Google AI has developed a new machine learning approach called NeuralGCM to simulate the Earth's atmosphere. This hybrid model combines differentiable solvers and machine-learning components to improve stability, accuracy, and computational efficiency in weather and climate prediction. NeuralGCM integrates a differentiable dynamical core with a learned physics module, providing stable and accurate forecasts over various timescales. It can gradually increase the rollout length from 6 hours to 5 days, capturing interactions between learned physics and large-scale dynamics. In performance evaluation, NeuralGCM has shown comparable accuracy with leading models for 1- to 15-day weather forecasts. In climate simulations, it accurately tracks climate metrics over multiple decades and simulates phenomena like tropical cyclones, while also offering significant computational savings. For businesses, AI solutions can help identify automation opportunities, define KPIs, select appropriate AI solutions, and implement them gradually to redefine the company's way of work and stay competitive with AI. For AI KPI management advice and insights into leveraging AI, you can connect with us at hello@itinai.com. Discover AI-driven sales processes at itinai.com to redefine your sales processes and customer engagement with AI. For further consultation and updates, you can join our AI Lab in Telegram @itinai for free consultation or follow us on Twitter @itinaicom.
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