Which environmental impact is associated with the training of AI models?

The training of AI models is associated with increased carbon emissions due to the significant computational resources required. Training complex AI models typically involves extensive data processing, which demands substantial energy consumption. This energy, often derived from fossil fuels, contributes to carbon emissions, raising concerns about the environmental sustainability of AI practices.

In contrast to the other choices, the reality is that AI model training can strain energy resources, leading to a higher carbon footprint rather than promoting biodiversity, enhancing urban landscapes, or reducing resource consumption. Understanding the environmental impact of AI is critical as it invites discussions around sustainable practices, including the search for greener energy solutions for training processes and model optimizations that require less computational power.