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The discussion centers on the coexistence of AI and sustainability, highlighting the dual nature of AI's impact on the environment. While AI can exacerbate environmental issues due to high energy consumption, it also offers innovative solutions for sustainability challenges. The need to leverage AI for environmental benefits while minimizing its ecological footprint is emphasized.
AI's role in enhancing weather predictions and analyzing satellite imagery showcases its potential to address climate change. However, the article stresses the importance of equitable access to AI technologies, particularly for communities in the Global South. Collaborative efforts and innovative practices are essential to ensure that AI contributes positively to sustainability.
• AI's energy consumption poses significant environmental challenges.
• AI can enhance weather predictions and support climate research.
AI models are algorithms that learn from data to make predictions or decisions, crucial for weather forecasting.
Inference refers to the process of generating predictions from trained AI models, which requires substantial energy.
Energy efficiency in AI involves optimizing data centers to reduce power consumption while maintaining performance.
Queen Mary conducts research on using AI for sustainability and improving energy efficiency in data centers.
Google's GenCast program exemplifies AI's capability to outperform traditional weather prediction models.
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