

As for the power/environmental impact, for what they do LLMs are actually very low impact per-request.
Worth noting that a request is often dozens of requests now that there’s “reasoning,” even for search. As I understand it, a model will take a question , figure out the context (one request), reform the question so it yields better results (another request), if it’s doing a web search there’s requests for each result, another to compare, another to check if it answers the original request, if not it loops and does it all over again. So one request is easily, and often, dozens of requests. This is one way Ai companies can say to investors, “see, look at how much usage has increased.”
Also, we need to factor in the power to scrape and train each of those models, build the datacenters which is near impossible as these companies are not transparent about it and actively try to obstruct investigations into it. Then there’s the redundancy of all these different companies competing and doing roughly the same thing at the same time, as fast as they can, so it’s orders of magnitude inefficient energy consuming before it gets its first user prompt.
Comparing it to other assaults on the environment is not only hard to do, but a case of “the worse negates the bad” fallacy.






Used this all the time until I recently stumbled across the cli program
units