2026-03-20 01:07 UTC
Replies (30)
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@agiletortoise@mastodon.social 2026-03-20 01:15
@EmilyEnough This is a legitimate rant. There’s a lot of quicksand out there right now.
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@mikemccaffrey@neurodifferent.me 2026-03-20 05:04
@EmilyEnough Wow, I have thought a lot about how coding LLMs are antithetical to my own OCD tendencies that want everything to be built and formatted in a very specific way (i.e. the right way), but had not considered how terrible the interface would be for folks who prefer not to have to process information conversationally. I would love to read an entire book or series of articles about how LLMs as an interface enforce neurotypical modes of communication on neurodiverse people.
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@dragonfi@social.jsteuernagel.de 2026-03-20 07:08
@EmilyEnough plagiarism laundering machine Never thought about it like this, but it is indeed similar to alaundering. You’re trying to give directions to a lossily compressed copy of the entire works of human writing. This line sums up the futility extremely well.
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@TimWardCam@c.im 2026-03-20 13:32
@EmilyEnough "I became a professional computer toucher because they do exactly what you tell them to. Not always what you wanted, but exactly what you asked for." In the 1970s, yes, when you wrote every single byte of code in the machine and could watch every bus cycle on a logic analyser. I reckon the rot set in long before LLMs - I reckon it started with on-chip cache, so you could no longer see how each instruction operated through each clock cycle, because some instructions no longer needed to touch the bus at all.
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@hosford42@techhub.social 2026-03-20 15:55
@EmilyEnough "squishy" computing
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@jzakotnik@mastodon.social 2026-03-20 21:25
@EmilyEnough very interesting observation, thanks a lot. I haven’t perceived it that way - I used to work a lot with probabilistic models, simulated annealing and genetic algorithms and in that case the computer works entirely deterministic but the result is always different. So I lost my expectation to a deterministic result long time ago ;-)
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@cybervegan@autistics.life 2026-03-21 00:34
@EmilyEnough Very astute and exactly my experience too - I went into computing for the same kinds of reasons and as you say LLMs break that. Thank you for expressing it so clearly.
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@jesterchen@social.tchncs.de 2026-03-21 12:32
@EmilyEnough 🏆🏆🏆
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@lettosprey@tech.lgbt 2026-03-21 12:35
@EmilyEnough There are so many "My biggest problem with LLM, even if it wasn't for ", there should be collection of them somewhere. But, yes, this bit bugs (pun intended) me and worries me. I'm more and more falling for BEAM family languages (Erlang, Elixir and Gleam) because of how they are designed to be as predictable as possible. It may not be too odd that I see a lot less AI push in that ecosystem compared to other ones.
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@metin@graphics.social 2026-03-21 13:12
@EmilyEnough Well said. This could never have been LLM-generated. 🙂👍
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@Chase@chaos.social 2026-03-21 17:25
@EmilyEnough this is a very justified rant But the thought of computers being too autistic so people had to turn them neurotypical by adding llms is just so funny
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@mathias@pawb.fun 2026-03-22 20:38
@EmilyEnough As your fellow ND professional computer toucher, I'm 100% with you - the unpredictability drives me batty. If I want a RNG I'll call one - what I intend to be deterministic should be, verifiably, repeatably. Lipsticked pig LLMs have snuck into what I have to do for work and beating one's head against that BS is a good way to eventually flame the fuck out of tech. Corporate controlled computing was a mistake.
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@art_codesmith@toot.cafe 2026-03-23 10:37
@EmilyEnough Yeah, very telling that the people most excited about LLM seem to be middle managers and C-levels: people adept at the "waffling about" conversations.
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@wallabra@bark.lgbt 2026-03-23 14:07
@EmilyEnough Another thing is that it seems to hijack the thinking autonomy of a lot of people. People defer to an LLM instead of putting the struggle and effort into researching and learning. I'm not anti-convenience, but when we don't need to think about things anymore, the brain's thinking facilities just atrophy.
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@trisweb@m.trisweb.com 2026-03-23 14:34
@EmilyEnough “ You’re trying to give directions to a lossily compressed copy of the entire works of human writing.” — Perfect.
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@qole@techhub.social 2026-03-23 15:21
@EmilyEnough @drahardja Exactly. I too need my automations to be deterministic. The element of surprise is fine for a novel, but not for a health care integration.
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@kawazoe@transfem.social 2026-03-23 16:37
@EmilyEnough@hachyderm.io To paraphrase some random professional in the industry no one cares about: "If English and other natural languages were specific enough to describe tasks to a computer, we wouldn't have invented programming languages, and bugs wouldn't happen." (Uncle Bob) Some people just refuse to understand that you can't solve all of your problems by speaking English.
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@ghosttie@mastodon.gamedev.place 2026-03-23 17:12
@EmilyEnough this makes me wonder if only NT people fall for LLMs, because ND people just take one look and go "this thing is a liar"
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@twosky2000@mastodon.social 2026-03-23 17:51
@EmilyEnough I think llm's have some buttons and knobs, but it is mostly self-reflection. I'm astonished how fast it picks a vibe(not necessarily what I want or need, but it is a possible reaction). I can see that 2 people get completely different results just because they frase their Idee different. It reminds me of Google search geniuses and when Google not just had the mainstream results. But I think it is a hype and used extractive. I don't see reasonable use from the commercial side.
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@Sonic2k@oldbytes.space 2026-03-23 19:34
@EmilyEnough How right and on point you are
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@doomsey@hachyderm.io 2026-03-23 23:04
@EmilyEnough I have a slightly different view. An LLM has some of the same language processing issues that I do, to the point that “I have LLM brain” is a useful cognitive model. It makes them surprisingly easy to “play” for me. The ability to take something I don’t understand and rewrite it into something else that aligns better with the corpus of normals-thought is definitely useful to me for understanding how normal communicate and bypassing my own limitations there.
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@SearingTruth@infosec.exchange 2026-03-24 02:46
@EmilyEnough "There is zero artificial intelligence today. There could have been, but 50 years ago the decision was made by most scientists and companies to go with machine learning, which was quick and easy, instead of the difficult task of actually reverse engineering and then replicating the human brain. So instead what we have today is machine learning combined with mass plagiarism which we call ‘generative AI’, essentially performing what is akin to a magic trick so that it appears, at times, to be intelligent. While the topic of machine learning is complex in detail, it is simple in concept, which is all we have room for here. Essentially machine learning is simply presenting many thousands or millions of samples to a computer until the associative components ‘learn’ what it is, for example pictures of a daisy from all angles and incarnations. Then companies scoured the internet in the greatest crime of mass plagiarism in history, and used the basic ability of machine learning to recognize nouns, verbs, etc. to chop up and recombine actual human writings and thoughts into ‘generative AI’. So by recognizing basic grammar and hopefully deducing the basic ideas of a query, and then recombining human writings which appear to match that query, we get a very faulty appearance of intelligence - generative AI. But the problem is, as I said in the beginning, there is no actual intelligence involved at all. These programs have no idea what a daisy, or love, or hate, or compassion, or a truck, or horse, or wagon, or anything else, actually is. They just have the ability to do a very faulty combinatorial trick to appear as if they do. And while the human brain consumes around 20 watts, these massive pattern matching computers consume ever increasing billions. However there is hope that actual general intelligence can be created because, thankfully, a handful of scientists rejected machine learning and instead have been working on recreating the connectome of the human brain for 50 years, and they are within a few decades of achieving that goal and truly replicating the human brain, creating true general intelligence. In the meantime it's important for our species to recognize the danger of relying on generative AI for anything, as it's akin to relying on a magician to conjure up a real, physical, living, bunny rabbit. So relying on it to drive cars, or control any critical systems, will always result in massive errors, often leading to real destruction and death." SearingTruth
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@kallisti@infosec.exchange 2026-03-24 11:53
@EmilyEnough "I found a computer. Wait a second, this is cool. It does what I want it to do. If it makes a mistake, it's because I screwed up." Horrible that this amazing core trait of computers is getting eroded.
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@operationpuppet@gamerstavern.online 2026-03-28 22:44
@EmilyEnough THIS! So much this. I've said before that the worst thing about how we use LLMs is they destroy the basic computing concept of Garbage In=Garbage Out. They turn it into Anything In=Maybe Garbage Out.
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@amanda@jawns.club 2026-04-02 10:41
@EmilyEnough "LLMs are the final act of the finance bros and capitalists wrestling modern technology away from the technically literate proletariat who built it." This was a 🤯 moment for me. Truly 🎯
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@Loosf@yiff.life 2026-04-03 03:40
@EmilyEnough yeah YEAH
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@netzhexe@chaos.social 2026-03-20 07:50
@EmilyEnough THIS oh my GODDESS 🤯 :autism: 🙏🏼
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@uriel@x.keinpfusch.net 2026-03-21 04:48
@EmilyEnough My biggest problem with the concept of LLMs, even if they weren’t a giant plagiarism laundering machine Also known as “training”. When people are trained in art, they don’t reinvent art from scratch. This is why you can’t really sue an LLM for plagiarism: you can’t even identify specific victims in the first place. and disaster for the environment, Nope. The whole IT sector uses about 3–5% of global electricity, so poor home insulation is a much bigger problem overall. is that they introduce so much unpredictability into computing. We call it a statistical method, or more precisely a stochastic system. Because, to a large extent, human behaviour itself can be modelled as a stochastic process. If I wanted to spend my time communicating in a superficial, neurotypical style my autistic ass certainly wouldn’t have gone into computering. The problems you face when communicating with LLMs are the same ones you face when communicating with people, because statistically speaking an LLM mimics how people communicate. This is why computer‑mediated communication was used before, and is still used, when computers were not trying to mimic humans. The core issue is that mimicking humans reproduces the same communication problems people already have with one another; and the “unpredictability” of the other party is nothing new in human interaction. LLMs mimic humans, so the problems you encounter with LLMs are the same problems you encounter with humans. The point is that you consider it normal when you face exactly the same issues with other people.
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@monkee@chaos.social 2026-03-21 10:33
@EmilyEnough "They turn a very autistic do-what-you-say, say-what-you-mean commmunication style with the machine into a neurotypical conversation talking around the issue, but never directly addressing the substance of problem." OMG - That's perfect. Maybe also explains why everyone loves them that much. 🤨
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@sotolf@polymaths.social 2026-03-23 11:10
@EmilyEnough I feel this so much! :)