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.
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.
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?
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.
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.