Foundation Models for Generalist Geospatial Artificial Intelligence

1 code implementation • 28 Oct 2023 • Johannes Jakubik, Sujit Roy, C. E. Phillips, Paolo Fraccaro, Denys Godwin, Bianca Zadrozny, Daniela Szwarcman, Carlos Gomes, Gabby Nyirjesy, Blair Edwards, Daiki Kimura, Naomi Simumba, Linsong Chu, S. Karthik Mukkavilli, Devyani Lambhate, Kamal Das, Ranjini Bangalore, Dario Oliveira, Michal Muszynski, Kumar Ankur, Muthukumaran Ramasubramanian, Iksha Gurung, Sam Khallaghi, Hanxi, Li, Michael Cecil, Maryam Ahmadi, Fatemeh Kordi, Hamed Alemohammad, Manil Maskey, Raghu Ganti, Kommy Weldemariam, Rahul Ramachandran

This paper introduces a first-of-a-kind framework for the efficient pre-training and fine-tuning of foundational models on extensive geospatial data.

Earth Observation Imputation

TensorBank: Tensor Lakehouse for Foundation Model Training

no code implementations • 5 Sep 2023 • Romeo Kienzler, Leonardo Pondian Tizzei, Benedikt Blumenstiel, Zoltan Arnold Nagy, S. Karthik Mukkavilli, Johannes Schmude, Marcus Freitag, Michael Behrendt, Daniel Salles Civitarese, Naomi Simumba, Daiki Kimura, Hendrik Hamann

Storing and streaming high dimensional data for foundation model training became a critical requirement with the rise of foundation models beyond natural language.