the beautiful code
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I asked ChatGPT with help about bare metal 32-bit ARM (For the Pi Zero W) C/ASM, emulated in QEMU for testing, and after the third iteration of "use printf for output" -> "there's no printf with bare metal as target" -> "use solution X" -> "doesn't work" -> "ude printf for output" ... I had enough.
wrote on last edited by [email protected]QEMU makes it pretty painless to hook up gdb just FYI; you should look into that. I think you can also have it provide a memory mapped UART for I/O which you can use with newlib to get printf debugging
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QEMU makes it pretty painless to hook up gdb just FYI; you should look into that. I think you can also have it provide a memory mapped UART for I/O which you can use with newlib to get printf debugging
The latter is what I tried, and also kinda wanted ChatGPT to do, which it refused
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All programs can be written with on less line of code.
All programs have at least one bug.By the logical consequences of these axioms every program can be reduced to one line of code - that doesn't work.
One day AI will get there.
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Sorry, the language my original post might seem confrontational, but that is not my intension; I m trying to find value in LLM, since people are excited for it.
I am not a professional programmer nor do I program any industrial sized project at the moment. I am a computer scientist, and my current research project do not involve much programming. But I do teach programming to undergrad and master students, so I want to understand what is a good usecase for this technology, and when can I expect it to be helpful.
Indeed, I am frustrated by this technology, and that might shifted my language further than I intended to. When everyone is promoting this as a magically helpful tool for CS and math, yet I fail to see any good applications for either in my work, despite going back to it every couple month or so.
I did try @eslint/migrate-config, unfortunately it added a good amount of bloat and ends up not working.
So I just gived up and read the doc.
Gotcha. No worries. I figured you were coming in good faith but wasn't certain. Who is pushing llm's for programming that hard? In my bubble, which often includes Lemmy, most people HATE them for all uses. I get that tech bros and linked in crazies probably push this tech for coding a lot, but outside of that, most devs I know IRL either are lukewarm or dislike llm's for dev work.
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Honest question: I haven't used AI much. Are there any AIs or IDEs that can reliably rename a variable across all instances in a medium sized Python project? I don't mean easy stuff that an editor can do (e.g. rename QQQ in all instances and get lucky that there are no conflicts). I mean be able to differentiate between local and/or library variables so it doesn't change them, only the correct versions.
Itellij is actually pretty good at this. Besides that, cursor or windsurf should be able to. I was using cursor for a while and when I needed to reactor something, it was pretty good at picking that up. It kept crashing on me though, so I am now trying windsurf and some other options. I am missing the auto complete features in cursor though as I would use this all the time to fill out boilerplate stuff as I write.
The one key difference in cursor and windsurf when compared to other products is that it will look at the entire context again for any changes or at least a little bit of it. You make a change, it looks if it needs to make changes elsewhere.
I still don't trust AI to do much though, but it's an excellent helper
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Honest question: I haven't used AI much. Are there any AIs or IDEs that can reliably rename a variable across all instances in a medium sized Python project? I don't mean easy stuff that an editor can do (e.g. rename QQQ in all instances and get lucky that there are no conflicts). I mean be able to differentiate between local and/or library variables so it doesn't change them, only the correct versions.
Okay, I realize I'm that person, but for those interested:
tree,catandsedget the job done nicely.And... it's my nap time, now. Please keep the Internet working, while I'm napping. I have grown fond of parts of it. Goodnight.
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Honest question: I haven't used AI much. Are there any AIs or IDEs that can reliably rename a variable across all instances in a medium sized Python project? I don't mean easy stuff that an editor can do (e.g. rename QQQ in all instances and get lucky that there are no conflicts). I mean be able to differentiate between local and/or library variables so it doesn't change them, only the correct versions.
For the most part "Rename symbol" in VSCode will work well. But it's limited by scope.
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For the most part "Rename symbol" in VSCode will work well. But it's limited by scope.
Yeah, I'm looking for something that would understand the operation (? insert correct term here) of the language well enough to rename intelligently.
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I’ve heard that a Claude 4 model generating code for an infinite amount of time will eventually simulate a monkey typing out Shakespeare
It will have consumed the GigaWattHours capacity of a few suns and all the moisture in our solar system, but by Jeeves, we'll get there!
...but it won't be that impressive once we remember concepts like "monkey, typing, Shakespeare" were already embedded in the training data.
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Practically all LLMs aren't good for any logic. Try to play ASCII tic tac toe against it. All GPT models lost against my four year old niece and I wouldn't trust her writing production code
Once a single model (doesn't have to be a LLM) can beat Stockfish in chess, AlphaGo in Go, my niece in tic tac toe and can one-shot (on the surface, scratch-pad allowed) a Rust program that compiles and works, than we can start thinking about replacing engineers.
Just take a look at the dotnet runtime source code where Microsoft employees currently try to work with copilot, which writes PRs with errors like forgetting to add files to projects. Write code that doesn't compile, fix symptoms instead of underlying problems, etc. (just take a look yourself).
I don't say that AI (especially AGI) can't replace humans. It definitely can and will, it's just a matter of time, but state of the Art LLMs are basically just extremely good "search engines" or interactive versions of "stack overflow" but not good enough to do real "thinking tasks".
extremely good "search engines" or interactive versions of "stack overflow"
Which is such a decent use of them! I've used it on my own hardware a few times just to say "Hey give me a comparison of these things", or "How would I write a function that does this?" Or "Please explain this more simply...more simply....more simply..."
I see it as a search engine that connects nodes of concepts together, basically.
And it's great for that. And it's impressive!
But all the hype monkeys out there are trying to pedestal it like some kind of techno-super-intelligence, completely ignoring what it is good for in favor of "It'll replace all human coders" fever dreams.
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someone drank the koolaid.
LLMs will never code for two reasons.
one, because they only regurgitate facsimiles of code. this is because the models are trained to ingest content and provide an interpretation of the collection of their content.
software development is more than that and requires strategic thought and conceptualization, both of which are decades away from AI at best.
two, because the prevalence of LLM generated code is destroying the training data used to build models. think of it like making a copy of a copy of a copy, et cetera.
the more popular it becomes the worse the training data becomes. the worse the training data becomes the weaker the model. the weaker the model, the less likely it will see any real use.
so yeah. we're about 100 years from the whole "it can't draw its hands" stage because it doesn't even know what hands are.
wrote on last edited by [email protected]This is just your ego talking. You can't stand the idea that a computer could be better than you at something you devoted your life to. You're not special. Coding is not special. It happened to artists, chess players, etc. It'll happen to us too.
I'll listen to experts who study the topic over an internet rando. AI model capabilities as yet show no signs of slowing their exponential growth.
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It will have consumed the GigaWattHours capacity of a few suns and all the moisture in our solar system, but by Jeeves, we'll get there!
...but it won't be that impressive once we remember concepts like "monkey, typing, Shakespeare" were already embedded in the training data.
If we just asked Jeeves in the first place we wouldn't be in this mess.
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Ai code is specifically annoying because it looks like it would work, but its just plausible bullshit.
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Honest question: I haven't used AI much. Are there any AIs or IDEs that can reliably rename a variable across all instances in a medium sized Python project? I don't mean easy stuff that an editor can do (e.g. rename QQQ in all instances and get lucky that there are no conflicts). I mean be able to differentiate between local and/or library variables so it doesn't change them, only the correct versions.
Find and Replace?
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Its like having a junior developer with a world of confidence just change shit and spend hours breaking things and trying to fix them, while we pay big tech for the privilege of watching the chaos.
I asked chat gpt to give me a simple squid proxy config today that blocks everything except https. It confidently gave me one but of course it didnt work. It let through http and despite many attempts to get a working config that did that, it just failed.
So yeah in the end i have to learn squid syntax anyway, which i guess is fine, but I spent hours trying to get a working config because we pay for chat gpt to do exactly that....
It confidently gave me one
IMO, that's one of the biggest "sins" of the current LLMs, they're trained to generate words that make them sound confident.
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This is just your ego talking. You can't stand the idea that a computer could be better than you at something you devoted your life to. You're not special. Coding is not special. It happened to artists, chess players, etc. It'll happen to us too.
I'll listen to experts who study the topic over an internet rando. AI model capabilities as yet show no signs of slowing their exponential growth.
you're a fool. chess has rules and is boxed into those rules. of course it's prime for AI.
art is subjective, I don't see the appeal personally, but I'm more of a baroque or renaissance fan.
I doubt you will but if you believe in what you say then this will only prove you right and me wrong.
what is this?
once you classify it, why did you classify it that way? is it because you personally have one? did you have to rule out what it isn't before you could identify what it could be? did you compare it to other instances of similar subjects?
now, try to classify it as someone who doesn't have these. someone who has never seen one before. someone who hasn't any idea what it could be used for. how would you identify what it is? how it's used? are there more than one?
now, how does AI classify it? does it comprehend what it is, even though it lacks a physical body? can it understand what it's used for? how it feels to have one?
my point is, AI is at least 100 years away from instinctively knowing what a hand is. I doubt you had to even think about it and your brain automatically identified it as a hand, the most basic and fundamentally important features of being a human.
if AI cannot even instinctively identify a hand as a hand, it's not possible for it to write software, because writing is based on human cognition and is entirely driven on instinct.
like a master sculptor, we carve out the words from the ether to perform tasks that not only are required, but unseen requirements that lay beneath the surface that are only known through nuance. just like the sculptor that has to follow the veins within the marble.
the AI you know today cannot do that, and frankly the hardware of today can't even support AI in achieving that goal, and it never will because of people like you promoting a half baked toy as a tool to replace nuanced human skills. only for this toy to poison pill the only training data available, that's been created through nuanced human skills.
I'll just add, I may be an internet rando to you but you and your source are just randos to me. I'm speaking from my personal experience in writing software for over 25 years along with cleaning up all this AI code bullshit for at least two years.
AI cannot code. AI writes regurgitated facsimiles of software based on it's limited dataset. it's impossible for it to make decisions based on human nuance and can only make calculated assumptions based on the available dataset.
I don't know how much clearer I have to be at how limited AI is.
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Honest question: I haven't used AI much. Are there any AIs or IDEs that can reliably rename a variable across all instances in a medium sized Python project? I don't mean easy stuff that an editor can do (e.g. rename QQQ in all instances and get lucky that there are no conflicts). I mean be able to differentiate between local and/or library variables so it doesn't change them, only the correct versions.
I'm going to laugh in Java, where this has always been possible and reliable. Not like ai reliable, but expert reliable. Because of static types.
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I use pycharm for this and in general it does a great job. At work we've got some massive repos and it'll handle it fine.
The "find" tab shows where it'll make changes and you can click "don't change anything in this directory"
Yes, all of JetBrains' tools handle project-wide renames practically perfectly, even in weirder things like Angular projects where templates may reference variables.
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Find and Replace?
that will catch too many false positives
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It confidently gave me one
IMO, that's one of the biggest "sins" of the current LLMs, they're trained to generate words that make them sound confident.
They aren’t explicitly trained to sound confident, that’s just how users tend to talk. You don’t often see “I don’t know but you can give this a shot” on Stack Overflow, for instance. Even the incorrect answers coming from users are presented confidently.
Funnily enough, lack of confidence in response is something I don’t think LLMs are currently capable of, since it would require contextual understanding of both the question, and the answer being given.
