Cool, now how much power was consumed before even a single prompt was ran in training that model, and how much power is consumed on an ongoing basis adding new data to those AI models even without user prompts. Also how much power was consumed with each query before AI was shoved down our throats, and how many prompts does an average user make per day?
I did some quick math with metas llama model and the training cost was about a flight to Europe worth of energy, not a lot when you take in the amount of people that use it compared to the flight.
Whatever you’re imagining as the impact, it’s probably a lot less. AI is much closer to video games then things that are actually a problem for the environment like cars, planes, deep sea fishing, mining, etc. The impact is virtually zero if we had a proper grid based on renewable.
If their energy consumption actually was so small, why are they seeking to use nuclear reactors to power data centres now?
Because demand for data centers is rising, with AI as just one of many reasons.
But that’s not as flashy as telling people it takes the energy of a small country to make a picture of a cat.
Also interesting that we’re ignoring something here – big tech is chasing cheap sources of clean energy. Don’t we want cheap, clean energy?
Didn’t xitter just install a gas powered data center that’s breaking EPA rules for emissions?
Yes, yes it did. And as far as I can tell, it’s still belching it out, just so magats can keep getting owned by it. What a world
Sure we do. Do we want the big tech corporations to hold the reins of that though?
If cheap(er/better) energy is invented then that’s good, why would tech corpos be able to “hold the reins” of it exclusively?
Well, patents and what have you are a thing. I’m mostly thinking that I wouldn’t want e.g. Facebook to run any nuclear reactors or energy grids. That’s something I prefer the government does.
Nuclear reactors already exist, that’s not new tech.
To be fair, nuclear power is cool as fuck and would reduce the carbon footprint of all sorts of bullshit.
Volume of requests and power consumption requirements unrelated to requests made, at least I have to assume. Certainly doesn’t help that google has forced me to make a request to their ai every time I run a standard search.
Seriously. I’d be somewhat less concerned about the impact if it was only voluntarily used. Instead, AI is compulsively shoved in every nook and cranny of digital product simply to justify its own existence.
The power requirement for training is ongoing, since mere days after Sam Altman released a very underehelming GPT-5, he begins hyping up the next one.
I also never saw a calculation that took into amount my VPS costs. The fckers scrape half the internet, warming up every server in the world connected to the internet. How much energy is that?
That’s not small…
100’s of Gigawatts is how much energy that is. Fuel is pretty damn energy dense.
A Boeing 777 might burn 45k Kg of fuel, at a density of 47Mj/kg. Which comes out to… 600 Megawatts
Or about 60 houses energy usage for a year in the U.S.
It’s an asinine way to measure it to be fair, not only is it incredibly ambiguous, but almost no one has any reference as to how much energy that actually is.
Because the training has diminishing returns, meaning the small improvements between (for example purposes) GPT 3 and 4 will need exponentially more power to have the same effect on GPT 5. In 2022 and 2023 OpenAI and DeepMind both predicted that reaching human accuracy could never be done, the latter concluding even with infinite power.
So in order to get as close as possible then in the future they will need to get as much power as possible. Academic papers outline it as the one true bottleneck.
And academia will work on that problem. It reminds me of intel processors “projected” to use kilowatts of energy, then smart people made other types of chips and they don’t need 2000 watts.
Academia literally got cut by more than a third and Microsoft is planning to revive breeder reactors.
You might think academia will work on the problem but the people running these things absolutely do not.
Found the American.
I’d like to understand what this math was before accepting this as fact.
I usually liken it to video games, ya. Is it worse that nothing? Sure, but that flight or road trip, etc, is a bigger concern. Not to mention even before AI we’ve had industrial usage of energy and water usage that isn’t sustainable… almonds in CA alone are a bigger problem than AI, for instance.
Not that I’m pro-AI cause it’s a huge headache from so many other perspectives, but the environmental argument isn’t enough. Corpo greed is probably the biggest argument against it, imo.
A flight to Europe’s worth of energy is a pretty asinine way to measure this. Is it not?
It’s also not that small the number, being ~600 Megawatts of energy.
However, training cost is considerably less than prompting cost. Making your argument incredibly biased.
Similarly, the numbers released by Google seem artificially low, perhaps their TPUs are massively more efficient given they are ASICs. But they did not seem to disclose what model they are using for this measurement, It could be their smallest, least capable and most energy efficient model which would be disingenuous.
The real question is why anyone would want to use more power than a regular search engine to get answers that might confidently lie to you.
if it’s Google that they would use us the search engine, search results are turning to shit. it just often doesn’t show you the relevant stuff. The AI overview is wrong. Ads sometimes take up the entire first page of results. so I see why someone would just want to show a question into the void and get a quick response instead of having to sort through five crappy results, after filtering that down from 15 possibly relevant ones
I use DuckDuckGo. I use its AI features mainly for stock projections and to search for information on company earnings release. Because when I try to search for earnings schedule by myself, I get conflicting information. DDG AI is actually pretty useful to read troves of webpages and find the relevant information for me in that regard.
The company has signed agreements to buy over 22 gigawatts of power from sources including solar, wind, geothermal, and advanced nuclear projects since 2010.
None of those advanced nuclear projects are yet actually delivering power, AFAIK. They’re mostly in planning stages.
The above isn’t all to run AI, of course. Nobody was thinking about datacenters just for AI training in 2010. But to be clear, there are 94 nuclear power plants in the US, and a rule of thumb is that they produce 1GW each. So Google is taking up the equivalent of roughly one quarter of the entire US nuclear power industry, but doing it with solar/wind/geothermal that could be used to drop our fossil fuel dependence elsewhere.
How much of that is used to run AI isn’t clear here, but we know it has to be a lot.
None of those advanced nuclear projects are yet actually delivering power, AFAIK.
…and they won’t be for at least 5-10 years. In the meantime they’ll just use public infrastructure and then when their generation plans fall through they’ll just keep doing that.
This feels like PR bullshit to make people feel like AI isn’t all that bad. Assuming what they’re releasing is even true. Not like cigarette, oil, or sugar companies ever lied or anything and put out false studies and misleading data.
However, there are still details that the company isn’t sharing in this report. One major question mark is the total number of queries that Gemini gets each day, which would allow estimates of the AI tool’s total energy demand.
Why wouldn’t they release this. Even if each query uses minimal energy, but there are countless of them a day, it would mean a huge use of energy.
Which is probably what’s happening and why they’re not releasing that number.
That’s because it is. This is to help fence riders feel better about using a product that factually consumes insane amounts of resources.
In total, the median prompt—one that falls in the middle of the range of energy demand—consumes 0.24 watt-hours of electricity, the equivalent of running a standard microwave for about one second. The company also provided average estimates for the water consumption and carbon emissions associated with a text prompt to Gemini.
The human mind uses about 100 watt. The equivalent would be 400 questions per hour, 6 per minute or one every 10 seconds. That’s close to human capacity.
There are zero downsides when mentally associating an energy hog with “1 second of use time of the device that is routinely used for minutes at a time.”
With regard to sugar: when I started counting calories I discovered that the actual amounts of calories in certain foods were not what I intuitively assumed. Some foods turned out to be much less unhealthy than I thought. For example, I can eat almost three pints of ice cream a day and not gain weight (as long as I don’t eat anything else). So sometimes instead of eating a normal dinner, I want to eat a whole pint of ice cream and I can do so guilt-free.
Likewise, I use both AI and a microwave, my energy use from AI in a day is apparently less than the energy I use to reheat a cup of tea, so the conclusion that I can use AI however much I want to without significantly affecting my environmental impact is the correct one.
You should probably not eat things because of how much calories they have or don’t have, but because of how much of their nutrients you need, and how much they lack other, dangerous shit. Also eat slowly until you’re full and no more. Also move a lot.
We shouldn’t need calculators for this healthy lifestyle.
The reason for needing to know which foods are healthy is because… well, we forgot.
I’m not saying that ice cream is healthier than a normal dinner, just that if I really crave something sweet then the cost to my health of eating it periodically is actually quite low, whereas the cost of some other desserts (baked sweets are often the worst offenders) is relatively high. That means that a lot can be gained simply by replacing one dessert with a different, equally tasty dessert. Hence my ice cream advocacy.
In addition:
This report was also strictly limited to text prompts, so it doesn’t represent what’s needed to generate an image or a video.
Now do training centers, since it’s obvious they are never going to settle on a final model as they pursue the Grail of AGI. I could do the exact same comparison with my local computer and claim that running a prompt only uses X amount of watts because the GPU heats up for a few seconds and is done. But if I were to do some fine tuning or other training, that fan will stay on for hours. A lot different.
Microwaves are very energy heavy. This isn’t very reassuring at all.
There were people estimating 40w in earlier threads on lemmy which was ridiculous.
This seems more realistic.
40 watt hours.
So as thought virtually no impact. AI is here and not leaving. It will outlast humans on earth probably.
As thought by whom? Dumbasses?
median prompt size
Someone didn’t pass statistics, but did pass their marketing data presention classes.
Wake me up when they release useful data.
It is indeed very suspicious that they talk about “median” and not “average”.
For those who don’t understand what the difference is, think of the following numbers:
1, 2, 3, 34, 40
The median is 3, because it’s in the middle.
The average is 16 (1+2+3+34+40=80, 80/5=16).
the big thing to me is I want them to compare the same thing with web searches. so they want to use median then fine but median ai query to median google search.
Tbh, that won’t be useful, like the guy above stated.
Google searches are very similar in terms of work that needs to be done. You could expect the average and the median to be very close. For example, take these numbers: 1,1,2,2,3. The median is 2, the average is 1.8.
AI requests vary wildly. GPT-5 for example uses multiple different internal models ranging from very small text-only models to huge, reasoning models and image generation models. While there’s no way to know how much energy they use without OpenAI publishing data, you can compare how long computation takes.
For a fast, simple text-only answer ChatGPT using GPT-5 takes a second or so to start writing and maybe 5 seconds to finish. To generate an image it might take a minute or two. And if you dump some code in there and tell it to make large adaptions to the code it can take 10+ minutes to generate that. That’s a factor of more than 100x. If most answers are done by the small text-only models, then the median will be in the 5 second range while the average might be closer to 100 seconds or so, so median and average diverge a lot.
