I have similar feelings about getting AI-generated "communications" from people (email, whatsapp, whatever).
The value of having a human send me a message is that there is also a signal in there - the human at least understands what whey they sent me. They may misunderstand the concept, they may be mostly inarticulate, they may in fact be altogether wrong, but at least I know what they think, and I know when to ask them for clarification.
When a message is sent from an AI, I have no idea if the human doing the copy-and-paste even understands what they are sending me. The signal that they understand the contents of the message, that signal is missing.
It's no different to asking someone a question, and them pasting parts of a manpage as their entire response: I can't tell if they understood what they sent me.
> Adobe is primarily a professional program and even at higher fees it's a miniscule amount compared to the rate of the professional using it.
I feel that that is an optimistic take - for now the professional using it can command high salaries. It will not remain that way. The endgame for AI in an economy is to drive the value of labour and knowledge to zero.
The irony here is that the article, written solely by Claude, is also a volley at authors.
The substack popup to join and follow the author made me giggle: Why would I join that substack to read that "author" when I already have multiple free AIs that can give me the same take, but without all the waffle?
In the past, I might have signed up to read the author (I have signed up to a few authors before), but if all the author has to offer is basically already available to me for free, why would I join up?
Okay, then who gets to decide that? If platforms cannot advertise as child-friendly, they are dead in the water. Now who do you propose gets to decide which platforms are child-friendly and which are not?
They want their specific content shown to as many people as possible. They don't want to have their content limited to over-18 or NSFW websites.
The thing is, I think that the content-hosting platforms' broad "NSFW content is not welcome" rules is great. While I may not object to seeing a male nipple pop up in my feed, I won't object if male nipples never pop up either.
It is working the way I want it to, but it sounds to me that the complaint is that I should at least see this type of content occasionally even if I don't seek it out, which seems completely bonkers to me.
> Unique stuff worth playing is extremely rare, if you're not 7 years old and you played more than a couple of games in your life of course.
This is a hot take indeed. Unless you use the word unique to pick only a single game from each genre, even a single genre has more games than I can hope to finish in a lifetime.
I mean, I still play Dune 2, warcraft II, sc:broodwars and C&C, in addition to Starcraft II.
I have used tcc as a scripting language in the past. I expect that if your shell script catches the compilation, that sort of approach will satisfy your requirements, even if tcc itself does not.
TCC is partly what motivated me to try. But I want to get closer to lower the Kolmogorov Complexity. I'm happy to sacrifice C compatibility. In fact I'm happy to sacrifice much of the power of C. And I'd be happier with code that was somewhat slower.
And the original TCC code is not easy to understand. It is a lot cleverer than I can cope with!
FWIF, I find I don't have much trouble. I think it's related to how I'm a software developer who also found as an adult learner German easier than French. From the abstract:
inanimate subjects with animate verbs
process waits for input, a method threw an exception, server accepts the request,
German has longer syntactic dependencies than English because readers (and listeners) often must *under* several intervening clauses of the sentences read before they can *stand* the split-apart word or what the author was saying.
I'm a fluent reader. Heck reading has been a primary hobby since I was a little kid. But also I'm from a Caribbean country where English is the official, but not the native language. And I've been studying/exposed to Japanese for quite a few years. Maybe that diversity/stretch makes a difference.
That makes sense, because fluent readers are using more System 1 processing to read - they’re not thinking about it for the most part, they’re just pattern matching instinctively based on text they’ve been exposed to previously (“trained on”). AI writing breaks those patterns so compromises their fluency.
Whereas a second language reader or poor reader is exerting more conscious attention to understand the text, so it doesn’t matter as much if it doesn’t conform to standard patterns.
Except LLMs are "System I" writers. You'll be more satisfied with what they've written if you haven't really understood it and just let it wash over you.
It only falls apart when you actually try to figure out what's being said.
I find the most passionate advocates of LLMs right now to be the people who are
1) also the most passionate advocates of not reading or reviewing their output in any detail. They seem to be actively annoyed by the idea that people think they should. And
2) people who have a strange theory of mind about LLMs that excuses the low quality of their output. I've heard many times people advancing the theory that LLMs are coding in a particular way because the way that LLMs code is the way that they (the LLMs themselves!) are best able to work with the code.
In fact, I get the impression from these people that they think that their touching the code would actually ruin this delicate balance that the LLM is trying to make. This is actually crazy thinking. On a pretty obvious level, they already think that any LLM they encounter is a super-intelligent God acting in mysterious ways, and that they only way you can ruin its plan is by questioning it.
> I find the most passionate advocates of LLMs right now ...
Whether or not that's true, you have to keep in mind that it's not true of everyone.
I'm a passionate advocate of LLMs. I implemented my first neural net, for image recognition, in the late 1980s (based on Bart Kosko's work, I'm not claiming to have invented anything.) Now, I use LLMs daily for coding and other tasks. I don't usually "vibe code" unless it's a simple enough project that the code quality really doesn't matter - a simple example would be data integration, where as long as the data in the target system matches the data in the source system, I don't care much about how the sausage in between is made.
But otherwise, I'm approving or denying every tool call, like a caveman, and when they mess up, I explain to them why. I interrupt them and redirect them when they need it. I change code myself and let them know. With all that, they're still incredibly useful - more useful than most "junior programmers", realistically. No human software developer can hope to match LLMs on many significant dimensions of development. But that doesn't mean experienced and competent humans have no role, at least currently.
The disconnect here is that your characterization of "the low quality of their output" is too simplistic. The quality of their natural language writing is different, for the kinds of reasons stated in the OP. Some of the accusations of "lower quality" really boil down to "too compressed for humans to easily understand", again as the OP points out. And the quality of their code has a lot to do with how they're prompted.
One of the biggest barriers to good LLM output - both writing and code generation - is that they're trained on data generated by humans who fit George Carlin's observation that half of them are stupider than average. When it comes to coding, on average they don't have enough education not to think that imperative code with minimally-restricted mutation all over the place is a good idea. They think dynamic typing, so that code can't be statically verified, is a good idea. They reflect our own collective limitations. If you recognize that and redirect them to sources of good practices, they can be much better.
In short, they're much more of a mirror than most people realize or admit.
With all this noise, it should not be forgotten that we appear to have figured out roughly how a significant component of intelligence works, and have real life, useful proofs of concept. All the technical criticism, to me, is just coming from people who don't seem to understand how intellectual advancement works. The political criticism is another matter.
I have similar feelings about getting AI-generated "communications" from people (email, whatsapp, whatever).
The value of having a human send me a message is that there is also a signal in there - the human at least understands what whey they sent me. They may misunderstand the concept, they may be mostly inarticulate, they may in fact be altogether wrong, but at least I know what they think, and I know when to ask them for clarification.
When a message is sent from an AI, I have no idea if the human doing the copy-and-paste even understands what they are sending me. The signal that they understand the contents of the message, that signal is missing.
It's no different to asking someone a question, and them pasting parts of a manpage as their entire response: I can't tell if they understood what they sent me.
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