discolé monade

this is just one of amazingly st00pid threads that YOU can enjoy... if you act now.

holy shite. just gonna come on in here and go for the jugular. weird flex....but ok.

da'fuq? who is mrs white? wait....wait...THAT mrs white?

i'm just kidding. get back in here and play this stupid shit.

russell crowe, in a hotel with a _______________________

you know she was the slap heard around the world....back then. late 80's

but that is now an after fact, i wanted actual... fuck it... keep it rollin;

TELESCOPE ffs

all right.... zsa zsa gabor, in beverly hills, with a ______________

everyone say THANKS INSIPID!

lmao........

nooo so obvious. you suck. i bet you get the part in the pron, where the pizza guy rings the bell... and BOOM. you're done. damn. this could have been THE thread.

in the observatory, with a ______________

AI is considered highly resource-intensive and potentially wasteful, with its environmental footprint expanding rapidly due to energy consumption, water usage for cooling, and the generation of electronic waste (e-waste). While AI can aid in sustainability, its current development phase involves massive data centers that consumed roughly 4.4% of U.S. electricity in 2023, a number projected to surge in the coming years. Here is a breakdown of how wasteful AI is across different categories: 1. Energy Consumption and Carbon Footprint Training vs. Usage: Training a single large AI model can consume over 1,200 MWh of electricity, equivalent to powering 120 U.S. homes for a year. Inference (Daily Use): Over 80% of AI's electricity consumption comes from the inference phase—using the model to generate responses. Comparison to Search: A single ChatGPT request requires roughly ten times more electricity than a standard Google search. Advanced Models: "Reasoning" models, which "think" before they speak, can consume up to 50–100 times more energy than standard AI queries. 2. Massive Water Usage Data centers require significant amounts of water for cooling to prevent servers from overheating. Daily Impact: Generating a 100-word email with ChatGPT-4 can consume 519 milliliters of water—roughly a full bottle. Total Volume: By 2027, global AI demand is expected to consume 4.2 to 6.6 billion cubic meters of water, exceeding the total annual water withdrawal of countries like Denmark. 3. Electronic Waste (E-Waste) and Mining The rapid advancement of AI hardware leads to short lifespans for equipment. Hardware Turnover: GPUs and other high-performance computing components are replaced every 2–5 years, contributing to the 62 million tonnes of e-waste produced globally in 2022. Raw Materials: Manufacturing AI hardware requires mining rare earth elements, which contributes to habitat destruction and soil degradation. 4. Hidden Costs and Inefficiencies Underreported Data: Many AI companies do not disclose the exact energy or water consumption of their models, making it difficult to fully calculate the environmental impact. "Red AI" vs. "Green AI": The current, dominant trend is "Red AI," which focuses on larger, more accurate models at the expense of environmental efficiency. Conversely, "Green AI" aims for more efficient, sustainable methods. Superfluous Usage: Creating five seconds of AI video can consume as much electricity as running a microwave for over an hour.

the destruction of the human body and it's acceleration through aging. i blew a vein in my palm. lol just leaning. or plunging. or making macramaing. take your pick. but i love the indigo hue.