核心概念
Geoscience foundation models revolutionize data analysis and prediction in Earth sciences through versatile multimodal capabilities and formal geoscience knowledge representations.
要約
Geoscience foundation models (GFMs) integrate diverse data for Earth system understanding. GFMs extract insights from structured and unstructured data, enabling comprehensive analysis. Collaboration between experts fosters innovation in GFMs. Challenges include validation, scalability, and addressing bias. GFMs hold promise for climate change, natural hazards, and sustainability insights. Recent advances include large language models for constructing GFMs.
統計
"The availability of massive volumes of Earth system data, already exceeding dozens of petabytes with hundreds of terabytes transmitted daily."
"GFMs empower them to address a wide array of prediction, simulation, and decision tasks related to the intricate interactions among Earth system components."
"Models can generate multiple types of output including synthetic seismic waves, temperature/pressure fields, surface displacement maps."
"Foundation models are trained on massive datasets comprising hundreds of billions of data samples."
"Substantial computing resources are leveraged to train and run these massive models with thousands of GPUs/TPUs used in parallel computing grids."
引用
"By unraveling the causal mechanisms underlying observed patterns and changes, GFMs contribute to advancing our knowledge of the Earth system."
"Collaboration between domain experts and computer scientists plays a pivotal role in fostering innovations in these invaluable tools for understanding the past, present, and future of our planet."
"Recent advancements in foundation models research have the potential to disrupt the prevailing task-specific paradigm in geoscience by enabling a more versatile approach to data analysis and prediction."