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.
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?
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.
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?
Sure we do. Do we want the big tech corporations to hold the reins of that though?
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
https://tennesseelookout.com/2025/07/07/a-billionaire-an-ai-supercomputer-toxic-emissions-and-a-memphis-community-that-did-nothing-wrong/
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.
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.
That’s not ~600 Megawatts, it’s 587 Megawatt-hours.
Or in other terms that are maybe easier to understand: 5875 fully charged 100kWh Tesla batteries.