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Recent progress in self-supervision shows that pre-training large neural networks on vast amounts of unsupervised data can lead to impressive increases in generalisation for downstream tasks. Such models, recently coined as foundation models, have been transformational to the field of natural language processing. While similar models have also been trained on large corpuses of images, they are not well suited for remote sensing data. To stimulate the development of foundation models for Earth monitoring, we propose to develop a new benchmark comprised of a variety of downstream tasks related to climate change. We believe that this can lead to substantial improvements in many existing applications and facilitate the development of new applications. This proposal is also a call for collaboration with the aim of developing a better evaluation process to mitigate potential downsides of foundation models for Earth monitoring.
Author Information
Alexandre Lacoste (ServiceNow)
Evan Sherwin (Stanford University)
I have devoted my professional career to evaluation of pathways toward a very low-carbon global energy system, developing expertise in energy modeling, statistics, machine learning, econometrics, and numerous engineering disciplines, economics, and policy domains as needed.
Hannah Kerner (University of Maryland, College Park)
Hamed Alemohammad (Radiant Earth Foundation)
Björn Lütjens (Massachusetts Institute of Technology)
Jeremy Irvin (Stanford University)
David Dao (ETH Zurich)
David Dao is a PhD student at ETH Zurich and the founder of GainForest, a non-profit working on decentralized technology to prevent deforestation. His research focuses on the deployment of novel machine learning systems for sustainable development and ecosystem monitoring. David served as a workshop co-organizer at ICLR, ICML and NeurIPS, and is a core member at Climate Change AI, a Global Shaper at World Economic Forum and a Climate Leader at Climate Reality. He is a research intern with Microsoft and was a former researcher at UC Berkeley and Stanford University.
Alex Chang (Service Now)
Mehmet Gunturkun (Service Now)
Alexandre Drouin (ServiceNow)
Pau Rodriguez (Element AI, a ServiceNow company)
David Vazquez (ServiceNow)
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