Egregoros

We had this discussion before and you are making an argument that I
-already agree with
-is only tangentially related to what I am saying here

>People can just stay on GLM5.1
they can also hand-code. If SOTA devving costs money and you have to pay again if you want it under a second identity, that's a detriment.
If GLM 5.1 is not profitable for the model trainer, there will not be GLM N.1 in future. Open Weights models *could* lag behind which would make SOTA be OAI / DarioCorp -dependent. I believe quite a few people would be deterred and/or chance it under their real account and catch a C&D from Nintendo for it

idk I just don't get why you are making the argument that GLM 5.1 inference is profitable for providers at all here.
The issue is something else. If you are seriously implying that GLM 5.1 is good enough that people would use it over $100 2028 Claude, then I guess we disagree about that.
It's as if I said "training models could be an issue to do anonymously if Nvidia puts phone # verification in their GPUs and you have to buy a second one" and you replied with "a 2023 chromebook will be cheap forever"
It's besides the point.

@WandererUber @lain

probably coming off as a bit of the anti llm for the sake of anti llm side but-

idk how that happens tbh ik web ui models are kinda shit especially without harnesses (agentic stuff inmean) and really haven't ever vibe coded.

but I've used it as a reseaech assistant (with all the deep research bells and whistles google afforded me) and while certainly helpful (still doesn't replace normal searching for me, probably as I prefer searching first) l. Its obviously not a smart thing and makes stupid as hell errors or honestly fails to get the point (which is kinda obvious since they are fundamentally word generators)

One example is how It starts phrasing everything with basis on a fact which should have been treated irrelevant.

I tried to use it to write a slop paper and report (uni obligation) it was so bad that I basically didnit manually. Ig it is me actually having standards but it felr quite bad and focised on entirelynthe wrongnthings and had such terrible flow that babying itnto get something worthwhile was harder than actually writing it myself

code (surprisingly due to the NLP roots of the architecture) is probably a best case scenario in hindsight which is why they actually end up being surprisingly useful for thay

>Ig it is me actually having standards
yes I think so. I have largely the same experience as you do, although I did like research and building basic knowledge with Grok (not so much post-nerf)

LLM Arena found out people largely rate the incorrect emoji-laden,bullet-pointed slop torrent higher than the correct concise answer.
This is what I was talking about. A lot of decision makers simply do not have the intelligence to understand what is going on. It's like when people can't tell a pic is AI, but for text and they can't tell it's incorrect.

that's an LLM-type answer because you gave a sequence of words that are likely to appear in similar conversations but are not actually a response to what I actually mean.

It's similar in the sense that one's incompetence in a field makes the AI seem more correct than it is. If one looks at the answers after spending a few days actually learning, suddenly they don't seem so intelligent anymore (they still were helpful because they gave you keywords to research the actual rules. The intricacies of its' explanations are probably incorrect though)
You immediately notice this with topics you know about, thus it is similar to Gell-Mann amnesia.

@WandererUber @lain Nah I mean like I had it evaluate something on a whim as I wanted to see what the statistical text machine would say about my work which I painstakingly put into a meter (I'm fammiliar with how it should sound since as a sikh I've been raised on that kind of poetey)

Its through it thay Iearned that it actually had a conplex set of rules (I did verify it according to wikipedia) and it was mostly correct, some word choice changes tn suggested felt off but the actual analysis of the meter was quite correct