Raw LLM Responses

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G Haha 😄 nice game idea, but ChatGPT doesn’t have “life tokens.” I can’t lose poin… ytc_UgwUhKy1A… G Ai is perfectly fine in some situations Like it can help game developers get in… ytc_UgwG1h8kE… G This is what I do on Pneumatic Workflow-automating processes while ensuring my t… ytc_Ugwq3cmCS… G Have you ever talked to customer service? 9/10 they are totally useless (nothing… rdc_kyze96j G Interestingly enough, AI with neither succeed nor fail. Some AI (not LLMs) are a… ytc_Ugx5lo5Ii… G makes no sense, to derail the algorythm you would need to make a dent in the hug… ytc_Ugx_b3CZe… G I never want to be the party pooper but why the hell is the climate impact of ge… ytc_Ugzr4tejY… G About the only thing that would be best automated by robots is for sex. I want … ytc_UgjhUWrc9…
Comment
@protoney860why do you think I don't know how much AI uses? I'm not saying the amounts because it takes like 3 seconds to google it, doesn't mean I haven't looked into it. but heres some data "Large AI models like GPT-3, with many billions of parameters, are often trained and deployed on large clusters of servers with multiple graphic processing units (GPUs). These servers are so power-hungry they can consume a few kilowatts each, the equivalent of the average power consumption of an entire house. So, despite the recent algorithmic and hardware efficiency improvements, AI model training and inference still result in enormous energy consumption. Air pollution and carbon emissions are well-known environmental costs of AI. But, a much lesser-known fact is that AI models are also water guzzlers. They consume fresh water in two ways: onsite server cooling (scope 1) and offsite electricity generation (scope 2)." "Artificial Intelligence or AI consumes roughly up to 9 liters of water per kWh of its energy used in cooling towers and air mechanisms to dispatch heat." "AI's projected water usage could hit 6.6 billion m³ by 2027, signaling a need to tackle its water footprint." etc.
youtube Viral AI Reaction 2024-09-30T07:1…
Coding Result
DimensionValue
Responsibilitynone
Reasoningunclear
Policyunclear
Emotionindifference
Coded at2026-04-27T06:26:44.938723
Raw LLM Response
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