Webinar I Building More Accurate Spatial Models with Google PDFM Embeddings and CARTO

Miguel Álvarez, Head of Data Science at CARTO, and Gautam Prasad from Google Research explain how PDFM embeddings are built, what signals they include (search trends, POIs, mobility, weather, air quality), and how to integrate them into workflows using CARTO Workflows on BigQuery. You’ll also see a practical demo predicting liquor sales in Iowa and comparing traditional sociodemographic features vs. PDFM embeddings. You’ll learn: 03:34 – Inside Google’s Population Dynamics Foundation Model (PDFM) 09:34 – Interpolation & forecasting examples with PDFM 13:04 – How CARTO integrates PDFM embeddings in Workflows 20:25 – Demo: predicting liquor sales with PDFM + CARTO on BigQuery 31:09 – Q&A: when and how to use PDFM embeddings Resources mentioned: CARTO AI Agents: https://carto.com/blog/how-organizations-are-using-ai-to-democratize-spatial-analysis Personalizing services with spatial analytics in Google Cloud: https://carto.com/blog/personalizing-services-spatial-analytics-in-google-cloud From Imagery to Insight: Google AlphaEarth Foundations in CARTO: https://carto.com/blog/google-alphaearth-foundations-in-carto Connect with the speakers on LinkedIn: Miguel Álvarez: https://www.linkedin.com/in/mglalvarez/ Gautam Prasad: https://www.linkedin.com/in/drgautamprasad Start exploring geospatial foundation models and embeddings in your own workflows. https://carto.com/signup/ #GeospatialAI #GooglePDFM #SpatialModeling #BigQuery #CARTO