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.
Google processes over 5 trillion search queries per year. Attaching an AI inference call to most if not all of those will increase electricity consumption by at least an order of magnitude.
Edit: using their own 0.24Wh number, that equates to 1.2 billion kWh per year, or about the equivalent of 114,285 USA homes.
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.
Please show your math.
One Nvidia H100 DGX AI server consumes 10.2kW at 100% utilization, meaning that
one hour’s42 day’s use of one server is equivalent to the electricity consumption of the average USA home in one year. This is just a single 8-GPU server; it excludes the electricity required by the networking and storage hardware elsewhere in the data center, let alone the electricity required to run the facility’s climate control.xAI alone has deployed hundreds of thousands of H100 or newer GPUs. Let’s SWAG 160K GPUs = ~20K DGX servers = >200MW for compute alone.
H100 is old. State of the art GB200 NVL72 is 120kW per rack.
Musk is targeting not 160K, but literally one million GPUs deployed by the end of this year. He has built multiple new natural gas power plants which he is now operating without any environmental permits or controls, to the detriment of the locals in Memphis.
This is just one company training one typical frontier model. There are many competitors operating at similar scale and sadly the vast majority of their new capacity is running on hydrocarbons because that’s what they can deploy at the scale they need today.
I should have specified it was an earlier llama model. They have scaled up to more then a flight or two. You are mostly right except for how much a house uses. It’s about 10,500 kW per year, you’re off by a thousand. It uses in an hour about 8 hours of house time, which is still a lot though, specially when you consider musks 1 million gpus.
Their first model took 2 600 000 kwh, a plane takes about 500 000. The actual napkin math was 5 flights. I had done the math like 2 years ago but yeah, I was mistaken and should have at least specified it was for their first model. Their more recent ones have been a lot more energy intensive I think.
Thanks for catching, you are right that the average USA home is 10.5MWh/year instead of kWh. I was mistaken. :)
Regarding the remainder, my point is that the scale of modern frontier model training, and the total net-new electricity demand that AI is creating is not trivial. Worrying about other traditional sources of CO2 emissions like air travel and so forth is reasonable, but I disagree with the conclusion that AI infrastructure is not a major environmental and climate change concern. The latest projects are on the scale of 2-5GW per site, and the vast majority of that new electricity capacity will come from natural gas or other hydrocarbons.
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?
Sir we do not make reasonable points in here, you’re supposed to hate AI irrationally and shut up.
AI is the driver of the parabolic spike in global data center buildouts. No other use case comes close in terms of driving new YoY growth in tech infra capex spend.
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.
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.
Did the EU suddenly develop a tech industry overnight or are you unaware where all the major AI companies are located?
I’d like to understand what this math was before accepting this as fact.
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.
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.
This doesn’t really track with companies commissioning power plants to support power usage of AI training demand
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.
There were people estimating 40w in earlier threads on lemmy which was ridiculous.
This seems more realistic.
40 watt hours.
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).
So as thought virtually no impact. AI is here and not leaving. It will outlast humans on earth probably.
As thought by whom? Dumbasses?
