Wakko

You’re trying to analogize your way into a subject you clearly haven’t studied.

There’s pre-existing research here. Godel’s Incompleteness Theorem holds, plus others.

There’s already a known upper bound here that you’re clearly unaware of.

There’s as yet been zero LLM-based architectures that have created new information. Everything they produce is somewhere within the training data. LLMs are a very specialized data compression algorithm, in a fashion.

The stall is around whether Recursive Self-Improvement is achievable. Recent papers out of China are trying to chart a course to it. But, until someone succeeds, The current pace of improvement is already slowing signs of slowing. It’s not about where the finish line is placed, it’s about how fast they get there.

Thank you for admitting that you’re a disgusting pedo.

The actual reason is partially answered in other comments. Most people are focusing on who did it and they’re not asking the most obvious question - how bad does a game have to be to get noticed by Visa and MasterCard?

The games in question aren’t merely “NSFW”. Visa doesn’t care about vanilla porn. The delisted games dealt in subject matter that is difficult to justify.

MasterCard doesn’t need to help anybody buy “games” about incest, rape, or sexual assault of minors.

Do you have any benchmarks or data to back this “reckoning”

I work with LLMs daily. I read papers as they hit arxiv. Also daily. You clearly don’t.

I’m not interested in convincing anyone, which is why I’m speaking non-technically.

The benchmarks being cited aren’t as interesting as you appear to believe they are. You’ve not fully grasped the fact that solving pre-made problems where the solutions are known or knowable isn’t anywhere close to the same thing as asking truly novel research questions independent of a human prompt. For OpenAI to also be embroiled in allegations of plagiarism only serves to underscore the gap between the two concepts.

I’m aware of what the pace is. You might want to check up on the current controversy surrounding OpenAI’s math “achievements”.

By my reckoning, the difference between Mythos and Opus is smaller than the difference between Opus and Sonnet. Same with the difference between GPT 5.5 to 5.6 is smaller than the difference between GPT 4 to GPT 5.

The size of improvements over time is diminishing. We’re not in “big bang” territory anymore and we’re about two years into the “incremental refinement” period. We’re about to enter the next AI Winter unless somebody comes up with a new architectural component as revolutionary as transformers have been for ML models.

The core problem is that LLMs do not create. Full stop. All creativity is borne by the human inputs. Until that changes - until the model gains the capability to truly create new information, we’ve hit the limits in raw capability.

Recursive self-improving AI isn’t happening like they expected. AGI is nowhere in sight.

The pace of advancement is slowing down and they need a cover story for why they’re not living up to their own hype.

I don’t think it’s professional use either. I’m suspecting structural racism - the people drawn to companion AIs are likely highly educated but unable to use their education fully in their current role. Just my gut speculation. But I’m curious if there’s enough data to show that kind of correlation.

I think you’re on to something. I think the next logical question to ask is - “What proportion of post-graduate non-Whites land in what kinds of roles?” Is there a reason this demographic is using AI companions more that correlates to the kinds of jobs they’re doing?

It’s much, much worse than that.

To have functional social beings requires social supports that haven’t existed in the USA in decades. It’d be more accurate to say that the vast majority of non-melanated Americans are dysfunctional. Cracker Culture is built on being exploitative, isolating, and abusive toward their fellow human.

That’s an awful lot of typing instead of just saying “I’m a lying liar who doesn’t know what he’s talking about. That’s why I offer no actual data - because the actual numbers destroy my entire argument.”

That’s an “I have no idea what I’m talking about” if I ever heard one.

“Citation needed” IS polite. You claim it’s not polluting, so clearly you know the CO2 emissions numbers from SpaceX’s datacenters that are being run off direct-connect to natural gas generators. So, how about it? How “not polluting” are they?

It’s pretty insignificant

Citation needed. You’re just straight-up lying or clueless as to what’s actually going on.

The ecological damage is not made up.

Bias plus volume. Memes used to be hand-crafted. That takes time.

Now, there’s a dozen websites to auto-generate them by the thousands. Plus AI.

No man in the wrong can stand against a fellow thats right and keeps on a-comin’.
— Texas Ranger Bill McDonald

Impossible to name it that, 'cuz straight he ain’t.

Slavery was abolished in the 19th century,

Cute that you think that. Try reading the 14th Amendment to the US Constitution sometime. You’ll find that the USA did not abolish slavery. We just institutionalized it into the penal system. Look up some of the jobs performed by the inmates of the Louisiana state correctional system and then tell me slavery has been abolished.

ROFL.

Thanks for admitting you have no idea what you’re talking about. Again.

Thanks for admitting you haven’t got a legitimate argument.

I’m only using an over the top example to hopefully make my point more clear.

If that’s the only example available that illustrates the point, then you have not spent enough time thinking through your idea.

Do better.