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Earth scientists are championing the use of AI for weather forecasting and earthquake detection, emphasizing its energy efficiency and speed in generating breakthroughs. While environmentalists often criticize AI for its high energy consumption, researchers argue that AI can significantly reduce the energy costs associated with traditional computational methods. The debate highlights a divide between environmentalists and Earth scientists, who see AI as a vital tool for advancing climate science.
AI models, particularly machine learning, are transforming how data is processed in Earth sciences, allowing for more efficient calculations and predictions. For instance, Google's climate and sustainability team is developing generative AI models that can predict extreme weather events more accurately than traditional methods. This innovative approach not only enhances forecasting capabilities but also addresses the urgent need for effective climate risk management.
• AI can enhance weather forecasting and earthquake detection efficiency.
• Google's AI models predict extreme weather events with greater accuracy.
Machine learning is an AI technique that autonomously extracts insights from data pools, enhancing predictive capabilities.
Generative AI models create numerous forecasts based on limited input, improving risk assessment for rare events.
Data centers house AI tools and require significant energy and water for cooling, impacting environmental resources.
Google is developing AI models that enhance climate forecasting and risk management, showcasing AI's potential in environmental science.
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