• hperrin@lemmy.ca
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    1 month ago

    I feel like the AI industry did this to themselves by absolutely shoving it down our throats at every possible chance they had.

    AI in general isn’t a bad technology, it just has very limited use cases where it’s actually good at things. Most things it’s used for are things it’s bad at. Kind of like using a steam locomotive to clean the bottom of your pool.

      • crunchy@lemmy.dbzer0.com
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        1 month ago

        I can count on one hand the number of jobs or functions I’ve seen people try to get AI to do that isn’t already done better by a hard-coded program or an Excel spreadsheet.

      • TehPers@beehaw.org
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        1 month ago

        I’ve used it as a sort of find and replace in the past, but by feeding it the output from Ripgrep to skip the “find” part. The “replace” was just unwrapping unnecessarily confusing “try” blocks and allowing errors to propagate to the appropriate handlers. This would have required a syntax-aware replacement tool (and some exist but I didn’t really feel like learning one for a one-off).

        As a simple “find this text and replace with this other text” it makes no sense.

    • anachronist@midwest.social
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      1 month ago

      They spent a trillion dollars on it. It can’t be a slightly better search and a way for schoolchildren to cheat. It has to be the next industrial revolution, otherwise their investment was not justified.

    • Powderhorn@beehaw.org
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      1 month ago

      Kind of like using a steam locomotive to clean the bottom of your pool.

      I’m surprised that wasn’t tried on the reflecting pool in D.C. “We love the old-timey trains, don’t we, folks? And now were going to use one in the most amazing way the world has ever seen!”

      • TehPers@beehaw.org
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        1 month ago

        Powered by “clean coal” of course, right? It’d have been more effective than dumping a couple bottles of hydrogen peroxide into the pool at least since the emissions would prevent future algae growth more effectively.

        • Powderhorn@beehaw.org
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          1 month ago

          Oh, they did dump some H202 along the edges, giving a dark blue hue surrounding the algae bloom. Apparently, a comprehensive distribution either didn’t come to mind or was nixed. Alternatively, clearing it up immediately would negate Trump’s claim that the green hue was the result of vandalism and thus, well …

    • definitemaybe@lemmy.ca
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      1 month ago

      Exactly. And the few things GenAI does well aren’t that compute intensive and can run on local models.

      LLMs are terrible at writing new text that matters, i.e. anything at all technical or important. But they’re good at reformatting content into properly structured English, editing text for grammar, and explaining everyday concepts. But they’re so good at those things, that a tiny model running on consumer hardware can do it.

      So, I don’t understand how anyone can possibly expect LLMs to be a profitable business. Where are the moats?

    • what@beehaw.org
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      1 month ago

      There are lists of technology which will work for AI such as programmer. which require analytics of AI and work with that frame of mind.

      We were shown the list in my school 15 years ago and told “some day soon AI will take these jobs, so choose wisely” with a rough percentage for each job.

      Okay, let AI take my job then, that would happen anyway. Jobs have been gouged ever since society has mutated apart from its basic building blocks. I at least want peace of mind!

  • belated_frog_pants@beehaw.org
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    1 month ago

    You love to see it.

    Llms are the tech, which can be interesting.

    “AI” is the moron capitalism auto-theft bubble of this stupid shit and cannot go away fast enough.

  • Powderhorn@beehaw.org
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    1 month ago

    LLMs have some use cases, just far fewer than the hype fawns over. Automating tedium is a good use; we’ve been using computers for this for years. Automating creativity and services is terrible, and in the latter case, merely an extension of phone trees that make it impossible to reach a real person.

    I have a good example from yesterday: I use CashApp for all of my banking needs, and I get distributions twice a month to cover rent and essentials. Well, yesterday, I had an unexpected charge that was partially reversed but left me in overdraft. I reached out to my mom and explained the situation, at which point begins four fucking hours of hell on both ends, and, of course, customer service tries to keep you in an “AI” loop before letting one talk to a real person.

    But surprise! This is another “AI” with more elaborate scripts, each more insulting than the last. Yes, I’m sure I’ve entered all the information in correctly. Yes, I’ve tried it multiple times. The issue here is that the app is not doing today what it did yesterday under identical circumstances. No matter how I tried to describe the edge case we’d apparently run into, the chatbot insisted it was user error; everything’s fine on their end.

    Eventually, I get a link to talk with an alleged “real person,” and the process repeats. It doesn’t much matter if they’re real or not when sticking to the script nets the same results as the first two chatbots.

    The error message mom is getting when attempting to send money (and she attempted this multiple times) was “Your app is not up to date; please redownload and try again.” And, of course, she had the most recent version and was able to confirm that. Her chatbot experience served only to frustrate her, so I looked at what I could figure out on my end, though she’s on iOS, so replicating the issue was impossible.

    Eventually, after trying to access my account through the Web portal instead, I run into a prompt telling me I need to create a new $cashtag. What’s happened to the one I’ve been using without issue for years? “Customer service” muses that I did something to my account myself, or that there’s been fraud I’d have clearly known about. That’s the handle people pay me via, and changing it is not in my interest. But the “AI” knows all, and obviously everything is hunky-dory on their infrastructure end, so it’s a me problem. Also, I can’t have it back.

    After further useless steps I’m guided through, we arrive where we were three fucking hours prior, I finally acquiesce and set up a new tag.

    This is when the lightbulb goes off: There’s a nonzero chance that my tag being canceled had unexpected downstream effects. On the fourth call with my mom, I tell her I had to pick a new one and share it, suggesting she give it one more try.

    And it goes through as expected.

    So, the error message she was getting and that chatbots were attempting to fix was a complete red herring. An error message of “the $cashtag you selected is no longer active” would have been useful. The “AI” being aware of the incorrect error message would have also been useful. Telling me that my tag had been canceled to start instead of walking me in circles, uninstalling, reinstalling, clearing cache, the whole nine yards, would have been useful.

    Instead, two people spent four hours each trying to figure out two problems, one caused by the other. A full workday on a Saturday dedicated to troubleshooting issues the bots were blithely unaware of, even though it’s literally impossible this is the first time these specific issues came up at the company. That’s more than $200 of free labour to arrive somewhere that should have been known to the system.

    This is what you cause when you don’t use LLMs as intended.

    That said, I still use it as a far more powerful Grammarly, as even on my laptop, I have a nasty propensity for typing totally correct spellings of incorrect words, and it’s great as a fresh set of eyes where I’d fill in the word that should have been there upon editing. I generated a server image for a Discord based on an out-of-context line (a comically oversized rooster in an Alpine valley – taller than the Alps themselves – looking down on a scale cow, with a far less involved prompt), and there was much mirth and merriment.

    But these are no-stakes, low-impact uses. As soon as it’s adjacent to something mission critical, not just for a business but also their customers, the level of scrutiny for software needs to be as high as it was pre-ChatGPT. And since that negates imagined cost-savings, ain’t gonna happen.

    You can eventually work a screw into some materials with a hammer and insistence that it’s an improvement over a bespoke fucking screwdriver, but the substrate is damaged as a result.

    Just so with LLMs. But more and more people are expected to use them in a work environment without anything approaching sufficient training, often in situations where they aren’t domain experts. Garbage in, garbage out.

  • Water&Wings@beehaw.org
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    1 month ago

    I have ADHD and OCD, which means writing reports, proposals, and even simple emails is very difficult for me in a number of ways. For the last year or so, I tell ChatGPT what I want to say and I work to polish or complete what it gives me, and out comes exactly what I wanted.

    I’m not able to do that stuff myself. I’m just not mentally able to do it by myself. I strongly support ChatGPT and will continue to use it as as I can.