Dr. Fei-Fei Li's North Star Targets the Room — and Misses the World

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?

At Earth scale, we already have trillions of tokens every month: all open, physics-anchored, multi-sensor, multi-temporal data. The only data quality issue is clouds here and there. The ultimate substrate to reason about space and time — crops, grids, floods, supply chains, and emissions. I know my experience in space makes me biased, but what am I missing? How is Earth AI not the biggest missed opportunity of spatial AI and AI in general? (We at LGND AI are taking advantage of this, of course.)

I’d love to chat with Fei-Fei Li. It would be amazing if someone can help make that connection. What are we missing?

Originally posted on LinkedIn.