Migratory birds are critical for the health of human agriculture and the environment. But our knowledge of their movements is surprisingly little. Using “snapshots” based on Cornell University’s eBird database, scientists at the University of Massachusetts created BirdFlow, an artificial intelligence (AI) that accurately predicted migratory movements. Critical for the AI’s accuracy, the team first used PSC’s Bridges-2 system to remove observation biases from eBird and fill in gaps in the data.
The post BirdFlow AI: How Supercomputers and AI Unveil the Secrets of Migratory Bird Patterns appeared first on HPCwire.
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