aiqbench takeMachine Learning

This article focuses on the development of GeoCroissant, an initiative by SDSC to standardize and enhance geospatial data formats specifically for AI readiness in Earth science applications. By addressing the critical bottleneck of dataset interoperability, this work directly facilitates more efficient training and deployment of machine learning models on planetary-scale data.

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SDSC Helps Improve AI-Ready Geospatial Data Through GeoCroissant

HPCwireOctober 1, 20261 min read

Oct. 1, 2026 — Researchers working with Earth science data often face a basic but time-consuming challenge: Determining what datasets exist, what they contain and whether they can be used together. Doug Fils, with the University of California San Diego Halıcıoğlu School of Data Science and Computing’s San Diego Supercomputer Center (SDSC), is helping advance a […] The post SDSC Helps Improve AI-Ready Geospatial Data Through GeoCroissant appeared first on HPCwire.

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