The training of artificial intelligence consumed an amount of electrical energy equivalent to the consumption of a typical family for 23 yearsas revealed by recent research.
On November 30, 2022, when OpenAI launched ChatGPT, according to the International Energy Agency (IEA)this event marked the beginning of an increase in the consumption of energy resources. GPU centers consumed between 1% and 1.3% of global electricity in 2022.
Furthermore, according to data from Google, owner of the Gemini AI model, the multinational increased its energy consumption by 16.2% in 2023.
Specialists assure that consumption skyrocketed because previously the majority of the population used the Google search engine, which requires CPU processors to work, which are less powerful than the GPUs of the AI centers.
This means that in order for us to obtain a response to a ChatGPT query, the graphics processing units require three times more energy consumption than a normal search, according to data from the Spanish Engineering Institute (IIE).
For exampleonly the energy consumed by training a model like GPT-3 is comparable to the consumption of a Spanish home over 23 years (78,437 kWh).
Besides, The new chatbots need water to function, both for the production of electricity and for cooling the equipment. The data center environment is sprayed so that the equipment does not heat up.
The United Nations Environment Program (UNEP)warns that, globally, AI-related infrastructure could consume six times more water than a country like Denmark until 2027.
Not only should we think about what they consume, but also about the waste they produce.. These data centers produce parts that often contain hazardous substances, such as mercury and lead. To manufacture a 2 kilo machine requires 800 kilos of raw materials.
Research by the University of Cambridge and the Institute of Environment Urban of the Chinese Academy of Sciences, published in Nature Computational Science, indicates that the generation of waste from technology will increase from 2,600 tons in 2023 to 2.5 million tons in 2030: the equivalent of throwing away between 2,100 and 13,300 million units of iPhone 15 Pro.
Source: Ambito
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