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    <title>Geoembeddings on Bruno Sánchez-Andrade Nuño</title>
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      <title>AI Is Paid by the Word</title>
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      <description>Tokens are literally what you pay for. The next wave of AI should flatten the stack — not add another agentic layer on top.</description>
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      <title>Visions of Earth Intelligence</title>
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      <description>From DRIP Earth to the Linear Bet: three paths to AI for Earth — Agentic AI, Embeddings, and Index-based retrieval. An invited talk at BSC AI Factory.</description>
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      <title>Dr. Fei-Fei Li&#39;s North Star Targets the Room — and Misses the World</title>
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      <description>Her new spatial AI north star centers on rooms, robots, AR/VR. But what about the largest, most consequential world model we have: Earth?</description>
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      <title>Google Earth AI: A Critical Take</title>
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      <description>Google launched Earth AI and the world is better for it. But reading the paper closely reveals something interesting: their geo moat is getting weaker, not stronger.</description>
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      <title>From Earth Pixels to GeoEmbeddings</title>
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      <description>How foundation models compress Earth observation data into rich mathematical vectors — the technology behind Clay and the future of planetary intelligence.</description>
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      <title>The Quest for &#34;What is Where?&#34;</title>
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      <description>From a keynote at the European Rover Challenge in Krakow: how AI foundational models are transforming Earth observation, and our ability to answer the age-old question of what is where on our planet.</description>
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