Geoembeddings

AI is paid by the word. That’s not a metaphor — tokens are literally what you pay for. That’s why AI loves to be verbose, to generate more “tokens”… it’s a feature, not a bug. This is literally how they reason, and this is how most AI is monetized, what you pay. “Vibe coding”, “Thinking”, “planning”, “agents” … layers upon layers of less and less visible internal narrative you paid. This is only getting worse as the “price per token” (what the “pricing page” shows) gets cheaper and we follow the Jevons paradox. There isn’t much attention to tokens used per outcome. ...

This is the article version of the invited talk I gave at the BSC AI Factory of Barcelona, during a CARTO event. The title ‘Earth Intelligence’ sounds like science fiction or philosophy. It isn’t. This is not a wish list for future data or tech I wish we had. We do in fact have enough data and tools. This is about the simplest, fastest way to access planetary insights right now. What a time to be working on this! ...

Dr. Fei-Fei Li’s new North Star targets the room… and misses the world. She is the godmother of AI — she changed history in 2006 when she realized that AI was rich in text and poor in images, so she created ImageNet, which gave eyes to AI. In her recent post, she argues that the next frontier is AI that understands space, 3D relations, and change over time. I agree. But the framing on spatial AI centers on rooms, robots, Augmented Reality, Virtual Reality, the physical world… What about the world itself — Earth? The largest, most consequential “world model” we have, and need. Why is it missing from this north star? ...

Google just launched “Earth AI.” Kudos and thank you to Christopher Phillips, James Manyika, and the team. The world is a better place today. They’ve also raised public awareness and set a higher bar for what planetary-scale awareness could and should be, and how AI can help get us there. Many have asked me for hot takes, since I’m also deep in geoAI. IMO Google also leaked that their geo moat is getting weaker. Their tech paper makes clear this is more about smart orchestration of (open) models than throwing compute at closed data. Earth data — “the other trillion tokens of AI” — is not incremental to text/images but orthogonal. ...

My key message on Monday at the geo day at AWS in London was that a fundamental shift in how we approach Earth Observation (EO) data is not just possible, but essential, with Geo Embeddings at its core. Phil Cooper, the host, introduced the session around the question of whether GIS has an identity crisis. I think that is not only true, but also that is because GIS has had an EO product problem for decades and finally AI seems to provide the stack to solve it… We must change GIS EO from pixel math and widgets, to frictionless semantic navigation through embeddings. ...

From a keynote at the European Rover Challenge last week in Krakow, and celebrating the 150th anniversary of “The Lunar Trilogy” by Jerzy Zulawski. Video at the end. The conference hall was buzzing. Outside, teams of students around the world were competing with their DIY robots on a Mars landscape, driven by the same age-old question that has fueled explorers for centuries: “What is where?” ...