Father, Hacker (Information Security Professional), Open Source Software Developer, Inventor, and 3D printing enthusiast

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Joined 3 years ago
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Cake day: June 23rd, 2023

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  • No, no. You’ve got the wrong idea.

    Will AI completely ruin a zillion people’s ability to think (beyond what social media already accomplished)? Quite possibly!

    I’m just saying there’s nothing we can do to stop it at this point.

    You’re about to head down a long, lonely road as normies start using and accepting AI more and more into their lives while you scream into the abyss. I’ve been there with fossil fuels, copyright, software patents, and Linux.

    People saying “Just use AI!” Is about to live rent free in your head as your most-hated phrase. Just like, “stop driving gas guzzlers!” Or, “stop bitching about Windows and just install Linux already!” Lives in so many others.

    At least most people don’t think of AI as a core part of their identity (e.g. pickup trucks) 🤷



  • (And we do all the fancy shit, looping, custom harnesses, orchestrations, handovers, savepoints, post delivery pipelines, autoremediation, blablabla, context, graphs blabla)

    Yeah that’s not what I’m talking about. That’s just coding stuff and I think everyone is learning a hard lesson right now that there’s really two ways to do AI (for code):

    1. You let the AI write all the code. Using those techniques you mentioned to try to keep it from fucking up too much.
    2. You use the AI to fix/write a little bit of the code at a time. Manually. As in, someone who knows software architecture really well tells the AI to write a function or two or maybe even a whole module and that’s it. They do this repeatedly until their task is complete.

    #1 is a very expensive way to do it but it seems to work, albeit with a huge learning curve and a much longer horizon before you get something stable. Even then, what you get can be a giant fucking mess that’s really, really hard to understand.

    #2 is much safer and works quite well, IMHO. When the AI fucks something up, it’s only a tiny little thing that’s easy to fix. This method really is just a way for developers to improve their productivity.

    With #2, it only takes a small amount of tokens to have the AI help you troubleshoot as well. At least, that’s been my experience.

    Having said that, the places where we are seeing the most growth in AI is small shit. For example, at my work they implemented an agent that scans customer complaints and filters out false positives. I work for a huge company that has a zillion products/services and the AI has tool calls into our ticketing systems to check if there was an outage at the time the customer complained. It’s not that smart, but it’s smart enough to tell if a ticket about system X was opened when system X had an outage. It can even tell if the customer was complaining about something relevant to the outage.

    Stuff like that runs 24/7 and eats up bazillions of tokens, but only on our local hardware (we have thousands of enterprise GPUs). At other companies, they’re doing similar things and slowly realizing they can replace OpenAI/Anthropic API calls with local ollama stuff.

    Even if your token bill is $10,000/month for a service like that, it’s still cheaper than paying an entire team of humans to perform the same function.

    That is the growing use of AI automation I was talking about.


  • It’s too late for that scenario. LLMs are already widespread on millions of computers.

    On my old 4060 Ti 16GB I can run Qwen3.8:14b and that’s actually good enough for loads and loads of things. It’s actually overkill for a lot of stuff too which is why tiny models are all the rage right now (e.g. 0.8b models).

    Let’s say the government banned LLMs. Are they really going to want to halt pharmaceutical and biomedical research like that? Are they going to start inspecting/requiring everyone’s computers be scanned regularly for AI models?

    No. It’s unrealistic to think they can do anything at all to stop AI. If we ban it in the US, the world will just use AI services offered from other countries and then the US won’t be able to compete because those countries will become vastly more productive.

    As much as everyone on Lemmy believes all AI output is “slop”, it really does do useful stuff! It’s just most of the useful stuff doesn’t make the news. It’s boring things like checking if an uploaded image is NSFW or if an uploaded document has everything it’s supposed to have or follows the correct format.

    AI/LLMs are also checking the grammar of basically everything that gets published. Anyone who’s not using AI for that is an idiot. It’s just way too fucking good at spotting grammatical errors, incorrect word use (often innocent typos that normal grammar checking tools miss), and similar problems.

    There’s fucktons of super useful, good ways to use AI. We’d be stupid to just ban it and pretend it isn’t good for a lot of things.

    We can regulate its use but that’s not really “regulating AI” as much as it is “regulating capitalism” or “regulating people”. Because the AI isn’t just going out on its own to spam misinformation or mislead consumers with generated product photos. Someone told it to do those things.

    What we need isn’t “AI regulation” is regular regulation that prevents companies from behaving badly.



  • Given the monumental difference between those two figures, investors across the world of finance are taking it as a sign that demand for AI is much lower than previously thought

    No. Demand for OpenAI’s services is lower than they thought.

    Every day, the open weights models get smarter and cheaper and new competitors are coming online every few weeks. They cost a fraction of what OpenAI charges.

    Demand for AI products and services is continuing to grow at a break-the-world pace. It’s just these big “AI first movers” are in trouble because it’s too easy to copy what they do. They expected an enormous “first mover advantage” (which is a real thing) but it turns out that AI is trivial to train and replicate (just have to scrape the Internet and scan a lot of books).

    In other words, it’s turning out that “first mover” is a disadvantage in this (AI) industry.