• Yep.

        This was never the fault of AI.
        Its always the corporations- by nature, they’re designed to go with what gets the most profit at any cost.
        Just look at what they do to the meat industry to living creatures and their living employees who have to deal with it.

        I don’t think people appreciate just how dangerously willing these current AI companies are to set fire to the upcoming few decades of society- all for a little bit of glory right now.

        The energy problem is definitely one thing I didn’t realize was quite so dire, but we’re on the cusp of total loss of control over your own likeness, and these companies really couldn’t care less.

    • Ai has replaced so much of what I used to Google search for, but without the blog fluff (though it adds its own flavour of fluff).

      All of it is low stakes, so I’m not worried about the accuracy as long as it keeps me moving on a task.

      • I tried this recently in hopes of finding an animation pilot, it was too willing to give me completely wrong answers (the most popular things or even kids shows) or it’d just make a name up. Admittedly, I was using 13b.Q4 models and they are not the newest ones.

        I ended up finding what I was looking for by pure coincidence: I did a generic search (finding adult swim pilots (I had combed the wikipedia page and their site already)) and one of the higher results is a reddit thread where someone was looking for the same show I was and they made the same mistake that I made (mistaking a Cartoon Hangover short for an Adult Swim pilot).

        After that I tried finding an even older and dumber animation that I had gotten on the PSN during the PS3 era, those terms tripped the AI up because it would only give me videogames.

        (Certain things are probably better to ask, I’d say I’m not sure about computation being worth it but then again search is pretty garbage these days unless it’s an obvious query that won’t be mixed up with other newer/more-popular terms)

  •  Zaktor   ( @Zaktor@sopuli.xyz ) 
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    4 months ago

    de Vries, who now works for the Netherlands’ central bank, estimated that if Google were to integrate generative A.I. into every search, its electricity use would rise to something like twenty-nine billion kilowatt-hours per year. This is more than is consumed by many countries, including Kenya, Guatemala, and Croatia.

    Why on earth would they do that? Just cache the common questions.

    It’s been estimated that ChatGPT is responding to something like two hundred million requests per day, and, in so doing, is consuming more than half a million kilowatt-hours of electricity. (For comparison’s sake, the average U.S. household consumes twenty-nine kilowatt-hours a day.)

    Ok, so the actual real world estimate is somewhere on the order of a million kilowatt-hours, for the entire globe. Even if we assume that’s just US, there are 125M households, so that’s 4 watt-hours per household per day. A LED lightbulb consumes 8 watts. Turn one of those off for a half-hour and you’ve balanced out one household’s worth of ChatGPT energy use.

    This feels very much in the “turn off your lights to do you part for climate change” distraction from industry and air travel. They’ve mixed and matched units in their comparisons to make it seem like this is a massive amount of electricity, but it’s basically irrelevant. Even the big AI-every-search number only works out to 0.6 kwh/day (again, if all search was only done by Americans), which isn’t great, but is still on the order of don’t spend hours watching a big screen TV or playing on a gaming computer, and compares to the 29 kwh already spent.

    Math, because this result is so irrelevant it feels like I’ve done something wrong:

    • 500,000 kwh/day / 125,000,000 US households = 0.004 kwh/household/day
    • 29,000,000,000 kwh/yr / 365 days/yr / 125,000,000 households = 0.6 kwh/household/day, compared to 29 kwh base
    • Just cache the common questions.

      AI models work in a feedback loop. The fact that you’re asking the question becomes part of the response next time. They could cache it, but the model is worse off for it.

      Also, they are Google/Microsoft/OpenAI. They will do it because they can and nobody is stopping them.

      •  Zaktor   ( @Zaktor@sopuli.xyz ) 
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        14 months ago

        This is AI for search, not AI as a chatbot. And in the search context many requests are functionally similar and can have the same response. You can extract a theme to create contextual breadcrumbs that will be effectively the same as other people doing similar things. People looking for Thai food in Los Angeles will generally follow similar patterns and need similar responses, even if it comes in the form of several successive searches framed as sentences with different word ordering and choices.

        And none of this is updating the model (at least not in a real-time sense that would require re-running a cached search), it’s all short-term context fed in as additional inputs.

  • So I did a little math.

    This site says a single ChatGPT query consumes 0.00396 KWh.

    Assume an average LED light bulb is 10 watts, or 0.01 kwh/hr. So if I did the math right, no guarantees there, a single ChatGPT query is roughly equivalent to leaving a light bulb on for 20 minutes.

    So if you assume the average light bulb in your house is on a little more than 3 hours a day, if you make 10 ChatGPT queries per day it’s the equivalent of adding a new light bulb to your house.

    Which is definitely not nothing. But isn’t the end of the world either.

    • I have a feeling it’s not going to be the ordinary individual user that’s going to drive the usage to problematic levels.

      If a company can make money off of it, consuming a ridiculous amount of energy to do it is just another cost on the P & L.

      (Assuming of course that the company using it either pays the electric bill, or pays a marked-up fee to some AI/cloud provider)

  • The bigger companies focus on huge model sizes instead and ever increasing them. Lots of advanced are being made with smaller and more affordable models that can be run on consumer devices but the big companies don’t focus on that as it can’t generate as much profit.

    • The problem is that all of the current discussion and hype is about Chat GPT and similar whole internet models. They are not as useful as more specialized small model ones, but they also not as easy to hype.