this post was submitted on 01 Jul 2025
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I know she's exaggerating but this post yet again underscores how nobody understands that it is training AI which is computationally expensive. Deployment of an AI model is a comparable power draw to running a high-end videogame. How can people hope to fight back against things they don't understand?
It's closer to running 8 high-end video games at once. Sure, from a scale perspective it's further removed from training, but it's still fairly expensive.
really depends. You can locally host an LLM on a typical gaming computer.
Well that's sort of half right. Yes you can run the smaller models locally, but usually it's the bigger models that we want to use. It would also be very slow on a typical gaming computer and even a high end gaming computer. To make it go faster not only is the hardware used in datacenters more optimised for the task, it's also a lot faster. This is both a speed increase per unit as well as more units being used than you would normally find in a gaming PC.
Now these things aren't magic, the basic technology is the same, so where does the speed come from? The answer is raw power, these things run insane amounts of power through them, with specialised cooling systems to keep them cool. This comes at the cost of efficiency.
So whilst running a model is much cheaper compared to training a model, it is far from free. And whilst you can run a smaller model on your home PC, it isn't directly comparable to how it's used in the datacenter. So the use of AI is still very power hungry, even when not counting the training.