Can machine studying assist predict excessive climate occasions and local weather change? Christopher Bretherton, senior director of local weather modeling on the Allen Institute for Synthetic Intelligence, or AI2, explores the know-how’s potential to boost local weather modeling with AI Podcast host Noah Kravitz in an episode recorded stay on the NVIDIA GTC world AI convention. Bretherton explains how machine studying helps overcome the restrictions of conventional local weather fashions and underscores the function of localized predictions in empowering communities to arrange for climate-related dangers. By ongoing analysis and collaboration, Bretherton and his staff goal to enhance local weather modeling and allow society to raised mitigate and adapt to the impacts of local weather change.
Keep tuned for extra episodes recorded stay from GTC, and watch the replay of Bretherton’s GTC session on utilizing machine studying for local weather modeling.
Time Stamps
2:03: What’s local weather modeling and the way can it put together us for local weather change?
5:28: How can machine studying assist improve local weather modeling?
7:21: What have been the restrictions of conventional local weather fashions?
10:24: How does a local weather mannequin work?
12:11: What data are you able to get from a local weather mannequin?
13:26: What are the present local weather fashions telling us concerning the future?
15:56: How does machine studying assist allow localized local weather modeling?
18:39: What, if something, can people or small communities do to arrange for what local weather change has in retailer for us?
25:59: How do you measure the accuracy or efficiency of an emulator that’s doing one thing like local weather modeling out into the long run?
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