Generative AI like ChatGPT requires energy-intensive training by feeding large amounts of data to models. For example, Hugging Face reported that its multilingual text-generating AI consumed 433 megawatt hours during training; This is equivalent to powering 40 average American homes for a year. The power consumption of artificial intelligence is not limited to education; Using AI tools to solve problems such as rendering text or images consumes significant amounts of computing power and energy.
Efforts to increase AI efficiency may paradoxically lead to increased energy consumption. De Vries warns that the effort to increase the efficiency of AI could lead to an increase in the use and application of AI, ultimately leading to increased demand for resources.
Given the energy intensity of AI, de Vries emphasizes the importance of choosing AI applications wisely and considering their environmental impact; because widespread adoption of AI could lead to energy consumption levels comparable to those of countries such as the Netherlands or Argentina.
Source: Ferra
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