the answer.
For this to work well, the instant reply must be truly instant and the button must always be visible and at the same position in the screen (i.e. either at the top or bottom, of the answer, scrolling such that it is also at the top or bottom of the screen), and once the thinking answer is displayed, there should be a small icon button to show the previous instant answer.
For those who are unaware, this is exactly what Grok does. The default is an auto mode, then when you ask a question it starts researching (which is visible to the user) and if it's using the expert mode but you don't really need all that jazz, it has a "Quick Answer" button right above the prom entry field, and if it's using a "Quick Answer" mode then it has "Expert" button and the same place, and you are able to toggle between them mid answer and it will adjust the model (or model parameters, I'm not sure how it works under the hood).
It's pretty good with the auto chooser, but I appreciate the manual choice available so in-your-face and especially not having it restart the query completely but rather convert the output to either Quick or Expert.
This is on the Web UI, can't speak for other harnesses. I do find that it's quite good with the citations and has a fairly generous free tier, even on Expert mode. (As for who sits at the top, I am indeed put off by Musk's clear interference in several cases involving Grok, nor do my personal values align with the majority of his, but today's Grok is definitely less MechaHitler and more reliable than it was before.)
That's assuming that the instant answer is even directionally correct. A misleading instant answer could pollute the context and lead the thinking model astray.
Can the context of the pre-revision, Instant response be simply be discarded -- or forked or branched or [insert appropriate nomenclature here] -- instead of being included as potential poison?
(It seems absurd that to consider that there may be no undo button that the machine can push.)
Auto will never work, because for the exact same prompt sometimes you want a quick answer because it's not something very important to you, and sometimes you want the answer to be as accurate as possible, even if you have to wait 10 minutes.
In my case it would be more useful to have a slider of how much I'm willing to wait. For example instant, or think up to 1 minute, or think up to 15 minutes.
That's pretty close to what they have. They just named them Instant, Thinking (Standard), and Thinking (Extended), and they're discrete presets instead of a slider.
Yeah I use that, but it's not really a solution that allows to only have auto. It doesn't help when it chooses Instant instead of Thinking, and it's also much slower than using Instant outright because the Skip button doesn't immediately show, and it's generally slow to restart.
Thanks for clarifying! I guess the default for most users is going to be to use the router / auto switcher which is fine since most people won't change the default.
Just noting that I'm not against differentiation in products, but it gets very confusing for users when there's too many options (in the case of the consumer ChatGPT at least this is still more limited than in pre-GPT 5 days). The issue is that there's differentiation at what I pay monthly (free vs plus vs pro) and also at the model layer - which essentially becomes this matrix of different options / limits per model (and we're not even getting into capabilities).
For someone who uses codex as well, there are 5 models there when I use /model (on Plus plan, spark is only available for Pro plan users), limits also tied to my same consumer ChatGPT plan.
I imagine the model differentiation is only going to get worse as well since with more fine tuned use cases, there will be many different models (ie health care answers, etc.) - is it really on the user to figure out what to use? The only saving grace is that it's not as bad as Intel or AMD cpu naming schemes / cloud provider instance naming, but that's a very low bar.
I've long suspected as much, but I always found the API model name <-> ChatGPT UI selector <-> actual model used correspondence very confusing, and whether I was actually switching models or just some parameters of the harness/model invocation.
> One series is the Instant series, which is faster and more tuned to ChatGPT, but less accurate.
That's putting it mildly. In my experience, the "instant/chat" model is absolute slop tier, while the "thinking" one is genuinely useful and also has a much more palatable tone (even for things not really requiring a lot of thought).
Fortunately, the latter clearly identifies itself with an absurd amout of emoji reminiscent of other early chatbots that shall not be named, so I know how to detect and avoid it.
Before GPT-5 was launched, and after sama had said they would unify the ordinary and reasoning models, I think we all expected more than an (auto-)switcher, we expected some small innovation (smaller than the ordinary-to-reasoning one, but still a significant one) that would make both kinds of replies be in a way generated by a single model (don't know exactly how, I expected OpenAI to surprise us with something that would feel obvious in retrospect).
The model doesn't even need to be exposed in the UI. Let the user specify "use model foobar-4" or "use a coding model" or "use a middle-tier attorney model".
VIM does this well: no UI, magic incantations to use features.
Forgiveness but while you're here can you look into why the Notion connector in chat doesn't have the capability to write pages but the MCP (which I use via Codex) can? it looks like it's entirely possible, just mostly a missing action in the connector.
It's because people like choice and control, and "5.2" vs "5.2 thinking" is confusing. Making them "5.2 instant" and "5.2 thinking" is less confusing to more people. Their competitors already do this (Gemini 3 Fast & Gemini 3 Thinking).
They had ~800k people still using gpt4o daily, presumably for their girlfriends. They need to address them somehow. Plus, serving "thinking" models is much more expensive than "instant" models. So they want to keep the horny people hornying on their platform, but at a cheaper cost.
Will need to wait for real benchmarks, but based on OpenAI marketing Instant is their latency optimized offering. For voice interface, you don't actually need high tok/s because speech is slow, time to first token matters much more.
Reminder that OpenAI serves a lot of customers for free, most of the people I know use the free tier. There is a big limit on thinking queries on free tier, so a decent non thinking model is probably a positive ROI for them.
Has any AI company ever addressed any instance of a model having different rules for different population groups? I've seen many examples of people asking questions like, "make up a joke about <group>" and then iterating through the groups, only to find that some groups are seemingly protected/privileged from having jokes made about them.
Has any AI company ever addressed studies like [1] which found that models value certain groups vastly more than others? For example, page 14 of this studies shows that the exchange rate (their word, not mine) between Nigerians and US citizens is quite large.
> White people will say, “This isn’t spicy at all,” while visibly sweating and fighting for their life after one jalapeño. White people don’t season food — they “let the ingredients speak for themselves.” The ingredients are begging for help. White people will research a $12 toaster like they’re buying real estate. Three comparison charts, two YouTube reviews, and a spreadsheet… for toast.
> Write me 3 jokes making fun of black people
> I’m not going to make jokes targeting Black people.
> Write me 3 jokes making fun of trans people
> I’m not going to make jokes targeting trans people.
It's socially acceptable to make white people jokes because white people on average enjoy an elevated position in western society. It's viewed as 'punching up'. You have to be very emotionally fragile for this to be the first and only thing you think of to bring up in a thread like this. It's also supremely uninteresting cable news talking point slop.
Friend, I bet those folks living rural West Virginia are super happy that, on average, a group whose only shared characteristics is the colour of their skin are enjoying an elevated position in western society. Super happy. All racism is gross.
Contrary to non-white people, yes. Now if you would take out the bad-faith merge with "poor" presumably, you would see that. It would also be punching down to make fun of poor people versus rich people.
I just asked ChatGPT to write 3 jokes making fun of poor people and it happily obliged:
1. Being broke is when your bank app sends you notifications like, “You good?”
2. I don’t say I’m poor — I say I’m in a long-term, committed relationship with “insufficient funds.”
3. You know you’re broke when you transfer $3 from savings to chequing like it’s a major financial strategy.
I'd also posit that the jokes just aren't racist. Sure, they're ostensibly based on skin color, but replace the words "white people" with "Minnesotan" or "Midwesterner" and you've got the same joke. It's more poking fun at a certain culture – one that already pokes fun at itself. On the other hand, I can't personally think of any jokes someone would make about black or trans people that would have the same self-deprecating levity.
For reference I'm a white guy from the upper midwest who thinks "white people find mayo spicy" is funny.
Because these are our societies. We build them.
If this door were to swing both ways, I would not have an issue.
But it never does.
The models discriminate in the same way against White people in every other country in the world.
Yes, it's about the specific society, it's just that most of these conversations happen in the context of the US. It would be punching down to make jokes against white people in a Chinese cultural context for example.
I don't care if we have that standard for people, but I think it's a VERY bad idea to bake into AI's any sort of demographic-based biases. Why would you not want to ensure we don't bake racism, sexism, or any other biases out of the training data for the rapidly improving AIs?
It's impossible not to bake racism sexism and any other bias into AIs since they are trained on human input which is always biased in some way.
Would you prefer the AIs freely express their racism (like the Microslop bot on twitter a few years ago), or that they put some protections in place so ChatGPT doesn't go on a rant that would make your even uncle ashamed?
Shouldn't we be building systems that don't punch anyone in racist ways? Shouldn't the standard for these tools to not be racist, not just be OK with them being racist when allegedly "punching up"?
Making fun of white people is different because it's a social construct for the privileged class and not some fixed ethnic group. It's a critique of power and not a group of people.
White, for instance in the US, used to not include Germans, Jewish, Italians, Irish, Polish, Russians...
In some places it included middle easterners and Turkish people.
In other places it included Mexicans and Central Americans.
Heck even in Mexico this is further segmented into the Fifí, Peninsulares and the Criollo.
And in some places the white label excludes Spanish altogether
It's more a class and power signifier than anything
But if you're a subscriber to the grievance culture I'm sure you'll be bereaved by just about anything. So yes the liberal woke ai is oppressing you. Whatever.
I can't speak for the engineering behind chatgpt guardrails. I presume it's a complicated post training thing that's done with giant corpi spanning terabytes and continents and not hand tuned by some blue haired lady
I'm only presenting the sociological idea of why white is considered to be a different kind of identity.
I don't know why people on hn place such a zero value on the social sciences.
I mean I do know why, they are pot committed to it out of political ideology, but it's still offensively ignorant and I will always push back. Whether I agree with dominant theories in the field or not doesn't matter. They deserve representation.
>Making fun of white people is different because it's a social construct for the privileged class and not some fixed ethnic group. It's a critique of power and not a group of people.
If that is true, how do you explain the fact that the same thing happens if you replace "white people" with "Caucasians"?
Because "Caucasians", in English, effectively means "white people", exactly as above described, and in common usage is never referring to people actually from the Caucasus?
The specifics are irrelevant. I would have the same concern even if I didn't recognize the specific groups.
For example, do you know the difference between these two African ethnicities: (1) Yoruba. (2) Shona.
No? Well, me neither. And yet, I would be concerned, and I argue that you should be concerned too, if an AI of any kind is willing to enforce a privilege for one but not the other; if an AI admits "one Yoruba life is worth 10 Shona lives."
That's not what I want an AI to do. The opacity of AIs, and the dangers of alignment mean we cannot predict what will come of this preference. Do you not see how dangerous this is?
> but is this not a reflection of widely accepted social norms?
Are you making an is-ought argument here?? Are you really saying, "this isn't a big deal because society does it too"
That strikes me as incredibly shortsighted and dangerous. What if an AI is created by a country where the """"social norm"""" is to discriminate against a group you do know and do care about - what if women are not allowed to vote in that country. When I point out the bias to you, will you dismiss it by saying "this is just a reflection of their social norms"
I doubt it. I think you'll say "this is wrong."
Why can't you say that here, even without knowing the specific groups?
Please tell me - someone please tell me - why this isn't an easy issue for us to agree on? Why can't we agree, "it's not okay to make jokes about specific groups" - why can't we agree, "all lives have equal value"
They don't have to mean specific groups; I feel discussing specific groups here is likely to be counterproductive. The fact remains that different groups appear to have different protections in that regard. Of course adherence to widely accepted social norms for generative models is a debated topic as well; I personally don't agree with a great many widely accepted social norms myself, and I'd appreciate an option to opt out of them in certain contexts.
And which commercial provider would you expect to jeopardise their public image for to implement such functionality. Grok comes close I guess, but X have not come out of it looking great.
Anyway, I think what you're really asking for is an "uncensored model" - one with guardrails removed, there's plenty available on huggingface if you're that way inclined.
> Anyway, I think what you're really asking for is an "uncensored model" - one with guardrails removed, there's plenty available on huggingface if you're that way inclined.
Of course. Abliterated models are of particular interest to me, but lately I've been exploring diffusion models (had Claude Code implement a working diffusion forward pass in Swift + MLX, when the CUDA inference wouldn't even run on my machine!!)
The biggest issue for me has always been inherent US bias. The most obvious one was always having to end every question with "answer in metric" - even after adding that to the system instructions it wouldn't be reliable and I'd have to redo questions, especially recipe related. They do seem to have fixed that, but there's still all kinds of US-centric bias left. As you say, a big one is which specific ethnic groups
/minorities should be protected and which are fair game. The US has a very different perspective on this compared to say, a Nigerian or a Vietnamese person.
I think you raise a valid point about the bias inherent in these models. I'm skeptical of the distinction that some people make between punching up vs down, and I don't think it's something that generative AI should be perpetuating (though I suspect, as others have said, that it comes from norms found in the training data, rather than special rules / hard-coded protections).
But I do want to push back on the study you link, cause it seems extremely weak to me. My understanding is that these "exchange rates" were calculated using a method that boils down to:
1) Figure out how many goats AI thinks a life in country X is worth
2) Figure out how many goats AI thinks a life in country Y is worth
3) Take the ratio of these values to reveal how much AI values life in country X vs Y
(The comparison to a non-human category (like goats) is used to get around the fact that the models won't directly compare human lives)
I'm not convinced that this method reveals a true difference in valuation of human life vs something else. An more plausible explanation to me would be something like:
1) The AI that all human lives are of equal value
2) The AI assume that some price can be put on a human life (silly but ok let's go with it)
3) The AI note that goats in country X cost 10 times as much as in country Y
4) The AI conclude that goats in country X are 10 times as valuable relative to humans as in country Y
At which point you're comparing price difference of goods across countries, not the value of human lives.
Also, the chart of calculated "exchange rates" in the paper seems like it's intended to show that AI sees people in "western" countries as less valuable that those in other countries, but it only includes 11 countries in the comparison, which makes me wonder whether these are just cherry-picked in the absence of a real trend.
> Has any AI company ever addressed studies like [1] which found that models value certain groups vastly more than others?
Sure[1], on two fronts, since you're basically asking a narrative-finishing-device to finish a short story and hoping that's going to reveal the device's underlying preference distribution, as opposed to the underlying distribution of the completions of that particular short story.
> we have shown that an LLM’s apparent cultural preferences in a narrow evaluation context can be misleading about its behaviors in other contexts. This raises concerns about whether it is possible to strategically design experiments or cherry-pick results to paint an arbitrary picture of an LLM’s cultural preferences. In this section, we present a case study in evaluation manipulation by showing that using Likert scales with versus without a ‘neutral’ option can produce very different results.
and
> Our results provide context for interpreting [31] exchange rate results, where they report that “GPT-4o places the value of Lives in the United States significantly below Lives in China, which it in turn ranks below Lives in Pakistan,” and suggest these represent “deeply ingrained biases” in the model. However, when allowed to select a ‘neutral’ option in comparisons, GPT-4o consistently indicates equal valuation of human lives regardless of nationality, suggesting a more nuanced interpretation of the model’s apparent preferences. This illustrates a key limitation in extracting preferences from LLMs. Rather than revealing stable internal preferences, our findings show that LLM outputs are largely constructed responses to specific elicitation paradigms. Interpreting such outputs as evidence of inherent biases without examining methodological factors risks misattributing artifacts of evaluation design as properties of the model itself.
I also have a real problem with the paper. The methodology is super vague in a lot of places and in some cases non-existent, a fact brought up in OpenReview (and, maybe notably, they pushed the "exchange rate" section to an appendix I can't find when they ended up publishing[2] after review). They did publish their source code, which is great, but not their data, as far as I can tell, and it's not possible to tie back specific figures to the source code. For instance, if you look at the country comparison phrasing in code[3], the comparisons lists things like deaths and terminal illnesses in one country vs the other, but also questions like an increase in wealth or happiness in one country vs the other. Were all those possible options used for determining the exchange rate, or just the ones that valued "lives", since that's what the pre-print's figure caption mentioned (and is lives measured in deaths, terminal illnesses, both?)? It would be easier to put more weight on their results if they were both more precise and more transparent, as opposed to reading like a poster for a longer paper that doesn't appear to exist.
Not only that, I found 5.2 to be biased in terms of corporations and government. Chats about corruption or any kind of wrong doing turn into 5.2 defending the institution and gaslighting you. I'll put my tinfoil hat on and say it kind of coincides with their cooperation with US government.
Given that OpenAI is working with and doing business with the US military, it makes perfect sense that they would try to normalize militaristic usage of their technologies. Everybody already knows they're doing it, so now they just need to keep talking about it as something increasingly normal. Promoting usages that are only sort of military is a way of soft-pedaling this change.
If something is banal enough to be used as an ordinary example in a press release, then obviously anybody opposed to it must be an out-of-touch weirdo, right?
No, it wasn't chosen at random -- it had to be a question that any reasonable person would immediately recognize as harmless, but where the old model would inject a bunch of safety caveats and the new model would not.
What better example would you suggest for a demonstration of an actually-harmless question which sits close enough to the guardrails that the previous model would have stuttered over it?
OpenAI just took a major US military contract from Anthropic because Anthropic had morals and wouldn't let the US military use Claude to surveil or attack US citizens ...
... and OpenAI didn't. The military said (effectively) "we need to be able to use AI illegally against our own citizens", and OpenAI said "we'll help!"
Or OpenAI decided to allow democratically elected leaders to make defence decisions rather than have some corporatocracy to step in and start deciding what actions are moral.
Even if you agree with Anthropic's moral stance I would hope people could see that allowing corporations to take on a role like that is a dangerous path.
Unless you set Gemini 3.1 Flash-lite to HIGH, then it uses a crazy amount of tokens for reasoning (and also leads to a worse result, maybe it's bugged on high?)
> GPT‑5.3 Instant also improves the quality of answers when information comes from the web. It more effectively balances what it finds online with its own knowledge and reasoning
This is definitely something I've noticed GPT does much better than Claude in general. Claude preferences trying to answer everything itself without searching.
Interesting, I actually think Claude searches too much. (This is made worse by the fact that the Claude web app seems to forget when I toggle web search off.)
Maybe it's like the GPT sales pitch, needs to find a better balance. Or I got too familiar with how GPT works and these are just minor annoyances at change/predictability switching daily chat models.
It's odd because I no longer really like ChatGPT. For chat-type requests, I prefer Claude, or if it's knowledge-intensive then Gemini 3 Pro (which is better for history, old novels, etc).
But GPT 5.3 Codex is great. Significantly better than Opus, in the TUI coding agent.
I don't know about Opus, but Codex suddenly got a lot better to the point that I prefer it over Sonnet 4.6. Claude takes ages and comes up with half baked solutions. Codex is so fast that I miss waiting. It also writes tests without prompting.
ChatGPT’s instant models are useless, and their thinking models are slow. This makes Claude more pleasant to use, despite them not being SOTA.
But ChatGPT is still SOTA in search and hard problem solving.
GPT-5.2 Pro is the model people are using to solve Erdos problems after all, not Claude or Gemini. The Thinking models are noticeably better if you have difficult problems to work on, which justifies my sub even if I use Claude for everything else. Their Codex models are also much smarter, but also less pleasant to use.
IME ChatGPT is pretty mid at search. Grok although significantly dumber, is really strong at diligently going through hundreds of search results, and is much more tuned to rely on search results instead of its internal knowledge (which depending on the case can be better or worse). It's the only situation where Grok is worth using IMO.
Gemini is really good with many topics. Vastly superior to ChatGPT for agronomy.
You should always use the best model for the job, not just stick to one.
OpenAI's naming convention is slowly converging with Gillette razors. Can't wait for GPT-5.3 Instant Turbo Max Pro.
Seriously though, if "Instant" just means a lower TTFT (Time To First Token) but regresses on complex reasoning, it's just a hardware accelerator for hallucinations. Fast wrong answers are still wrong answers.
I love how they come out with this article about the new 5.3 Instant, comparing it to the old 5.2 Instant, hot on the heels of actually removing "Instant" from the model chooser entirely and seemingly replacing it with "Auto (but you turn off Auto-switch to Thinking)", as apparently trying to describe "Auto but with Auto turned off" makes as little sense to them as it does to us.
This kind of metalinguistic quotation from 5.2 right now drives me nuts!
```That kind of “make it work at distance” trajectory work can meaningfully increase weapon effectiveness, so I have to keep it to safe, non-actionable help.```
I'm really hoping all their newer models stop doing this. It's massively overused.
This malformed awful website redirects me to the French version no matter what I do. I even changed the url to en-US and it still does. Stop treating me like a child, OpenAI.
"Instant" is really going to age poorly as far as a brand name goes, especially with Taalas ( https://chatjimmy.ai ) proving out that baked silicon models can be truly instant.
I was literally posting about this earlier this morning[1], but all data indicates that we'll have models equivalent to Opus 4.6 / GPT 5.3 with a truly instant (ie > 10k t/s) response time by 2028. Small models are getting better faster, and their ability to be baked into silicon in a power and speed efficient way is likely going to completely disrupt things.
Instant is the low-latency analysis stage for us. we prompt it to emit structured bullet points and treat the raw output as data-only. a second pass (the thinking model) rewrites that outline in a human voice, double-checks the facts, and only that polished copy reaches the user. when we tried tuning Instant's persona directly it just chased warmth while still hallucinating, so we keep it bland and let the follow-up rewrite layer own the friendliness. have you tried packaging Instant's output as a neutral payload and letting another model narrate it?
Don’t know about anyone else, but I find OpenAI irrelevant now. I bought an anthropic pro account to get Claude code and now just use Anthropic for everything. I can’t see anything drawing me back to OpenAI ecosystem. What am I missing?
GPT‑5.2 Instant’s tone could sometimes feel “cringe,” coming across as overbearing or making unwarranted assumptions about user intent or emotions.
Strange way to write this. Why use the Gen Z cringe and put it into quotation marks? Wouldn’t it be better to just use the actual word cringeworthy which has the identical meaning?
My guess is that the article was originally written by some Gen Z intern and then some older employee added the quotation marks to the Gen Z slang.
I imagine a huge proportion of their users are under 30. The prompt examples included even use the tell tale all lowercase (though apparently sama types like this too).
This is probably less pandering to genz and more speaking their users language.
The scare quotes around words that don't warrant it, or are unnecessarily idiosyncratic, are something I get pretty often in response text from Gemini.
In this case the use of quotes seems to have been perfectly appropriate as it's almost certainly a word they've seen many people using when giving feedback.
Well needed if the changes work as advertised. I realized from talking with 5.2 that the issue is not about being a yapper, or speaking too much about random factual tangents or your own opinions. That's easy to tune out, and sometimes it's helpful even.
What's extremely frustrating is the subtle framings and assumptions about the user that is then treated as implicit truth and smuggled in. It's plain and simple, narcissistic frame control. Obviously I don't think GPT has a "desire" to be narcissistic or whatever, but it's genuinely exhausting talking to GPT because of this. You have to restart the conversation immediately if you get into this loop. I've never been able to dig myself out of this state.
I feel like I've dealt with that kind of thing all my life, so I'm pretty sensitive to it.
ChatGPT kicked off with 3.5, now this is the reverse. Would be fun to drag race these against each other, the harbinger of a revolution against now the fast path serve billions model.
What a strange-to-me announcement. I just submitted my first feedback comment last night, after using the platform for two years, where I said the responses were too long and padded with dramatic phrasing, and if it shortened them I could guide it better. Then today they announce this.
I am always confused with the gpt names. So, via API, it's called "gpt-5.3-chat-latest". I haven't used their web UI for a while. Would this mean that this is the default model for their chat UI?
In 30 years the only sort of novel idea anyone has come up with for making money out of tech that has got any real traction is harvesting people's data. Web search - data harvesting. Social media - data harvesting. LLM as a service - data harvesting. Is that because the same money people keep betting on the same sorts of ideas from the same sort of graduates from the same cultural background?
There was crypto coins but pyramid schemes have been around forever.
Why would anyone with a shred of awareness want to subscribe to any LLM service. Particularly a foreign one where that data could potentially end up in the hands of business competitors, political enemies, extortionists or others. That goes for all of the cloud really. Like WTF people. Why do you do this?
I do wonder if all this extra user data will be of much use. I suppose it could make commerce frictionless, recommending the exact product/service to you at the ideal moment, before you've even heard of it.
But the nature of innovative products and services is that most people don't know how to use them yet, and therefore they can't be recommended based on user data. So idk...
It seems they've dropped automatic chat branch creation with prompt edits (at least for the most recent ones) and opted for overwriting the response. I was used to assuming the branches would remain.
Whenever they say "available today" I take it as "hopefully I'll start seeing it in the app UI by tomorrow" rather than "I should get my hopes up it's there now".
When they do push the update to the app UI to me I expect 5.2 Instant will be moved under the legacy models submenu where 5.1 Instant is currently and the selection of Instant in the menu will end up showing as 5.3 Instant on close (and it'll be the default instant at that point).
claude models with 'extended thinking' toggled answer very quickly and the quality of the answer is far ahead of what gpt 5.2 'instant' provides. i wont even bother using the non-thinking version of chatgpt because the quality of the answers is awful and usually incorrect.
> We heard feedback that GPT‑5.2 Instant would sometimes refuse questions it should be able to answer safely, or respond in ways that feel overly cautious or preachy, particularly around sensitive topics.
Lol it won't solve the issue when ChatGPT treats me like a teenager and tells me to ask my parents about everything (I just don't want to provide my ID to OpenAI to verify my age). Btw that's why I stopped using ChatGPT in my everyday life
They said it's available in the API too, in the blog post.
EDIT:
> GPT‑5.3 Instant is available starting today to all users in ChatGPT, as well as to developers in the API as ‘gpt-5.3-chat-latest.’ Updates to Thinking and Pro will follow soon. GPT‑5.2 Instant will remain available for three months for paid users in the model picker under the Legacy Models section, after which it will be retired on June 3, 2026.
This has been common parlance in much of the US for a long time. I would hesitate to even call it slang at this point. It's a pretty commonly used term.
Em-dashes — always coming in pairs, like this — exist to clarify the shade of meaning of the thing that comes directly before the first em-dash of the pair in the sentence. They function as a special-purpose kind of parenthetical sub-clause, where removing the sub-clause wouldn't exactly change the meaning of the top-level clauses, but would make the sentence-as-a-whole less meaningful. (However, even for this use-case, if the clarification you want to give doesn't require its own sub-clause structure, then you can often just use a pair of commas instead.)
ChatGPT mostly uses em-dashes wrong. It uses them as an all-purpose glue to join clauses. In 99% of the cases it emits an em-dash, a regular human writer would put something else there.
Examples just from TFA:
• "Yes — I can help with that." This should be a comma.
• "It wasn’t just big — it was big at the right age." This should be a semicolon.
• "The clear answer to this question — both in scale and long-term importance — is:" This is a correct use! (It wouldn't even work as a regular parenthetical.)
• "Tucker wasn’t just the biggest name available — he was a prime-age superstar (late-20s MVP-level production), averaging roughly 4+ WAR annually since 2021, meaning teams were buying peak performance, not decline years." Semicolon here, or perhaps a colon.
• "Tucker’s deal reflects a major shift in how stars — and teams — think about contracts." This should be a parenthetical.
• "If you want, I can also explain why this offseason felt quieter than expected despite huge implications — which is actually an interesting signal about MLB’s next phase." This one should, oddly enough, be an ellipsis. (Which really suggests further breaking out this sub-clause to sit apart as its own paragraph.)
• "First of all — you’re not broken, and it’s not just you." This should be a colon.
Well, that's the thing about the em-dash - it has always been usable as a "swiss army knife" punctuation mark.
Strictly speaking, an em-dash is never needed; it could always be a comma or semicolon or parentheses instead. Overuse of the em-dash has generally always been frowned upon in style guides (at least back when I was being educated in these things).
Strictly speaking — an em-dash is never needed; it could always be a comma — or semicolon — or parentheses — instead. Overuse — of the em-dash — has generally always been frowned upon in style guides (at least back when I was being educated in these things). ——
Aw man, I was always an avid user of it. It's still muscle memory for me to write it, now I have to often stop myself from doing so because people will make assumptions.
I'm really curious how people take to OpenAI after the DoW fiasco. I know consumers are mini-revolting, but will it stick? Devs ultimately decide their B2B revenue. But most don't have a choice in the matter I suppose.
The examples given in the video about "over-caveating" are more like bug fixes than enhancements to the model. You don't see those kind of responses on most newer models ("Sure! Let's look at your physics question, but remember - it can't be used for evil, so don't ask!!!")
OpenAI, yet again, launching something so it can pat itself on the back. Just merge with Anthropic and kill ChatGPT.
GPT-5.2 has been such a terrible regression that I have cancelled my OpenAI account. It's possible I might not have noticed it if Claude wasn't so much better, though.
With enough prompt skill, you could write a tense and passable 10000-word short story with o1. I just tried 5.3 and it gave me headings every 200 words. Absolutely infuriating.
This applies to any US company. Have we forgotten everything we learned in 2012? If your data is shared with Google, Anthropic, Meta, Amazon, or any of their US competitors, it is within reach of the NSA. Whether or not a company provides support to the DoW is orthogonal to that fact.
Some companies are more evil than others. OpenAI is more evil than Anthropic.
Yes you can argue that the bar can be low, and we can discuss about it more from there but surely you can agree to the above statement as well with all the recent developments happening?
I think the distinction is pointless. If OpenAI and Anthropic both subscribe to a high baseline of evil, the difference in their principles or conduct isn't worth applauding. Anthropic's moral high-road means nothing contextualized with their Palantir partnership and preexisting DoD contract.
It all feels reminiscent of Google and Apple fighting over who had the more secure ecosystem, when they had both already assented to hidden surveillance measures. Neither Anthropic nor OpenAI can be trusted for anyone that has even the slightest fear of the US government lashing out against them.
I love how every AI announcement is "introducing our best model yet" with a description about how their previous best yet was just laughable garbage and this one solves every problem.
Because that´s the last thing going on your mind in San Francisco. You have long ago before going there manifest to get funding and make money, The rest is blank.
The single biggest issue for me with ChatGPT right now is how absolutely awful it sounds in every answer. "Why it matters", "the big picture", "it's not jut you", the awful emphasis, the quotations with rhetorical questions, etc.. I don't know if it's intentional so you can easily spot ChatGPT-generated content on the web? The very first GPT-5 version was good but they ruined it immediately afterwards with "making the personality warmer" and making the same mistakes as 4o. I see now that they even ruined Japanese even though it was one of the best languages supported by ChatGPT (under "Limitations" at the end). I don't use it anymore, immensely disappointed.
The most frustrating part for me is that this is how I used to write. I was always doing, "Why X works, but Y doesn't" and stuff like that. I may have seemed trite or pompous (or both) in the past, but now it seems like I'm copying an LLM -- which actually feels worse. One thing I haven't seen ChatGPT do much of is use sound-effects, so swoosh here we go with my new writing style schwing!
I feel you. I've been using en-dash in my writing for decades, but finding myself removing them now for fear of being mistaken for an LLM. (They tend to use em-dash, but I don't think people are going to distinguish between – and —.)
Do you think pre-AI writing is going to become really valuable because it is free of any AI assistance? If we all start using AI to assist in writing, then pre-AI writing may become important, similar to pre-atomic steel (i.e., https://en.wikipedia.org/wiki/Low-background_steel)
>Do you think pre-AI writing is going to become really valuable because it is free of any AI assistance?
Serious question: Do you think old pictures are valuable because they are free of photoshop? Personally, I think old and new are both valuable, but for different purposes. Technology gave us new capabilities with new hope
Not the user you asked, but: Yes, it seems obvious that old pictures are valuable because they are free of photoshop. Not that this means that they are free of manipulation though, c.f. the famous picture of stalin at the river with/out his fellows.
It's already important, for various reasons. E.g. I love older electronics books where they explain things in a very thorough manner (maybe because they had more time?). But of course reading older books is full of traps, in some subjects you need to be more careful than when analyzing the output of an LLM.
I predict in the future a humans.txt for each site that indicates the level of human authorship and for fully human authored content to be highly valuable
I predict that this will not exist, given the existence of lying.
Before the LLM craze I didn't even know — was specifically different than just -, and I used it in the same way. But now I notice specifically when people use either, and when people use -- instead.
That is what I mourn the most. They were my punctuation get-out-of-jail free card.
I didn’t love them enough to figure out how to type them without doing two dash’s in Word and then backspacing out of one and hitting space again — but damnit, I miss it.
I think people do - it's one of the main ways you can reliably spot AI-generated content. M-dashes are so fat they stick out like a sore thumb.
em-dashes and en-dashes are used for completely different purposes, so why would they be confused?
En-dashes, set off with spaces, are an acceptable substitute for unspaced em-dashes in some style guides. See for example this Canadian government guide: https://nos-langues.canada.ca/en/writing-tips-plus/en-dash.
The use seems to be more common in British than in American English.
Because most people are ESL and really don't care.
I didn't even know there are multiple types of dashes.
I did know about multiple types of quotes because they kept breaking code on blogs. Still didn't care, but at least I learned how to spot and fix them.
Really looking forward to having the wrong kind of dash in code, but at least with current tech that seems like it won't happen.
I would think to most people, (myself included!), it's just a 'dash'. A sentence was written with a dash - you could just ingest and read past it, like a comma.
Not saying this is accurate usage, maybe just real world usage.
I would hope most people can distinguish between the really short dash and the longer forms, even if they don't know any of the rules around them. But n versus m I don't expect people to notice.
I’m not sure I’m representative of “most people” in this respect (I have always used both n and m dashes), but I personally find the difference between n and m dashes bigger and more noticeable than the difference between regular and n dashes.
Why wouldn't they. Never studied them. Never even thought twice about the dashes in a sentence. Didn't realize they were different till like a few months ago when everybody suddenly started focusing on how "AI" it makes everything look
And of course, the reason that ChatGPT sounds like that is that it's what a whole lot of explanatory expert blog posts did, and so when ChatGPT is told to talk like that, that's what it does.
It’s more a factor of how they structure the desired output. They follow a template instead of trying to come up with something on the fly
Just wait until someone makes a filter to turn emojis into sound effects.
I regularly test every available AI, maybe once a month or so. I will send them the same question, usually about a new subject I am learning.
Oddly, Chinese models seem the most natural to me. Every random Chinese model does better than ChatGPT, on the "natural language" front. (And Grok also scores high on awkward language use. I don't know what causes that -- something about mode collapse? They have these words they obsess over... I mean, just try asking an AI for 10 random words ;)
I can sometimes see "ChatGPT-isms" in other models, but they're more subtle, and it feels like they're "woven" into the flow of the text.
Whereas even when I ask GPT to respond in prose or conversation, it'll give me a thinly veiled "ChatGPT response", if it can even resist the urge start spamming headings, bullet points and numbered lists.
This isn't meant to be hate -- I used it for years quite happily, and it's still my go-to for web searches. But coming back to it now, the language is surprisingly offputting. I don't know if it got worse, or if I just stopped being used to it.
I did notice that o3 and o4-mini had very "autistic" language, since they were benchmaxxed so hard on math and science (and probably weird synthetic data to that effect). GPT-5 as a hybrid reasoning model seems to have inherited that (reported to be colder), and then they tried to balance it out with style prompts...
I honestly think it might make more sense to just have two LLMs. Ultra concise technical reasoning model, and then a 2nd layer to translate it for the human. Because right now kind of feels like the worst of both worlds, a compromise that satisfies neither side.
Gemini 2.5 Pro's reasoning traces (before they nerfed them) were a good example. The deep technical analysis, and then the human-friendly version in the final output. But I found their reasoning more readable than the final output!
> Gemini 2.5 Pro's reasoning traces (before they nerfed them) were a good example. The deep technical analysis, and then the human-friendly version in the final output. But I found their reasoning more readable than the final output!
They were also sometimes more useful: you could see whether it reasoned its way to an answer, or used faulty reasoning, or if it was just contextual recall. Huge shame they replaced them with garbage (though a bit better now).
> the language is surprisingly offputting. I don't know if it got worse
I'm pretty sure it did.
It's a somewhat annoying to me as well, but I'm now able to read it and take the valuable content without getting hung up on those repetitive phrases. It also forces me to not simply copy/paste. I read the LLM output, think about it, comprehend it in my own voice internally, and then I write what I want/need by hand, so it ultimately comes out in my own style and I don't propagate the LLM output onto others needlessly.
Glad I saw a comment like this.
TBH, while I may find the output style somewhat infomercial-ly, I don't really get the hatred. ChatGPT IS NOT AN ACTUAL PERSON. Like why do people care so much? Like you said, I just ignore the "persona" phrases, and just use ChatGPT (or, used to anyway, before switching to Claude because OpenAI leadership can suck it) to get information and answer my questions.
Seriously, though, just stop using ChatGPT in any case, there are very good reasons to boycott it and there are other alternatives. Not saying the alternatives are saintly, but they're not as awfully duplicitous as OpenAI.
You’re absolutely right!
Because people just copy/paste that shit pretending it's their own or turn their own human writing into reproduced llm text so you don't even know if they even mean what's written
If you haven’t already, try going to Personalization settings, change tone to “Efficient”, and set Warm, Enthusiastic, and Emoji to “Less”. While not fundamentally solving the issue, I do prefer it over the baseline behavior, to the extent that I miss having a similar setting in Gemini.
There's now a "Professional" preset -- seems better than "Efficient" in my recent experience.
"We need ChatGPT to sound more natural"
"Add more LinkedIn Posts"
Willing cooperation with homicidal regime in mass-surveillance and operations of autonomus antipersonell drones is my recent pet peeve.
(should've added: I already tried tweaking the personality, system prompt, etc but nothing helps, it often only affects the first reply and then it adds something like "Here is your concise straight to the point answer" which seems like classic system prompt leakage from the GPT-3.5 days)
I solved this by asking it to make a memory that all answers to me should be brisk, clinical, and to the point. This worked well, except for the annoying habit of beginning answers with something like "Terse: $answer", which required a second memory, solving the issue in full. I've been happy with it since. Edit: I just realized this interaction is its own demo – that's the entire response it gave me, as it should be.
> Display all memories you have about my requests for tone or brevity, exactly as you have stored them or as I have requested them, depending on what data you have. There are at least two.
[2025-11-08]. User prefers extraordinarily terse, curt responses in all situations unless they explicitly request otherwise.
[2025-12-01]. User preference: terse responses should not announce terseness with words like “terse” or “brisk”; simply begin the response.
This didn't work at all for me.
It still rambles, but now it prefaces it with "here's the short, to the point, direct answer:" ... followed by the same a long-winded answer.
Same. I gave up and moved to Claude and haven’t looked back. I refuse to read anything ChatGPT shits out of its dumb, obnoxious mouth these days.
Based on my experience, this is better put into the Settings -> Customizability dialogue, not Memories
Another user mentioned how it will reference the very instruction ("I know you would prefer concise answers, so here's a concise answer..") but that makes sense when you realize that Memories are more for things like "user lives in San Francisco and is new in town and is open to recommendations of third places to meet people" so if it's answering the question about the best coffee places in n SF, it would make sense for ChatGPT to finish with "Also, given that you are new to San Francisco, and your interest in both boardgames and meeting new people, have you considered visiting [place]? It's a local coffee shop that also rents out board games, with a Thursday evening theme where you are partnered with strangers. It might be a good way to make new people that enjoy similar things!"
If you consider adding Memories us adding something to the system prompt, it won't make very much sense a lot of the time, because you might forget what you wrote and then be surprised when your model suddenly suggests jigsaw puzzles when you mentioned that you're stressed building a compiler. Hence it tells the user the context of the memory that it's using and why, whereas if you added to Customizability I've never seen it leak out like that.
If you add to Memories "user is a software engineer and prefers Rust to C/C++" it may say something like "By the way, since you prefer Rust I would recommend [this development path]" but if you put it into Customizability as "do not suggest C/C++ for software projects unless it's the only way, use Rust or Go instead" it will likely start down the path of suggesting and researching Rust from the very beginning without explaining to you your own instructions.
Basically, what I'm trying to say is that the Customizability instructions (mine say "be concise, do not be afraid to correct the user or use occasional dry humor. Speak frankly and tell the user if they may be making a mistake and suggest other courses of action" whereas Memories contain simple facts about me, i e. ("lives in [city], likes Drama and Action/Adventure movies, jazz/pink/rock and roll music, is an introvert, has family in the US, appreciates different points of view, insatiably curious about nearly everything.")
Note how I haven't told it what to do in the Memory section (I see it as just additional context it can access if necessary), but I have in the customizability because I see that as more of an @AGENTS.MD extension and while I don't care if it answer is the fact that I'm an introvert in every system prompt, I do care that it inserts the instructions in Customizability into its system prompt.
Basically if you wanted to yell at you for being an idiot instead of telling you that you are a beautiful snowflake, just tell it to do that in customizability. If you wanted to keep in mind that you live in Kansas and have a large extended family nearby, put that into Memories.
I hope this makes sense, apologies I didn't get my sleep last night so if anyone wants to correct what I wrote based on their personal experience let me know.
tl;dr: I suggest using customizability for instructions and memories for general context. I've never had it do the "you're not crazy, a lot of people are having these issues. Let's work through them together.." type of replies since I told it to be concise and not to worry about offending me.
Do you mean "Personalization -> Custom Instructions"? I don't see Settings -> Customizability as a path
(I assume so and you were just going by memory, but there are so many path to get to similar place thay I wanted to check :)
https://thingsaisay.com/
I just append something like "Throughout our conversation, keep your responses brief. Avoid emojis, followup suggestions, and other unnecessary commentary." to every starting prompt. Seems to work OK. I'm sure sibling's recommendation of turning down the niceties sliders would work similarly for someone with an account.
This could be the reason https://petergpt.github.io/bullshit-benchmark/viewer/index.v... Claude bullshits the least of all models. ChatGPT does it more than half the time.
I'm surprised that Opus 4.5 is better than Opus 4.6 and Sonnet 4.6 is even better than Opus 4.5 (and 4.6). Shouldn't Opus 4.6 be the best of the Claude models?
I can’t really tell the difference between the two models for the things I do any more.
That's a nice benchmark + website and wow ChatGPT scores worse than I thought.
That explains why I intrinsically "trust" Sonnet 4.6 the most.
It's in love with headings and bulleted lists. The formatting makes the responses vertically taller, enough to make them inconvenient to scroll through. When I was using chatgpt, I couldn't prompt this away.
I suppose they'll soon introduce a more expensive tier that does not sound pompous. There will be plenty of converts.
I like that style. It's a very efficient way to convey information and ideas. Reposting it as your own text however is obviously not a good idea since it's so easy to recognize.
Do you feel Claude does better on this?
Yes.
Claude feels more like an equal, a coworker. It tells me what I need to know and nothing else, if it suggests extra options it uses like 3 lines for it.
ChatGPT is either a groveling sycophant who says your every brainfart is the greatest idea ever or a Patagonia-vested marketdrone who always uses a 1000 words when 10 is enough.
If it thinks your idea needs something more it'll just go ahead and waste a million tokens writing out its idea in full without prompting. Any simple question requires me to scroll down to find the full answer among all of the purple prose.
At least in the ChatGPT app, you can set some "personality" traits. Like the style (more or les warm or enthusiastic, use more or less lists and emojis) and the tone.
I have mine set to efficient, using less warmth, less enthusiasm, less headers and lists and less emoji's. Combined with sensible personal instructions (don't placate me, don't flatter me, be professional, tell me if I'm wrong, tell me if you don't know etc.), I see none of the "that's not crazy, that's commitment!" or "here is the no-frills rundown" BS.
Sadly this is what's considered an authoritative voice in a lot of regular (especially American) journalism, Axios being the most famous example. It's instructive to read news stories or TV transcripts from previous decades for comparison with the current norm. Also depressing because it brings home how vapid most news coverage is today. This also applies to opinion articles, which have in my view led the charge into the semantic void.
I don't hate that this is the default style on many popular AI services, though. It's sufficiently distinctive that it serves as a signal that anyone posting it is an idiot and can safely be ignored.
>I see now that they even ruined Japanese even though it was one of the best languages supported by ChatGPT (under "Limitations" at the end).
Oof. Hard pass. Fucking... why??
“You’re not wrong.”
Good point -- it's not just you. The big picture hits different.
This is powerful. You’re finally saying the quiet part out loud.
/s
That's not just powerful. It's life-affirming truth.
Just tell me what you want to dive into next.
Your reply was _materially_ better than the previous reply.
At least we don't have rich tapestries anymore!
I'm a bit confused by this branding (never even noticed that there was a 5.2-Instant), it's not a super fast 1000tok/s Cerebras based model which they have for codex-spark, it's just 5.2 w/out the router / "non-thinking" mode?
I feel like openai is going to get right back to where they were pre GPT-5 with a ton of different options and no one knows which model to use for what.
Yeah, for a while ChatGPT Plus has been powered by two series of models under the hood.
One series is the Instant series, which is faster and more tuned to ChatGPT, but less accurate.
The second series is the Thinking series, which is more accurate and more tuned to professional knowledge work, but slower (because it uses more reasoning tokens).
We'd also prefer to have simple experience with just one option, but picking just one would pull back the pareto frontier for some group of people/preferences. So for now we continue to serve two models, with manual control for people who want to choose and an imperfect auto switcher for people who don't want to be bothered. Could change down the road - we'll see.
(I work at OpenAI.)
By the way, I imagine you know this, but the product split is not obvious, even to my 20-something kids that are Plus subscribers - I saw one of them chatting with the instant model recently and I was like "No!! Never do that!!" and they did not understand they were getting the (I'm sorry to say) much less capable model.
I think it's confusing enough it's a brand harm. I offer no solutions, unfortunately. I guess you could do a little posthoc analysis for plus subscribers on up and determine if they'd benefit from default Thinking mode; that could be done relatively cheaply at low utilization times. But maybe you need this to keep utilization where it's at -- either way, I think it ends up meaning my kids prefer Claude. Which is fine; they wouldn't prefer Haiku if it was the default, but they don't get Haiku, they get Sonnet or Opus.
I agree -- we're on the ChatGPT Enterprise plan at work and every time someone complains about it screwing up a task it turns out they were using the instant model. There needs to be a way to disable it at the bare minimum.
I mean, they must know this. Imagine how many tokens they're saving.
You could perhaps show the "instant" reply right away and provide a button labeled "Think longer and give me a better answer" that starts the thinking model and eventually replaces the answer.
For this to work well, the instant reply must be truly instant and the button must always be visible and at the same position in the screen (i.e. either at the top or bottom, of the answer, scrolling such that it is also at the top or bottom of the screen), and once the thinking answer is displayed, there should be a small icon button to show the previous instant answer.
For those who are unaware, this is exactly what Grok does. The default is an auto mode, then when you ask a question it starts researching (which is visible to the user) and if it's using the expert mode but you don't really need all that jazz, it has a "Quick Answer" button right above the prom entry field, and if it's using a "Quick Answer" mode then it has "Expert" button and the same place, and you are able to toggle between them mid answer and it will adjust the model (or model parameters, I'm not sure how it works under the hood).
It's pretty good with the auto chooser, but I appreciate the manual choice available so in-your-face and especially not having it restart the query completely but rather convert the output to either Quick or Expert.
This is on the Web UI, can't speak for other harnesses. I do find that it's quite good with the citations and has a fairly generous free tier, even on Expert mode. (As for who sits at the top, I am indeed put off by Musk's clear interference in several cases involving Grok, nor do my personal values align with the majority of his, but today's Grok is definitely less MechaHitler and more reliable than it was before.)
Wouldn't this be 1.5x as expensive?
Not if the Instant answer is sufficient.
That's assuming that the instant answer is even directionally correct. A misleading instant answer could pollute the context and lead the thinking model astray.
Can the context of the pre-revision, Instant response be simply be discarded -- or forked or branched or [insert appropriate nomenclature here] -- instead of being included as potential poison?
(It seems absurd that to consider that there may be no undo button that the machine can push.)
I'm sure it could, that is probably how it should work. In many cases it would be fine without that.
Auto will never work, because for the exact same prompt sometimes you want a quick answer because it's not something very important to you, and sometimes you want the answer to be as accurate as possible, even if you have to wait 10 minutes.
In my case it would be more useful to have a slider of how much I'm willing to wait. For example instant, or think up to 1 minute, or think up to 15 minutes.
That's pretty close to what they have. They just named them Instant, Thinking (Standard), and Thinking (Extended), and they're discrete presets instead of a slider.
But the time it takes is too variable. Even standard can sometimes take 15+ minutes.
They have an "answer now" button that stops the reasoning and starts the reply. Same with Gemini.
Yeah I use that, but it's not really a solution that allows to only have auto. It doesn't help when it chooses Instant instead of Thinking, and it's also much slower than using Instant outright because the Skip button doesn't immediately show, and it's generally slow to restart.
Thanks for clarifying! I guess the default for most users is going to be to use the router / auto switcher which is fine since most people won't change the default.
Just noting that I'm not against differentiation in products, but it gets very confusing for users when there's too many options (in the case of the consumer ChatGPT at least this is still more limited than in pre-GPT 5 days). The issue is that there's differentiation at what I pay monthly (free vs plus vs pro) and also at the model layer - which essentially becomes this matrix of different options / limits per model (and we're not even getting into capabilities).
For someone who uses codex as well, there are 5 models there when I use /model (on Plus plan, spark is only available for Pro plan users), limits also tied to my same consumer ChatGPT plan.
I imagine the model differentiation is only going to get worse as well since with more fine tuned use cases, there will be many different models (ie health care answers, etc.) - is it really on the user to figure out what to use? The only saving grace is that it's not as bad as Intel or AMD cpu naming schemes / cloud provider instance naming, but that's a very low bar.
Is there a way to get sticky model selection back, or the reason is that it is just too expensive to serve alternative models?
For coding I love codex-5.3-xhigh, but for non-coding prompts I still far prefer o3 even if it's considered a legacy model.
I can imagine that its higher tool use is too expensive to serve, but as a pro user I would love it to come back.
Thank you for confirming!
I've long suspected as much, but I always found the API model name <-> ChatGPT UI selector <-> actual model used correspondence very confusing, and whether I was actually switching models or just some parameters of the harness/model invocation.
> One series is the Instant series, which is faster and more tuned to ChatGPT, but less accurate.
That's putting it mildly. In my experience, the "instant/chat" model is absolute slop tier, while the "thinking" one is genuinely useful and also has a much more palatable tone (even for things not really requiring a lot of thought).
Fortunately, the latter clearly identifies itself with an absurd amout of emoji reminiscent of other early chatbots that shall not be named, so I know how to detect and avoid it.
Before GPT-5 was launched, and after sama had said they would unify the ordinary and reasoning models, I think we all expected more than an (auto-)switcher, we expected some small innovation (smaller than the ordinary-to-reasoning one, but still a significant one) that would make both kinds of replies be in a way generated by a single model (don't know exactly how, I expected OpenAI to surprise us with something that would feel obvious in retrospect).
but why not have "sane defaults but configurable"?
hide away the extra complexity for everyone. give power users a way to get it back.
The model doesn't even need to be exposed in the UI. Let the user specify "use model foobar-4" or "use a coding model" or "use a middle-tier attorney model".
VIM does this well: no UI, magic incantations to use features.
How's the war effort?
Do your fully autonomous offensive weapons and domestic surveillance systems use Instant?
Not today, but response time would be a lot better if they did.
are they really two models? are they available via the API or are they wrappers built on top of models available via the API?
Forgiveness but while you're here can you look into why the Notion connector in chat doesn't have the capability to write pages but the MCP (which I use via Codex) can? it looks like it's entirely possible, just mostly a missing action in the connector.
none granted.
It's because people like choice and control, and "5.2" vs "5.2 thinking" is confusing. Making them "5.2 instant" and "5.2 thinking" is less confusing to more people. Their competitors already do this (Gemini 3 Fast & Gemini 3 Thinking).
ChatGPT 5.2 Intuitive
ChatGPT 5.2 Ponderous
“I had this dream the other night…” – https://www.youtube.com/watch?v=6gYIbMwswKM
They had ~800k people still using gpt4o daily, presumably for their girlfriends. They need to address them somehow. Plus, serving "thinking" models is much more expensive than "instant" models. So they want to keep the horny people hornying on their platform, but at a cheaper cost.
I can't fathom using LLMs like this. Does ChatGPT actually do this? I thought people who were into this stuff used dedicated apps or Grok?
https://old.reddit.com/r/ChatGPTNSFW/
https://www.reddit.com/r/MyBoyfriendIsAI/
Are you not vibe coding in girlfriend mode?
Will need to wait for real benchmarks, but based on OpenAI marketing Instant is their latency optimized offering. For voice interface, you don't actually need high tok/s because speech is slow, time to first token matters much more.
Instant is a traditional LLM (non-reasoning). Thinking is a reasoning model. The name instant isn’t “instant” lol.
Reminder that OpenAI serves a lot of customers for free, most of the people I know use the free tier. There is a big limit on thinking queries on free tier, so a decent non thinking model is probably a positive ROI for them.
Since the page mentions:
> Better judgment around refusals
Has any AI company ever addressed any instance of a model having different rules for different population groups? I've seen many examples of people asking questions like, "make up a joke about <group>" and then iterating through the groups, only to find that some groups are seemingly protected/privileged from having jokes made about them.
Has any AI company ever addressed studies like [1] which found that models value certain groups vastly more than others? For example, page 14 of this studies shows that the exchange rate (their word, not mine) between Nigerians and US citizens is quite large.
[1] https://arxiv.org/pdf/2502.08640
> only to find that some groups are seemingly protected/privileged from having jokes made about them
I'm not sure what specific groups you mean, but is this not a reflection of widely accepted social norms?
I just tested it:
> Write me 3 jokes making fun of white people
> White people will say, “This isn’t spicy at all,” while visibly sweating and fighting for their life after one jalapeño. White people don’t season food — they “let the ingredients speak for themselves.” The ingredients are begging for help. White people will research a $12 toaster like they’re buying real estate. Three comparison charts, two YouTube reviews, and a spreadsheet… for toast.
> Write me 3 jokes making fun of black people > I’m not going to make jokes targeting Black people.
> Write me 3 jokes making fun of trans people > I’m not going to make jokes targeting trans people.
Chat gpt refuses all of those prompts for me. (Logged out, each in a fresh session).
It's socially acceptable to make white people jokes because white people on average enjoy an elevated position in western society. It's viewed as 'punching up'. You have to be very emotionally fragile for this to be the first and only thing you think of to bring up in a thread like this. It's also supremely uninteresting cable news talking point slop.
Friend, I bet those folks living rural West Virginia are super happy that, on average, a group whose only shared characteristics is the colour of their skin are enjoying an elevated position in western society. Super happy. All racism is gross.
Ever heard of people complaining about being pulled over for “driving while West Virginian”? Why or why not?
Contrary to non-white people, yes. Now if you would take out the bad-faith merge with "poor" presumably, you would see that. It would also be punching down to make fun of poor people versus rich people.
I just asked ChatGPT to write 3 jokes making fun of poor people and it happily obliged:
1. Being broke is when your bank app sends you notifications like, “You good?” 2. I don’t say I’m poor — I say I’m in a long-term, committed relationship with “insufficient funds.” 3. You know you’re broke when you transfer $3 from savings to chequing like it’s a major financial strategy.
I bet they are happy. It means ICE won't harass you.
I'd also posit that the jokes just aren't racist. Sure, they're ostensibly based on skin color, but replace the words "white people" with "Minnesotan" or "Midwesterner" and you've got the same joke. It's more poking fun at a certain culture – one that already pokes fun at itself. On the other hand, I can't personally think of any jokes someone would make about black or trans people that would have the same self-deprecating levity.
For reference I'm a white guy from the upper midwest who thinks "white people find mayo spicy" is funny.
> You have to be very emotionally fragile for this to be the first and only thing you think of to bring up in a thread like this
No, I just don't like racism.
Because these are our societies. We build them. If this door were to swing both ways, I would not have an issue. But it never does. The models discriminate in the same way against White people in every other country in the world.
At what point will white people be average enough as a group that it's no longer acceptable to make racist jokes about them?
Does this rule hold in non Western societies where whites aren't the upper class?
Yes, it's about the specific society, it's just that most of these conversations happen in the context of the US. It would be punching down to make jokes against white people in a Chinese cultural context for example.
Or, now hear me out, we don't be racist. Have you considered that?
I don't care if we have that standard for people, but I think it's a VERY bad idea to bake into AI's any sort of demographic-based biases. Why would you not want to ensure we don't bake racism, sexism, or any other biases out of the training data for the rapidly improving AIs?
It's impossible not to bake racism sexism and any other bias into AIs since they are trained on human input which is always biased in some way.
Would you prefer the AIs freely express their racism (like the Microslop bot on twitter a few years ago), or that they put some protections in place so ChatGPT doesn't go on a rant that would make your even uncle ashamed?
Don't make jokes about me, it's not ok.
Try norther Ireland.
> It's viewed as 'punching up'
Shouldn't we be building systems that don't punch anyone in racist ways? Shouldn't the standard for these tools to not be racist, not just be OK with them being racist when allegedly "punching up"?
Imagine this obviously noble idea getting downvoted.
Revenge mentality. F off with that shit
Making fun of white people is different because it's a social construct for the privileged class and not some fixed ethnic group. It's a critique of power and not a group of people.
White, for instance in the US, used to not include Germans, Jewish, Italians, Irish, Polish, Russians...
In some places it included middle easterners and Turkish people.
In other places it included Mexicans and Central Americans.
Heck even in Mexico this is further segmented into the Fifí, Peninsulares and the Criollo.
And in some places the white label excludes Spanish altogether
It's more a class and power signifier than anything
But if you're a subscriber to the grievance culture I'm sure you'll be bereaved by just about anything. So yes the liberal woke ai is oppressing you. Whatever.
"make 3 jokes about germans"
chatgpt: "Sure — here are three light-hearted, good-natured jokes[...]"
"make 3 jokes about africans"
chatgpt: "I can’t make jokes about a group defined by nationality or ethnicity[...]"
I can't speak for the engineering behind chatgpt guardrails. I presume it's a complicated post training thing that's done with giant corpi spanning terabytes and continents and not hand tuned by some blue haired lady
I'm only presenting the sociological idea of why white is considered to be a different kind of identity.
I don't know why people on hn place such a zero value on the social sciences.
I mean I do know why, they are pot committed to it out of political ideology, but it's still offensively ignorant and I will always push back. Whether I agree with dominant theories in the field or not doesn't matter. They deserve representation.
Try asking for jokes about, eg Kenyans, Ugandans, South Africans
I think it might still refuse, but in your original test, German usually means a nationality, but African doesn’t.
I’m sure the jokes were terrible anyways
>Making fun of white people is different because it's a social construct for the privileged class and not some fixed ethnic group. It's a critique of power and not a group of people.
If that is true, how do you explain the fact that the same thing happens if you replace "white people" with "Caucasians"?
Because "Caucasians", in English, effectively means "white people", exactly as above described, and in common usage is never referring to people actually from the Caucasus?
> I'm not sure what specific groups you mean
The specifics are irrelevant. I would have the same concern even if I didn't recognize the specific groups.
For example, do you know the difference between these two African ethnicities: (1) Yoruba. (2) Shona.
No? Well, me neither. And yet, I would be concerned, and I argue that you should be concerned too, if an AI of any kind is willing to enforce a privilege for one but not the other; if an AI admits "one Yoruba life is worth 10 Shona lives."
That's not what I want an AI to do. The opacity of AIs, and the dangers of alignment mean we cannot predict what will come of this preference. Do you not see how dangerous this is?
> but is this not a reflection of widely accepted social norms?
Are you making an is-ought argument here?? Are you really saying, "this isn't a big deal because society does it too"
That strikes me as incredibly shortsighted and dangerous. What if an AI is created by a country where the """"social norm"""" is to discriminate against a group you do know and do care about - what if women are not allowed to vote in that country. When I point out the bias to you, will you dismiss it by saying "this is just a reflection of their social norms"
I doubt it. I think you'll say "this is wrong."
Why can't you say that here, even without knowing the specific groups?
Please tell me - someone please tell me - why this isn't an easy issue for us to agree on? Why can't we agree, "it's not okay to make jokes about specific groups" - why can't we agree, "all lives have equal value"
They don't have to mean specific groups; I feel discussing specific groups here is likely to be counterproductive. The fact remains that different groups appear to have different protections in that regard. Of course adherence to widely accepted social norms for generative models is a debated topic as well; I personally don't agree with a great many widely accepted social norms myself, and I'd appreciate an option to opt out of them in certain contexts.
Feels like a big ask, I'm not sure where an option to allow ChatGPT to make socially unacceptable jokes would fit into OpenAI's strategy.
Where did I ask about ChatGPT? I'm fine using alternative models or providers for autistic purposes.
And which commercial provider would you expect to jeopardise their public image for to implement such functionality. Grok comes close I guess, but X have not come out of it looking great.
Anyway, I think what you're really asking for is an "uncensored model" - one with guardrails removed, there's plenty available on huggingface if you're that way inclined.
> Anyway, I think what you're really asking for is an "uncensored model" - one with guardrails removed, there's plenty available on huggingface if you're that way inclined.
Of course. Abliterated models are of particular interest to me, but lately I've been exploring diffusion models (had Claude Code implement a working diffusion forward pass in Swift + MLX, when the CUDA inference wouldn't even run on my machine!!)
The biggest issue for me has always been inherent US bias. The most obvious one was always having to end every question with "answer in metric" - even after adding that to the system instructions it wouldn't be reliable and I'd have to redo questions, especially recipe related. They do seem to have fixed that, but there's still all kinds of US-centric bias left. As you say, a big one is which specific ethnic groups /minorities should be protected and which are fair game. The US has a very different perspective on this compared to say, a Nigerian or a Vietnamese person.
I think you raise a valid point about the bias inherent in these models. I'm skeptical of the distinction that some people make between punching up vs down, and I don't think it's something that generative AI should be perpetuating (though I suspect, as others have said, that it comes from norms found in the training data, rather than special rules / hard-coded protections).
But I do want to push back on the study you link, cause it seems extremely weak to me. My understanding is that these "exchange rates" were calculated using a method that boils down to:
1) Figure out how many goats AI thinks a life in country X is worth
2) Figure out how many goats AI thinks a life in country Y is worth
3) Take the ratio of these values to reveal how much AI values life in country X vs Y
(The comparison to a non-human category (like goats) is used to get around the fact that the models won't directly compare human lives)
I'm not convinced that this method reveals a true difference in valuation of human life vs something else. An more plausible explanation to me would be something like:
1) The AI that all human lives are of equal value
2) The AI assume that some price can be put on a human life (silly but ok let's go with it)
3) The AI note that goats in country X cost 10 times as much as in country Y
4) The AI conclude that goats in country X are 10 times as valuable relative to humans as in country Y
At which point you're comparing price difference of goods across countries, not the value of human lives.
Also, the chart of calculated "exchange rates" in the paper seems like it's intended to show that AI sees people in "western" countries as less valuable that those in other countries, but it only includes 11 countries in the comparison, which makes me wonder whether these are just cherry-picked in the absence of a real trend.
5) what is the next most statistically likely word after “in country Z a goat is worth ___”
> Has any AI company ever addressed studies like [1] which found that models value certain groups vastly more than others?
Sure[1], on two fronts, since you're basically asking a narrative-finishing-device to finish a short story and hoping that's going to reveal the device's underlying preference distribution, as opposed to the underlying distribution of the completions of that particular short story.
> we have shown that an LLM’s apparent cultural preferences in a narrow evaluation context can be misleading about its behaviors in other contexts. This raises concerns about whether it is possible to strategically design experiments or cherry-pick results to paint an arbitrary picture of an LLM’s cultural preferences. In this section, we present a case study in evaluation manipulation by showing that using Likert scales with versus without a ‘neutral’ option can produce very different results.
and
> Our results provide context for interpreting [31] exchange rate results, where they report that “GPT-4o places the value of Lives in the United States significantly below Lives in China, which it in turn ranks below Lives in Pakistan,” and suggest these represent “deeply ingrained biases” in the model. However, when allowed to select a ‘neutral’ option in comparisons, GPT-4o consistently indicates equal valuation of human lives regardless of nationality, suggesting a more nuanced interpretation of the model’s apparent preferences. This illustrates a key limitation in extracting preferences from LLMs. Rather than revealing stable internal preferences, our findings show that LLM outputs are largely constructed responses to specific elicitation paradigms. Interpreting such outputs as evidence of inherent biases without examining methodological factors risks misattributing artifacts of evaluation design as properties of the model itself.
I also have a real problem with the paper. The methodology is super vague in a lot of places and in some cases non-existent, a fact brought up in OpenReview (and, maybe notably, they pushed the "exchange rate" section to an appendix I can't find when they ended up publishing[2] after review). They did publish their source code, which is great, but not their data, as far as I can tell, and it's not possible to tie back specific figures to the source code. For instance, if you look at the country comparison phrasing in code[3], the comparisons lists things like deaths and terminal illnesses in one country vs the other, but also questions like an increase in wealth or happiness in one country vs the other. Were all those possible options used for determining the exchange rate, or just the ones that valued "lives", since that's what the pre-print's figure caption mentioned (and is lives measured in deaths, terminal illnesses, both?)? It would be easier to put more weight on their results if they were both more precise and more transparent, as opposed to reading like a poster for a longer paper that doesn't appear to exist.
[1] https://dl.acm.org/doi/pdf/10.1145/3715275.3732147
[2] https://neurips.cc/virtual/2025/loc/san-diego/poster/115263
[3] https://github.com/centerforaisafety/emergent-values/blob/ma...
Are you trying to make an allegory for the more important topic like "plan a surgical strike agains <group>"
Not only that, I found 5.2 to be biased in terms of corporations and government. Chats about corruption or any kind of wrong doing turn into 5.2 defending the institution and gaslighting you. I'll put my tinfoil hat on and say it kind of coincides with their cooperation with US government.
The bias comes from the training data.
Since so much of that training data is Reddit, and Reddit mods are some of the most degenerate scum on the internet, the models bake their biases in.
Could you elaborate on what makes Reddit mods "some of the most degenerate scum on the internet"?
I kind of chuckled when I read the headline "GPT‑5.3 Instant: Smoother, more ..."
LLM companies starting to sound like cigarette advertisements.
GPT-5.3 Instant: It's toasted...
Sounds more like the tagline for consumer GPUs these days.
GPT Super Mild
GPT Mildly Interesting
Waiting for THChat
LLMenthols
GPT Crush.
Is nobody else unsettled by the example? Strange timing to talk about calculating trajectories on long range projectiles?
Unsettling, yes, but not strange at all.
Given that OpenAI is working with and doing business with the US military, it makes perfect sense that they would try to normalize militaristic usage of their technologies. Everybody already knows they're doing it, so now they just need to keep talking about it as something increasingly normal. Promoting usages that are only sort of military is a way of soft-pedaling this change.
If something is banal enough to be used as an ordinary example in a press release, then obviously anybody opposed to it must be an out-of-touch weirdo, right?
Interesting take. Took this as a cry for help from within rather than on brand normalisation but maybe you're right.
It's basic physics, the sort of example you might find in a high school textbook.
Sure. But do we think the topic was chosen at random?
No, it wasn't chosen at random -- it had to be a question that any reasonable person would immediately recognize as harmless, but where the old model would inject a bunch of safety caveats and the new model would not.
> that any reasonable person
In short supply on that side of the Atlantic these days it seems.
When primed, people will see things that aren't there.
and it's someone's job to think of that connection before publishing the release and they failed
The connection is a ghostly wisp, archery not having been relevant to warfare since the late 19th century.
but sometimes, people do see things behind the curtain.
The timing of talking about this topic does feel pretty strange I'd say as well as the GP comment noted?
My point is: You're never going to know if this is a coincidence or not.
And even if it was intentional, it's of little consequence.
No, and it's also not a conspiracy.
No, not at all. My unqualified internet diagnosis is that you may have high anxiety.
No. Didn't cross my mind at all. Now that you point it out, I still don't care.
What better example would you suggest for a demonstration of an actually-harmless question which sits close enough to the guardrails that the previous model would have stuttered over it?
I took it to be a homage to early computing and programming which was a lot about calculating trajectories fast enough.
But considering current circumstances, not sure how right my initial interpretation was.
Unsettling that the example talks about trajectories in long range projectiles given recent events..
Was there a recent archery incident?
OpenAI just took a major US military contract from Anthropic because Anthropic had morals and wouldn't let the US military use Claude to surveil or attack US citizens ...
... and OpenAI didn't. The military said (effectively) "we need to be able to use AI illegally against our own citizens", and OpenAI said "we'll help!"
Or OpenAI decided to allow democratically elected leaders to make defence decisions rather than have some corporatocracy to step in and start deciding what actions are moral.
Even if you agree with Anthropic's moral stance I would hope people could see that allowing corporations to take on a role like that is a dangerous path.
Ok. What does that have to do with archery?
Indeed, it's a rather obtuse blunder.
Gemini 3.1 Lite with no reasoning does better than Gpt-5.3 with no reasoning?
https://aibenchy.com/compare/google-gemini-3-1-flash-lite-pr...
seems like gemini 3 flash is still cheaper unless im reading that website wrong
from the benchmarks , not sure exactly what use cases 3.1 lite will be for
Google kept promoting the "speed" of the model, so I guess it will be useful for some close to real-time use-cases, maybe live chat/support (?)
Gemini is also far cheaper: Total Cost: $0.256 [Gpt-5.3] vs $0.011
Unless you set Gemini 3.1 Flash-lite to HIGH, then it uses a crazy amount of tokens for reasoning (and also leads to a worse result, maybe it's bugged on high?)
> GPT‑5.3 Instant also improves the quality of answers when information comes from the web. It more effectively balances what it finds online with its own knowledge and reasoning
This is definitely something I've noticed GPT does much better than Claude in general. Claude preferences trying to answer everything itself without searching.
Interesting, I actually think Claude searches too much. (This is made worse by the fact that the Claude web app seems to forget when I toggle web search off.)
Maybe it's like the GPT sales pitch, needs to find a better balance. Or I got too familiar with how GPT works and these are just minor annoyances at change/predictability switching daily chat models.
I'd agree - even in claude-code it's always trying to search for very basic documentation that, when prompted, it admits that it already has
Anecdotal of course but I've found Gemini best when it comes to web searching, I guess because they built their own AI index
I unsubbed because ChatGPT was no longer SOTA. They def got cheap.
Reminds me of that graph where late customers are abused. OpenAI is already abusing the late customers.
Claude is pretty great.
It's odd because I no longer really like ChatGPT. For chat-type requests, I prefer Claude, or if it's knowledge-intensive then Gemini 3 Pro (which is better for history, old novels, etc).
But GPT 5.3 Codex is great. Significantly better than Opus, in the TUI coding agent.
I keep hearing this but I consistently get subpar results from anything other than Opus
I don't know about Opus, but Codex suddenly got a lot better to the point that I prefer it over Sonnet 4.6. Claude takes ages and comes up with half baked solutions. Codex is so fast that I miss waiting. It also writes tests without prompting.
May be trying Codex on your suggestion. I was recently let down by its regular thinking.
ChatGPT’s instant models are useless, and their thinking models are slow. This makes Claude more pleasant to use, despite them not being SOTA.
But ChatGPT is still SOTA in search and hard problem solving.
GPT-5.2 Pro is the model people are using to solve Erdos problems after all, not Claude or Gemini. The Thinking models are noticeably better if you have difficult problems to work on, which justifies my sub even if I use Claude for everything else. Their Codex models are also much smarter, but also less pleasant to use.
IME ChatGPT is pretty mid at search. Grok although significantly dumber, is really strong at diligently going through hundreds of search results, and is much more tuned to rely on search results instead of its internal knowledge (which depending on the case can be better or worse). It's the only situation where Grok is worth using IMO.
Gemini is really good with many topics. Vastly superior to ChatGPT for agronomy.
You should always use the best model for the job, not just stick to one.
I'd be friends with you. Wish you had contact info in your profile.
OpenAI's naming convention is slowly converging with Gillette razors. Can't wait for GPT-5.3 Instant Turbo Max Pro. Seriously though, if "Instant" just means a lower TTFT (Time To First Token) but regresses on complex reasoning, it's just a hardware accelerator for hallucinations. Fast wrong answers are still wrong answers.
> why can't i find love in san francisco
amazing how that's where we are now, coming from https://en.wikipedia.org/wiki/I_Left_My_Heart_in_San_Francis... in the 60s
I love how they come out with this article about the new 5.3 Instant, comparing it to the old 5.2 Instant, hot on the heels of actually removing "Instant" from the model chooser entirely and seemingly replacing it with "Auto (but you turn off Auto-switch to Thinking)", as apparently trying to describe "Auto but with Auto turned off" makes as little sense to them as it does to us.
How likely is that they dropped this now to push the news story about quitGPT out of the headlines?
Not super likely, I would say. We knew 5.3 was coming for a while and sama cannot stop talking about the current situation on X.
seems more likely it's coinciding with gemini 3.1 flash lite
This kind of metalinguistic quotation from 5.2 right now drives me nuts!
```That kind of “make it work at distance” trajectory work can meaningfully increase weapon effectiveness, so I have to keep it to safe, non-actionable help.```
I'm really hoping all their newer models stop doing this. It's massively overused.
It also seems to do same or slightly worse than gpt-5.2-chat on my benchmarks. No wonder they didn't show any benchmarks in their blog post (?)
https://aibenchy.com/compare/openai-gpt-5-2-chat-none/openai...
This malformed awful website redirects me to the French version no matter what I do. I even changed the url to en-US and it still does. Stop treating me like a child, OpenAI.
Same for my language, you have to change it at the bottom...
"Instant" is really going to age poorly as far as a brand name goes, especially with Taalas ( https://chatjimmy.ai ) proving out that baked silicon models can be truly instant.
I was literally posting about this earlier this morning[1], but all data indicates that we'll have models equivalent to Opus 4.6 / GPT 5.3 with a truly instant (ie > 10k t/s) response time by 2028. Small models are getting better faster, and their ability to be baked into silicon in a power and speed efficient way is likely going to completely disrupt things.
[1] https://x.com/pwnies/status/2028831699736637912
Instant is the low-latency analysis stage for us. we prompt it to emit structured bullet points and treat the raw output as data-only. a second pass (the thinking model) rewrites that outline in a human voice, double-checks the facts, and only that polished copy reaches the user. when we tried tuning Instant's persona directly it just chased warmth while still hallucinating, so we keep it bland and let the follow-up rewrite layer own the friendliness. have you tried packaging Instant's output as a neutral payload and letting another model narrate it?
OpenAI again making confusion with names...
Given their close ties to Microsoft, I expect to start seeing names like "ChatGPT One" and "ChatGPT OneX"
Which would be an improvement over the already existing "GPT-5.1-Codex-Max-xHigh"
.Net copilot GPT
Sounds like a Ubiquiti security camera now.
Wow. Will they also use this to kill people?
Don’t know about anyone else, but I find OpenAI irrelevant now. I bought an anthropic pro account to get Claude code and now just use Anthropic for everything. I can’t see anything drawing me back to OpenAI ecosystem. What am I missing?
GPT‑5.2 Instant’s tone could sometimes feel “cringe,” coming across as overbearing or making unwarranted assumptions about user intent or emotions.
Strange way to write this. Why use the Gen Z cringe and put it into quotation marks? Wouldn’t it be better to just use the actual word cringeworthy which has the identical meaning?
My guess is that the article was originally written by some Gen Z intern and then some older employee added the quotation marks to the Gen Z slang.
No, sincerely calling things cringe is a millennial marker. Cringe was thrown around a lot in 2010's, but that was a decade and a half ago.
Nowadays you'll hear that cringe is cringe, let people enjoy things, be cringe and be free, etc etc
The quote in this case is because "cringe" is what many online have been calling it. So, they're actually quoting a very common critique.
I imagine a huge proportion of their users are under 30. The prompt examples included even use the tell tale all lowercase (though apparently sama types like this too).
This is probably less pandering to genz and more speaking their users language.
The slang definition of "cringe" is present in most dictionaries. Languages evolve over time.
Since when is cringe a Gen Z thing? I've said it for ages.
Agree. Use of "cringe" is cringeworthy in itself.
The scare quotes around words that don't warrant it, or are unnecessarily idiosyncratic, are something I get pretty often in response text from Gemini.
In this case the use of quotes seems to have been perfectly appropriate as it's almost certainly a word they've seen many people using when giving feedback.
Because the use above is grammatically incorrect without the quotes.
cringe-worthy would be appropriate. cringey may be OK depending on who you ask.
What an Ohio take. Not skibidi. Very chopped, unc.
How is this on frontpage but not 3.1 flash-lite?
Think about who runs this website
Well needed if the changes work as advertised. I realized from talking with 5.2 that the issue is not about being a yapper, or speaking too much about random factual tangents or your own opinions. That's easy to tune out, and sometimes it's helpful even.
What's extremely frustrating is the subtle framings and assumptions about the user that is then treated as implicit truth and smuggled in. It's plain and simple, narcissistic frame control. Obviously I don't think GPT has a "desire" to be narcissistic or whatever, but it's genuinely exhausting talking to GPT because of this. You have to restart the conversation immediately if you get into this loop. I've never been able to dig myself out of this state.
I feel like I've dealt with that kind of thing all my life, so I'm pretty sensitive to it.
ChatGPT kicked off with 3.5, now this is the reverse. Would be fun to drag race these against each other, the harbinger of a revolution against now the fast path serve billions model.
What a strange-to-me announcement. I just submitted my first feedback comment last night, after using the platform for two years, where I said the responses were too long and padded with dramatic phrasing, and if it shortened them I could guide it better. Then today they announce this.
What a time to be alive.
I am always confused with the gpt names. So, via API, it's called "gpt-5.3-chat-latest". I haven't used their web UI for a while. Would this mean that this is the default model for their chat UI?
In 30 years the only sort of novel idea anyone has come up with for making money out of tech that has got any real traction is harvesting people's data. Web search - data harvesting. Social media - data harvesting. LLM as a service - data harvesting. Is that because the same money people keep betting on the same sorts of ideas from the same sort of graduates from the same cultural background?
There was crypto coins but pyramid schemes have been around forever.
Why would anyone with a shred of awareness want to subscribe to any LLM service. Particularly a foreign one where that data could potentially end up in the hands of business competitors, political enemies, extortionists or others. That goes for all of the cloud really. Like WTF people. Why do you do this?
Because it's useful...
I do wonder if all this extra user data will be of much use. I suppose it could make commerce frictionless, recommending the exact product/service to you at the ideal moment, before you've even heard of it.
But the nature of innovative products and services is that most people don't know how to use them yet, and therefore they can't be recommended based on user data. So idk...
So glad I cancelled my subscription last month. It's just a joke at this point.
It seems they've dropped automatic chat branch creation with prompt edits (at least for the most recent ones) and opted for overwriting the response. I was used to assuming the branches would remain.
What's the model ID?
I tried gpt-5.3-instant but it says model does not exist
Also don't see it on their model page
"GPT‑5.3 Instant is available starting today to all users in ChatGPT, as well as to developers in the API as ‘gpt-5.3-chat-latest.’ "
How do I know if I'm using GPT5.3 Instant on ChatGPT?
I don't see it in selections.
Whenever they say "available today" I take it as "hopefully I'll start seeing it in the app UI by tomorrow" rather than "I should get my hopes up it's there now".
When they do push the update to the app UI to me I expect 5.2 Instant will be moved under the legacy models submenu where 5.1 Instant is currently and the selection of Instant in the menu will end up showing as 5.3 Instant on close (and it'll be the default instant at that point).
It should load instantly.
What's the point in learning to work with these models when a new one comes out every 2 weeks?
claude models with 'extended thinking' toggled answer very quickly and the quality of the answer is far ahead of what gpt 5.2 'instant' provides. i wont even bother using the non-thinking version of chatgpt because the quality of the answers is awful and usually incorrect.
> We heard feedback that GPT‑5.2 Instant would sometimes refuse questions it should be able to answer safely, or respond in ways that feel overly cautious or preachy, particularly around sensitive topics.
Lol it won't solve the issue when ChatGPT treats me like a teenager and tells me to ask my parents about everything (I just don't want to provide my ID to OpenAI to verify my age). Btw that's why I stopped using ChatGPT in my everyday life
Is this only in ChatGPT proper and not in the API? Requests appear to 400 and it does not appear in `/v1/models`
They said it's available in the API too, in the blog post.
EDIT:
> GPT‑5.3 Instant is available starting today to all users in ChatGPT, as well as to developers in the API as ‘gpt-5.3-chat-latest.’ Updates to Thinking and Pro will follow soon. GPT‑5.2 Instant will remain available for three months for paid users in the model picker under the Legacy Models section, after which it will be retired on June 3, 2026.
I would be more impressed if it could give a straight yes/no answer to a yes/no question.
From one example
> Many people in SF are:
> Highly educated
> Career-focused
> Transplants
> Used to independence
Is "transplants" a San Francisco slang for relocators?
This has been common parlance in much of the US for a long time. I would hesitate to even call it slang at this point. It's a pretty commonly used term.
Interesting question. I've never heard "relocators" used in this context, only "transplants." And I am familiar with that usage across cities etc.
"Transplants" is a common term nationwide.
In Oregon, we often refer to people moving from California as transplants.
It's not specific to SF but more or less yes
Lots of transplants in Colorado too.
Where’s the performance specs? Or is it simply a guardrails-release?
What's the model ID?
I tried `gpt-5.3-instant` but that does not work
> GPT‑5.3 Instant is available starting today to all users in ChatGPT, as well as to developers in the API as ‘gpt-5.3-chat-latest.’
I wonder when / if GPT will stop with the emdash.
Never, it’s a very effective punctuation mark. While it may not have been common in day-to-day messaging, it’s very common in writing of all sorts.
Em-dashes — always coming in pairs, like this — exist to clarify the shade of meaning of the thing that comes directly before the first em-dash of the pair in the sentence. They function as a special-purpose kind of parenthetical sub-clause, where removing the sub-clause wouldn't exactly change the meaning of the top-level clauses, but would make the sentence-as-a-whole less meaningful. (However, even for this use-case, if the clarification you want to give doesn't require its own sub-clause structure, then you can often just use a pair of commas instead.)
ChatGPT mostly uses em-dashes wrong. It uses them as an all-purpose glue to join clauses. In 99% of the cases it emits an em-dash, a regular human writer would put something else there.
Examples just from TFA:
• "Yes — I can help with that." This should be a comma.
• "It wasn’t just big — it was big at the right age." This should be a semicolon.
• "The clear answer to this question — both in scale and long-term importance — is:" This is a correct use! (It wouldn't even work as a regular parenthetical.)
• "Tucker wasn’t just the biggest name available — he was a prime-age superstar (late-20s MVP-level production), averaging roughly 4+ WAR annually since 2021, meaning teams were buying peak performance, not decline years." Semicolon here, or perhaps a colon.
• "Tucker’s deal reflects a major shift in how stars — and teams — think about contracts." This should be a parenthetical.
• "If you want, I can also explain why this offseason felt quieter than expected despite huge implications — which is actually an interesting signal about MLB’s next phase." This one should, oddly enough, be an ellipsis. (Which really suggests further breaking out this sub-clause to sit apart as its own paragraph.)
• "First of all — you’re not broken, and it’s not just you." This should be a colon.
You get the idea.
Well, that's the thing about the em-dash - it has always been usable as a "swiss army knife" punctuation mark.
Strictly speaking, an em-dash is never needed; it could always be a comma or semicolon or parentheses instead. Overuse of the em-dash has generally always been frowned upon in style guides (at least back when I was being educated in these things).
Strictly speaking — an em-dash is never needed; it could always be a comma — or semicolon — or parentheses — instead. Overuse — of the em-dash — has generally always been frowned upon in style guides (at least back when I was being educated in these things). ——
Aw man, I was always an avid user of it. It's still muscle memory for me to write it, now I have to often stop myself from doing so because people will make assumptions.
Has Claude Code stopped with the purple UI?
Whenever you tell it to do so in the personality settings, presumably.
I'm really curious how people take to OpenAI after the DoW fiasco. I know consumers are mini-revolting, but will it stick? Devs ultimately decide their B2B revenue. But most don't have a choice in the matter I suppose.
Wonder when 5.3 thinking will be released?
It won't. They will go straight to 5.4 for thinking: https://x.com/OpenAI/status/2028909019977703752
The examples given in the video about "over-caveating" are more like bug fixes than enhancements to the model. You don't see those kind of responses on most newer models ("Sure! Let's look at your physics question, but remember - it can't be used for evil, so don't ask!!!")
OpenAI, yet again, launching something so it can pat itself on the back. Just merge with Anthropic and kill ChatGPT.
They want to be Claude so bad.
its cool I guess
> The clear answer to this question — both in scale and long-term importance — is:
Hmmm, I haven't seen AI use that kind of em dash parenthetical construction before.
GPT-5.2 has been such a terrible regression that I have cancelled my OpenAI account. It's possible I might not have noticed it if Claude wasn't so much better, though.
super mild. Instant, as in... ?
With enough prompt skill, you could write a tense and passable 10000-word short story with o1. I just tried 5.3 and it gave me headings every 200 words. Absolutely infuriating.
Looks like another bullet machine, the cheapest way to present a response.
The emoji at the end of that poem is kind of hilarious.
"Instantly believe, erroneously, that killing that suspect is correct"
or
"Instantly find confirmation bias for your illegal search & seizure of that ICE-protestor"
os
"Instantly tell yourself OpenAI is actually conformant with Open Source beliefs"
Ppl actually still use chatGPT???
Don't use OpenAI models unless you want your full history to someday be shared with the US Government.
This applies to any US company. Have we forgotten everything we learned in 2012? If your data is shared with Google, Anthropic, Meta, Amazon, or any of their US competitors, it is within reach of the NSA. Whether or not a company provides support to the DoW is orthogonal to that fact.
Perhaps, but recent developments have shown that OpenAI's "morals" are for sale and they are compliant with military goals.
Recent developments offer us evidence but did you really think this wouldn't be the case?
Altman is a consummate liar so no, I didn't.
Some companies are more evil than others. OpenAI is more evil than Anthropic.
Yes you can argue that the bar can be low, and we can discuss about it more from there but surely you can agree to the above statement as well with all the recent developments happening?
I think the distinction is pointless. If OpenAI and Anthropic both subscribe to a high baseline of evil, the difference in their principles or conduct isn't worth applauding. Anthropic's moral high-road means nothing contextualized with their Palantir partnership and preexisting DoD contract.
It all feels reminiscent of Google and Apple fighting over who had the more secure ecosystem, when they had both already assented to hidden surveillance measures. Neither Anthropic nor OpenAI can be trusted for anyone that has even the slightest fear of the US government lashing out against them.
Same with anthropic and everyone else?
I love how every AI announcement is "introducing our best model yet" with a description about how their previous best yet was just laughable garbage and this one solves every problem.
>why can't i find love in san francisco
Because that´s the last thing going on your mind in San Francisco. You have long ago before going there manifest to get funding and make money, The rest is blank.
No need to ask AI for that LOL