• HalfSalesman@lemmy.world
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    9 days ago

    We have robots doing the dangerous jobs in this meme. Its just they don’t do 100% of the work. They also don’t do 100% of knowledge work either to this day. If you have an AI make you a power point and then you don’t edit it and do quality assurance on it you are going to have one jank ass powerpoint.

    Even if the crazy miracles its doing with decomp & recomp work on video games lately: that still requires a ton of human involvement.

    They might eventually be able to do 100% of physical labor though. And 100% of knowledge work. They just are not there yet. The former requires use to have enough physical materials though.

    • frank@sopuli.xyz
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      9 days ago

      Yeah, as an automation engineer, I freaking hate this narrative. “I want the AI to do the dishes not write music”

      You don’t need AI for that, you have automation for it. further automation might be cool too, but the LLM has no place in doing a useful task like that.

      You can tell most people making this narrative haven’t ever been to a factory

      • Pixel_Jock_17@piefed.ca
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        9 days ago

        I hate the ai boom.

        We needed to continue to advance automation. Weve had it for years and its all we need. It just needs to continue to improve!

        Why bring on this fucking massive philosophical and ethical issue in an already crazy world? What the fuck are we even doing here?

    • HertzDentalBar@lemmy.blahaj.zone
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      10 days ago

      I was going to say the same. Robots are doing all that right now. But also that robots are not AI but robots can use AI. Don’t need AI to do 90% of shit we need em to do.

    • UnderpantsWeevil@lemmy.world
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      9 days ago

      BYD very famously invested in high end manufacturing equipment early on in it’s history. But, in trying to maintain, upgrade, and expand the equipment alongside increased production demand, the senior managers discovered that this was significantly more expensive than just hiring and training more local machinists to build the cars manually.

      They ended up downsizing their automated team and hiring/training a huge number of skilled professionals. This allowed the company to grow far more rapidly, while still implementing new changes to their models with minimal re-engineering of their production floor.

      Now, BYD is one of the largest car markets in the world, and they are slowing moving back to re-automate jobs that have become consistent and routine.

  • mrgoosmoos@lemmy.ca
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    9 days ago

    turns out, a lot of manual labour tasks are too complex to automate easily. even if the work is repetitive and seems like it would be simple, there’s a lot of things that you can’t just stick a robot into and have it work

    computer tasks, on the other hand… it’s a lot easier, and there’s much better training data, and the stakes are theoretically (and often in practice) lower.

    now, as for WHY we’re not globally prioritizing automating the dangerous stuff completely, that’d be because money, I imagine

    • REDACTED@infosec.pub
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      9 days ago

      There’s irony in how easy it is to automate jobs that are generally regarded as “higher ups”, more intelligent as opposed to lower-tier jobs. And those managers and executives would likely be pretty bad workers.

      • mrgoosmoos@lemmy.ca
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        9 days ago

        I used to despise the thought of AI in the workplace doing my job for me

        but after seeing what apparently above-average employees output… I understand why it seems appealing

        ex: sent my coworker instructions that made note of particular things, and a template file with clearly documented instructions inside the file. they used the wrong template file, not the one I explicitly sent the filepath for. they asked me to review the file. I made note of the issues that cropped up because they didn’t follow the instructions. they asked me to do a final review. I noticed that some of their fixes to my notes did the opposite of what I asked, or were just ignored. like, yeah, AI can do just as well as that. but it can’t do it properly, and that’s what we need

  • 🇨🇦 tunetardis@piefed.ca
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    10 days ago

    The other day I learned about fatbergs and the people tasked with climbing down into sewers with shovels to remove them. Can’t this be a job for AI? Please?

      • 🇨🇦 tunetardis@piefed.ca
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        9 days ago

        Well, from what I’ve read, it’s a job that involves a lot of unexpected complications that has resisted automation. In fairness though, I’m not sure how much machine learning in its present form would help?

  • jqubed@lemmy.world
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    10 days ago

    I understand what community I’m in, but I feel like this relates to something I’ve thought about since using a rental electric vehicle. There are a lot of people who can write programs for computers. There are far fewer people who can create electronic devices reliably work in an outdoor, exposed environment. I started suspecting one reason so many charging stations want to use an app to collect payments online is because it’s easy to connect to Square or Cybersource or whatever. Making a card reader that supports magstripe, chip, or NFC and can survive being exposed to sun, rain, snow, ice, and extreme temperatures is a lot harder. Gas pumps have done this for decades, although I’m sure the roofs help, but even they had to turn to companies like Verifone when cards started using chips, and those companies didn’t make things easy (they’re why gas pumps play commercials now).

    • Echo Dot@feddit.uk
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      10 days ago

      Is magstrip that’s the problem. It means as an exposed component that has to be in the environment and can’t be enclosed. NFC readers can read the chips through several millimetres of materials so they can be totally embedded.

      Real solution is for North America to just get off Mag strip no one’s used it in the rest of the world in about 20 years.

        • jqubed@lemmy.world
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          4 days ago

          Mostly no. When they finally transitioned to chips in the US about 15 years ago there was a period where the card issuers maintained the liability for transactions made with stolen cards, but largely after 2015 (except for gas pumps with credit card functionality) any fraudulent transaction made using magstripe fell on the merchant to suffer the loss. Liability is a reason credit cards are much more popular in the US: if a fraudulent transaction is made the cardholder is normally not out any money, whereas a fraudulent transaction on a debit card could result in a permanent loss of money for the cardholder.

          The merchants were responsible for upgrading their credit card terminals at their own cost, so that was how they incentivized upgrading. Still, some organizations with larger numbers of terminals or legacy software implementations were slow to switch to terminals that supported chips. One large local hospital and clinical medical group we visit a lot for specialists and physical therapy only stopped using magstripe this year. The front desk staff told me they were still using the old terminals because of how many they would have to replace and how those integrated with their billing software. They would have to upgrade everything: thousands of terminals across a dozen hospitals and many more clinics along with a major software upgrade or change of providers, and as a non-profit organization owned by the state’s public university system that wasn’t prioritized until it couldn’t be sustained any longer.

          And as @[email protected] said, merchants have the option to swipe the magnetic strip if the chip has a read error, but the merchant is then risking the liability for a fraudulent purchase.

        • Echo Dot@feddit.uk
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          9 days ago

          Yeah the US banking system is really archaic. They still use signatures as a form of security.

          I’m really not sure what the resistance to modernisation is. But it causes all sorts of problems like this, that the rest of the world just never experiences.

    • merc@sh.itjust.works
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      9 days ago

      The very premise of this meme is ridiculous.

      Mining was one of the earliest adopters of automation. “Robots” have been doing mining jobs for decades, for centuries if you are generous with how you define “robot”. Mining companies keep searching for any job they can automate. Even the guys who drive the enormous mine trucks were replaced when they found they could let a machine drive the trucks instead.

      The only difference is that nobody yet knew how to automate “knowledge work”. The latest generation of AI can simulate knowledge work, which apparently is good enough for some jobs. But, the fact that it hasn’t yet taken some of the few remaining mining and chemistry jobs is a clue that it has severe limitations.

      Sure, you can automate the creation of powerpoint presentations, which is “knowledge work”, but is there a mining company that is willing to fire the guy who supervises the robots and replace him with ChatGPT? These are ruthless profit-driven companies. If AI could do that guy’s job, he’d be unemployed.

      • Equinox1289@sh.itjust.works
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        9 days ago

        Current LLMs are limited by the fact that they can’t train during inference. i.e. They can’t learn. If we find something better than backpropagation or diffusion, then things are going to actually be different. At that point, the models would be able to compose ideas together instead of just predict the next token in sequence based on previous training.

        • merc@sh.itjust.works
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          9 days ago

          Current LLMs are limited by the fact that they can’t train during inference. i.e. They can’t learn

          Learning is much more than just training during inference.

          True unsupervised learning is still in its infancy, and requires a completely different architecture than the current fancy auto-suggest boom. Unsupervised learning has been the dream since at least the 1950s when AI was an aspiration, even before transistors existed. Nobody has figured out how to do it yet.

          If pigs learn to fly, then things are going to actually be different.

    • CultLeader4Hire@lemmy.world
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      9 days ago

      If you consider LLMs to be robots I guess? I don’t think robots are writing emails, like a robot is not sitting down at a keyboard and typing out emails in your average office, or any office at any scale really

    • UnderpantsWeevil@lemmy.world
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      9 days ago

      Not anywhere near at equivalent scale.

      “Artisanal Mining” (ie, press-ganged children forced into mine work in conflict zones) continues to be a lucrative industry in a way freelance accounting or contracting increasingly is not.

      Automation is coming for the high margin jobs, while leaving humans to the low margin manual labor.

  • A_Chilean_Cyborg@feddit.cl
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    10 days ago

    Robots do, there is anlot of automation now in big mines, Copper be extracted in ElTeniente mine in chile, in the middle of the andes and the “miners” can sit comfortably in a control room in the city of rancagua with a cup of coffee.

    • Diplomjodler@lemmy.world
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      9 days ago

      Those machines are not robots in the sense that they can do stuff at least partially autonomously. Everything is tenor controlled, i.e. There’s a human in the loop at all times. Present day robots can’t even do the simplest tasks without being teleoperated.

      • pishadoot@sh.itjust.works
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        9 days ago

        Automation of robotics in an uncontrolled physical environment is so, so hard to program for.

        This is why we got advanced language, music, art, speaking models first. There’s SO much of that data (they stole and pillaged every scrap, but the fact is that it exists) that models can be trained on.

        There isn’t vast stores of raw sensor data that maps physical environments to servo, hydraulic, pneumatics correlated with optical, heat, tactile feedback etc.

        If you think about how uncoordinated toddlers are, and how many years it takes to map all the inputs humans receive and learn how that translates to our environment so we can move around without much thought, you’ll kind of get what I mean. That information just hasn’t been collected on a large scale in a way that machine learning can train on it.

        This is the underlying challenge of autonomous robotics. We’ll get there, but for now we still need humans controlling pretty much everything that doesn’t have an ultra-controlled space like factory floors.

        I was in a grocery store the other day and they had some sign on a Roomba looking thing that was struggling to navigate the produce section. I can’t imagine how hard it would be to create a machine that can reliably and safely mine ores autonomously.

      • redballooon@lemmy.world
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        9 days ago

        Who cares as long as thr dangerous work in the mines is not handed out to children and other victims of capitalism anymore?

          • pishadoot@sh.itjust.works
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            9 days ago

            I think you’re conflating the term “robotics” with “autonomous robots.”

            Robotics is a very, very old term.

          • redballooon@lemmy.world
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            9 days ago

            Robotics has been a field long before the current AI hype started. It’s been about sensory and precise motors and steel mobility under all sorts of conditions.

  • Tja@programming.dev
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    9 days ago

    Why don’t robots do something useful, like transporting things, washing the dishes or my clothes!!1!

    empties the dishwasher and hops in a car