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That's intriguing, thanks for showing your chain of thought

@Enema_Cowboy weird question, I haven't thought of them while I was reading the article as well but as far as I remember strange attractors was on rnns and rnns only. I might be mistaken though.

Also thanks for the comment, hope you liked reading the post

@mike @virtuous_sloth that's so intriguing. I have to check that out.

Thanks

@virtuous_sloth @mike well that sounds intriguing

@mike always, I am open for feedback that's how I learn at least

Also similar thing happened on reddit; someone called my blog post ai generated, I told them nope its all written by me and they apologized. That's not normal At least not according to my experience

@virtuous_sloth @mike On a personal belief I don't think so but this must be tried or at least done an experiment.

I believe someone out there are currently working on it

@mike Yeah I see your pov. I just made some remarks and some of them were satirical which you can obviously see through my writing style. I do agree with your stance on rigidity.

Also thanks for the comment I hope you have enjoyed scrolling through those gifs

@drmambobob hi
Before I reply completely you must know that I'm not an expert on this topic but just a curious guy.

You made a great remark, it is essentially the same problem scaled up. The obvi part is that you cannot get something from nothing. The main reason I assume the paper authors are talking about it differently with llms is that while a regression model just gets stale, olm goes probabilistic hell. It basically actively deletes its output diversity until it produces a single acceptable response.

I hope this answers your question.

@dpiponi @Quantensalat Thanks, will check.

@onekind I would be interested in this as well.

@troed Just to make you angry.

@kieraaa I don't know, someone should simulate that.

@kaidu Sure, the title is satirical, but I don't think that you have done a great job while reading it. Since both the article and my post specifically talk about one of the training methods...

@laalsaas yep

@dpiponi @Quantensalat Yep, i also did imply this on my post's last remarks. https://smsk.dev/2026/04/26/ai-cannot-self-improve-and-math-behind-proves-it/#:~:text=The%20smarter%20path%20–%20and%20what%20labs%20are%20quietly%20shifting%20toward%20–%20is%C2%A0better%20data%2C%20better%20curation%2C%20better%20grounding%20in%20reality.%20Which%2C%20ironically%2C%20means%20humans%20stay%20in%20the%20loop%20longer%20than%20the%20singularitarians%20wanted.

@Quantensalat @dpiponi yes. I did used the same tactic while naming my post as satire. its annoying....

@anne_twain YEP, most of the people whom commented assumes they develop every iteration with fresh data; that comes from internet ...

@noplasticshower Thanks, ill look into it

@ghostinthenet Yep

@Quantensalat @dpiponi That's what I hate about these companies.