There were people estimating 40w in earlier threads on lemmy which was ridiculous.

This seems more realistic.

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?

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.

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.

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?

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.

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.

Yet they've never needed to commission power plants to dedicate power to these facilities. It's almost like there's some new, uniquely power-hungry demand that's driving this that's sprung up in the last 5 or so years...

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?

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 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.