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 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.

> 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

```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.

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

Reminds me of that graph where late customers are abused. OpenAI is already abusing the late customers.

Claude is pretty great.

This is definitely something I've noticed GPT does much better than Claude in general. Claude preferences trying to answer everything itself without searching.

LLM companies starting to sound like cigarette advertisements.

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

https://aibenchy.com/compare/google-gemini-3-1-flash-lite-pr...

https://aibenchy.com/compare/openai-gpt-5-2-chat-none/openai...

Nowadays you'll hear that cringe is cringe, let people enjoy things, be cringe and be free, etc etc

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.)

This is probably less pandering to genz and more speaking their users language.

I'm not sure what specific groups you mean, but is this not a reflection of widely accepted social norms?

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?

But GPT 5.3 Codex is great. Significantly better than Opus, in the TUI coding agent.

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.

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.