this post was submitted on 14 Nov 2023

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computer science is dead now that LLMs can do what people can’t: write trivial crossword apps (archive.ph)

submitted 1 year ago by self@awful.systems to c/techtakes@awful.systems

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this article is incredibly long and rambly, but please enjoy as this asshole struggles to select random items from an array in presumably Javascript for what sounds like a basic crossword app:

At one point, we wanted a command that would print a hundred random lines from a dictionary file. I thought about the problem for a few minutes, and, when thinking failed, tried Googling. I made some false starts using what I could gather, and while I did my thing—programming—Ben told GPT-4 what he wanted and got code that ran perfectly.

Fine: commands like those are notoriously fussy, and everybody looks them up anyway.

ah, the NP-complete problem of just fucking pulling the file into memory (there’s no way this clown was burning a rainforest asking ChatGPT for a memory-optimized way to do this), selecting a random item between 0 and the areay’s length minus 1, and maybe storing that index in a second array if you want to guarantee uniqueness. there’s definitely not literally thousands of libraries for this if you seriously can’t figure it out yourself, hackerman

I returned to the crossword project. Our puzzle generator printed its output in an ugly text format, with lines like "s""c""a""r""*""k""u""n""i""s""*" "a""r""e""a". I wanted to turn output like that into a pretty Web page that allowed me to explore the words in the grid, showing scoring information at a glance. But I knew the task would be tricky: each letter had to be tagged with the words it belonged to, both the across and the down. This was a detailed problem, one that could easily consume the better part of an evening.

fuck it’s convenient that every example this chucklefuck gives of ChatGPT helping is for incredibly well-treaded toy and example code. wonder why that is? (check out the author’s other articles for a hint)

I thought that my brother was a hacker. Like many programmers, I dreamed of breaking into and controlling remote systems. The point wasn’t to cause mayhem—it was to find hidden places and learn hidden things. “My crime is that of curiosity,” goes “The Hacker’s Manifesto,” written in 1986 by Loyd Blankenship. My favorite scene from the 1995 movie “Hackers” is

most of this article is this type of fluffy cringe, almost like it’s written by a shitty advertiser trying and failing to pass themselves off as a relatable techy

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[–] Soyweiser@awful.systems 17 points 1 year ago* (last edited 1 year ago) (2 children)

But I knew the task would be tricky

Is it just me or isn't this not even that tricky (just a bit of work, so I agree with him on the free evening thing, esp when you are a bit rusty)? Anyway, note how he does give a timeframe for doing this himself (an evening) but doesn't mention how long he worked on the chatgpt stuff, nor does he mention if he succeeded at his project at all

E: anyway what he needs is an editor.

[–] self@awful.systems 13 points 1 year ago

this is the exact kind of clown who’d go “uh actually I have an editor” and fire up ChatGPT again

[+] datarama@awful.systems 14 points 1 year ago (2 children)

[deleted]

[–] thesmokingman@programming.dev 11 points 1 year ago (1 children)

I’ve been conducting DevOps and SRE interviews for years now. There’s a huge difference between someone that can copypasta SO code and someone that understands the SO code. LLMs are just another extension of that. GitHub Copilot is great for quickly throwing together an entire Terraform file. Understanding how to construct the project, how to tie it all together, how to test it, and the right things to feed into Copilot requires actually having some skill with the work.

I might hire this person at a very junior level if they exhibited a desire to actually understand what’s going on with the code. Here an LLM can serve as a “mentor” by spitting out code very quickly. Assuming you take the time to understand that code, it can help. If you just commit, push, deploy, you can’t figure out the deeper problems that span files and projects.

To me the only jobs that might not be safe are for executives a good programmer probably doesn’t want to work for.

[–] self@awful.systems 9 points 1 year ago (2 children)

I help maintain an open-source OS for industrial embedded applications.

fuck yes. there’s something weirdly exciting about work like that — not only is it a unique set of constraints, but it’s very likely that an uncountable number of people (myself possibly included) have interacted with your code without ever knowing they did

But the explicit purpose of generative AI is the devaluation of intellectual and creative labour, and right now, a lot of money is being spent on an attempt to make people like me redundant. Perhaps this is just my anxiety speaking, but it makes me terribly uneasy.

absolitely same. I keep seeing other programmers uncritically fall for poorly written puff pieces like this and essentially do everything they can to replace themselves with an LLM, and the pit drops out of my stomach every time. I’ve never before seen someone misunderstand their own career and supposed expertise so thoroughly that they don’t understand that the only future in that direction is one where they’re doing a much more painful version of the same job (programming against cookie cutter LLM code) for much, much less pay. it’s the kind of goal that seems like it could only have been dreamed up by someone who’s never personally survived poverty, not to mention the damage LLM training is doing to the concept of releasing open source code or even just programming for yourself, since there’s nothing you can do to stop some asshole company from pilfering your code.

[–] fnix@awful.systems 6 points 1 year ago (3 children)

the only future in that direction is one where they’re doing a much more painful version of the same job (programming against cookie cutter LLM code) for much, much less pay.

To the extent that LLMs actually make programming more “productive”, isn’t the situation analogous to the way the power loom was bad for skilled handweavers whilst making textiles more affordable for everyone else?

I should perhaps say that I’m saying this as someone who is just starting out as a web developer (really chose the right time for that, hah). I try to avoid LLMs and even strictly unnecessary libraries for now because I like learning about how everything works under the hood and want to get an intimate grasp of what I’m doing, but I can also see that ultimately that’s not what people pay you for that and that once you’ve built up sufficient skill to quickly parse LLM output, the demands of the market may make using them unavoidable.

To be honest, I feel as conflicted & anxious about it all as others already mentioned. Maybe I am just too green to fully understand the value that I would eventually bring, but can I really, in good conscience, say that a customer should pay me more when someone else can provide a similar product that’s “good enough” at a much lower price?

Sorry for being another bummer. :(

[–] self@awful.systems 9 points 1 year ago (2 children)

I’m not sure the power loom analogy works, because power looms are (to my non-weaver knowledge) fit for purpose. if power looms’ output required significant rework by a skilled weaver (being paid significantly less for essentially the same amount of work done more tediously, per my point above), relied on stolen patterns from all of the world’s handweavers, and they were crushingly inefficient to run per woven piece, I seriously doubt history would remember them as a successful invention

unfortunately, we’re living in uniquely awful times, and decades of tech’s strange, manipulated culture have turned many programmers into nihilistic utopians with no ability to think things through on a systemic level. generative AI as a whole is nothing but an underhanded wage reduction tactic, but (by design) our industry doesn’t have the solidarity to fight it in any way that works (see the Writers’ Guild’s successful strike)

[–] swlabr@awful.systems 8 points 1 year ago

Totally agree.

IMO a better analogy would be clothing sweatshops rather than the power loom. Same utilitarian effect of textile affordability increases. Same ethical fuckery with exploitation of labour.

[–] locallynonlinear@awful.systems 6 points 1 year ago (1 children)

Commoditization is a real market force, and yes, it will come for this industry as it has for others.

Personally, I think we need to be much, much more creative and open to understanding ourselves and the potential of the future. It's hard to know specifics, but there is broad domains.

Lately, I've been hacking at home with more hardware, and creating interesting low scale, low energy input systems that help me... garden. Analyzing soil samples, planning plots and low energy irrigation, etc, etc. It's been fun because the work is less about programming in depth and more broad systems thinking. I even have ideas for making a small scale company off this. At that point, purely the programming won't be the bottleneck.

If it helps, as an engineer, take a step back and think about nature and how systems and niches within systems evolve. Nature isn't actually in the business of replacing due to redundancy, it's in the business of compounding dependency via waste resources, and the shifting roles as a result of that. We need to be ready to creatively take our experience, perspective, and energy gradient to new places. It's no different for any other part of nature.

[–] locallynonlinear@awful.systems 4 points 1 year ago (1 children)

since there’s nothing you can do to stop some asshole company from pilfering your code.

Currently. Though I think that there is a future where adversarial machine learning might be able to greatly increase the cost of training on pilfered data by encoding human generated inputs in a way that runs counter to training algorithms.

https://glaze.cs.uchicago.edu/

[–] corbin@awful.systems 6 points 1 year ago (2 children)

Even if there were Glaze/Nightshade for computer programs, it could be reverse-engineered just like any other code obfuscation. This is the difference between code and most other outputs of labor: code is syntactic and formal, allowing for decidable objective analyses.

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[–] bitofhope@awful.systems 14 points 1 year ago (2 children)

shuf -n 100 /usr/share/dict/words

Master hacker

I would have expected JS standard library to contain something along the lines of random.sample but apparently not. A similar thing exists in something called underscore.js and I gotta say it's incredibly in-character for JavaScript to outsource incredibly common utility functions to a module called "_".

Language bashing aside, there's something to enjoy about these credulous articles proclaiming AI superiority. It's not the writing itself, but the self-esteem boost regarding my own skills. I have little trouble doing these junior dev whiteboard interview exercises without LLM help, guess that's pretty impressive after all!

[–] zogwarg@awful.systems 5 points 1 year ago* (last edited 1 year ago)

Absolutely this, shuf would easily come up in a normal google search (even in googles deteriorated relevancy).

For fun, "two" lines of bash + jq can easily achieve the result even without shuf (yes I know this is pointlessly stupid)

cat /usr/share/dict/words | jq -R > words.json
cat /dev/urandom | od -A n -D | jq -r -n '
  import "words" as $w;
  ($w | length) as $l |
  label $out | foreach ( inputs * $l / 4294967295 | floor ) as $r (
    {i:0,a:[]} ;
    .i = (if .a[$r] then .i  else .i + 1 end) | .a[$r] = true ;
    if .i > 100 then break $out else $w[$r] end
  )
'

Incidentally this is code that ChatGPT would be utterly incapable of producing, even as toy example but niche use of jq.

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[–] locallynonlinear@awful.systems 12 points 1 year ago (2 children)

ah, the NP-complete problem of just fucking pulling the file into memory (there’s no way this clown was burning a rainforest asking ChatGPT for a memory-optimized way to do this),

It's worse than that, because there's been incredibly simple, efficient ways to k-sample a stream with all sorts of guarantees about its distribution with no buffering required for centuries. And it took me all of 1 minute to use a traditional search engine to find all kinds of articles detailing this.

If you can't bother learning a thing, it isn't surprising when you end up worshiping the magic of the thing.

[–] self@awful.systems 6 points 1 year ago

reading back, I wonder if they were looking for a bash command or something that’d do it? which both isn’t programming, and makes their inability to find an answer in seconds much worse

[–] naevaTheRat@lemmy.dbzer0.com 4 points 1 year ago* (last edited 1 year ago)

So I haven't programmed in a long time but like isn't a simple approach for this sort of thing (if want low numbers like 100) just something like:

from distribution I like(0, len(file)) get 100 samples read line at sample forall samples

or if file big

sort samples, stream file, if line = current sample add line to array, remove sample from other array.

Like that is literally off the top of my head. I'm sure there are real approachs but if googling is too hard isn't shit like that obvious?

edit: wait you'd have to dedupe this. also the real approach is called: (unspellable French word for pit of holdy water etc) sampling

[–] swlabr@awful.systems 10 points 1 year ago* (last edited 1 year ago) (1 children)

Ah yes, the future of coding. Instead of directly searching for stack overflow answers, we raise the sea level every time we need to balance a tree.

AI chuds got the wrong message about the guy that tried to use tensorflow to write fizzbuzz.

Edit: I looked it up. Tensorflow fizzbuzz guy is also an AI chud it seems

[–] swlabr@awful.systems 5 points 1 year ago

Bonus: this is how I visualise LLMs generating results: https://youtu.be/Jn4k2TPIJf0

[–] sc_griffith@awful.systems 10 points 1 year ago (1 children)

Our puzzle generator printed its output in an ugly text format... I wanted to turn output like that into a pretty Web page that allowed me to explore the words in the grid, showing scoring information at a glance. But Iknew the task would be tricky: each letter had to be tagged with the words it belonged to, both the across and the down. This was a detailed problem

I'm so confused. how could the generator have output something that amounts to a crossword, but not in such a way that this task is trivial? does he mean that his puzzle generator produces an unsorted list of words? what the fuck is he talking about

[–] self@awful.systems 5 points 1 year ago (1 children)

you know, you’re fucking right. I was imagining taking a dictionary and generating every valid crossword for an N x N grid from it, but like you said he claims to already have a puzzle generator. how in fuck is that puzzle generator’s output just a list of words (or a list of whatever the fuck "s""c""a""r""*""k""u""n""i""s""*" "a""r""e""a" is supposed to mean, cause it’s not valid syntax for a list of single characters with words delimited from * in most languages, and also why is that your output format for a crossword?) if it’s making valid crossword puzzles?

fractally wrong is my favorite kind of wrong, and so many of these AI weirdos go fractal

[–] 200fifty@awful.systems 5 points 1 year ago (2 children)

I... think (hope??) the "*" is representing filled in squares in the crossword and that he has a grid of characters. But in that case the problem is super easy, you just need to print out HTML table tags between each character and color the table cell black when the character is "*". It takes like 10 minutes to solve without chatgpt already. :/

[–] sc_griffith@awful.systems 6 points 1 year ago

I rejected that as too easy to be what he meant, but as soon as I read your words I knew in my heart you were right. associating these letters to words is essentially fizzbuzz difficulty, he can't do it, and he's writing in the new yorker that he can't do it. I'm feeling genuine secondhand embarrassment for him

[–] self@awful.systems 4 points 1 year ago

fuck me, so the only reason scoring was “tricky” to them was because this asshole chose unstructured text as their interchange format instead of, say, JSON? and even given that baffling design flaw in their puzzle generator (which is starting to feel like code GPT found and regurgitated that they didn’t know how to modify to make it suitable for their purposes) I can think of like 5 different ways to include scoring data and none of them are hard to implement

[–] ericbomb@lemmy.world 8 points 1 year ago

I felt like there was a 100% chance that there was a python library that you could just import and use in two lines.

Turns out it's like 4 lines depending on which of the multiple ones you use.

I do love internet people who make cool things because they are smarter than me and share.

[–] m@blat.at 8 points 1 year ago

@self This was the point where I started wanting to punch things:

“At one company where I worked, someone got in trouble for using HipChat, a predecessor to Slack, to ask one of my colleagues a question. “Never HipChat an engineer directly,” he was told. We were too important for that.”

Bless his heart. That, dearie, isn’t “engineers are so special”, it’s managers wanting to preserve old-fashioned lines of communication and hierarchy because they fear becoming irrelevant. Gatekeeping access to other people’s knowledge to make yourself important goes back millennia.

[–] iamnearlysmart@awful.systems 6 points 1 year ago (1 children)

Really love the bit about how gpt is able to tackle the simple stuff so easily. If an original insight, I take my hat off to you. I came to the edge of it, but never quite really saw it as you point out.

[–] self@awful.systems 7 points 1 year ago

if you never have, find YouTube videos of folks trying to use an LLM to generate code for a mildly obscure language. one I watched that gave the game away was where someone tried to get ChatGPT to write a game in Commodore BASIC, which they then pasted directly into a Commodore 64 emulator to run. not only did the resulting “game” perform like a nonsensical mashup of the simple example code from two old programming books, there was a gigantic edit in the middle of the video where they had to stop and make a significant number of fixes to the LLM’s output, where it either fictionalized something like a line number or constant, or where the mashup of the two examples just didn’t function. after all that programming on their part for an incredibly substandard result, their conclusion was still (of course) that the LLM did an amazing job

[–] sailor_sega_saturn@awful.systems 5 points 1 year ago* (last edited 1 year ago)

If anyone else can't load archive.ph due to having normie Google DNS like me, here is the URL: https://www.newyorker.com/magazine/2023/11/20/a-coder-considers-the-waning-days-of-the-craft