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.
There were people estimating 40w in earlier threads on lemmy which was ridiculous.
This seems more realistic.
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?
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.
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 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.
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.
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.
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.
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.
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.
Yeah that’s a good point, too. 😊
On a “respond to an individual query” level, yeah it’s not that much. But prior to response the data center had to be constructed, the entire web had to be scraped, the models trained, the servers continually ran regardless of load. There’s also way too many “hidden” queries across the web in general from companies trying to summarize every email or product.
All of that adds to the energy costs. This equivocation is meant to make people feel less bad about the energy impact of using AI, when so much of the cost is in building AI.
Furthermore, that’s the median value–the one that falls right in the middle of the quantity of queries. There’s a limit to how much less energy a query to the left of the median can use; there’s a significantly higher runway to the right of the median for excess energy use. This also only accounted for text queries; images and video generation efforts are gonna use a lot more.
All of that adds to the energy costs
But do you actually know how much that is? Or are you just assuming it’s a lot.
Your points are valid, but I think that building AI has benefits beyond simply enabling people to use that AI. It advances the state of the art and makes even more powerful AI possible. Still, it would be good to know about the amortized cost per query of building the AI in addition to the cost of running it.
Individually you’re spot on. Your AI use doesn’t matter. But, and this is where companies tend to leave off, when you take into account how many millions (or billions) of times something is done in a day (like AI prompts), then that’s when it genuinely matters.
To me, this is akin to companies trying to pass the blame to consumers when it’s the companies themselves who are the biggest climate offenders.
I don’t see why this argument works better against AI than it does against microwaves. Those are used hundreds of millions of times a day too.
You’re right. But if I had to pick a why, I’d go with how microwaves at least provide a service for households by heating up food.
AI’s only viable service (at the time of this writing) is a replacement for viagra for techbros when they need to get an erection.
This doesn’t really track with companies commissioning power plants to support power usage of AI training demand
They want to handle lots of prompts.
The article also mentions each enquiry also evaporates 0.26 of a milliliter of water… or “about five drops”.
I wonder how many people clutching their pearls over this also eat meat…
Microwaves are very energy heavy. This isn’t very reassuring at all.
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.
Nice share! Mistral also shared data about one of its largest model (not the one that answer in LeChat, since that one is Medium, a smaller model, that I guess has smaller energetic requirements)
https://mistral.ai/news/our-contribution-to-a-global-environmental-standard-for-ai
Let’s see OpenAI’s numbers
So as thought virtually no impact. AI is here and not leaving. It will outlast humans on earth probably.
