微软在 Nature 期刊发表新研究,展示了机器学习如何改善历史上极难预测的 2 到 6 周中期天气预报。该工作有望帮助更好地应对极端天气、管理自然资源和做出农业决策,同时也表明未来可能需要构建围绕模型的智能验证系统来持续校准预测。
In @Nature this week, our new research shows how machine learning can improve weather forecasts two to six weeks out, a timeframe that's historically been very difficult to predict. It's exciting to see the potential of this work to help us better prepare for extreme weather, manage natural resources, and make more informed decisions in agriculture. There's a broader lesson here... the future may not just be about ever-more-capable models, but about building intelligent verification systems around them: systems that learn where models are systematically wrong, reason about cause and effect, and continuously calibrate predictions against reality. Read more: https://www.microsoft.com/en-us/research/story/new-ai-framework-bridges-a-critical-gap-in-mid-range-weather-forecasts/
来源:Satya Nadella · x.com