Google DeepMind: The Podcast

The Nature of AI: Solving the Planet's Data Gap with Drew Purves

Further reading:Natural forests of the world: <a href="https://sciety.org/articles/activity/10.31223/x5zx6p">paper</a>, <a href="https://github.com/google-deepmind/forest_typology">data and benchmarks</a>Forest loss drivers: <a href="https://iopscience.iop.org/article/10.1088/1748-9326/add606">paper,</a> <a href="https://www.wri.org/insights/forest-loss-drivers-data-trends">summary from WRI</a>, and blog from <a href="https://www.globalforestwatch.org/blog/data-and-tools/new-drivers-data-forest-loss/">GFW</a>Forest loss drivers code: <a href="https://developers.google.com/earth-engine/datasets/catalog/projects_landandcarbon_assets_wri_gdm_drivers_forest_loss_1km_v1_2_2001_2024">Google Earth Engine</a>; at <a href="https://datasets.wri.org/datasets/dominant-drivers-of-tree-cover-loss-at-1km?map=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">WRI</a>; at <a href="https://www.globalforestwatch.org/map/?map=eyJkYXRhc2V0cyI6W3siZGF0YXNldCI6InRyZWUtY292ZXItbG9zcy1ieS1kb21pbmFudC1kcml2ZXIiLCJvcGFjaXR5IjoxLCJ2aXNpYmlsaXR5Ijp0cnVlLCJsYXllcnMiOlsidHJlZS1jb3Zlci1sb3NzLWJ5LWRvbWluYW50LWRyaXZlciJdfSx7ImRhdGFzZXQiOiJwb2xpdGljYWwtYm91bmRhcmllcyIsImxheWVycyI6WyJkaXNwdXRlZC1wb2xpdGljYWwtYm91bmRhcmllcyIsInBvbGl0aWNhbC1ib3VuZGFyaWVzIl0sIm9wYWNpdHkiOjEsInZpc2liaWxpdHkiOnRydWV9XX0%3D&amp;mapMenu=eyJtZW51U2VjdGlvbiI6ImRhdGFzZXRzIiwiZGF0YXNldENhdGVnb3J5IjoiZm9yZXN0Q2hhbmdlIn0%3D">GFW</a>; or <a href="https://zenodo.org/records/15366671">Zenodo</a>. Deep learning based remote sensing (open source): <a href="https://github.com/google-deepmind/jeo">Jeo</a>, <a href="https://github.com/google-deepmind/geeflow">GeeFlow</a>Species mapping paper: <a href="https://arxiv.org/abs/2503.11900">Arxiv</a>Google resources: <a href="https://earthengine.google.com/">Google Earth Engine</a>. <a href="https://agri.withgoogle.com/">Agri with Google</a>, <a href="https://blog.google/outreach-initiatives/entrepreneurs/ai-nature-climate-accelerator-nonprofits-speciesnet/">wildlife cameras</a>Perch: <a href="https://github.com/google-research/perch">code,</a> <a href="https://www.nature.com/articles/s41598-023-49989-z.epdf">paper</a>Perch x coral reefs: <a href="https://blog.google/outreach-initiatives/arts-culture/a-new-ai-tool-to-help-monitor-coral-reef-health/">Blog</a>Agile Modelling: <a href="https://arxiv.org/abs/2505.03071">paper</a>, <a href="https://github.com/google-research/perch-hoplite">code</a>DolphinGemma: <a href="https://blog.google/technology/ai/dolphingemma/">blog</a> 
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