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Joined 1 year ago
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Cake day: July 9th, 2023

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  • a quick web search uses much less power/resources compared to AI inference

    Do you have a source for that? Not that I’m doubting you, just curious. I read once that the internet infrastructure required to support a cellphone uses about the same amount of electricity as an average US home.

    Thinking about it, I know that LeGoog has yuge data centers to support its search engine. A simple web search is going to hit their massive distributed DB to return answers in subsecond time. Whereas running an LLM (NOT training one, which is admittedly cuckoo bananas energy intensive) would be executed on a single GPU, albeit a hefty one.

    So on one hand you’ll have a query hitting multiple (comparatively) lightweight machines to lookup results - and all the networking gear between. One the other, a beefy single-GPU machine.

    (All of this is from the perspective of handling a single request, of course. I’m not suggesting that Wikipedia would run this service on only one machine.)



  • Thank you for responding! I really liked this bit

    with a (decently designed) UI, you merely have to remember the path you took to get to wherever you want to go, what buttons to press, what mouse movements to execute.

    I think that’s very insightful. I certainly have developed muscle-memory for many of my most-frequent commands in the CLI or editor of choice.

    I agree about Visual Studio as a preference. I’ve used (or at least tried) dozens of IDE setups down the years from vi/emacs to JetBrains/VS to more esoteric things like Code Bubbles. I’ve found my personal happy place but I’d never tell someone else their way of working was wrong.

    (Except for emacs devs. (Excepting again evil-mode emacs devs - who are merely confused and are approaching the light.)) ;)


  • I hope you take this in good humor and at least consider a TUI for your next project.

    Absolutely. I see what you did there… 😉

    But seriously, thank you for your response!

    I think your comment about GUIs being better at displaying the current state and context was very insightful. Most CLI work I do is generally about composing a pipeline and shoving some sort of data through it. As a class of work, that’s a common task, but certainly not the only thing I do with my PC.

    Multistage operations like, say, Bluetooth pairing I definitely prefer to use the GUI for. I think it is partially because of the state tracking inherent in the process.

    Thanks again!


  • As someone who genuinely loves the command line - I’d like to know more about your perspective. (Genuinely. I solemnly swear not to try to convince you of my perspective.)

    What about GUIs appeals to you over a command line?

    I like the CLI because it feels like a conversation with the computer. I explain what I want, combining commands as necessary, and the machine responds.

    With GUIs I feel like I’m always relearning tools. Even something as straightforward as ‘find and replace’ has different keyboard shortcuts in most of the text-editing apps I use - and regex support is spotty.

    Not to say that I think the terminal is best for all things. I do use an IDE and windowing environments. Just that - when there are CLI tools I tend to prefer them over an equivalent GUI tool.

    Anyway, I’m interested to hear your perspective- what about GUIs works better for you? What about the CLI is failing you?

    Thank you!




  • So… unlike Stable Diffusion or LLMs, the point of this research isn’t actually to generate a direct analog to the input, in this case video games. It’s testing to see if a generative model can encode the concepts of an interactive environment.

    Games in general have long been used in AI research because they are models of some aspect of reality. In this case, the researchers want to see if a generative AI can learn to predict the environment just by watching things happen. You know, like real brains do.

    E.g. can we train something that learns the rules of reality just by watching video combined with “input signals”. If so, it opens up whole new methods for training robots to interact with the real world.

    That’s why this is newsworthy beyond just “AI Buzz” cycle.



  • Nah. AI-generated content doesn’t “ruin” the internet any more than Disney can “ruin” Star Wars.

    The good stuff is still there. Always has been. Low effort Sora vids don’t reduce the entertainment value of - say - Tom Scott’s oeuvre.

    What AI spam does its the same thing all spam has ever done - increases the amount of noise we have to filter.

    Noise is always cheaper to manufacture than signal so it always appears to dominate. … but any given noise has no lasting commercial value, while high quality signal always does. That’s why the old newspaper companies are still around even when you can just read Twitter to get the gist of world events.

    Intelligence and thoughtful design matter.

    We’re gonna see a lot of AI spam for a couple years. But I promise you someone is already working hard to figure out how to identify it.

    When I first joined the internet it was considered virtually impossible to detect and block spam reliably. Now, email spam is a rare annoyance that only impacts us occasionally.

    Someone will crack AI-detection, or better yet, solve “this is noise” detection once and for all.