Aurora, a large-scale foundation model trained on more than one million hours of diverse geophysical data, outperforms operational forecasts in predicting air quality, ocean waves, tropical cyclone tracks and high-resolution weather, all at orders of magnitude lower computational cost.
It is inferred that most bacterial phyla were ancestrally anaerobic and adopted aerobic lifestyles after the GOE, however, in the cyanobacterial ancestor, aerobic metabolism likely predated the GOE, which may have facilitated the evolution of oxygenic photosynthesis.
It is argued that such methods that reveal the decision processes of AI models can foster trust in their results and facilitate the broader adoption of AI.
This study establishes a benchmark for landslide susceptibility mapping, providing a scalable and adaptable framework for geospatial hazard prediction, and hold significant implications for land-use planning, disaster management, and environmental conservation in vulnerable regions worldwide.
Article Galaxy Pages is a free service from Research Solutions, a company that offers access to content in collaboration with publishing partners, online repositories and discovery services.