GeoAI

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. ...

TL;DR: Training Clay v1.5 was “carbon neutral” and actually emitted ~10 tonnes of CO₂e. Moreover, focusing on lower emissions during geoAI training is a climate distraction compared to understanding geoembeddings. A year ago we trained Clay model v1.5 — still one of the most capable geoAI models today: open-source, open-data, open-license. At the time we promised to publish its emissions. I just updated the docs, but sharing this longer post since it proved harder — and had deeper pragmatic implications — than I expected. ...