I think if we, as a community, really put our heads together, we could figure out how to define and make useful user-respecting tools that incorporate LLMs. There are a lot of hard problems, like the massive power consumption, and the ethical use of data, that I don’t really know how to solve.
I think a start would be to focus on making smaller, lower-complexity models that are built for purpose, rather than trying to make a jillion-parameter jack-of-all-trades trades model. I think it would also make sense to focus initially on areas where there are already large corpuses of freely available text, like all the writings in the public domain. But I don’t really have a good idea of what these tools would be used for, exactly, which is where I’m stuck.
The energy consumption can be measured, very approximately, by the cost of the tokens. If you design agentic tools to make use of fewer, cheaper tokens then you’re likely also minimizing the energy usage.
How vague of a guess is that when people rely on those closed systems? We all know Corporate AI is hiding the actual costs with creative accounting while they enjoy abusing the environment…
If those cloud models are getting comparable results but using way more electricity, why would companies be running them? They like making profit, don’t they? They’re not some kind of Captain Planet villains chortling at being maximally wasteful.
We know the AI megacorporations are not profiting off it. Why would you pretend otherwise? Other you are very ignorant, or you’re being dishonest right now.
I think if we, as a community, really put our heads together, we could figure out how to define and make useful user-respecting tools that incorporate LLMs. There are a lot of hard problems, like the massive power consumption, and the ethical use of data, that I don’t really know how to solve.
I think a start would be to focus on making smaller, lower-complexity models that are built for purpose, rather than trying to make a jillion-parameter jack-of-all-trades trades model. I think it would also make sense to focus initially on areas where there are already large corpuses of freely available text, like all the writings in the public domain. But I don’t really have a good idea of what these tools would be used for, exactly, which is where I’m stuck.
The energy consumption can be measured, very approximately, by the cost of the tokens. If you design agentic tools to make use of fewer, cheaper tokens then you’re likely also minimizing the energy usage.
How vague of a guess is that when people rely on those closed systems? We all know Corporate AI is hiding the actual costs with creative accounting while they enjoy abusing the environment…
Comparisons can be made using open AI models. I run some locally on my own hardware, I know exactly how much energy they use.
I wasn’t talking about the closed source models you use. I was talking about the cloud ones you were just discussing.
And I said comparisons can be made.
If those cloud models are getting comparable results but using way more electricity, why would companies be running them? They like making profit, don’t they? They’re not some kind of Captain Planet villains chortling at being maximally wasteful.
We know the AI megacorporations are not profiting off it. Why would you pretend otherwise? Other you are very ignorant, or you’re being dishonest right now.