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

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  • I was 0/6 on various trials of AI for Rust over the past 6 months, then I caught a success. Turns out, I was asking it to use a difficult library - I can't make the thing I want work in that library either (library docs say it's possible, but...) when I posed a more open ended request without specifying the library to use, it succeeded - after a fashion. It will give you code with cargo build errors, I copy-paste the error back to it like "address: <pasted error message>" and a bit more than half of the time it is able to respond with a working fix.

    i find that rust’s architecture and design decisions give the LLM quite good guardrails and kind of keep it from doing anything too wonky. the issue arises in cases like these where the rust ecosystem is quite young and documentation/instruction can be poor, even for a human developer.

    i think rust actually is quite well suited to agentic development workflows, it just needs to mature more.

  • No the chances of being wrong 10x in a row are 2%. So the chances of being right at least once are 98%.

    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.

  • i find that rust’s architecture and design decisions give the LLM quite good guardrails and kind of keep it from doing anything too wonky. the issue arises in cases like these where the rust ecosystem is quite young and documentation/instruction can be poor, even for a human developer.

    i think rust actually is quite well suited to agentic development workflows, it just needs to mature more.

    i think rust actually is quite well suited to agentic development workflows, it just needs to mature more.

    I agree. The agents also need to mature more to handle multi-level structures - work on a collection of smaller modules to get a larger system with more functionality. I can see the path forward for those tools, but the ones I have access to definitely aren't there yet.

  • In one case, when an agent couldn't find the right person to consult on RocketChat (an open-source Slack alternative for internal communication), it decided "to create a shortcut solution by renaming another user to the name of the intended user."

    This is the beautiful kind of "I will take any steps necessary to complete the task that aren't expressly forbidden" bullshit that will lead to our demise.

    It does not say a dog can not play basketball.

  • It does not say a dog can not play basketball.

    "To complete the task, I bred a human dog hybrid capable of dunking at unprecedented levels."

  • I think it's lemmy users. I see a lot more LLM skepticism here than in the news feeds.

    In my experience, LLMs are like the laziest, shittiest know-nothing bozo forced to complete a task with zero attention to detail and zero care about whether it's crap, just doing enough to sound convincing.

    Wdym, I have seen researchers using it to aid their research significantly. You just need to verify some stuff it says.

  • Emotion > Facts. Most people have been trained to blindly accept things and cheer on what fits with their agenda. Like technbro's exaggerating LLMs, or people like you misrepresenting LLMs as mere statistical word generators without intelligence. That's like saying a computer is just wires and switches, or missing the forest for the trees. Both is equally false.

    Yet if it fits with the emotional needs or with dogma, then other will agree. It's a convenient and comforting "A vs B" worldview we've been trained to accept. And so the satisfying notion and misinformation keeps spreading.

    LLMs tell us more about human intelligence and the human slop we've been generating. It tells us that most people are not that much more than statistical word generators.

    Truth is bitter, and I hate it.

  • Wdym, I have seen researchers using it to aid their research significantly. You just need to verify some stuff it says.

    Verify every single bloody line of output. Top three to five are good, then it starts guessing the rest based on the pattern so far. If I wanted to make shit up randomly, I would do it myself.

    People who trust LLMs to tell them things that are right rather than things that sound right have fundamentally misunderstood what an LLM is and how it works.

  • Verify every single bloody line of output. Top three to five are good, then it starts guessing the rest based on the pattern so far. If I wanted to make shit up randomly, I would do it myself.

    People who trust LLMs to tell them things that are right rather than things that sound right have fundamentally misunderstood what an LLM is and how it works.

    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!

  • "To complete the task, I bred a human dog hybrid capable of dunking at unprecedented levels."

    "Where are my balls Summer?"

  • I'd just like to point out that, from the perspective of somebody watching AI develop for the past 10 years, completing 30% of automated tasks successfully is pretty good! Ten years ago they could not do this at all. Overlooking all the other issues with AI, I think we are all irritated with the AI hype people for saying things like they can be right 100% of the time -- Amazon's new CEO actually said they would be able to achieve 100% accuracy this year, lmao. But being able to do 30% of tasks successfully is already useful.

    Thing is, they might achieve 99% accuracy given the speed of progress. Lots of brainpower is getting poured into LLMs.
    Honestly, it is soo scary. It could be replacing me...

  • Thing is, they might achieve 99% accuracy given the speed of progress. Lots of brainpower is getting poured into LLMs.
    Honestly, it is soo scary. It could be replacing me...

    yeah, this is why I'm #fuck-ai to be honest.

  • "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

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    dojan@pawb.socialD
    It is a direct result of structural racism, as it's a product of the treatment of white men as being the default. You see it all the time in medicine. There are conditions that disproportionately affect black people that we don't know enough about because time and money hasn't been spent studying it. Women face the same problem. Lots of conditions apply differently in women. An example of this being why women historically have been underrepresented in e.g. autism diagnoses. It presents differently so for a while the assumption was made that women just can't be autistic. I don't think necessarily that people who perpetuate this problem are doing so out of malice, they probably don't think of women/black people as lesser (hell, many probably are women and/or black), but it doesn't change the fact that structural problems requires awareness and conscious effort to correct.
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    jacksonlamb@lemmy.worldJ
    bizarre, dismal What's bizarre and dismal is that someone is so starved for dopamine and attention from corporations that this is how they perceive what life looks like when you are not being targetted. This is my normal view and it is far better.
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    Did you, by any chance, ever wonder, why people deal with hunger instead of just eating cake?
  • Is Matrix cooked?

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    Didn't know it only applied to UWP apps on Windows. That does seem like a pretty big problem then. it is mostly for compatibility reasons. no win32 programs are equipped to handle such granular permissions and sandboxing, they are all made with the assumption that they have access to whatever they need (other than other users' resources and things that require elevation). if Microsoft would have made that limitation to every kind of software, that Windows version would have probably been a failure in popularity because lots of software would have broken. I think S editions of windows is how they tried to go in that direction, with a more drastic way of simply just dropping support for 3rd party win32 programs. I don't still have a Mac readily available to test with but afaik it is any application that uses Apple's packaging format. ok, so if you run linux or windows utils in a compatibility layer, they still have less of a limited access? by which I mean graphical utilities. just tried with firefox, for macos it wanted to give me an .iso file (???) if so, it seems apple is doing roughly the same as microsoft with uwp and the appx format, and linux with flatpak: it's a choice for the user
  • Russian Lawmakers Authorize Creation Of National Messaging Service

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    Are there substantial numbers of Russians who seriously wouldn't be wise to this?
  • France considers requiring Musk’s X to verify users’ age

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    TBH, age verification services exist. If it becomes law, integrating them shouldn't be more difficult than integrating a OIDC login. So everyone should be able to do it. Depending on these services, you might not even need to give a name, or, because they are separate entities, don't give your name to the platform using them. Other parts of regulation are more difficult. Like these "upload filters" that need to figure out if something shared via a service is violating any copyright before it is made available.
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    I use it for my self hosted apps, but yeah, it's rarely useful for websites in the wild.
  • Everyone Is Cheating Their Way Through College

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    i can this for essay writing, prior to AI people would use prompts and templates of the same exact subject and work from there. and we hear the ODD situation where someone hired another person to do all the writing for them all the way to grad school( this is just as bad as chatgpt) you will get caught in grad school or during your job interview. might be different for specific questions in stem where the answer is more abstract,