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this post was submitted on 10 May 2026
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Big brain tech dude got yet another clueless take over at HackerNews etc? Here's the place to vent. Orange site, VC foolishness, all welcome.
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In other Scott of Siskind news, he just posted an entirely unnecessary amount of words to aggressively push back against the adage that "all exponentials sooner or later turn into sigmoids" as if it was by itself a load bearing claim of the side arguing against the direct imminence of the machine god.
It's just a bunch of arguing by analogy ( "helping you build intuition" ) and you-can't-really-knows while implying AI 2027 was very science much rigorous, but it also feels kind of desperate, like why are you bothering with this overperformative setting-the-record-straight thing, have you been feeling inadequate as an AI-curious stats fondler of note lately?
The idea of “the exponential curve goes up forever” has always been silly and an idea rooted in capitalism for me (“no bro you don’t get it we’re gonna get infinite money forever”). Limited resources exist, and people are already very fed up with the ludicrous amounts of water and electricity data centres take up. Making bigger models that need to run for longer is also probably going to take an exponential amount of resources (and also make people hate you more).
taking a quick look at it... it's actually short by Scott's standards, but still overly long, given that the only point he makes is claiming Lindy's Law is applicable to predicting AI progress in absence of other information. Edit: glancing at it again... its not that short, I kinda skimmed until I got to Scott's actual point my first time glancing at it. You can't blame me for not reading it.
Yeah, he straw-mans AI critics/skeptics as trying to make an argument from ignorance, then tries to argue against that strawman using Lindy's Law (which assumes ignorance and a pareto distribution). He completely ignores that AI critics are actually making detailed arguments about LLM companies consuming all the good and novel training data, hitting the limits on what compute costs they can afford, running into problems of the long lead time for building datacenters, etc. Which is pretty ironic given his AI 2027 makes a nominal claim to accounting for all that stuff (in actuality it basically all rests on METR's task horizons, and distorts even that already questionable dataset).
As if LLMs being the last step before AGI/ASI/The Metal Messiah is a foregone conclusion. As far as I can tell even the AI 2027 thing only argues that once the bots completely nail down programming (any minute now) then the foom happens and the models will magic themselves into true AI, because apparently being good at solving coding problems is a sufficient proxy for superintelligence, hence the METR infatuation.
I mean, to be fair that's not unique to them - software engineers have been worse than physicists in assuming that all of reality and human experience is downstream from their chosen field.