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AI agents wrong ~70% of time: Carnegie Mellon study

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  • "Where are my balls Summer?"

    The first dunk is the hardest

  • It's not that bad, the output isn't random.
    Time to time, it can produce novel stuffs like new equations for engineering.
    Also, verification does not take that much effort. At least according to my colleagues, it is great.
    Also works well for coding well-known stuffs, as well!

    It's not completely random, but I'm telling you it fucked up, it fucked up badly, time after time, and I had to check every single thing manually. It's correctness run never lasted beyond a handful. If you build something using some equation it invented you're insane and should quit engineering before you hurt someone.

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    And it won’t be until humans can agree on what’s a fact and true vs not.. there is always someone or some group spreading mis/dis-information

  • If that’s the quality of answer you’re getting, then it’s a user error

    No, I know the data I gave it and I know how hard I tried to get it to use it truthfully.

    You have an irrational and wildly inaccurate belief in the infallibility of LLMs.

    You're also denying the evidence of my own experience. What on earth made you think I would believe you over what I saw with my own eyes?

    Why are you giving it data. It's a chat and language tool. It's not data based. You need something trained to work for that specific use. I think Wolfram Alpha has better tools for that.

    I wouldn't trust it to calculate how many patio stones I need to build a project. But I trust it to tell me where a good source is on a topic or if a quote was said by who ever or if I need to remember something but I only have vague pieces like old timey historical witch burning related factoid about villagers who pulled people through a hole in the church wall or what was a the princess who was skeptic and sent her scientist to villages to try to calm superstitious panic .

    Other uses are like digging around my computer and seeing what processes do what. How concepts work regarding the think I'm currently learning. So many excellent users. But I fucking wouldn't trust it to do any kind of calculation.

  • You probably wanted to show off how smart you are, but instead you showed that you can't even talk to people without help of your favourite slop bucket.
    It didn't answer my curiosity about what came first, but it solidified my conviction that your brain is cooked all the way, probably beyond repair. I would say you need to seek professional help, but at this point you would interpret it as needing to talk to the autocomplete, and it will cook you even more.
    It started funny, but I feel very sorry for you now, and it sucked all the humour out.

    You just can't talk to people, period, you are just a dick, you were also just proven to be stupider than a fucking LLM, have a nice day 😀

  • I actually have a fairly positive experience with ai ( copilot using claude specificaly ). Is it wrong a lot if you give it a huge task yes, so i dont do that and using as a very targeted solution if i am feeling very lazy today . Is it fast . Also not . I could actually be faster than ai in some cases.
    But is it good if you are working for 6h and you just dont have enough mental capacity for the rest of the day. Yes . You can just prompt it specificaly enough to get desired result and just accept correct responses. Is it always good ,not really but good enough. Do i also suck after 3pm . Yes.
    My main issue is actually the fact that it saves first and then asks you to pick if you want to use it. Not a problem usualy but if it crashes the generated code stays so that part sucks

    You should give Claude Code a shot if you have a Claude subscription. I'd say this is where AI actually does a decent job: picking up human slack, under supervision, not replacing humans at anything. AI tools won't suddenly be productive enough to employ, but I as a professional can use it to accelerate my own workflow. It's actually where the risk of them taking jobs is real: for example, instead of 10 support people you can have 2 who just supervise the responses of an AI.

    But of course, the Devil's in the detail. The only reason this is cost effective is because of VC money subsidizing and hiding the real cost of running these models.

  • Why are you giving it data. It's a chat and language tool. It's not data based. You need something trained to work for that specific use. I think Wolfram Alpha has better tools for that.

    I wouldn't trust it to calculate how many patio stones I need to build a project. But I trust it to tell me where a good source is on a topic or if a quote was said by who ever or if I need to remember something but I only have vague pieces like old timey historical witch burning related factoid about villagers who pulled people through a hole in the church wall or what was a the princess who was skeptic and sent her scientist to villages to try to calm superstitious panic .

    Other uses are like digging around my computer and seeing what processes do what. How concepts work regarding the think I'm currently learning. So many excellent users. But I fucking wouldn't trust it to do any kind of calculation.

    Why are you giving it data

    Because there's a button for that.

    It’s output is dependent on the input

    This thing that you said... It's false.

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    Wow. 30% accuracy was the high score!
    From the article:

    Testing agents at the office

    For a reality check, CMU researchers have developed a benchmark to evaluate how AI agents perform when given common knowledge work tasks like browsing the web, writing code, running applications, and communicating with coworkers.

    They call it TheAgentCompany. It's a simulation environment designed to mimic a small software firm and its business operations. They did so to help clarify the debate between AI believers who argue that the majority of human labor can be automated and AI skeptics who see such claims as part of a gigantic AI grift.

    the CMU boffins put the following models through their paces and evaluated them based on the task success rates. The results were underwhelming.

    ⚫ Gemini-2.5-Pro (30.3 percent)
    ⚫ Claude-3.7-Sonnet (26.3 percent)
    ⚫ Claude-3.5-Sonnet (24 percent)
    ⚫ Gemini-2.0-Flash (11.4 percent)
    ⚫ GPT-4o (8.6 percent)
    ⚫ o3-mini (4.0 percent)
    ⚫ Gemini-1.5-Pro (3.4 percent)
    ⚫ Amazon-Nova-Pro-v1 (1.7 percent)
    ⚫ Llama-3.1-405b (7.4 percent)
    ⚫ Llama-3.3-70b (6.9 percent),
    ⚫ Qwen-2.5-72b (5.7 percent),
    ⚫ Llama-3.1-70b (1.7 percent)
    ⚫ Qwen-2-72b (1.1 percent).

    "We find in experiments that the best-performing model, Gemini 2.5 Pro, was able to autonomously perform 30.3 percent of the provided tests to completion, and achieve a score of 39.3 percent on our metric that provides extra credit for partially completed tasks," the authors state in their paper

  • Ah, my bad, you're right, for being consistently correct, I should have done 0.3^10=0.0000059049

    so the chances of it being right ten times in a row are less than one thousandth of a percent.

    No wonder I couldn't get it to summarise my list of data right and it was always lying by the 7th row.

    That looks better. Even with a fair coin, 10 heads in a row is almost impossible.

    And if you are feeding the output back into a new instance of a model then the quality is highly likely to degrade.

  • You just can't talk to people, period, you are just a dick, you were also just proven to be stupider than a fucking LLM, have a nice day 😀

    Did the autocomplete told you to answer this? Don't answer, actually, save some energy.

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    Now I'm curious, what's the average score for humans?

  • The 256 thing was written by a person. AI doesn't have exclusive rights to being dumb, plenty of dumb people around.

    you're right, the dumb of AI is completely comparable to the dumb of human, there's no difference worth talking about, sorry i even spoke the fuck up

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    I asked Claude 3.5 Haiku to write me a quine in COBOL in the bs2000 dialect. Claude does now that creating a perfect quine in COBOL is challenging due to the need to represent the self-referential nature of the code. After a few suggestions Claude restated its first draft, without proper BS2000 incantations, without a perform statement, and without any self-referential redefines. It's a lot of work. I stopped caring and moved on.

    For those who wonder: https://sourceforge.net/p/gnucobol/discussion/lounge/thread/495d8008/ has an example.

    Colour me unimpressed. I dread the day when they force the use of 'AI' on us at work.

  • Why are you giving it data

    Because there's a button for that.

    It’s output is dependent on the input

    This thing that you said... It's false.

    There's a sleep button on my laptop. Doesn't mean I would use it.

    I'm just trying to say you're saying the feature that everyone kind of knows doesn't work. Chatgpt is not trained to do calculations well.

    I just like technology and I think and fully believe the left hatred of it is not logical. I believe it stems from a lot of media be and headlines. Why there's this push From media is a question I would like to know more. But overall, I see a lot of the same makers of bullshit yellow journalism for this stuff on the left as I do for similar bullshit on the right wing spaces towards other things.

  • America: "Good enough to handle 911 calls!"

    Is there really a plan to use this for 911 services??

  • Wow. 30% accuracy was the high score!
    From the article:

    Testing agents at the office

    For a reality check, CMU researchers have developed a benchmark to evaluate how AI agents perform when given common knowledge work tasks like browsing the web, writing code, running applications, and communicating with coworkers.

    They call it TheAgentCompany. It's a simulation environment designed to mimic a small software firm and its business operations. They did so to help clarify the debate between AI believers who argue that the majority of human labor can be automated and AI skeptics who see such claims as part of a gigantic AI grift.

    the CMU boffins put the following models through their paces and evaluated them based on the task success rates. The results were underwhelming.

    ⚫ Gemini-2.5-Pro (30.3 percent)
    ⚫ Claude-3.7-Sonnet (26.3 percent)
    ⚫ Claude-3.5-Sonnet (24 percent)
    ⚫ Gemini-2.0-Flash (11.4 percent)
    ⚫ GPT-4o (8.6 percent)
    ⚫ o3-mini (4.0 percent)
    ⚫ Gemini-1.5-Pro (3.4 percent)
    ⚫ Amazon-Nova-Pro-v1 (1.7 percent)
    ⚫ Llama-3.1-405b (7.4 percent)
    ⚫ Llama-3.3-70b (6.9 percent),
    ⚫ Qwen-2.5-72b (5.7 percent),
    ⚫ Llama-3.1-70b (1.7 percent)
    ⚫ Qwen-2-72b (1.1 percent).

    "We find in experiments that the best-performing model, Gemini 2.5 Pro, was able to autonomously perform 30.3 percent of the provided tests to completion, and achieve a score of 39.3 percent on our metric that provides extra credit for partially completed tasks," the authors state in their paper

    sounds like the fault of the researchers not to build better tests or understand the limits of the software to use it right

  • sounds like the fault of the researchers not to build better tests or understand the limits of the software to use it right

    Are you arguing they should have built a test that makes AI perform better? How are you offended on behalf of AI?

  • you're right, the dumb of AI is completely comparable to the dumb of human, there's no difference worth talking about, sorry i even spoke the fuck up

    No worries.

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    Why would they be right beyond word sequence frecuencies?

  • There's a sleep button on my laptop. Doesn't mean I would use it.

    I'm just trying to say you're saying the feature that everyone kind of knows doesn't work. Chatgpt is not trained to do calculations well.

    I just like technology and I think and fully believe the left hatred of it is not logical. I believe it stems from a lot of media be and headlines. Why there's this push From media is a question I would like to know more. But overall, I see a lot of the same makers of bullshit yellow journalism for this stuff on the left as I do for similar bullshit on the right wing spaces towards other things.

    Again with dismissing the evidence of my own eyes!

    I wasn't asking it to do calculations, I was asking it to put the data into a super formulaic sentence. It was good at the first couple of rows then it would get stuck in a rut and start lying. It was crap. A seven year old would have done it far better, and if I'd told a seven year old that they had made a couple of mistakes and to check it carefully, they would have done.

    Again, I didn't read it in a fucking article, I read it on my fucking computer screen, so if you'd stop fucking telling me I'm stupid for using it the way it fucking told me I could use it, or that I'm stupid for believing what the media tell me about LLMs, when all I'm doing is telling you my own experience, you'd sound a lot less like a desperate troll or someone who is completely unable to assimilate new information that differs from your dogma.

  • Large Language Model Performance Doubles Every 7 Months

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    V
    in yes/no type questions, 50% success rate is the absolute worst one can do. Any worse and you're just giving an inverted correct answer more than half the time
  • Men are opening up about mental health to AI instead of humans

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    spankmonkey@lemmy.worldS
    I'm aware of what you are saying and disagree. You apparently take disagreement personally as most of your comments in that post to various other users are hostile too. Please be aware of how you are approaching discourse.
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    C
    Now we need an open source browser runtime...
  • AI cheating surge pushes schools into chaos

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    C
    Sorry for the late reply, I had to sit and think on this one for a little bit. I think there are would be a few things going on when it comes to designing a course to teach critical thinking, nuances, and originality; and they each have their own requirements. For critical thinking: The main goal is to provide students with a toolbelt for solving various problems. Then instilling the habit of always asking "does this match the expected outcome? What was I expecting?". So usually courses will be setup so students learn about a tool, practice using the tool, then have a culminating assignment on using all the tools. Ideally, the problems students face at the end require multiple tools to solve. Nuance mainly naturally comes with exposure to the material from a professional - The way a mechanical engineer may describe building a desk will probably differ greatly compared to a fantasy author. You can also explain definitions and industry standards; but thats really dry. So I try to teach nuances via definitions by mixing in the weird nuances as much as possible with jokes. Then for originality; I've realized I dont actually look for an original idea; but something creative. In a classroom setting, you're usually learning new things about a subject so a student's knowledge of that space is usually very limited. Thus, an idea that they've never heard about may be original to them, but common for an industry expert. For teaching originality creativity, I usually provide time to be creative & think, and provide open ended questions as prompts to explore ideas. My courses that require originality usually have it as a part of the culminating assignment at the end where they can apply their knowledge. I'll also add in time where students can come to me with preliminary ideas and I can provide feedback on whether or not it passes the creative threshold. Not all ideas are original, but I sometimes give a bit of slack if its creative enough. The amount of course overhauling to get around AI really depends on the material being taught. For example, in programming - you teach critical thinking by always testing your code, even with parameters that don't make sense. For example: Try to add 123 + "skibbidy", and see what the program does.
  • The Enshitification of Youtube’s Full Album Playlists

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    dual_sport_dork@lemmy.worldD
    Especially when the poster does not disclose that it's AI. The perpetual Youtube rabbit hole occasionally lands on one of these for me when I leave it unsupervised, and usually you can tell from the "cover" art. But only if you're looking at it. Because if you just leave it going in the background eventually you start to realize, "Wow, this guy really tripped over the fine line between a groove and rut." Then you click on it and look: Curses! Foiled again. And golly gee, I'm sure glad Youtube took away the option to oughtright block channels. I'm sure that's a total coincidence. W/e. I'm a have-it-on-my-hard-drive kind of bird. Yt-dlp is your friend. Just use it to nab whatever it is you actually want and let your own media player decide how to shuffle and present it. This works great for big name commercial music as well, whereupon the record labels are inevitably dumb enough to post songs and albums in their entirety right there you Youtube. Who even needs piracy sites at that rate? Yoink!