Artificial intelligence (AI) has become an integral part of our daily lives, with applications ranging from personalized recommendations to autonomous vehicles. However, the rapid development and deployment of AI systems has raised concerns about their impact on the environment. The massive computing power required to train AI models, especially deep learning algorithms, consumes significant amounts of energy, contributing to greenhouse gas emissions and climate change. In response to this challenge, researchers and engineers have turned to federated learning, a distributed approach to training AI models that has the potential to significantly reduce AI's carbon footprint.

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