The energy expenditure for GPT models is basically a per-token calculation. Having it generate a list of 3-4 token responses would barely be a blip compared to having it read and respond entire articles.
There might even be a case for certain tasks with a GPT model being more energy efficient than making multiple google searches for the same. Especially considering all the backend activity google tacks on for tracking users and serving ads, complaining about someone using a GPT model for something like generating a list of words is a little like a climate activist yelling at someone for taking their car to the grocery store while standing across the street from a coal-burning power plant.
… someone using a GPT model for something like generating a list of words is a little like a climate activist yelling at someone for taking their car to the grocery store while standing across the street from a coal-burning power plant.
no, it’s like a billion people taking their respective cars to the grocery store multiple times a day each while standing across the street from one coal-burning power plant.
each person can say they are the only one and their individual contribution is negligible. but get all those drips together and you actually have a deluge of unnecessary wastage.
Except each of those drips are subject to the same system that preferences individualized transport
This is still a perfect example, because while you’re nit-picking the personal habits of individuals who are a fraction of a fraction of the total contributors to GPT model usage, huge multi-billion dollar entities are implementing it into things that have no business using it and are representative for 90% of llm queries.
Similar for castigating people for owning ICE vehicles, who are not only uniquely pressued into their use but are also less than 10% of GHG emissions in the first place.
Stop wasting your time attacking individuals using the tech for help in their daily tasks, they aren’t the problem.
The energy expenditure for GPT models is basically a per-token calculation. Having it generate a list of 3-4 token responses would barely be a blip compared to having it read and respond entire articles.
There might even be a case for certain tasks with a GPT model being more energy efficient than making multiple google searches for the same. Especially considering all the backend activity google tacks on for tracking users and serving ads, complaining about someone using a GPT model for something like generating a list of words is a little like a climate activist yelling at someone for taking their car to the grocery store while standing across the street from a coal-burning power plant.
no, it’s like a billion people taking their respective cars to the grocery store multiple times a day each while standing across the street from one coal-burning power plant.
each person can say they are the only one and their individual contribution is negligible. but get all those drips together and you actually have a deluge of unnecessary wastage.
Except each of those drips are subject to the same system that preferences individualized transport
This is still a perfect example, because while you’re nit-picking the personal habits of individuals who are a fraction of a fraction of the total contributors to GPT model usage, huge multi-billion dollar entities are implementing it into things that have no business using it and are representative for 90% of llm queries.
Similar for castigating people for owning ICE vehicles, who are not only uniquely pressued into their use but are also less than 10% of GHG emissions in the first place.
Stop wasting your time attacking individuals using the tech for help in their daily tasks, they aren’t the problem.