It is: /u/AutoModerator can be used for that.
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¹: Often correlating with a marked decline in the quality of their technical writing. I don't know which direction the arrow of causality goes, but I have observed LLM use inducing madness under reasonably-controlled circumstances – different phenomenon, similar principle. I suspect the use of AI codegen systems is causing the reduction in discernment ability, rather than a sudden drop in discernment ability causing increased use of AI codegen systems.
> “In January 1956, we assembled my wife and three children together with some graduate students. To each member of the group, we gave one of the cards, so that each one became, in effect, a component of the computer program”
> In the summer of 1956, John McCarthy, Marvin Minsky, Claude Shannon and Nathan Rochester organized a conference on the subject of what they called "artificial intelligence" (a term coined by McCarthy for the occasion). Newell and Simon proudly presented the group with the Logic Theorist. It was met with a lukewarm reception.
> “They didn't want to hear from us, and we sure didn't want to hear from them: we had something to show them! [...] In a way it was ironic because we already had done the first example of what they were after; and second, they didn't pay much attention to it.”
> Logic Theorist soon proved 38 of the first 52 theorems in chapter 2 of the Principia Mathematica. The proof of theorem 2.85 was actually more elegant than the proof produced laboriously by hand by Russell and Whitehead. Simon was able to show the new proof to Russell himself who "responded with delight".
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Tools that could cheat:
> Around 1983, Eurisko, an early attempt at evolving general heuristics, unexpectedly assigned the highest possible fitness level to a parasitic mutated heuristic, H59, whose only activity was to artificially maximize its own fitness level by taking unearned partial credit for the accomplishments of other heuristics.
Mel finally gave in and wrote the code,
but he got the test backwards,
and, when the sense switch was turned on,
the program would cheat, winning every time.
Tools that could communicate:
> A significant advance in modems was the Hayes Smartmodem, introduced in 1981. The Smartmodem was an otherwise standard 103A 300 bit/s direct-connect modem, but it introduced a command language which allowed the computer to make control requests, such as commands to dial or answer calls, over the same RS-232 interface used for the data connection. In data mode, all data forwarded from the computer was modulated and sent over the connected telephone line as it was with any other modem. In command mode, data forwarded from the computer would be interpreted as commands. In this way, the modem could be instructed by the computer to perform various operations, such as hang up the phone or dial a number. The modem would normally start up in command mode. The command set used by this device became a de facto standard, the Hayes command set, which was integrated into devices from many other manufacturers.
> The experimental challenge consists in showing that a distributed set of agents can develop from scratch a vocabulary to identify each other through names and spatial descriptions. […] When there is already a sufficiently shared language, the first part (initiation) may be absent. In that case only linguistic means are used to identify the object. […] When more agents use the same word for the same meaning, communicative success increases and therefore the word-meaning association becomes more stable. It has been shown in an earlier paper that coherence emerges (see Figure 1) [8]. In the following subsections the mechanism is defined more formally and a concrete example of language formation is given. […] A mechanism has been presented in which a group of distributed agents develops a vocabulary to name themselves and to identify each other using spatial relations. It was shown that a vocabulary indeed emerges in a group of agents through a series of conversations. The mechanism also copes with the entry of new agents or new meanings.
> With its origin in the Georgetown machine translation effort, SYSTRAN was one of the few machine translation systems to survive the major decrease of funding after the ALPAC Report of the mid-1960s. The company was established to work on translation of Russian to English text for the United States Air Force during the Cold War. The quality of the translations, although only approximate, was usually adequate for understanding content. By 1998, "for as little as $29.95" one could "buy a program for translating in one direction between English and a major European language of your choice" to run on a PC.
and, of course, every interactive program ever made.
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Comment adapted from: https://en.wikipedia.org/w/index.php?title=Logic_Theorist&ol... https://en.wikipedia.org/w/index.php?title=Reward_hacking&ol... https://users.cs.utah.edu/~elb/folklore/mel.html https://en.wikipedia.org/w/index.php?title=Modem&oldid=13732... https://en.wikipedia.org/w/index.php?title=Hayes_Microcomput... https://doi.org/10.1162/artl.1995.2.3.319 https://en.wikipedia.org/w/index.php?title=SYSTRAN&oldid=136... https://en.wikipedia.org/w/index.php?title=Machine_translati...
> The word “briskly” here means “quickly, so as to get the Baudelaire children to leave the house.”
> “Wipi!” Sunny shrieked, which meant “I’d much prefer gardening to sitting around watching my siblings struggle through law books.”
But they're not going to backdoor an Apple ][e, or a random 80m¢ microcontroller, for basically any value of "they"; so you can just use one of those instead, and save yourself the hassle.
Just write a new OS. It's a weekend project to get enough groundwork that you can bootstrap a clean system from clean source code.
> And wouldn't there be difficulty comparing binaries built from significantly different environments?
Not really. Starting from stage 0, compile the compiler under test (stage 1), then use the compiled compiler to compile the compiler (stage 2), and compare the stage 2 artefacts. Provided that your comparison program is known-good, and the stage 2 build is deterministic (not the case for some real-world programs, but true for things like tcc), this lets you verify that the two compilation procedures work identically.
The authors I'm aware of making >$20k don't do any significant gating. That practice is only really common with people republishing through Amazon (which probably demands it).
Then maybe we should do away with "business". Small operations do not tend to operate that way, and broadly everyone prefers their output (if not price) in the domains in which they operate – with a few notable exceptions. In theory, software should allow small operations to each serve millions of people, such that we (e.g.) only need a few thousand search engine providers to meet the needs of the entire world's population. Not everything has to be enterprise-scale, and indeed many things should not be.
If "business" means treating people badly, then we don't need it.
It does give us a new heuristic, though: people who are willing to completely cut generative AI out of their lives (cold-turkey, if you ever started using it) are a much smaller group of, predominantly thoughtful, people. You do have to give up Claude to be part of this group, but from what you say, that's no great loss, and no longer being deafened is worth it.
This has considerable advantages over conventional elitism, because the barrier-to-entry is negative in almost all cases.
The one exception I've found is assistive tech, where the state-of-the-art is so poor that vibecoded slop is genuinely an improvement over the state-of-the-art, and in many cases the tooling simply isn't available to make your own assistive tech (unless you want to bootstrap an entire networked computing environment, which isn't very helpful when you want to do your online banking and do not, in fact, work at your bank).
But there are not many principled exceptions where you could seriously argue that the trade-off is worth it. Take mathematics, for example, which we often see touted as a "good use-case" of generative AI. The primary advantage of generative AI in mathematics is being able to search though a vast corpus of ivory towers and inconsistent terminology (without proper attribution) to locate and connect ideas that can help solve problems. The deficiency this is addressing is elitism, inadequate communication, and inadequate indexing within academic mathematics. This problem is entirely created by the academic mathematicians, and has been known for nearly a century (per https://en.wikipedia.org/w/index.php?title=Nicolas_Bourbaki&...):
> Bourbaki was founded in response to the effects of the First World War which caused the death of a generation of French mathematicians; as a result, young university instructors were forced to use dated texts. While teaching at the University of Strasbourg, Henri Cartan complained to his colleague André Weil of the inadequacy of available course material, which prompted Weil to propose a meeting with others in Paris to collectively write a modern analysis textbook.
To my knowledge, this is the only organised project to clean up and improve mathematical communication. Everything else (Metamath, Mizar, AFP, Lean) is yet another ivory tower. The Wikipedia article on this topic (https://en.wikipedia.org/wiki/Mathematical_knowledge_managem...) risks deletion as non-notable, that's how little anyone's actually trying. They made their own bed, and generative AI will only provide a brief respite from having to lie in it. (I was surprised how many other "compelling" use-cases evaporated when I applied this razor to them: the sibling comment https://news.ycombinator.com/item?id=49392265 points out one such.)
Vibe-coding assistive tech which doesn't yet exist, as a temporary scaffold to improve the quality-of-life of yourself and others in a social world dominated by non-essential access barriers is, to my knowledge, the only exception to this principle that can be justified. If you treat people who make other excuses, or who don't even bother with excuses, as not worth listening to, you lose little – and doubly-so, if you make your stance clear, so that others know the "cost" of gaining your attention.
I was abstracting Richard Stallman's argument to its (il)logical structure: P and ¬P are whether the license restriction is enforceable, etcetera. "Erosion" was talking about people who, seeing free software as a good idea, begin to adhere to Stallmanite orthodoxy (which is, largely, philosophically-unsound): that was not aimed at you, but at Richard Stallman himself (the Ur-Stallmanite, we could say). I saw this as generalising your criticism. I didn't notice you were making a broader point about the law, so this was somewhat of a supercalifragilisticexpialidocious non-sequitur; thanks for clarifying your point.
If the intermediate tokens represent reasoning or thought, you would expect "aha" to occur after the thoughts that led to the realisation, including the thoughts encoding the explanation: they don't have any other state. There is no reason to draw the conclusion you've drawn. Furthermore, what LLMs are doing isn't thought.
Quite a lot of Richard Stallman's arguments are pure rhetoric, actually. And, I mean, I guess it worked, in that the GPL and FSF ended up being quite influential; but the trouble with building a philosophy on rhetoric is that people start to believe that rhetoric – including you –, and it erodes and replaces the foundations of their beliefs, so it'll all come crashing down sooner or later.
I don't really think we need to engage with the rhetoric on an intellectual level, since it's obviously wrong: far better to read philosophers whose reasoning is sound, or to come up with your own ideas.
Being able to automatically generate large quantities of code that is worse than a good human programmer can produce is not helpful in this world you're envisioning.
(from https://en.wikipedia.org/w/index.php?title=Sumo&oldid=136533...), so I'm not sure this is a counterexample.