Popular #largelanguagemodels #OpenAI’s #ChatGPT #GoogleBard are energy-intensive, requiring #massive #serverfarms 2 provide enough data 2 train the powerful programs. Cooling those same data centers also makes the #AI #chatbots incredibly thirsty. New research suggests training for #GPT3 alone consumed 185,000 gallons (700,000 liters) of water. Average user’s conversational exchange w ChatGPT basically amounts to dumping a large bottle of fresh water out on the ground https://gizmodo.com/chatgpt-ai-water-185000-gallons-training-nuclear-1850324249

If you're worried about #ChatGPT & other #ArtificialIntelligence, Jon Naughton (Observer) thinks you might be focusing on the wrong aspect of the #AI 'revolution';

whatever its impact on human communication & analysis, behind the #technology sits a massive requirement for #energy to run the software from massive #serverfarms it requires for computation.

So, the real danger of AI may in the end by its growing role in the #climatecrisis

#solar situation: in order to know #watts up you have to be aware of your #volts and #amps. #ohm is not just a #mantra to call out to #Buddha. Living simply includes decreasing your energy needs with efficient appliances . Nowadays so many things charge via USB so there are many choices. Do an energy audit and eliminate #phantomLoads . we can design better and conserve resources. #ServerFarms are devouring our grid capacity. Does #mastodon distributed model avoid this?