AI agents wrong ~70% of time: Carnegie Mellon study
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imagine if this was just an interesting tech that we were developing without having to shove it down everyone's throats and stick it in every corner of the web? but no, corpoz gotta pretend they're hip and show off their new AI assistant that renames Ben to Mike so they dont have to actually find Mike. capitalism ruins everything.
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It doesn't matter if you need a human to review. AI has no way distinguishing between success and failure. Either way a human will have to review 100% of those tasks.
I have been using AI to write (little, near trivial) programs. It's blindingly obvious that it could be feeding this code to a compiler and catching its mistakes before giving them to me, but it doesn't... yet.
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A human can review something close to correct a lot better than starting the task from zero.
In University I knew a lot of students who knew all the things but "just don't know where to start" - if I gave them a little direction about where to start, they could run it to the finish all on their own.
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AI cant even understand it's own brain to write about it
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It is a lot harder to notice incorrect information in review, than making sure it is correct when writing it.
Depends on the context, there is a lot of work in the scientific methods community trying to use NLP to augment traditionally fully human processes such as thematic analysis and systematic literature reviews and you can have protocols for validation there without 100% human review
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Are you guys sure. The media seems to be where a lot of LLM hate originates.
that is such a ridiculous idea. Just because you see hate for it in the media doesn't mean it originated there. I'll have you know that i have embarrassed myself by screaming at robot phone receptionists for years now. stupid fuckers pretending to be people but not knowing shit. I was born ready to hate LLMs and I'm not gonna have you claim that CNN made me do it.
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It is a lot harder to notice incorrect information in review, than making sure it is correct when writing it.
harder to notice incorrect information in review, than making sure it is correct when writing it.
That depends entirely on your writing method and attention span for review.
Most people make stuff up off the cuff and skim anything longer than 75 words when reviewing, so the bar for AI improving over that is really low.
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Wrong 70% doing what?
I’ve used LLMs as a Stack Overflow / MSDN replacement for over a year and if they fucked up 7/10 questions I’d stop.
Same with code, any free model can easily generate simple scripts and utilities with maybe 10% error rate, definitely not 70%
it specifies the tasks in the article
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The person who uses fancy autocomplete to write their code will be exactly the person who thinks they're better than everyone. Those traits are correlated.
Do you use an IDE for writing your code or do you use a notepad like a "real" programmer?
An IDE like Intellij has fancy shit like generating getters, setters, constructors, equals hashscode, you should never use those, real programmers write those by hand.Your attention detail is very good btw, which I am ofc being sarcastic about because if you had any you'd have noticed I have never said I write my code with chat gpt, I said Unit tests, sql for unit tests.
Ofc attention to detail is not a requirement of software engineering so you should be good. (This was also sarcasm I feel like you need this to be pointed out for you).
Also by your implied logic that the code being not written by you = bad, no company should ever hire Junior engineers, I mean what are you gonna do? Fucking read the code they wrote?
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Claude why did you make me an appointment with a gynecologist? I need an appointment with my neurologist, I’m a man and I have Parkinson’s.
Got it, changing your gender to female. Is there anything else I can assist you with?
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Right, so this is really only useful in cases where either it's vastly easier to verify an answer than posit one, or if a conventional program can verify the result of the AI's output.
It’s usually vastly easier to verify an answer than posit one, if you have the patience to do so.
I'm envisioning a world where multiple AI engines create and check each others' work... the first thing they need to make work to support that scenario is probably fusion power.
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You get how that's fucking useless, generally?
As useless as a cubicle farm full of unsupervised workers.
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Run something with a 70% failure rate 10x and you get to a cumulative 98% pass rate.
LLMs don't get tired and they can be run in parallel.I have actually been doing this lately: iteratively prompting AI to write software and fix its errors until something useful comes out. It's a lot like machine translation. I speak fluent C++, but I don't speak Rust, but I can hammer away on the AI (with English language prompts) until it produces passable Rust for something I could write for myself in C++ in half the time and effort.
I also don't speak Finnish, but Google Translate can take what I say in English and put it into at least somewhat comprehensible Finnish without egregious translation errors most of the time.
Is this useful? When C++ is getting banned for "security concerns" and Rust is the required language, it's at least a little helpful.
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As useless as a cubicle farm full of unsupervised workers.
Tjose are people who could be living their li:es, pursuing their ambitions, whatever. That could get some shit done. Comparison not valid.
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It’s usually vastly easier to verify an answer than posit one, if you have the patience to do so.
I'm envisioning a world where multiple AI engines create and check each others' work... the first thing they need to make work to support that scenario is probably fusion power.
It’s usually vastly easier to verify an answer than posit one, if you have the patience to do so.
I usually write 3x the code to test the code itself. Verification is often harder than implementation.
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I'd compare LLMs to a junior executive. Probably gets the basic stuff right, but check and verify for anything important or complicated. Break tasks down into easier steps.
A junior developer actually learns from doing the job, an LLM only learns when they update the training corpus and develop an updated model.
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It’s usually vastly easier to verify an answer than posit one, if you have the patience to do so.
I usually write 3x the code to test the code itself. Verification is often harder than implementation.
Yes, but the test code "writes itself" - the path is clear, you just have to fill in the blanks.
Writing the proper product code in the first place, that's the valuable challenge.
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I'm in a workplace that has tried not to be overbearing about AI, but has encouraged us to use them for coding.
I've tried to give mine some very simple tasks like writing a unit test just for the constructor of a class to verify current behavior, and it generates output that's both wrong and doesn't verify anything.
I'm aware it sometimes gets better with more intricate, specific instructions, and that I can offer it further corrections, but at that point it's not even saving time. I would do this with a human in the hopes that they would continue to retain the knowledge, but I don't even have hopes for AI to apply those lessons in new contexts. In a way, it's been a sigh of relief to realize just like Dotcom, just like 3D TVs, just like home smart assistants, it is a bubble.
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How do I set up event driven document ingestion from OneDrive located on an Azure tenant to Amazon DocumentDB? Ingestion must be near-realtime, durable, and have some form of DLQ.
DocumentDB is not for one drive documents (PDFs and such). It's for "documents" as in serialized objects (json or bson).
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Do you use an IDE for writing your code or do you use a notepad like a "real" programmer?
An IDE like Intellij has fancy shit like generating getters, setters, constructors, equals hashscode, you should never use those, real programmers write those by hand.Your attention detail is very good btw, which I am ofc being sarcastic about because if you had any you'd have noticed I have never said I write my code with chat gpt, I said Unit tests, sql for unit tests.
Ofc attention to detail is not a requirement of software engineering so you should be good. (This was also sarcasm I feel like you need this to be pointed out for you).
Also by your implied logic that the code being not written by you = bad, no company should ever hire Junior engineers, I mean what are you gonna do? Fucking read the code they wrote?
Were you prone to this weird leaps of logic before your brain was fried by talking to LLMs, or did you start being a fan of talking to LLMs because your ability to logic was...well...that?