They say it's a waste that you pay for the tokens and then the inference provider pays for the electricity. Isn't that how everything works? I pay cucumbers and the farmers have to pay for the water and the fertilizer...
I hope that reasoning is an after-the-fact justification by the LLM that wrote this.
It's a ver interesting idea and I wouldn't mind trying it out, but with a smaller model. At 0.5t/s and reading many gigabytes from the SDD every second... I wonder if this wouldn't be extremely practical if targeting a 500gib or 250gib model, something that is still outside most consumers' laptop.
It is worth thinking about, when you're buying something, how much of what you're paying is the supplier's margin. And whether they have efficiency advantages over you doing it yourself. But for large LLMs it does seem like there's a pretty big efficiency advantage to the rack-scale hardware in datacenters compared to hacks like this.
here at 0.5 tok/s, it's like getting 1/100 of a tomato for your lunch per hour, and you can't just let it grow, you have to look at it growing just as you're about to eat, and it doesn't accumulate between meals
I hope that reasoning is an after-the-fact justification by the LLM that wrote this.
It's a ver interesting idea and I wouldn't mind trying it out, but with a smaller model. At 0.5t/s and reading many gigabytes from the SDD every second... I wonder if this wouldn't be extremely practical if targeting a 500gib or 250gib model, something that is still outside most consumers' laptop.