politics complaint aside, your observation about people using this to complain about a neopronoun seems apt. none of the content of complaints about drag’s use of neopronouns actually seem relevant to drag’s use of neopronouns. someone trolling with neopronouns is trivially handled by just accepting the neopronouns…

music has things that can be described mathematically in ways that are largely historical, but not axiomatic in a math sense. but if learning music helps you learn math and/or visa versa, power to you.

it might be a difference of language but it’s important to recognize that courts are part of your system of governance regardless of the words you use to describe it, and are subject to most of the same incentives and corrupting influences, and some thatare unique to courts.

courts are part of the government…

jailbreaks actually are relevant with the use of llm for anything with i/o, such as “automated administrative assistants”. hide jailbreaks in a webpage and you have a lot of vectors for malware or social engineering, broadly hacking. as well as things like extracting controlled information.

novelty is the spice of life

what money saved on wages?? it’s competing with a dollar a day laborers. $10 per 1 million tokens, for the “bad” (they all suck) models (something that cant even do this job!). if you can pretend the hallucinations dont matter, you are getting a phone call for (4 letters per token, 6 minute avg support call, 135 wpm talking rate let’s say 120 to be nice -> 720 tokens per call) = $0.0072 per call. the average call center employee handles around 40 calls a day, so hey, the bad cant-actually-do-it chatgpt 4 is 70 cents per day cheaper than your typical call center indian!

Except. that is the massively subsidized money hemorrhaging rate. We know that oai should be charging probably an oom or two more. and the newer models are vastly more expensive, o1 takes around 100x the compute, and still couldnt be a call center employee. so that price is actually at least $30 per day. Cheaper than a us employee, but still cant actually do the job anyway.

except current robot systems and people are likely cheaper, especially when you consider companies are liable for what llm say. which leaves, essentially, scams and other slop, as the last remaining use cases. multi trillion dollar business without a use case.

the tech is barely good enough that it is vaguely maybe feasibly cheaper to waste someone’s time using a robot rather than a human- oh wait we do that already with other tech.

“in 20 years imagine how good it’ll be!” alas, no, it scales logarithmically at best and all discussion is poisoned by “what it might be!” in the future, rather than what it is.

regardless of where you want to define the starting point of the boom, it’s been clear for months up to years depending on who you ask that they are plateuing. and harshly. stop listening to hypesters and people with a financial interest in llm being magic.

Oh! Hahahaha. No.

the vc techfeudalist wet dreams of llm replacing humans are dead, they just want to milk the illusion as long as they can.

gets where first?

all this started in 2023? alas no time marches on, llm have been a thing for decades and the main boom happened more in 2021. progress is not fast, no, these are companies throwing as much compute at their problems as they can. deepseek’s caused a 2t drop by being marginal progress in a field (llms specifically) out of ideas.

Well both of those things have been true months if not years, so if those are the conditions for a pop then they are met.

an arms race for what? more efficient slop? most of their value comes from the expected exclusivity - that say openai is the only one who can run something like o1. deepseek has made that collapse. i doubt they will stop doing stuff, but i dont think you understand the nature of the situation here.

also lol, “performs well in synthetic tests it was optimized to score well in” yes that literally describes every llm. Make no mistake: none of this has a real use case. not deepseek’s model, not openai’s, not apples, etc. this is all nonsense, literally. the stock market lost 2 trillion dollars overnight because something that doesnt have a use case was one upped by something else that also doesnt have a use case. it’s very funny.

tech has been subsidizing ai costs by magnitudes for years trying to make fetch happen, slop is slop. it’s overvalued like crazy and the first hint of market competition has drained trillions from the stocks because it’s an overvalued bubble. if china can do that by releasing competition then ok. maybe we should all be putting these trillions in things actually useful to humans.

reads like every corporate admemo. why sacrifice your voice? i preferred the original.

without linking to examples or analyses this is unhelpful.

another comment pointed out elsewhere that the titles are rarely made by the writer, so im inclined to believe that the atlantic recieved this piece and wanted to slant it for those who just read the headline, yeah.

credit to michael rose, they want all diabetes medications to be cheaper or free.