A collective agenda for AI on the Earth sciences | AI and Climate Science | Discovery
0This AI for Good Discovery discusses a collective artificial intelligence (AI) agenda for the Earth sciences. Building a common agenda presents several challenges. The use of AI to advance Earth system science research and applications is often hindered by a lack of quality data and access to computing infrastructure. In addition, most problems in Earth sciences aim to do inferences about the system, where accurate predictions are just a tiny part of the whole problem. Machine learning models alone are excellent approximators, but very often do not respect the most elementary laws of physics, like mass or energy conservation, so consistency and confidence are compromised. Models, assumptions, and data should go hand in hand.
Join this Climate Discovery with Prof. Camps-Valls as he introduces several ways to bridge the Physics and machine learning interplay. Interpretable and physics-aware machine learning models are necessary steps towards understanding the data-generating processes, for which causality promises great advances too. In his talk, Prof. Maskey illustrates several NASA Earth Science Data System’s (ESDS) initiatives in addressing these challenges. The talk focuses on using AI to enhance user experience by enabling the search and discovery of petabytes of data, providing platforms for sharing and reusing AI training data and models, developing pipelines to transition AI models to production, and using citizen science to advance AI models over time.
🎙 Speakers:
Gustau Camps-Valls, Professor in Electrical Engineering, Universitat de València
Manil Maskey, Senior Research Scientist, National Aeronautics and Space Administration (NASA)
🎙 Moderators:
Duncan Watson-Parris, Postdoctoral Research Associate, @oxforduniversity
Philip Stier, Head of Atmospheric, Oceanic and Planetary Physics, University of Oxford
Shownotes:
00:00 Opening
00:54 Intro
2:26 Gustau Camps-Valls, Universitat de València
37:07 Manil Maskey, NASA
1:12:08 Q&A
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