The bullshit is that anon wouldn't be fsked at all.
If anon actually used ChatGPT to generate some code, memorize it, understand it well enough to explain it to a professor, and get a 90%, congratulations, that's called "studying".
this post was submitted on 05 Feb 2025
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Professors hate this one weird trick called "studying"
Yeah, if you memorized the code and it's functionality well enough to explain it in a way that successfully bullshit someone who can sight-read it... You know how that code works. You might need a linter, but you know how that code works and can probably at least fumble your way through a shitty 0.5v of it
virtual machine
Yeah fake. No way you can get 90%+ using chatGPT without understanding code. LLMs barf out so much nonsense when it comes to code. You have to correct it frequently to make it spit out working code.
If we're talking about freshman CS 101, where every assignment is the same year-over-year and it's all machine graded, yes, 90% is definitely possible because an LLM can essentially act as a database of all problems and all solutions. A grad student TA can probably see through his "explanations", but they're probably tired from their endless stack of work, so why bother?
If we're talking about a 400 level CS class, this kid's screwed and even someone who's mastered the fundamentals will struggle through advanced algorithms and reconciling math ideas with hands-on-keyboard software.
Are you guys just generating insanely difficult code? I feel like 90% of all my code generation with o1 works first time? And if it doesn't, I just let GPT know and it fixes it right then and there?
the problem is more complex than initially thought, for a few reasons.
One, the user is not very good at prompting, and will often fight with the prompt to get what they want.
Two, often times the user has a very specific vision in mind, which the AI obviously doesn't know, so the user ends up fighting that.
Three, the AI is not omnisicient, and just fucks shit up, makes goofy mistakes sometimes. Version assumptions, code compat errors, just weird implementations of shit, the kind of stuff you would expect AI to do that's going to make it harder to manage code after the fact.
unless you're using AI strictly to write isolated scripts in one particular language, ai is going to fight you at least some of the time.
I asked an LLM to generate tests for a 10 line function with two arguments, no if branches, and only one library function call. It's just a for loop and some math. Somehow it invented arguments, and the ones that actually ran didn't even pass. It made like 5 test functions, spat out paragraphs explaining nonsense, and it still didn't work.
This was one of the smaller deepseek models, so perhaps a fancier model would do better.
I'm still messing with it, so maybe I'll find some tasks it's good at.
from what i understand the "preview" models are quite handicapped, usually the benchmark is the full fat model for that reason. the recent openAI one (they have stupid names idk what is what anymore) had a similar problem.
If it's not a preview model, it's possible a bigger model would help, but usually prompt engineering is going to be more useful. AI is really quick to get confused sometimes.
It might be, idk, my coworker set it up. It's definitely a distilled model though. I did hope it would do a better job on such a small input though.
My first attempt at coding with chatGPT was asking about saving information to a file with python. I wanted to know what libraries were available and the syntax to use them.
It gave me a three page write up about how to write a library myself, in python. Only it had an error on damn near every line, so I still had to go Google the actual libraries and their syntax and slosh through documentation
I just generated an entire angular component (table with filters, data services, using in house software patterns and components, based off of existing work) using copilot for work yesterday. It didn't work at first, but I'm a good enough software engineer that I iterated on the issues, discarding bad edits and referencing specific examples from the extant codebase and got copilot to fix it. 3-4 days of work (if you were already familiar with the existing way of doing things) done in about 3-4 hours. But if you didn't know what was going on and how to fix it you'd end up with an unmaintainable non functional mess, full of bugs we have specific fixes in place to avoid but copilot doesn't care about because it doesn't have an idea of how software actually works, just what it should look like. So for anything novel or complex you have to feed it an example, then verify it didn't skip steps or forget to include something it didn't understand/predict, or make up a library/function call. So you have to know enough about the software you're making to point that stuff out, because just feeding whatever error pops out of your compiler may get you to working code, but it won't ensure quality code, maintainability, or intelligibility.
Can not confirm. LLMs generate garbage for me, i never use it.
A lot of people assume their not knowing how to prompt is a failure of the AI. Or they tried it years ago, and assume it’s still as bad as it was.
Garbage for me too except for basic beginners questions
deepseek rnows solid, autoapprove works sometimes lol
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isn't it kinda dumb to have coding exams that aren't open book? if you don't understand the material, on a well-designed test you'll run out of time even with access to the entire internet
when in the hell would you ever be coding IRL without access to language documentation and the internet? isn't the point of a class to prepare you for actual coding you'll be doing in the future?
disclaimer did not major in CS. but did have a lot of open book tests—failed when I should have failed because I didn't study enough, and passed when I should have passed because the familiarity with the material is what allows you to find your references fast enough to complete the test
Most of my CS exams in more advanced classes were take home. Well before the internet though. They were some of the best finals I ever took.
Assignments involved actual coding but exams were generally pen and paper when I got my degree. If a question involved coding, they were just looking for a general understanding and didn't nitpick syntax. The "language" used was more of a c++-like pseudocode than any real specific language.
ChatGPT could probably do well on such exams because making up functions is fair game, as long as it doesn't trivialize the question and demonstrates an overall understanding.
Yes It is laziness on the teacher's part
I mean, I don't know how to code but I imagine it's the same as with other subjects. like not being able to use a calculator during some math tests. The point of the examination is for you to demonstrate you know and understand the concepts. It's not for you to be tested in the same way you would be in the real world.
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pay for school
do anything to avoid actually learning
Why tho?
Job
Losing the job after a month of demonstrating you don't know what you claimed to is not a great return on that investment...
It is, because you now have the title on your resume and can just lie about getting fired. You just need one company to not call a previous employer or do a half hearted background check. Someone will eventually fail and hire you by accident, so this strategy can be repeated ad infinitum.
No actual professional company or job of value is not going to check your curriculum or your work history.... So like sure you may get that job at quality inn as a night manager making $12 an hour because they didn't fucking bother to check your resume...
But you're not getting some CS job making $120,000 a year because they didn't check your previous employer. Lol
Sorry, you're not making it past the interview stage in CS with that level of knowledge. Even on the off chance that name on the resume helps, you're still getting fired again. You're never building up enough to actually last long enough searching to get to the next grift.
I am sorry that you believe that all corporations have these magical systems in place to infallibly hire skilled candidates. Unfortunately, the idealism of academia does not always transfer to the reality of industry.
...you stopped reading halfway through my comment didn't you?
Idiot.
This person is LARPing as a CS major on 4chan
It's not possible to write functional code without understanding it, even with ChatGPT's help.
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